From c8bb9d6ab0c9cdef330ec3f9060a116d6f48ba62 Mon Sep 17 00:00:00 2001 From: Maximilian Igl Date: Sun, 12 Jul 2026 10:14:40 +0200 Subject: [PATCH] Sync from GitLab (2026-07-12) Last commit: 698eb022c3df2c14d59d7dde25a1dc51d8554e6c - Update public changelog for July sync This sync includes 21 commit(s) from GitLab. Excludes: - plugins/internal/ - .gitlab-ci.yml GitLab-Last-Synced-Commit: 698eb022c3df2c14d59d7dde25a1dc51d8554e6c Co-authored-by: Bertrand Douillard Co-authored-by: Jef Packer Co-authored-by: Maximilian Igl Co-authored-by: Michael Watson Co-authored-by: Peter Karkus Co-authored-by: Yuxiao Chen --- .../references/metrics.md | 6 +- CHANGELOG.md | 70 + data/scenes/README.md | 28 +- data/scenes/sim_scenes.csv | 1607 ++++++++ data/scenes/sim_suites.csv | 3437 ++++++++++++----- data/scenes/sim_suites_2505.csv | 1822 ++++----- docs/TELEMETRY.md | 4 + .../tests/test_transfuser_batched.py | 2 + pyproject.toml | 4 +- .../alpasim_controller/mpc_impl/linear_mpc.py | 7 +- src/controller/pyproject.toml | 2 +- .../tests/mpc_impl/test_linear_mpc.py | 63 + src/driver/pyproject.toml | 2 +- src/driver/src/alpasim_driver/main.py | 4 + .../alpasim_driver/models/alpamayo1_model.py | 29 + src/driver/src/alpasim_driver/models/base.py | 1 + src/driver/src/alpasim_driver/schema.py | 1 + .../tests/test_inference_seeding.py | 79 + .../alpasim_driver/tests/test_vam_batched.py | 1 + src/eval/src/eval/aggregation/utils.py | 44 +- src/eval/src/eval/data.py | 13 +- src/eval/src/eval/schema.py | 8 + src/eval/src/eval/scorers/__init__.py | 2 + .../src/eval/scorers/open_loop_collision.py | 107 + src/eval/tests/conftest.py | 3 + src/eval/tests/test_open_loop_collision.py | 158 + src/eval/tests/test_scenario_evaluator.py | 36 +- src/grpc/alpasim_grpc/v0/logging.proto | 4 + src/grpc/alpasim_grpc/v0/runtime.proto | 7 + src/physics/alpasim_physics/backend.py | 2 +- src/physics/pyproject.toml | 2 +- src/physics/tests/test_backend.py | 2 +- src/runtime/alpasim_runtime/address_pool.py | 20 +- src/runtime/alpasim_runtime/config.py | 43 +- src/runtime/alpasim_runtime/daemon/engine.py | 29 +- .../alpasim_runtime/daemon/scheduler.py | 682 +++- src/runtime/alpasim_runtime/errors.py | 19 + src/runtime/alpasim_runtime/event_loop.py | 2 +- src/runtime/alpasim_runtime/events/policy.py | 8 + src/runtime/alpasim_runtime/events/step.py | 2 +- .../alpasim_runtime/nre_introspection.py | 4 +- .../alpasim_runtime/route_generator.py | 8 +- .../alpasim_runtime/runtime_context.py | 34 + .../services/sensorsim_service.py | 68 +- .../alpasim_runtime/simulate/__main__.py | 9 +- .../alpasim_runtime/telemetry/rpc_wrapper.py | 88 +- .../telemetry/telemetry_context.py | 287 +- .../alpasim_runtime/unbound_rollout.py | 17 +- src/runtime/alpasim_runtime/worker/ipc.py | 28 +- src/runtime/alpasim_runtime/worker/main.py | 46 +- src/runtime/pyproject.toml | 2 +- .../tests/services/test_sensorsim_service.py | 39 +- .../tests/services/test_traffic_service.py | 45 + src/runtime/tests/test_address_pool.py | 8 +- src/runtime/tests/test_config.py | 4 + src/runtime/tests/test_daemon_engine.py | 18 +- .../tests/test_daemon_request_plumbing.py | 42 +- src/runtime/tests/test_daemon_scheduler.py | 882 +++-- src/runtime/tests/test_event_policy.py | 1 + src/runtime/tests/test_route_generator.py | 12 + src/runtime/tests/test_telemetry_context.py | 107 +- src/runtime/tests/test_unbound_rollout.py | 40 +- src/runtime/tests/test_worker_ipc.py | 10 +- src/runtime/tests/test_worker_main.py | 140 + src/runtime/tests/test_worker_pool.py | 5 + src/tools/run-on-slurm/resume_slurm_job.sh | 15 +- src/tools/run-on-slurm/submit.sh | 66 +- .../alpasim_trafficsim/catk/batching.py | 131 + .../alpasim_trafficsim/catk/model_adapter.py | 84 +- .../alpasim_trafficsim/config/server.yaml | 4 +- .../alpasim_trafficsim/grpc/catk_predictor.py | 223 +- .../alpasim_trafficsim/grpc/config.py | 4 +- .../alpasim_trafficsim/grpc/servicer.py | 303 +- .../grpc/session/history.py | 168 +- src/trafficsim/tests/test_batching.py | 174 + src/trafficsim/tests/test_catk_integration.py | 33 +- .../tests/test_laneline_elevation.py | 1 - src/trafficsim/tests/test_service.py | 283 +- .../tests/test_sparse_history_freeze.py | 19 +- src/utils/alpasim_utils/artifact.py | 133 +- src/utils/alpasim_utils/ground_snap.py | 61 + .../alpasim_utils}/ply_io.py | 0 .../telemetry/alpasim-runtime-dashboard.json | 871 ++++- .../metrics_plot_recording_rules.yml | 18 +- src/utils/tests/test_artifact.py | 161 +- src/utils/tests/test_ground_snap.py | 77 + src/utils/tests/test_grpc_boundary_rs.py | 152 + src/{physics => utils}/tests/test_ply_io.py | 19 +- src/utils_rs/src/grpc_boundary.rs | 224 ++ src/utils_rs/src/lib.rs | 7 + src/utils_rs/utils_rs.pyi | 33 + src/wizard/alpasim_wizard/configuration.py | 12 +- src/wizard/alpasim_wizard/context.py | 9 +- src/wizard/alpasim_wizard/deployment/slurm.py | 81 +- src/wizard/alpasim_wizard/scenes/csv_utils.py | 53 +- src/wizard/alpasim_wizard/scenes/sceneset.py | 26 +- src/wizard/alpasim_wizard/schema.py | 9 + src/wizard/alpasim_wizard/services.py | 16 +- .../alpasim_wizard/telemetry/prometheus.py | 140 +- .../telemetry/resources/dcgm-counters.csv | 18 + .../telemetry/resources/prometheus_sidecar.sh | 36 +- .../telemetry/slurm_process_exporter.py | 77 +- src/wizard/alpasim_wizard/utils.py | 21 +- src/wizard/alpasim_wizard/wizard.py | 6 + src/wizard/configs/base_config.yaml | 21 +- src/wizard/configs/driver/alpamayo1.yaml | 1 + src/wizard/configs/topology/1gpu.yaml | 5 +- src/wizard/configs/topology/2gpu.yaml | 7 +- .../configs/topology/8gpu_12rollouts.yaml | 7 +- .../configs/topology/8gpu_64rollouts.yaml | 11 +- .../configs/topology/8gpu_no_replicas.yaml | 5 +- src/wizard/configs/topology/daemon.yaml | 6 +- src/wizard/configs/trafficsim/catk.yaml | 12 +- src/wizard/configs/trafficsim/disabled.yaml | 7 + src/wizard/pyproject.toml | 2 +- src/wizard/tests/test_runtime_server_mode.py | 50 +- src/wizard/tests/test_scene_csvs.py | 136 +- src/wizard/tests/test_sceneset.py | 76 +- src/wizard/tests/test_slurm_deployment.py | 102 +- .../tests/test_slurm_process_exporter.py | 12 +- 120 files changed, 10919 insertions(+), 3615 deletions(-) create mode 100644 src/driver/src/alpasim_driver/tests/test_inference_seeding.py create mode 100644 src/eval/src/eval/scorers/open_loop_collision.py create mode 100644 src/eval/tests/test_open_loop_collision.py create mode 100644 src/runtime/tests/services/test_traffic_service.py create mode 100644 src/trafficsim/alpasim_trafficsim/catk/batching.py create mode 100644 src/trafficsim/tests/test_batching.py create mode 100644 src/utils/alpasim_utils/ground_snap.py rename src/{physics/alpasim_physics => utils/alpasim_utils}/ply_io.py (100%) create mode 100644 src/utils/tests/test_ground_snap.py create mode 100644 src/utils/tests/test_grpc_boundary_rs.py rename src/{physics => utils}/tests/test_ply_io.py (94%) create mode 100644 src/utils_rs/src/grpc_boundary.rs create mode 100644 src/wizard/alpasim_wizard/telemetry/resources/dcgm-counters.csv create mode 100644 src/wizard/configs/trafficsim/disabled.yaml diff --git a/.agents/skills/optimize-slurm-topology/references/metrics.md b/.agents/skills/optimize-slurm-topology/references/metrics.md index bcf9854a..f84b50b1 100644 --- a/.agents/skills/optimize-slurm-topology/references/metrics.md +++ b/.agents/skills/optimize-slurm-topology/references/metrics.md @@ -17,7 +17,7 @@ Prometheus file-SD targets are written to `/prometheus/targets/alpasim.json`. Central file-SD publication uses -`wizard.telemetry.file_sd_dir` when configured. +`wizard.prometheus.file_sd_dir` when configured. ## Query Surface @@ -121,6 +121,10 @@ those raw exporter internals matter. | `DCGM_FI_DEV_FB_USED` | `alpasim-dcgm` | `gpu` | GPU framebuffer memory used in MiB. | Above 90% is a hard constraint signal. Reduce cache, concurrency, replicas, or co-location. | | `DCGM_FI_DEV_FB_FREE` | `alpasim-dcgm` | `gpu` | Free GPU framebuffer memory in MiB. | Use directly as allocatable memory headroom; add used and reserved memory to derive physical total memory. | | `DCGM_FI_DEV_FB_RESERVED` | `alpasim-dcgm` | `gpu` | Driver-reserved GPU framebuffer memory in MiB. | Add to used and free memory to derive total physical framebuffer memory. | +| `DCGM_FI_PROF_SM_ACTIVE` | `alpasim-dcgm` | `gpu` | Fraction of cycles at least one warp was resident on an SM, averaged over all SMs (0-1). | Real chip usage. High `DCGM_FI_DEV_GPU_UTIL` with low SM active means small or serialized kernels (e.g. co-located processes time-slicing); the GPU has compute headroom. | +| `DCGM_FI_PROF_SM_OCCUPANCY` | `alpasim-dcgm` | `gpu` | Fraction of resident warps relative to maximum resident warps, averaged over all SMs (0-1). | Distinguishes many-SMs-thin-work from genuinely packed SMs. Low occupancy with high SM active suggests latency-bound kernels. | +| `DCGM_FI_PROF_PIPE_TENSOR_ACTIVE` | `alpasim-dcgm` | `gpu` | Fraction of cycles the tensor core pipe was active (0-1). | Proximity to peak matmul throughput for NN inference workloads; near zero during inference means work is not hitting tensor cores. | +| `DCGM_FI_PROF_DRAM_ACTIVE` | `alpasim-dcgm` | `gpu` | Fraction of cycles the device memory interface was active (0-1). | High with low SM/tensor activity means memory-bandwidth-bound; co-locating more compute on the GPU will not help. | | `node_cpu_seconds_total` | `alpasim-node` | `mode` | Node CPU seconds by mode. | Dashboard converts idle rate to node CPU utilization. If node CPU is saturated, service scaling may not help. | | `node_memory_MemAvailable_bytes` | `alpasim-node` | none | Available host memory. | Low available memory indicates node memory pressure. | | `node_memory_MemTotal_bytes` | `alpasim-node` | none | Total host memory. | Used with available memory to compute host memory utilization. | diff --git a/CHANGELOG.md b/CHANGELOG.md index 5569c759..4593316d 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -2,6 +2,76 @@ This document lists major updates which change UX and require adaptation. It should be sorted by date (more recent on top) and link to MRs which introduce the changes. +## July 2026 public sync updates (12.07.26) + +This sync expands the public scene catalog, improves rollout reliability and +scheduling, and adds new telemetry, evaluation, and Slurm controls. + +### Scene catalogs and artifact loading + +The public 26.04 catalog is available as the `public_2604` suite, containing +1,606 scenes after removing known-invalid artifacts. Scene-suite CSV rows now +pin an exact artifact with `test_suite_id`, `scene_id`, and `uuid`; suite lookup +no longer selects the newest artifact sharing a scene ID. + +Artifacts whose parquet vector map is stored under `fastmap/` are now +supported. AlpaSim loads it after the preferred `map_data/` and `clipgt/` +sources, aligns its height to the reconstruction ground mesh, and retains XODR +as the final fallback. + +**Migration**: Add a matching `uuid` column to custom suite CSVs. Every +`(scene_id, uuid)` pair must exist in the corresponding scene catalog. + +### Runtime reliability and scheduling + +Failed rollouts are retried up to `runtime.max_rollout_retries` times, with a +default of two retries. Renderer startup now waits for channel readiness and +retries known transient NRE initialization failures. Invalid vector maps return +the structured `ROLLOUT_ERROR_CODE_INVALID_SCENE_MAP` error code. + +Scene-affine renderer dispatch now spreads non-affine work across the +least-loaded renderers and bounds scene replication. New controls include +`max_renderers_per_scene`, `max_scenes_per_renderer`, and cache refresh timing. + +**Migration**: Replace a boolean override such as +`runtime.scene_affine_dispatch=true` with +`runtime.scene_affine_dispatch.enabled=true`. Public NRE releases without the +loaded-scene introspection RPC should leave this disabled. + +### Traffic simulation and evaluation + +Traffic simulation is explicitly disabled by default through +`trafficsim=disabled`; select `trafficsim=catk` to enable CATK. CATK now batches +requests, limits per-request CPU threading, and derives worker counts from the +selected topology. + +Evaluation adds the `open_loop_collision` metric, which checks planned ego +trajectories against recorded actors over a configurable horizon. Force-GT +warmup exclusion is now anchored to the actual renderer handover, preventing +warmup frames from leaking into aggregated metrics. Route generation can be +disabled with `runtime.simulation_config.route_generator_type=NONE`. + +The public Alpamayo 1 driver can derive deterministic per-inference seeds from +the session seed with `driver.model.force_determinism=true`. The low-speed MPC +linearization also corrects two erroneous derivative terms. + +**Migration**: Custom CATK configs should use +`catk.loader.prediction_steps` instead of `minimum_future_steps`. + +### Telemetry and Slurm execution + +Per-process Prometheus exporters can now be scraped by an external Prometheus +without starting the wizard-managed sidecar. Set +`wizard.prometheus.start_prometheus=false`; discovery publication and exporter +lifecycle remain active. Slurm telemetry adds GPU ownership metrics for joining +AlpaSim processes with DCGM data, and the Grafana dashboard includes the new +scheduler, GPU, process, and throughput panels. + +Slurm deployments can opt into CUDA MPS with `wizard.enable_mps=true` to allow +co-located GPU services to execute kernels concurrently. This option fails fast +for non-Slurm run methods. Slurm submission also supports automatic resubmission +of timed-out jobs. + ## Runtime telemetry with Prometheus and Grafana (30.06.26) AlpaSim runs now start Prometheus telemetry by default. The wizard allocates metrics ports, starts Prometheus support services, writes scrape configuration, diff --git a/data/scenes/README.md b/data/scenes/README.md index fec03ac3..77e4e1df 100644 --- a/data/scenes/README.md +++ b/data/scenes/README.md @@ -4,11 +4,15 @@ This directory contains public scene and test suite definitions for Alpasim. ## Files -- `sim_scenes.csv` - Current public scene artifact metadata - (uuid, scene_id, NRE version, path, artifact_repository, hf_revision) -- `sim_suites.csv` - Current public suite-to-scene mappings -- `sim_scenes_2505.csv` - Legacy public 25.07/25.05 scene artifact metadata -- `sim_suites_2505.csv` - Legacy public 25.07/25.05 suite-to-scene mappings +- `sim_scenes.csv` - Public scene artifact metadata for all current releases + (26.01 and 26.04) +- `sim_suites.csv` - Public suite-to-artifact mappings for all current releases +- `sim_scenes_2505.csv` / `sim_suites_2505.csv` - Legacy public 25.07 release + (not loaded by default) + +Each suite row includes a readable scene ID and the UUID of the exact artifact. +By contrast, `scenes.scene_ids=[...]` selects the most recently modified artifact +for each scene ID. ### Artifact Repositories @@ -18,10 +22,16 @@ are stored: ## Available Test Suites -| Suite ID | Scenes | Description | -|----------|--------|-------------| -| `public_2601` | 916 | All public NRE scenes from the 26.01 release. Requires sensorsim NRE-GA 26.02 or later. | -| `public_2507` | 910 | Legacy public NRE scenes from the 25.07 release, hosted on the 25.05 Hugging Face revision. | +All public scenes are hosted in the +[nvidia/PhysicalAI-Autonomous-Vehicles-NuRec](https://huggingface.co/datasets/nvidia/PhysicalAI-Autonomous-Vehicles-NuRec) +dataset on Hugging Face; the `hf_revision` column pins each scene to a dataset +revision. + +| Suite ID | Scenes | NRE | HF revision | Description | +|----------|--------|-----|-------------|-------------| +| `public_2604` | 1606 | 26.4.x | [26.04](https://huggingface.co/datasets/nvidia/PhysicalAI-Autonomous-Vehicles-NuRec/tree/26.04) | Public NRE scenes from the 26.04 release, excluding known-invalid scenes. Mostly new scenarios: only 159 scenes overlap with `public_2601`. | +| `public_2601` | 913 | 26.1.x | [26.01](https://huggingface.co/datasets/nvidia/PhysicalAI-Autonomous-Vehicles-NuRec/tree/26.01) | Public NRE scenes from the 26.01 release, excluding known-invalid scenes. Re-renders scenarios from `public_2507` with newer NRE. Requires sensorsim NRE-GA 26.02 or later. | +| `public_2507` | 910 | 25.7.x | [25.05](https://huggingface.co/datasets/nvidia/PhysicalAI-Autonomous-Vehicles-NuRec/tree/25.05) | Legacy public NRE scenes from the 25.07 release, hosted on the 25.05 Hugging Face revision. | ## Managing Scenes diff --git a/data/scenes/sim_scenes.csv b/data/scenes/sim_scenes.csv index 5cc40ad1..0283f296 100644 --- a/data/scenes/sim_scenes.csv +++ b/data/scenes/sim_scenes.csv @@ -915,3 +915,1610 @@ c2c0ccb3-5588-4dad-84f5-e91da799b07c,clipgt-ff587666-677a-436c-8a8f-b8ce169dcb30 948d7620-b37e-4b54-bf3e-d79ba662d630,clipgt-ff823af7-8c65-4672-aabc-a986cb4bbfdf,26.1.112-59673f88,sample_set/26.01_release/ff823af7-8c65-4672-aabc-a986cb4bbfdf/ff823af7-8c65-4672-aabc-a986cb4bbfdf.usdz,2026-03-16 22:00:27,huggingface,26.01 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+public_2507,clipgt-fad840eb-c6e8-4e96-a37c-f1061acb26d9,1a2ddb86-d32a-4538-9611-565d71a96c2b diff --git a/docs/TELEMETRY.md b/docs/TELEMETRY.md index 8599b87f..aa153f06 100644 --- a/docs/TELEMETRY.md +++ b/docs/TELEMETRY.md @@ -33,6 +33,10 @@ scrape_configs: refresh_interval: 10s ``` +On Slurm, the process exporter also publishes `alpasim_gpu_workload_info{gpu}` for every +node-local physical GPU assigned to a discovered AlpaSim process. Cross-system dashboards can join +this ownership signal to DCGM metrics by run, node, and GPU index. + For normal Docker Compose and Slurm runs, the wizard removes this file when the deployment exits. If a run crashes before cleanup, later AlpaSim startups conservatively remove old discovery files only when they are at least five hours old and all listed targets are unreachable. diff --git a/plugins/transfuser_driver/tests/test_transfuser_batched.py b/plugins/transfuser_driver/tests/test_transfuser_batched.py index fa82ebe8..6885061d 100644 --- a/plugins/transfuser_driver/tests/test_transfuser_batched.py +++ b/plugins/transfuser_driver/tests/test_transfuser_batched.py @@ -60,6 +60,7 @@ def _make_prediction_input( speed=speed, acceleration=acceleration, ego_pose_history=[], + inference_seed=seed, ) @@ -278,6 +279,7 @@ def test_wrong_frame_count_raises(self, transfuser_model): speed=10.0, acceleration=0.0, ego_pose_history=[], + inference_seed=0, ) with pytest.raises(ValueError, match=r"expects 1 frame"): diff --git a/pyproject.toml b/pyproject.toml index fb3fe0ea..a927f9f6 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "alpasim_workspace" -version = "0.96.0" +version = "0.111.0" description = "Workspace for Alpamayo Sim development" readme = "README.md" requires-python = ">=3.11,<3.13" @@ -69,7 +69,7 @@ alpasim-tools = { workspace = true } alpasim_driver = { workspace = true } alpasim_transfuser = { workspace = true } alpasim_wizard = { workspace = true } -trajdata-alpasim = { git = "https://github.com/NVlabs/trajdata", rev = "3caf3a8bd1a68f4a1545352aea82c535be9510b2" } +trajdata-alpasim = { git = "https://github.com/NVlabs/trajdata", rev = "a0c1310c5fba190c181c6fb4f00c06fc5c77b417" } alpasim-trafficsim = { workspace = true } [tool.uv] diff --git a/src/controller/alpasim_controller/mpc_impl/linear_mpc.py b/src/controller/alpasim_controller/mpc_impl/linear_mpc.py index c00f460c..67850813 100644 --- a/src/controller/alpasim_controller/mpc_impl/linear_mpc.py +++ b/src/controller/alpasim_controller/mpc_impl/linear_mpc.py @@ -219,7 +219,6 @@ def _linearize_dynamics(self, x_op: np.ndarray) -> tuple[np.ndarray, np.ndarray] v_cg_x = x_op[self.IVX] v_cg_y = x_op[self.IVY] yaw_rate = x_op[self.IYAW_RATE] - steering = x_op[self.ISTEERING] # Use kinematic model at low speeds use_kinematic = v_cg_x < params.kinematic_threshold_speed @@ -232,7 +231,7 @@ def _linearize_dynamics(self, x_op: np.ndarray) -> tuple[np.ndarray, np.ndarray] sin_yaw = math.sin(yaw) if use_kinematic: - # Kinematic model linearization + # Kinematic model linearization. A[self.IX, self.IYAW] = -v_cg_x * sin_yaw A[self.IX, self.IVX] = cos_yaw @@ -242,14 +241,14 @@ def _linearize_dynamics(self, x_op: np.ndarray) -> tuple[np.ndarray, np.ndarray] A[self.IYAW, self.IYAW_RATE] = 1.0 A[self.IVX, self.IACCEL] = 1.0 + # Freeze v_cg_x as a scheduling parameter. Adding its product derivatives + # without an affine residual would double the operating-point terms. GAIN = 10.0 l_r = params.l_rig_to_cg L = params.wheelbase - A[self.IVY, self.IVX] = GAIN * steering * l_r / L A[self.IVY, self.IVY] = -GAIN A[self.IVY, self.ISTEERING] = GAIN * v_cg_x * l_r / L - A[self.IYAW_RATE, self.IVX] = GAIN * steering / L A[self.IYAW_RATE, self.ISTEERING] = GAIN * v_cg_x / L A[self.IYAW_RATE, self.IYAW_RATE] = -GAIN diff --git a/src/controller/pyproject.toml b/src/controller/pyproject.toml index c62cf63d..62067a67 100644 --- a/src/controller/pyproject.toml +++ b/src/controller/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "alpasim_controller" -version = "0.59.0" +version = "0.71.0" description = "A simple, open source controller + vehicle model" requires-python = ">=3.11,<3.13" dependencies = [ diff --git a/src/controller/tests/mpc_impl/test_linear_mpc.py b/src/controller/tests/mpc_impl/test_linear_mpc.py index 9a89cabf..76b4ef13 100644 --- a/src/controller/tests/mpc_impl/test_linear_mpc.py +++ b/src/controller/tests/mpc_impl/test_linear_mpc.py @@ -78,6 +78,32 @@ def test_compute_control_with_lateral_error(self): # Should command negative steering to correct positive y error assert output.control[0] < 0 + def test_control_is_continuous_at_kinematic_model_threshold(self): + """Crossing the speed threshold must not double the steering contribution.""" + controller = LinearMPC() + trajectory = _create_turning_trajectory() + state = np.array([0.0, 0.0, 0.0, 4.99, 0.666, 0.437, 0.251, 1.313]) + + below = controller.compute_control( + ControllerInput( + state=state, + reference_trajectory=trajectory, + timestamp_us=0, + ) + ) + state[3] = controller._vehicle_params.kinematic_threshold_speed + at_threshold = controller.compute_control( + ControllerInput( + state=state, + reference_trajectory=trajectory, + timestamp_us=0, + ) + ) + + assert below.status in ("solved", "solved_inaccurate") + assert at_threshold.status in ("solved", "solved_inaccurate") + assert abs(below.control[0] - at_threshold.control[0]) < 0.01 + class TestLinearMPCLinearization: """Tests for LinearMPC dynamics linearization.""" @@ -108,6 +134,28 @@ def test_linearize_dynamics_kinematic_model(self): assert not np.isnan(A_d).any() assert not np.isnan(B_d).any() + def test_kinematic_model_preserves_steady_turning_manifold(self): + """Steady low-speed lateral velocity and yaw rate should be preserved.""" + controller = LinearMPC() + params = controller._vehicle_params + velocity = params.kinematic_threshold_speed - 0.01 + steering = 0.25 + + state = np.zeros(controller.NX) + state[controller.IVX] = velocity + state[controller.IVY] = ( + velocity * steering * params.l_rig_to_cg / params.wheelbase + ) + state[controller.IYAW_RATE] = velocity * steering / params.wheelbase + state[controller.ISTEERING] = steering + command = np.array([steering, 0.0]) + + A_d, B_d = controller._linearize_dynamics(state) + next_state = A_d @ state + B_d @ command + + indices = [controller.IVY, controller.IYAW_RATE] + np.testing.assert_allclose(next_state[indices], state[indices], atol=1e-12) + def test_linearize_dynamics_dynamic_model(self): """At higher speeds, should use dynamic model.""" controller = LinearMPC() @@ -143,3 +191,18 @@ def _create_simple_trajectory( timestamps = np.array([i * dt_us for i in range(num_points)], dtype=np.uint64) return Trajectory(timestamps, positions, quaternions) + + +def _create_turning_trajectory() -> Trajectory: + """Create a gently curving trajectory that exercises lateral control.""" + timestamps = np.arange(0, 2_100_000, 100_000, dtype=np.uint64) + x = timestamps.astype(np.float64) * 5.0 / 1e6 + positions = np.stack( + [x, 0.08 * x**2, np.zeros_like(x)], + axis=1, + ).astype(np.float32) + quaternions = np.tile( + np.array([0.0, 0.0, 0.0, 1.0], dtype=np.float32), + (len(timestamps), 1), + ) + return Trajectory(timestamps, positions, quaternions) diff --git a/src/driver/pyproject.toml b/src/driver/pyproject.toml index 1ba8d013..f18cb93c 100644 --- a/src/driver/pyproject.toml +++ b/src/driver/pyproject.toml @@ -5,7 +5,7 @@ build-backend = "uv_build" [project] name = "alpasim_driver" -version = "0.57.0" +version = "0.70.0" description = "Adapters for open-source drivers in Alpasim" readme = "README.md" requires-python = ">=3.12,<3.13" diff --git a/src/driver/src/alpasim_driver/main.py b/src/driver/src/alpasim_driver/main.py index bc950c80..03546dfb 100644 --- a/src/driver/src/alpasim_driver/main.py +++ b/src/driver/src/alpasim_driver/main.py @@ -156,6 +156,7 @@ class Session: poses: list[PoseAtTime] = field(default_factory=list) dynamic_states: list[tuple[int, DynamicState]] = field(default_factory=list) current_command: DriveCommand = DriveCommand.STRAIGHT # Default to straight + inference_count: int = 0 @staticmethod def create( @@ -701,6 +702,8 @@ def _run_batch(self, batch: list[DriveJob]) -> list[ModelPrediction]: inputs = [] for job in batch: speed, acceleration = self._get_speed_and_acceleration(job.session) + inference_seed = job.session.seed + job.session.inference_count + job.session.inference_count += 1 inputs.append( PredictionInput( camera_images=self._prepare_camera_images(job.session), @@ -708,6 +711,7 @@ def _run_batch(self, batch: list[DriveJob]) -> list[ModelPrediction]: speed=speed, acceleration=acceleration, ego_pose_history=job.session.poses, + inference_seed=inference_seed, ) ) return self._model.predict_batch(inputs) diff --git a/src/driver/src/alpasim_driver/models/alpamayo1_model.py b/src/driver/src/alpasim_driver/models/alpamayo1_model.py index 1e927dfe..3fe24ad3 100644 --- a/src/driver/src/alpasim_driver/models/alpamayo1_model.py +++ b/src/driver/src/alpasim_driver/models/alpamayo1_model.py @@ -6,6 +6,7 @@ from __future__ import annotations import logging +import os import torch from alpamayo_r1 import helper @@ -19,10 +20,23 @@ AlpamayoBaseModel, build_ego_history, ) +from .base import ModelPrediction, PredictionInput logger = logging.getLogger(__name__) +def _configure_deterministic_runtime() -> None: + """Configure deterministic PyTorch execution for Alpamayo inference.""" + if torch.cuda.is_available(): + torch.backends.cudnn.deterministic = True + torch.backends.cudnn.benchmark = False + torch.backends.cudnn.allow_tf32 = True + torch.backends.cuda.matmul.allow_tf32 = True + torch.set_float32_matmul_precision("high") + torch.use_deterministic_algorithms(True) + os.environ["CUBLAS_WORKSPACE_CONFIG"] = ":4096:8" + + class Alpamayo1Model(AlpamayoBaseModel): """Alpamayo 1 wrapper implementing the common interface.""" @@ -41,6 +55,7 @@ def from_config( device=device, camera_ids=camera_ids, context_length=context_length or cls.DEFAULT_CONTEXT_LENGTH, + force_determinism=model_cfg.force_determinism, ) def __init__( @@ -52,6 +67,7 @@ def __init__( num_traj_samples: int = 1, top_p: float = 0.98, temperature: float = 0.6, + force_determinism: bool = False, ): """Initialize Alpamayo 1 model. @@ -63,7 +79,11 @@ def __init__( num_traj_samples: Number of trajectory samples to generate. top_p: Top-p sampling parameter for VLM generation. temperature: Temperature for VLM sampling. + force_determinism: Whether to make stochastic inference repeatable from + each prediction's inference seed. """ + if force_determinism: + _configure_deterministic_runtime() logger.info("Loading Alpamayo 1 checkpoint from %s", checkpoint_path) model = AlpamayoR1.from_pretrained(checkpoint_path, dtype=self.DTYPE).to(device) @@ -80,7 +100,16 @@ def __init__( top_p=top_p, temperature=temperature, ) + self._force_determinism = force_determinism def _create_chat_message(self, image_frames: torch.Tensor) -> list: """Create chat message using Alpamayo 1's helper (no camera indices).""" return self._helper.create_message(image_frames.flatten(0, 1)) + + def predict(self, prediction_input: PredictionInput) -> ModelPrediction: + """Generate a trajectory, reseeding stochastic inference when configured.""" + if self._force_determinism: + torch.manual_seed(prediction_input.inference_seed) + if torch.cuda.is_available(): + torch.cuda.manual_seed_all(prediction_input.inference_seed) + return super().predict(prediction_input) diff --git a/src/driver/src/alpasim_driver/models/base.py b/src/driver/src/alpasim_driver/models/base.py index 8b79900c..362b4d44 100644 --- a/src/driver/src/alpasim_driver/models/base.py +++ b/src/driver/src/alpasim_driver/models/base.py @@ -53,6 +53,7 @@ class PredictionInput: speed: float # m/s acceleration: float # m/s² ego_pose_history: list[Any] # list[PoseAtTime] + inference_seed: int # Session seed plus the zero-based inference count @dataclass diff --git a/src/driver/src/alpasim_driver/schema.py b/src/driver/src/alpasim_driver/schema.py index cd639b9e..a38276a0 100644 --- a/src/driver/src/alpasim_driver/schema.py +++ b/src/driver/src/alpasim_driver/schema.py @@ -26,6 +26,7 @@ class ModelConfig: device: str = MISSING # Device to run inference on (cuda/cpu) tokenizer_path: str | None = None # Only required for VAM use_classifier_free_guidance_nav: bool = False # A1.5 only + force_determinism: bool = False # Alpamayo 1 only @dataclass diff --git a/src/driver/src/alpasim_driver/tests/test_inference_seeding.py b/src/driver/src/alpasim_driver/tests/test_inference_seeding.py new file mode 100644 index 00000000..e6098ce7 --- /dev/null +++ b/src/driver/src/alpasim_driver/tests/test_inference_seeding.py @@ -0,0 +1,79 @@ +# SPDX-License-Identifier: Apache-2.0 +# Copyright (c) 2026 NVIDIA Corporation + +from types import SimpleNamespace +from unittest.mock import patch + +import numpy as np +import torch + +from ..main import DriveJob, EgoDriverService +from ..models.alpamayo1_model import Alpamayo1Model +from ..models.alpamayo_base import AlpamayoBaseModel +from ..models.base import DriveCommand, ModelPrediction, PredictionInput + + +class _CapturingModel: + def __init__(self) -> None: + self.inputs: list[PredictionInput] = [] + + def predict_batch(self, inputs: list[PredictionInput]) -> list[ModelPrediction]: + self.inputs.extend(inputs) + return [] + + +def _drive_job(session: SimpleNamespace) -> DriveJob: + return DriveJob( + session_id="session", + session=session, + command=DriveCommand.STRAIGHT, + pose=None, + timestamp_us=0, + result=None, # type: ignore[arg-type] + ) + + +def test_run_batch_assigns_consecutive_per_session_inference_seeds() -> None: + service = EgoDriverService.__new__(EgoDriverService) + service._model = _CapturingModel() + service._get_speed_and_acceleration = lambda session: (0.0, 0.0) + service._prepare_camera_images = lambda session: {} + session = SimpleNamespace(seed=123, inference_count=0, poses=[]) + + service._run_batch([_drive_job(session)]) + service._run_batch([_drive_job(session)]) + + assert [model_input.inference_seed for model_input in service._model.inputs] == [ + 123, + 124, + ] + assert session.inference_count == 2 + + +def test_alpamayo1_force_determinism_reseeds_each_prediction() -> None: + model = Alpamayo1Model.__new__(Alpamayo1Model) + model._force_determinism = True + prediction_input = PredictionInput( + camera_images={}, + command=DriveCommand.STRAIGHT, + speed=0.0, + acceleration=0.0, + ego_pose_history=[], + inference_seed=123, + ) + + def random_prediction( + _model: AlpamayoBaseModel, + _prediction_input: PredictionInput, + ) -> ModelPrediction: + return ModelPrediction( + trajectory_xy=torch.rand((2, 2)).numpy(), + headings=np.zeros(2), + ) + + with patch.object(AlpamayoBaseModel, "predict", random_prediction): + first = model.predict(prediction_input) + torch.manual_seed(999) + second = model.predict(prediction_input) + + np.testing.assert_array_equal(first.trajectory_xy, second.trajectory_xy) diff --git a/src/driver/src/alpasim_driver/tests/test_vam_batched.py b/src/driver/src/alpasim_driver/tests/test_vam_batched.py index feec4022..6020c29c 100644 --- a/src/driver/src/alpasim_driver/tests/test_vam_batched.py +++ b/src/driver/src/alpasim_driver/tests/test_vam_batched.py @@ -63,6 +63,7 @@ def _make_prediction_input( speed=10.0, acceleration=0.0, ego_pose_history=[], + inference_seed=seed, ) diff --git a/src/eval/src/eval/aggregation/utils.py b/src/eval/src/eval/aggregation/utils.py index abde7595..0d8b8066 100644 --- a/src/eval/src/eval/aggregation/utils.py +++ b/src/eval/src/eval/aggregation/utils.py @@ -1,5 +1,5 @@ # SPDX-License-Identifier: Apache-2.0 -# Copyright (c) 2025 NVIDIA Corporation +# Copyright (c) 2025-2026 NVIDIA Corporation import json import logging @@ -24,6 +24,7 @@ def incr_counter_and_check_aggregation_start(log_dir: str) -> bool: if task_count == 0: logger.info("No array job, don't need to check counter.") return True + with lock: # Set `prev_finished_jobs` by loading it from the file if it exists. # Otherwise set it to 0. @@ -34,46 +35,45 @@ def incr_counter_and_check_aggregation_start(log_dir: str) -> bool: else: with open(Path(log_dir) / "post_eval_aggregation.json", "r") as f: data = json.load(f) - prev_finished_jobs = data["finished_jobs"] prev_finished_job_ids = data["finished_job_ids"] + prev_finished_jobs = len(set(prev_finished_job_ids)) logger.info( "Loaded post_eval_aggregation.json file, prev_finished_jobs: %d, prev_finished_job_ids: %s", prev_finished_jobs, prev_finished_job_ids, ) - # Increment the counter in the file (create it if it doesn't exist). + # Record each logical array task once. A requeued task may enter this + # function more than once if aggregation itself was interrupted. + finished_job_ids = sorted(set(prev_finished_job_ids) | {task_id}) with open(Path(log_dir) / "post_eval_aggregation.json", "w") as f: json.dump( { - "finished_jobs": prev_finished_jobs + 1, - "finished_job_ids": prev_finished_job_ids + [task_id], + "finished_jobs": len(finished_job_ids), + "finished_job_ids": finished_job_ids, }, f, ) logger.info( - "Wrote post_eval_aggregation.json file, prev_finished_jobs + 1: %d, prev_finished_job_ids: %s", - prev_finished_jobs + 1, - prev_finished_job_ids, + "Wrote post_eval_aggregation.json file, finished_jobs: %d, finished_job_ids: %s", + len(finished_job_ids), + finished_job_ids, ) - # Check if we're the last job and should start post_eval_aggregation - if prev_finished_jobs < task_count - 1: + + if len(finished_job_ids) < task_count: logger.info( "Not the last job, skipping post_eval_aggregation. " - "prev_finished_jobs: %d, task_count: %d, prev_finished_job_ids: %s", - prev_finished_jobs, + "finished_jobs: %d, task_count: %d, finished_job_ids: %s", + len(finished_job_ids), task_count, - prev_finished_job_ids, + finished_job_ids, ) return False - elif prev_finished_jobs == task_count - 1: - # We're the last job - logger.info("Last job, starting post_eval_aggregation") - return True - elif prev_finished_jobs > task_count - 1: + if len(finished_job_ids) > task_count: logger.warning( - "More jobs finished than expected, probably running manually?" - " If not, this might be a bug?" + "More task IDs finished than expected: expected %d, found %d", + task_count, + len(finished_job_ids), ) - return True - return False + logger.info("All logical array tasks finished, starting post_eval_aggregation") + return True diff --git a/src/eval/src/eval/data.py b/src/eval/src/eval/data.py index 003fff7d..d02ffa5b 100644 --- a/src/eval/src/eval/data.py +++ b/src/eval/src/eval/data.py @@ -1980,18 +1980,15 @@ class SimulationResult: def first_driven_timestamp_us(self) -> int | None: """Earliest timestamp at which the ego is under policy control. - Computed as ``start_timestamp_us + force_gt_duration_us + - control_timestep_us`` — i.e. one control step past the last force-gt - step. Returns ``None`` when ``force_gt_duration_us`` was not - propagated (e.g. ground-truth baseline runs), in which case the - aggregation pipeline will not filter any timesteps. + This is the policy handover ``render_start_timestamp_us + + force_gt_duration_us`` (``= closed_loop_start``). Returns ``None`` when + ``force_gt_duration_us`` was not propagated (e.g. ground-truth baseline + runs), leaving the aggregation pipeline to filter no timesteps. """ if self.force_gt_duration_us is None: return None return ( - self.session_metadata.start_timestamp_us - + self.force_gt_duration_us - + self.session_metadata.control_timestep_us + self.session_metadata.render_start_timestamp_us + self.force_gt_duration_us ) @property diff --git a/src/eval/src/eval/schema.py b/src/eval/src/eval/schema.py index d7a855e1..21bddbed 100644 --- a/src/eval/src/eval/schema.py +++ b/src/eval/src/eval/schema.py @@ -138,11 +138,19 @@ class ImageScorerConfig: camera_logical_id: str = MISSING +@dataclass +class OpenLoopCollisionScorerConfig: + # Horizon in seconds: how far into each planned trajectory to check for + # collisions against surrounding agents' recorded trajectories. + horizon_s: float = MISSING + + @dataclass class ScorersConfig: min_ade: MinADEScorerConfig = MISSING plan_deviation: PlanDeviationScorerConfig = MISSING image: ImageScorerConfig = MISSING + open_loop_collision: OpenLoopCollisionScorerConfig = MISSING @dataclass diff --git a/src/eval/src/eval/scorers/__init__.py b/src/eval/src/eval/scorers/__init__.py index 553c7ffe..50a39b02 100644 --- a/src/eval/src/eval/scorers/__init__.py +++ b/src/eval/src/eval/scorers/__init__.py @@ -9,6 +9,7 @@ from eval.scorers.min_distance_to_obstacle import MinDistanceToObstacleScorer from eval.scorers.minADE import MinADEScorer from eval.scorers.offroad import OffRoadScorer +from eval.scorers.open_loop_collision import OpenLoopCollisionScorer from eval.scorers.plan_deviation import PlanDeviationScorer from eval.scorers.safety import SafetyScorer @@ -16,6 +17,7 @@ CollisionScorer, OffRoadScorer, MinDistanceToObstacleScorer, + OpenLoopCollisionScorer, GroundTruthScorer, MinADEScorer, PlanDeviationScorer, diff --git a/src/eval/src/eval/scorers/open_loop_collision.py b/src/eval/src/eval/scorers/open_loop_collision.py new file mode 100644 index 00000000..11643a06 --- /dev/null +++ b/src/eval/src/eval/scorers/open_loop_collision.py @@ -0,0 +1,107 @@ +# SPDX-License-Identifier: Apache-2.0 +# Copyright (c) 2026 NVIDIA Corporation + +import numpy as np + +from eval.data import ( + AggregationType, + MetricReturn, + RenderableTrajectory, + SimulationResult, +) +from eval.schema import EvalConfig, OpenLoopCollisionScorerConfig +from eval.scorers.base import Scorer + + +class OpenLoopCollisionScorer(Scorer): + """Scores whether each planned trajectory collides with logged agents. + + At every inference step the driver returns a planned trajectory. This + scorer sweeps the ego bounding box along the first ``horizon_s`` seconds of + that plan and, at each planned future pose, checks whether it intersects the + recorded bounding box of any surrounding agent at the same absolute time. + Unlike ``CollisionScorer`` (which tests the executed ego pose), this is an + open-loop check of the plan against the agents' recorded future motion. + + Metric name: ``open_loop_collision`` — 1.0 at an inference step whose plan + collides with any agent within the horizon, else 0.0. Aggregated with MEAN, + giving the fraction of inference steps that plan into a collision. Steps + whose plan has no future pose within the horizon are marked invalid and + excluded from aggregation. + """ + + def __init__(self, cfg: EvalConfig) -> None: + super().__init__(cfg) + scorer_config: OpenLoopCollisionScorerConfig = cfg.scorers.open_loop_collision + self.horizon_us = round(scorer_config.horizon_s * 1e6) + if self.horizon_us <= 0: + raise ValueError( + "scorers.open_loop_collision.horizon_s must be > 0 (>= 1e-6 s), got " + f"{scorer_config.horizon_s}" + ) + + def calculate(self, simulation_result: SimulationResult) -> list[MetricReturn]: + other_trajectories = { + agent_id: trajectory + for agent_id, trajectory in simulation_result.actor_trajectories.items() + if agent_id != "EGO" + } + + timestamps_us: list[int] = [] + collisions: list[bool] = [] + valids: list[bool] = [] + + responses = simulation_result.driver_responses.per_timestep_driver_responses + for response in responses: + now_us = response.now_time_us + plan = response.selected_trajectory + timestamps_us.append(now_us) + + # The first plan pose is the current ego pose, so only strictly + # future poses within the horizon form the open-loop check. + plan_timestamps = np.asarray(plan.timestamps_us) + in_horizon = (plan_timestamps > now_us) & ( + plan_timestamps <= now_us + self.horizon_us + ) + future_timestamps = plan_timestamps[in_horizon] + if len(future_timestamps) == 0: + collisions.append(False) + valids.append(False) + continue + + valids.append(True) + collisions.append( + self._plan_collides(plan, future_timestamps, other_trajectories) + ) + + return [ + MetricReturn( + name="open_loop_collision", + values=collisions, + valid=valids, + timestamps_us=timestamps_us, + time_aggregation=AggregationType.MEAN, + ) + ] + + @staticmethod + def _plan_collides( + plan: RenderableTrajectory, + future_timestamps: np.ndarray, + other_trajectories: dict[str, RenderableTrajectory], + ) -> bool: + """Return whether the plan intersects any agent within the horizon. + + For each future plan timestamp the ego box is placed at the planned + pose and tested against every agent present at that time. Returns on the + first intersection. + """ + for ts in future_timestamps: + ts = int(ts) + ego_polygon = plan.get_polygon_at_time(ts) + for trajectory in other_trajectories.values(): + if ts not in trajectory.time_range_us: + continue + if ego_polygon.intersects(trajectory.get_polygon_at_time(ts)): + return True + return False diff --git a/src/eval/tests/conftest.py b/src/eval/tests/conftest.py index a9fa7d88..82d2ce2a 100644 --- a/src/eval/tests/conftest.py +++ b/src/eval/tests/conftest.py @@ -49,6 +49,9 @@ def create_test_eval_config( "image": { "camera_logical_id": "camera_front_wide_120fov", }, + "open_loop_collision": { + "horizon_s": 3.0, + }, }, "database": { "upload_metadata": False, diff --git a/src/eval/tests/test_open_loop_collision.py b/src/eval/tests/test_open_loop_collision.py new file mode 100644 index 00000000..6735775d --- /dev/null +++ b/src/eval/tests/test_open_loop_collision.py @@ -0,0 +1,158 @@ +# SPDX-License-Identifier: Apache-2.0 +# Copyright (c) 2026 NVIDIA Corporation + +"""Behavioral tests for the open-loop collision scorer. + +Builds real ``RenderableTrajectory`` / ``DriverResponseAtTime`` objects (the +types the scorer computes on) and a light stand-in for the surrounding +``SimulationResult`` fields it reads. +""" + +from types import SimpleNamespace + +import numpy as np + +from eval.data import RAABB, DriverResponseAtTime, RenderableTrajectory +from eval.scorers.open_loop_collision import OpenLoopCollisionScorer + +# Identity orientation in the (x, y, z, w) convention used by the geometry +# layer: yaw 0, so a box's length runs along +x and width along +y. +_IDENTITY_QUAT = [0.0, 0.0, 0.0, 1.0] + + +def _raabb() -> RAABB: + # No corner rounding so boxes are exact 4.5 x 2.0 rectangles. + return RAABB(size_x=4.5, size_y=2.0, size_z=1.5, corner_radius_m=0.0) + + +def _trajectory( + timestamps_us: list[int], xy: list[tuple[float, float]] +) -> RenderableTrajectory: + positions = np.array([[x, y, 0.0] for x, y in xy], dtype=np.float32) + quaternions = np.array([_IDENTITY_QUAT] * len(xy), dtype=np.float32) + return RenderableTrajectory( + timestamps_us=np.array(timestamps_us, dtype=np.uint64), + positions=positions, + quaternions=quaternions, + raabb=_raabb(), + ) + + +def _driver_response(now_us: int, plan: RenderableTrajectory) -> DriverResponseAtTime: + return DriverResponseAtTime( + now_time_us=now_us, + time_query_us=now_us, + selected_trajectory=plan, + sampled_trajectories=[], + ) + + +def _scorer(horizon_s: float) -> OpenLoopCollisionScorer: + cfg = SimpleNamespace( + scorers=SimpleNamespace( + open_loop_collision=SimpleNamespace(horizon_s=horizon_s) + ) + ) + return OpenLoopCollisionScorer(cfg) + + +def _sim_result( + responses: list[DriverResponseAtTime], actor_trajectories: dict +) -> SimpleNamespace: + return SimpleNamespace( + actor_trajectories=actor_trajectories, + driver_responses=SimpleNamespace(per_timestep_driver_responses=responses), + ) + + +def test_flags_step_whose_plan_drives_into_a_logged_agent() -> None: + """A plan passing through a static agent within the horizon scores 1.0.""" + # Static agent parked at x=20; ego plan drives straight through x=20 at t=2s. + agent = _trajectory([0, 1_000_000, 2_000_000, 3_000_000], [(20.0, 0.0)] * 4) + plan = _trajectory( + [0, 1_000_000, 2_000_000, 3_000_000], + [(0.0, 0.0), (10.0, 0.0), (20.0, 0.0), (30.0, 0.0)], + ) + sim_result = _sim_result([_driver_response(0, plan)], {"agent": agent}) + + [metric] = _scorer(horizon_s=3.0).calculate(sim_result) + + assert metric.name == "open_loop_collision" + assert metric.values == [True] + assert metric.valid == [True] + assert metric.aggregate() == 1.0 + + +def test_clean_plan_and_horizon_clipping() -> None: + """A plan that only collides after the horizon scores 0.0.""" + # Agent parked at x=20. The plan is clear within a 1s horizon (only reaches + # x=10) but would collide at t=2s, so a 1s horizon must still score 0. + agent = _trajectory([0, 1_000_000, 2_000_000, 3_000_000], [(20.0, 0.0)] * 4) + plan = _trajectory( + [0, 1_000_000, 2_000_000, 3_000_000], + [(0.0, 0.0), (10.0, 0.0), (20.0, 0.0), (30.0, 0.0)], + ) + sim_result = _sim_result([_driver_response(0, plan)], {"agent": agent}) + + [metric] = _scorer(horizon_s=1.0).calculate(sim_result) + + assert metric.values == [False] + assert metric.valid == [True] + + +def test_mean_aggregates_collision_rate() -> None: + """MEAN over steps gives the fraction of plans that collide.""" + agent = _trajectory( + [0, 1_000_000, 2_000_000, 3_000_000, 4_000_000], [(20.0, 0.0)] * 5 + ) + colliding_plan = _trajectory( + [0, 1_000_000, 2_000_000], [(0.0, 0.0), (10.0, 0.0), (20.0, 0.0)] + ) + # Second plan swerves to y=10, clearing the agent (width 2.0 -> |y|<=1). + clean_plan = _trajectory( + [1_000_000, 2_000_000, 3_000_000, 4_000_000], + [(10.0, 0.0), (20.0, 10.0), (30.0, 10.0), (40.0, 10.0)], + ) + sim_result = _sim_result( + [_driver_response(0, colliding_plan), _driver_response(1_000_000, clean_plan)], + {"agent": agent}, + ) + + [metric] = _scorer(horizon_s=3.0).calculate(sim_result) + + assert metric.values == [True, False] + assert metric.timestamps_us == [0, 1_000_000] + assert metric.aggregate() == 0.5 + + +def test_ego_actor_is_skipped() -> None: + """The ego's own recorded trajectory is never treated as an obstacle. + + The plan drives straight along the ego's OWN recorded path, so the only + box overlap is ego-vs-ego. With EGO the sole actor, the metric must be 0.0; + it would be 1.0 if the ``agent_id != "EGO"`` filter were dropped. + """ + ego_recorded = _trajectory( + [0, 1_000_000, 2_000_000], [(0.0, 0.0), (10.0, 0.0), (20.0, 0.0)] + ) + plan = _trajectory( + [0, 1_000_000, 2_000_000], [(0.0, 0.0), (10.0, 0.0), (20.0, 0.0)] + ) + sim_result = _sim_result([_driver_response(0, plan)], {"EGO": ego_recorded}) + + [metric] = _scorer(horizon_s=3.0).calculate(sim_result) + + assert metric.values == [False] + assert metric.valid == [True] + + +def test_step_without_future_plan_is_invalid() -> None: + """A plan holding only the current pose cannot be scored and is invalid.""" + agent = _trajectory([0, 1_000_000], [(20.0, 0.0)] * 2) + plan = _trajectory([0], [(0.0, 0.0)]) + sim_result = _sim_result([_driver_response(0, plan)], {"agent": agent}) + + [metric] = _scorer(horizon_s=3.0).calculate(sim_result) + + assert metric.valid == [False] + assert np.isnan(metric.aggregate()) diff --git a/src/eval/tests/test_scenario_evaluator.py b/src/eval/tests/test_scenario_evaluator.py index a9b6c6b9..a4659aef 100644 --- a/src/eval/tests/test_scenario_evaluator.py +++ b/src/eval/tests/test_scenario_evaluator.py @@ -94,6 +94,24 @@ def test_gt_dist_traveled_is_full_recording_distance( assert result.aggregated_metrics["gt_dist_traveled_m"] == pytest.approx(9.0) +def test_first_driven_timestamp_uses_render_anchor( + minimal_eval_input: ScenarioEvalInput, + default_eval_config: EvalConfig, +) -> None: + """Handover is anchored on render_start + force_gt, independent of the gap.""" + minimal_eval_input.force_gt_duration_us = 200_000 + minimal_eval_input.session_metadata.render_start_timestamp_us = 250_000 + + simulation_result = SimulationResult.from_scenario_input( + minimal_eval_input, default_eval_config + ) + + assert simulation_result.first_driven_timestamp_us == ( + minimal_eval_input.session_metadata.render_start_timestamp_us + + minimal_eval_input.force_gt_duration_us + ) + + class SimpleScenarioEvaluatorClass: """Test the ScenarioEvaluator class. @@ -180,24 +198,6 @@ def test_no_collision_scenario( # With only EGO and no other actors, there should be no collisions assert result.aggregated_metrics.get("collision_any", 0.0) == 0.0 - def test_first_driven_timestamp_uses_force_gt_duration( - self, - minimal_eval_input: ScenarioEvalInput, - default_eval_config: EvalConfig, - ) -> None: - """Force-GT filtering starts one control step after the force-GT window.""" - minimal_eval_input.force_gt_duration_us = 200_000 - - simulation_result = SimulationResult.from_scenario_input( - minimal_eval_input, default_eval_config - ) - - assert simulation_result.first_driven_timestamp_us == ( - minimal_eval_input.session_metadata.start_timestamp_us - + minimal_eval_input.force_gt_duration_us - + minimal_eval_input.session_metadata.control_timestep_us - ) - class TestScenarioEvalResult: """Test the ScenarioEvalResult dataclass.""" diff --git a/src/grpc/alpasim_grpc/v0/logging.proto b/src/grpc/alpasim_grpc/v0/logging.proto index 3d6dd37d..8688934c 100644 --- a/src/grpc/alpasim_grpc/v0/logging.proto +++ b/src/grpc/alpasim_grpc/v0/logging.proto @@ -29,11 +29,15 @@ message RolloutMetadata { string scene_id = 2; uint32 batch_size = 3 [deprecated = true]; // always 1 uint32 n_sim_steps = 4; + // Egomotion-context origin (rig trajectory start), not the render anchor. fixed64 start_timestamp_us = 5; fixed64 control_timestep_us = 6; string nre_runid = 7; string nre_version= 8; string nre_uuid = 9; + // Render anchor (first camera frame shutter close) / start of force-GT. + // The policy handover is render_start_timestamp_us + force_gt_duration. + fixed64 render_start_timestamp_us = 10; } message ActorDefinitions { diff --git a/src/grpc/alpasim_grpc/v0/runtime.proto b/src/grpc/alpasim_grpc/v0/runtime.proto index 0f96fb7c..6926cc59 100644 --- a/src/grpc/alpasim_grpc/v0/runtime.proto +++ b/src/grpc/alpasim_grpc/v0/runtime.proto @@ -81,6 +81,12 @@ enum TimeAggregation { TIME_AGGREGATION_LAST = 5; } +enum RolloutErrorCode { + ROLLOUT_ERROR_CODE_NONE = 0; + ROLLOUT_ERROR_CODE_UNSPECIFIED = 1; + ROLLOUT_ERROR_CODE_INVALID_SCENE = 2; +} + message SimulationReturn { // A single named metric sampled at each simulation timestep. message TimestepMetric { @@ -98,6 +104,7 @@ message SimulationReturn { string error = 4; repeated TimestepMetric timestep_metrics = 5; map aggregated_metrics = 6; + RolloutErrorCode error_code = 7; } common.VersionId runtime_version = 1; diff --git a/src/physics/alpasim_physics/backend.py b/src/physics/alpasim_physics/backend.py index 280296d8..657d4adc 100644 --- a/src/physics/alpasim_physics/backend.py +++ b/src/physics/alpasim_physics/backend.py @@ -8,8 +8,8 @@ import scipy.spatial.transform as scipy_trans import warp as wp from alpasim_grpc.v0.physics_pb2 import PhysicsGroundIntersectionReturn -from alpasim_physics.ply_io import load_mesh_vf from alpasim_physics.utils import batch_so3_trans_2_se3, so3_trans_2_se3 +from alpasim_utils.ply_io import load_mesh_vf try: import polyscope as ps diff --git a/src/physics/pyproject.toml b/src/physics/pyproject.toml index 46fc09c7..f4fa7239 100644 --- a/src/physics/pyproject.toml +++ b/src/physics/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "alpasim-physics" -version = "1.53.0" +version = "1.66.0" description = "Physics micro-service of the Alpamayo Sim" requires-python = ">=3.11,<3.13" dependencies = [ diff --git a/src/physics/tests/test_backend.py b/src/physics/tests/test_backend.py index b3c96504..79752699 100644 --- a/src/physics/tests/test_backend.py +++ b/src/physics/tests/test_backend.py @@ -7,8 +7,8 @@ import pytest from alpasim_grpc.v0.common_pb2 import AABB, Pose, Quat, Vec3 from alpasim_physics.backend import PhysicsBackend -from alpasim_physics.ply_io import save_mesh_vf from alpasim_physics.utils import aabb_to_ndarray, pose_grpc_to_ndarray +from alpasim_utils.ply_io import save_mesh_vf @pytest.fixture diff --git a/src/runtime/alpasim_runtime/address_pool.py b/src/runtime/alpasim_runtime/address_pool.py index 9f5b8755..4f6ea830 100644 --- a/src/runtime/alpasim_runtime/address_pool.py +++ b/src/runtime/alpasim_runtime/address_pool.py @@ -49,9 +49,7 @@ def __init__( ): self.skip = skip self._total_capacity: int = 0 - self._all_addresses: frozenset[str] = ( - frozenset(addresses) if not skip else frozenset() - ) + self._address_order: tuple[str, ...] = tuple(addresses) if not skip else () self._slots: deque[ServiceAddress] = deque() if not skip: for addr in addresses: @@ -77,6 +75,18 @@ def free_addresses(self) -> set[str]: """Return unique addresses that currently have at least one free slot.""" return {slot.address for slot in self._slots} + @property + def address_order(self) -> tuple[str, ...]: + """All configured addresses, in config order for deterministic tie-breaking.""" + return self._address_order + + def free_slot_counts(self) -> dict[str, int]: + """Return the current number of free slots for each configured address.""" + counts = {address: 0 for address in self._address_order} + for slot in self._slots: + counts[slot.address] += 1 + return counts + def try_acquire_for_address(self, address: str) -> ServiceAddress | None: """Acquire a free slot for a specific *address*, or ``None`` if unavailable.""" if self.skip: @@ -87,10 +97,6 @@ def try_acquire_for_address(self, address: str) -> ServiceAddress | None: return slot return None - def all_addresses(self) -> frozenset[str]: - """All configured addresses, regardless of current slot availability.""" - return self._all_addresses - @property def total_capacity(self) -> int | None: """Total number of slots. None for skip pools (non-limiting).""" diff --git a/src/runtime/alpasim_runtime/config.py b/src/runtime/alpasim_runtime/config.py index b665f42c..e665ba44 100644 --- a/src/runtime/alpasim_runtime/config.py +++ b/src/runtime/alpasim_runtime/config.py @@ -262,6 +262,7 @@ class PhysicsUpdateMode(Enum): class RouteGeneratorType(Enum): MAP = 0 RECORDED = 1 + NONE = 2 class RenderBundling(Enum): @@ -353,10 +354,36 @@ class UserEndpointConfig: class RuntimePrometheusConfig: """Runtime Prometheus settings generated by the wizard.""" - url: str = MISSING + url: str | None = MISSING worker_ports: list[int] = MISSING +@dataclass +class SceneAffineDispatchConfig: + """Cache-aware routing of renderer jobs to GPUs with the scene loaded.""" + + # When True, the scheduler routes renderer jobs to GPUs that already + # have the requested scene cached, avoiding cold-load penalties. Requires + # an NRE build with the get_loaded_scenes RPC (renderer=internal_nre; + # public NRE drops don't have it yet). The remaining settings in this + # section only apply when enabled. + enabled: bool = False + + # Interval in seconds for periodically re-syncing the renderer pool's + # local scene cache from NRE via get_loaded_scenes. None disables + # periodic refresh. + cache_refresh_interval_s: float | None = 3.0 + + # Maximum loaded or loading renderer locations created for one scene. + max_renderers_per_scene: int = 2 + + # Maximum distinct scenes loading or executing on one renderer before it + # becomes ineligible for cold dispatch. Keeps the working set within the + # renderer's NRE backend cache. None disables the cap. (Multiple rollouts + # of the same scene can still be dispatched to the same renderer.) + max_scenes_per_renderer: int | None = None + + @dataclass class UserSimulatorConfig: """The section of simulator config created manually by the user""" @@ -374,19 +401,17 @@ class UserSimulatorConfig: # >1 = multi-worker mode with subprocess-based parallelism nr_workers: int = MISSING + # Number of times to retry a rollout after a failed attempt. + max_rollout_retries: int = 2 + renderer: RendererConfig = MISSING # Runtime scene provider configuration. scene_provider: SceneProviderConfig = MISSING - # When True, the scheduler routes renderer jobs to GPUs that already - # have the requested scene cached, avoiding cold-load penalties. - scene_affine_dispatch: bool = False - - # Interval in seconds for periodically re-syncing the renderer pool's - # local scene cache from NRE via get_loaded_scenes. None disables - # periodic refresh. Only effective when scene_affine_dispatch is True. - cache_refresh_interval_s: float | None = 5.0 + scene_affine_dispatch: SceneAffineDispatchConfig = field( + default_factory=SceneAffineDispatchConfig + ) prometheus: RuntimePrometheusConfig = MISSING diff --git a/src/runtime/alpasim_runtime/daemon/engine.py b/src/runtime/alpasim_runtime/daemon/engine.py index c9b26a0b..3d4bbffa 100644 --- a/src/runtime/alpasim_runtime/daemon/engine.py +++ b/src/runtime/alpasim_runtime/daemon/engine.py @@ -4,13 +4,13 @@ from __future__ import annotations import logging +import os from collections import defaultdict from collections.abc import Callable from uuid import uuid4 from alpasim_grpc.v0 import logging_pb2, runtime_pb2 from alpasim_runtime.address_pool import AddressPool -from alpasim_runtime.config import RendererKind from alpasim_runtime.daemon.scheduler import DaemonScheduler, DaemonUnavailableError from alpasim_runtime.errors import UnknownSceneError from alpasim_runtime.runtime_context import ( @@ -87,6 +87,7 @@ def build_simulation_return( success=result.success, rollout_uuid=result.rollout_uuid or "", error=result.error or "", + error_code=result.error_code, timestep_metrics=_build_timestep_metrics(result), aggregated_metrics=_build_aggregated_metrics(result), ) @@ -158,6 +159,7 @@ class InvalidRequestError(ValueError): def build_pending_jobs_from_request( request: runtime_pb2.SimulationRequest, + request_id: str, has_scene: Callable[[str], bool], ) -> list[PendingRolloutJob]: """Expand a SimulationRequest into individual PendingRolloutJob entries. @@ -167,6 +169,7 @@ def build_pending_jobs_from_request( Args: request: The simulation request to expand. + request_id: Identifier stamped onto every job for result routing. has_scene: Callable that returns True for known scene_ids. Raises: @@ -195,6 +198,7 @@ def build_pending_jobs_from_request( for rollout_idx in range(spec.nr_rollouts): jobs.append( PendingRolloutJob( + request_id=request_id, job_id=uuid4().hex, scene_id=spec.scenario_id, rollout_spec_index=spec_index, @@ -286,24 +290,13 @@ async def startup(self) -> None: version_ids=runtime_context.version_ids, ) - scene_affine = runtime_context.config.user.scene_affine_dispatch - if runtime_context.config.user.renderer.kind == RendererKind.video_model: - if scene_affine: - logger.info( - "Scene-affine dispatch auto-disabled: video_model renderer " - "has no per-scene GPU cache" - ) - scene_affine = False - + affine_config = runtime_context.config.user.scene_affine_dispatch scheduler = DaemonScheduler( pools=runtime_context.pools, runtime=worker_runtime, - scene_affine_dispatch=scene_affine, - cache_refresh_interval_s=( - runtime_context.config.user.cache_refresh_interval_s - if scene_affine - else None - ), + scene_affine_dispatch=affine_config, + max_rollout_retries=runtime_context.config.user.max_rollout_retries, + rollouts_dir=os.path.join(self._log_dir, "rollouts"), ) except Exception: if worker_runtime is not None: @@ -311,7 +304,7 @@ async def startup(self) -> None: raise try: - if scene_affine: + if affine_config.enabled: await scheduler.warm_start() except BaseException: await scheduler.shutdown(reason="warm_start failed") @@ -356,7 +349,7 @@ async def simulate( request_id = uuid4().hex try: - jobs = build_pending_jobs_from_request(request, self._has_scene) + jobs = build_pending_jobs_from_request(request, request_id, self._has_scene) except UnknownSceneError as exc: raise InvalidRequestError(str(exc)) from exc diff --git a/src/runtime/alpasim_runtime/daemon/scheduler.py b/src/runtime/alpasim_runtime/daemon/scheduler.py index 8e53f0bb..fecb2b7e 100644 --- a/src/runtime/alpasim_runtime/daemon/scheduler.py +++ b/src/runtime/alpasim_runtime/daemon/scheduler.py @@ -5,10 +5,14 @@ import asyncio import logging -from collections import defaultdict, deque +import shutil +from collections import Counter, defaultdict, deque from contextlib import suppress -from dataclasses import dataclass +from dataclasses import dataclass, replace +from pathlib import Path +from time import monotonic from typing import Protocol +from uuid import uuid4 from alpasim_runtime.address_pool import ( AddressPool, @@ -16,11 +20,12 @@ release_all, try_acquire_all, ) -from alpasim_runtime.config import BASE_SERVICE_NAMES +from alpasim_runtime.config import BASE_SERVICE_NAMES, SceneAffineDispatchConfig from alpasim_runtime.daemon.request_store import RequestStore from alpasim_runtime.nre_introspection import get_loaded_scenes from alpasim_runtime.worker.ipc import ( AssignedRolloutJob, + DispatchKind, JobResult, PendingRolloutJob, ServiceEndpoints, @@ -35,11 +40,45 @@ class DaemonUnavailableError(RuntimeError): pass +def _clear_retry_rollout_dir(pending_job: PendingRolloutJob, rollouts_dir: str) -> None: + """Remove artifacts that would otherwise be reused by a retry.""" + if not pending_job.session_uuid: + return + + if ( + Path(pending_job.scene_id).name != pending_job.scene_id + or Path(pending_job.session_uuid).name != pending_job.session_uuid + ): + raise ValueError( + "Retry rollout scene and session identifiers must each be one path " + f"component: scene_id={pending_job.scene_id!r} " + f"session_uuid={pending_job.session_uuid!r}" + ) + + rollouts_root = Path(rollouts_dir).resolve() + scene_dir = (rollouts_root / pending_job.scene_id).resolve() + rollout_dir = scene_dir / pending_job.session_uuid + resolved_rollout_dir = rollout_dir.resolve() + + if scene_dir.parent != rollouts_root or resolved_rollout_dir.parent != scene_dir: + raise ValueError( + "Retry rollout directory must be a direct child of the rollouts root " + f"and scene directory: scene_id={pending_job.scene_id!r} " + f"session_uuid={pending_job.session_uuid!r}" + ) + if rollout_dir.is_symlink(): + raise ValueError(f"Refusing to remove retry rollout symlink: {rollout_dir}") + if rollout_dir.exists(): + logger.info("Removing artifacts from failed rollout attempt: %s", rollout_dir) + shutil.rmtree(rollout_dir) + + @dataclass class _InFlightEntry: """Bookkeeping for a dispatched job awaiting its result.""" - scene_id: str + pending_job: PendingRolloutJob + dispatch_kind: DispatchKind # For telemetry pools: dict[str, AddressPool] acquired: dict[str, ServiceAddress] @@ -68,17 +107,16 @@ class PendingReservation: the caller. """ - request_id: str job: PendingRolloutJob renderer_slot: ServiceAddress - is_affine_hit: bool + dispatch_kind: DispatchKind class DispatchStrategy(Protocol): """Narrow interface for job-selection and pending-job bookkeeping. Two concrete implementations exist: ``FifoDispatch`` (strict submission - order) and ``SceneAffineDispatch`` (three-tier cache-aware priority). + order) and ``SceneAffineDispatch`` (bounded cache-aware replication). Dispatch follows a two-phase reservation/commit protocol: @@ -94,12 +132,13 @@ class DispatchStrategy(Protocol): @property def pending_count(self) -> int: ... - def add_pending(self, request_id: str, job: PendingRolloutJob) -> None: ... + def add_pending(self, job: PendingRolloutJob) -> None: ... def try_reserve(self) -> PendingReservation | None: """Select the best pending job and pre-acquire a renderer slot. - Returns ``None`` when no jobs are pending or no renderer slot is free. + Must only be called while ``pending_count > 0``. Returns ``None`` + when no renderer slot is free for any pending job. """ ... @@ -107,7 +146,13 @@ def commit(self, reservation: PendingReservation) -> None: """Finalize a reservation: remove from pending and record in-flight.""" ... - def on_result(self, scene_id: str, renderer_address: str, success: bool) -> None: + def on_result( + self, + scene_id: str, + renderer_address: str, + dispatch_kind: DispatchKind, + success: bool, + ) -> None: """Called when a job completes.""" ... @@ -116,7 +161,7 @@ def drain_pending_request_ids(self) -> set[str]: ... async def shutdown(self) -> None: - """Cancel background tasks and log summary statistics.""" + """Log summary statistics.""" ... @@ -125,32 +170,39 @@ class FifoDispatch: def __init__(self, *, renderer_pool: AddressPool) -> None: self._renderer_pool = renderer_pool - self._queue: deque[tuple[str, PendingRolloutJob]] = deque() + self._queue: deque[PendingRolloutJob] = deque() @property def pending_count(self) -> int: return len(self._queue) - def add_pending(self, request_id: str, job: PendingRolloutJob) -> None: - self._queue.append((request_id, job)) + def add_pending(self, job: PendingRolloutJob) -> None: + self._queue.append(job) def try_reserve(self) -> PendingReservation | None: - if not self._queue: - return None slot = self._renderer_pool.try_acquire() if slot is None: return None - request_id, job = self._queue[0] - return PendingReservation(request_id, job, slot, is_affine_hit=False) + return PendingReservation( + self._queue[0], + slot, + dispatch_kind="fifo", + ) def commit(self, reservation: PendingReservation) -> None: self._queue.popleft() - def on_result(self, scene_id: str, renderer_address: str, success: bool) -> None: + def on_result( + self, + scene_id: str, + renderer_address: str, + dispatch_kind: DispatchKind, + success: bool, + ) -> None: return def drain_pending_request_ids(self) -> set[str]: - ids = {req_id for req_id, _ in self._queue} + ids = {job.request_id for job in self._queue} self._queue.clear() return ids @@ -159,46 +211,90 @@ async def shutdown(self) -> None: class SceneAffineDispatch: - """Three-tier cache-aware dispatch strategy. - - Tier 1 -- Affine: pick a job whose scene is already cached *or - in-flight* on a free renderer GPU. Likely warm-cache hit. - - Tier 2 -- New scene: pick a job for a scene not yet cached by - any GPU. Maximises cache diversity across GPUs. - - Tier 3 -- Fallback: pick any pending job. + """Cache-aware dispatch with bounded per-scene renderer replication. + + Pending jobs are queued per scene, and the strategy tracks the scene + "locations" of each renderer address: cache contents confirmed by NRE + introspection snapshots (``sync_scene_cache``) plus cold loads committed + by this strategy that are still awaiting confirmation. + + ``try_reserve`` picks the next dispatch in two priority tiers: + + 1. ``cached_affine``: a renderer whose confirmed cache holds a pending + scene, so the rollout skips the cold load. Among matches, the address + with the most free slots wins, spreading work across replicas. + 2. cold load: walk pending scenes in arrival order and cold-load the + first one with fewer than ``max_renderers_per_scene`` locations onto + a renderer where it is absent. The dispatch kind records whether the + load creates the scene's first location (``cold_initial``) or an + additional one (``cold_replica``). Earlier-queued scenes replicate + up to the bound before later scenes get their first location, so a + later scene waits at most ``max_renderers_per_scene`` cold loads per + scene queued ahead of it. + + Cold loads land on the least-loaded eligible renderer: fewest active + scenes (loading or with in-flight rollouts) first, most free slots as + tie-break. Renderers with ``max_scenes_per_renderer`` active scenes + are ineligible for cold dispatch, which keeps each renderer's working + set within its NRE backend cache. """ def __init__( self, *, renderer_pool: AddressPool, - cache_refresh_interval_s: float | None = 5.0, + max_renderers_per_scene: int, + max_scenes_per_renderer: int | None, ) -> None: + if max_renderers_per_scene <= 0: + raise ValueError("max_renderers_per_scene must be positive") + if max_scenes_per_renderer is not None and max_scenes_per_renderer <= 0: + raise ValueError("max_scenes_per_renderer must be positive") self._renderer_pool = renderer_pool - self._cache_refresh_interval_s = cache_refresh_interval_s - - self._pending_by_scene: dict[str, deque[tuple[str, PendingRolloutJob]]] = {} - # In-flight scene<->address tracking so the dispatch tiers can - # see what's been dispatched but not yet released. - # Counts (not sets) because multiple jobs for the same scene - # can be on the same address (n_concurrent > 1). - self._inflight_addr_scenes: dict[str, dict[str, int]] = defaultdict( - lambda: defaultdict(int) - ) # address --> {scene --> count} - - # Per-address set of known cached scenes (written only by sync_scene_cache). + self._max_renderers_per_scene = max_renderers_per_scene + self._max_scenes_per_renderer = max_scenes_per_renderer + + self._pending_by_scene: dict[str, deque[PendingRolloutJob]] = {} + + # Successful introspection snapshots and committed cold loads respectively. self._address_scenes: dict[str, set[str]] = {} + self._loading_addr_scenes: dict[str, set[str]] = defaultdict(set) - self._affine_hits = 0 - self._total_dispatched = 0 + # Last snapshot per address, kept only to log cache-change diffs. + self._prev_snapshots: dict[str, frozenset[str]] = {} - self._cache_refresh_task: asyncio.Task[None] | None = None + # In-flight rollout counts per renderer address and scene. A scene is + # "active" on an address while it is loading or has in-flight rollouts; + # idle cached scenes are evictable by NRE and do not count. + self._inflight_addr_scenes: dict[str, Counter[str]] = defaultdict(Counter) + + self._dispatch_counts: Counter[DispatchKind] = Counter() + + def sync_scene_cache(self, address: str, scene_ids: list[str]) -> bool: + """Apply one authoritative cache snapshot from a renderer address. + + Replaces the cached-scene set for *address* with the snapshot; scenes + marked as loading that appear in it are confirmed and unmarked, while + loading scenes absent from it stay marked (the cold load is still in + flight — introspection only reports completed loads). + + Returns whether scheduler-relevant state changed: the cached set + differs, or a load was confirmed (which frees active-scene capacity + even when the cached set is unchanged), so the caller knows to run a + dispatch pass. + """ + scenes = set(scene_ids) + previous = self._address_scenes.get(address, set()) + loading = self._loading_addr_scenes.get(address) + confirmed_loading = set() if loading is None else loading & scenes + + self._address_scenes[address] = scenes + if loading is not None: + loading.difference_update(confirmed_loading) + if not loading: + del self._loading_addr_scenes[address] - def sync_scene_cache(self, address: str, scene_ids: list[str]) -> None: - """Overwrite the scene set for *address* with the server's authoritative list.""" - self._address_scenes[address] = set(scene_ids) + return previous != scenes or bool(confirmed_loading) def cached_scenes(self, address: str) -> set[str]: """Return the scenes known to be cached on *address*.""" @@ -208,27 +304,57 @@ def is_scene_cached(self, scene_id: str) -> bool: """True if at least one address has *scene_id* in its cache.""" return any(scene_id in scenes for scenes in self._address_scenes.values()) - async def warm_start(self) -> None: - """Perform initial cache sync from all NRE addresses, then start refresh loop. + def _scene_locations(self, scene_id: str) -> set[str]: + return { + address + for address in self._renderer_pool.address_order + if scene_id in self._address_scenes.get(address, set()) + or scene_id in self._loading_addr_scenes.get(address, set()) + } + + def _active_scene_counts(self) -> dict[str, int]: + """Distinct scenes loading or executing per renderer address.""" + return { + address: len( + set(self._inflight_addr_scenes.get(address, {})) + | self._loading_addr_scenes.get(address, set()) + ) + for address in self._renderer_pool.address_order + } - Raises ``IntrospectionNotSupportedError`` if any NRE server returns - UNIMPLEMENTED, allowing fast failure at startup when the NRE image is - incompatible with scene-affine dispatch. - """ - if self._renderer_pool.skip or not self._renderer_pool.all_addresses(): - return + async def refresh_cache(self, *, raise_on_unimplemented: bool = False) -> bool: + """Query all renderer addresses and sync the local cache mirror. - snapshot = await self._refresh_cache_once(raise_on_unimplemented=True) - if snapshot: - total_scenes = sum(len(s) for s in snapshot.values()) - logger.info( - "Warm-started %d renderer address(es) with %d cached scene(s)", - len(snapshot), - total_scenes, + Returns whether scheduler-relevant state changed. Raises + ``IntrospectionNotSupportedError`` when *raise_on_unimplemented* is + set and an NRE server returns UNIMPLEMENTED, allowing fast failure + at startup when the NRE image is incompatible with scene-affine + dispatch. + """ + changed = False + for address in sorted(self._renderer_pool.address_order): + loaded = await get_loaded_scenes( + address, raise_on_unimplemented=raise_on_unimplemented ) - - if self._cache_refresh_interval_s is not None: - self._cache_refresh_task = asyncio.create_task(self._cache_refresh_loop()) + if loaded is None: + continue + scene_ids = list(loaded.keys()) + current = frozenset(scene_ids) + previous = self._prev_snapshots.get(address, frozenset()) + if current != previous: + added = sorted(current - previous) + removed = sorted(previous - current) + logger.info( + "Cache changed on %s: +%d scene(s) %s, -%d scene(s) %s", + address, + len(added), + added or "[]", + len(removed), + removed or "[]", + ) + self._prev_snapshots[address] = current + changed = self.sync_scene_cache(address, scene_ids) or changed + return changed # -- pending-job bookkeeping -- @@ -236,60 +362,164 @@ async def warm_start(self) -> None: def pending_count(self) -> int: return sum(len(q) for q in self._pending_by_scene.values()) - def add_pending(self, request_id: str, job: PendingRolloutJob) -> None: + def add_pending(self, job: PendingRolloutJob) -> None: scene = job.scene_id if scene not in self._pending_by_scene: self._pending_by_scene[scene] = deque() - self._pending_by_scene[scene].append((request_id, job)) + self._pending_by_scene[scene].append(job) - def _pop_pending(self, scene_id: str) -> tuple[str, PendingRolloutJob]: + def _pop_pending(self, scene_id: str) -> PendingRolloutJob: q = self._pending_by_scene[scene_id] - entry = q.popleft() + job = q.popleft() if not q: del self._pending_by_scene[scene_id] - return entry + return job + + # -- job selection (two-tier priority) -- + + def _best_affine_match( + self, + address_scenes: dict[str, set[str]], + free_slot_counts: dict[str, int], + ) -> tuple[str, str] | None: + """Pair a pending scene with an address that already holds it. + + Candidates are addresses that have a free slot and hold at least one + scene with pending jobs. Among those, the address with the most free + slots wins (spreading affine work across replicas); its scene is the + earliest-queued pending scene it holds. + + Args: + address_scenes: Scene sets per renderer address to match pending + jobs against, e.g. ``_address_scenes`` for cached-scene + affinity. + free_slot_counts: Free slots per address, from ``try_reserve``. + + Returns: + The chosen ``(address, scene_id)`` pair, or ``None`` if no + address with a free slot holds a pending scene. + """ + matching_addresses = [ + address + for address in self._renderer_pool.address_order + if free_slot_counts[address] > 0 + and any( + scene in self._pending_by_scene + for scene in address_scenes.get(address, {}) + ) + ] + if not matching_addresses: + return None + address = max(matching_addresses, key=free_slot_counts.__getitem__) + scenes = address_scenes.get(address, {}) + scene = next(scene for scene in self._pending_by_scene if scene in scenes) + return address, scene + + def _reserve_affine( + self, + address_scenes: dict[str, set[str]], + free_slot_counts: dict[str, int], + ) -> PendingReservation | None: + """Reserve a slot for the best affine match in *address_scenes*. - # -- job selection (three-tier priority) -- + Returns a ``cached_affine`` reservation for the head job of the + matched scene's queue, or ``None`` when no match exists. + """ + match = self._best_affine_match(address_scenes, free_slot_counts) + if match is None: + return None + address, scene = match + slot = self._renderer_pool.try_acquire_for_address(address) + # _best_affine_match only returns addresses with free slots. + assert slot is not None + return PendingReservation( + self._pending_by_scene[scene][0], + slot, + dispatch_kind="cached_affine", + ) - def _is_scene_inflight(self, scene_id: str) -> bool: - """True if *scene_id* is in-flight on any renderer address.""" - return any(scene_id in scenes for scenes in self._inflight_addr_scenes.values()) + def _reserve_non_affine( + self, + job: PendingRolloutJob, + dispatch_kind: DispatchKind, + cold_candidates: list[str], + excluded_addresses: set[str], + ) -> PendingReservation | None: + """Reserve a slot for *job* on a renderer that will cold-load its scene. + + Args: + job: Pending job to reserve a slot for. + dispatch_kind: Recorded on the reservation, e.g. ``cold_initial`` + or ``cold_replica``. + cold_candidates: Cold-load-eligible addresses from + ``try_reserve``, ranked best-first. + excluded_addresses: Addresses to skip, typically ones that already + hold or are loading the job's scene. + + Returns: + The reservation with an acquired slot, or ``None`` if every + candidate is excluded. + """ + address = next( + (a for a in cold_candidates if a not in excluded_addresses), None + ) + if address is None: + return None + slot = self._renderer_pool.try_acquire_for_address(address) + assert slot is not None # candidates are filtered on free slots + return PendingReservation( + job, + slot, + dispatch_kind=dispatch_kind, + ) def try_reserve(self) -> PendingReservation | None: - # Tier 1: free GPU slot whose cached *or in-flight* scene has a - # pending job. Iterates free addresses (tiny, ~1-8) x scenes per - # address (small), NOT pending scenes (could be thousands). - for address in self._renderer_pool.free_addresses(): - scenes: set[str] = set(self.cached_scenes(address)) - inflight = self._inflight_addr_scenes.get(address) - if inflight: - scenes.update(inflight) - for scene in scenes: - if scene in self._pending_by_scene: - slot = self._renderer_pool.try_acquire_for_address(address) - if slot is None: - break - request_id, job = self._pending_by_scene[scene][0] - return PendingReservation(request_id, job, slot, is_affine_hit=True) - - # Tier 2: pending scene not yet cached or in-flight on any GPU. - for scene in self._pending_by_scene: - if not self.is_scene_cached(scene) and not self._is_scene_inflight(scene): - slot = self._renderer_pool.try_acquire() - if slot is None: - return None - request_id, job = self._pending_by_scene[scene][0] - return PendingReservation(request_id, job, slot, is_affine_hit=False) - - # Tier 3: fallback -- any pending job, FIFO renderer slot. - if not self._pending_by_scene: + # Slot and active-scene state only changes through commit/on_result, + # so one snapshot serves the whole call. + free_slot_counts = self._renderer_pool.free_slot_counts() + if not any(free_slot_counts.values()): return None - slot = self._renderer_pool.try_acquire() - if slot is None: + + # Tier 1: confirmed cache affinity. + reservation = self._reserve_affine(self._address_scenes, free_slot_counts) + if reservation is not None: + return reservation + + # Cold-load candidates: a free slot and active-scene headroom. Ranked + # once for all cold-load attempts — fewest active scenes first (keeping + # each renderer's NRE cache working set small); most free slots and + # configured order break ties. + active_scene_counts = self._active_scene_counts() + cold_candidates = sorted( + ( + address + for address in self._renderer_pool.address_order + if free_slot_counts[address] > 0 + and ( + self._max_scenes_per_renderer is None + or active_scene_counts[address] < self._max_scenes_per_renderer + ) + ), + key=lambda addr: (active_scene_counts[addr], -free_slot_counts[addr]), + ) + if not cold_candidates: return None - scene_deque = next(iter(self._pending_by_scene.values())) - request_id, job = scene_deque[0] - return PendingReservation(request_id, job, slot, is_affine_hit=False) + + # Tier 2: cold-load scenes in arrival order, adding a location on a + # renderer where the scene is absent, up to the per-scene bound. + for scene, jobs in self._pending_by_scene.items(): + locations = self._scene_locations(scene) + if len(locations) >= self._max_renderers_per_scene: + continue + reservation = self._reserve_non_affine( + jobs[0], + dispatch_kind="cold_initial" if not locations else "cold_replica", + cold_candidates=cold_candidates, + excluded_addresses=locations, + ) + if reservation is not None: + return reservation + return None # -- dispatch / result hooks -- @@ -298,90 +528,58 @@ def commit(self, reservation: PendingReservation) -> None: self._inflight_addr_scenes[reservation.renderer_slot.address][ reservation.job.scene_id ] += 1 - if reservation.is_affine_hit: - self._affine_hits += 1 - self._total_dispatched += 1 - - def on_result(self, scene_id: str, renderer_address: str, success: bool) -> None: - addr_scenes = self._inflight_addr_scenes.get(renderer_address) - if addr_scenes: - addr_scenes[scene_id] -= 1 - if addr_scenes[scene_id] <= 0: - del addr_scenes[scene_id] - if not addr_scenes: - del self._inflight_addr_scenes[renderer_address] + if reservation.dispatch_kind in {"cold_initial", "cold_replica"}: + self._loading_addr_scenes[reservation.renderer_slot.address].add( + reservation.job.scene_id + ) + self._dispatch_counts[reservation.dispatch_kind] += 1 + + def on_result( + self, + scene_id: str, + renderer_address: str, + dispatch_kind: DispatchKind, + success: bool, + ) -> None: + inflight = self._inflight_addr_scenes[renderer_address] + inflight[scene_id] -= 1 + if inflight[scene_id] <= 0: + del inflight[scene_id] + if not inflight: + del self._inflight_addr_scenes[renderer_address] + + if dispatch_kind not in {"cold_initial", "cold_replica"}: + return + + loading = self._loading_addr_scenes.get(renderer_address) + if loading is not None and scene_id in loading: + loading.remove(scene_id) + if not loading: + del self._loading_addr_scenes[renderer_address] + if success: + self._address_scenes.setdefault(renderer_address, set()).add(scene_id) def drain_pending_request_ids(self) -> set[str]: - ids = {req_id for jobs in self._pending_by_scene.values() for req_id, _ in jobs} + ids = { + job.request_id for jobs in self._pending_by_scene.values() for job in jobs + } self._pending_by_scene.clear() return ids # -- lifecycle -- async def shutdown(self) -> None: - if self._cache_refresh_task is not None: - self._cache_refresh_task.cancel() - with suppress(asyncio.CancelledError): - await self._cache_refresh_task - - if self._total_dispatched > 0: - pct = self._affine_hits / self._total_dispatched * 100 + total_dispatched = self._dispatch_counts.total() + if total_dispatched > 0: + affine_hits = self._dispatch_counts["cached_affine"] + pct = affine_hits / total_dispatched * 100 logger.info( "Scene-affine dispatch summary: %d/%d affine hits (%.1f%%)", - self._affine_hits, - self._total_dispatched, + affine_hits, + total_dispatched, pct, ) - async def _refresh_cache_once( - self, *, raise_on_unimplemented: bool = False - ) -> dict[str, frozenset[str]]: - """Query all renderer addresses and sync the local cache mirror. - - Returns a mapping of address → frozenset of cached scene IDs for each - address that responded successfully. - """ - unique_addresses = sorted(self._renderer_pool.all_addresses()) - snapshot: dict[str, frozenset[str]] = {} - for address in unique_addresses: - loaded = await get_loaded_scenes( - address, raise_on_unimplemented=raise_on_unimplemented - ) - if loaded is None: - continue - scene_ids = list(loaded.keys()) - self.sync_scene_cache(address, scene_ids) - snapshot[address] = frozenset(scene_ids) - return snapshot - - async def _cache_refresh_loop(self) -> None: - """Periodically re-sync the scene cache from NRE.""" - assert self._cache_refresh_interval_s is not None - num_addresses = len(self._renderer_pool.all_addresses()) - logger.info( - "Cache refresh loop started: %d address(es), interval=%.1fs", - num_addresses, - self._cache_refresh_interval_s, - ) - prev_snapshots: dict[str, frozenset[str]] = {} - while True: - await asyncio.sleep(self._cache_refresh_interval_s) - current_snapshots = await self._refresh_cache_once() - for address, current in current_snapshots.items(): - prev = prev_snapshots.get(address, frozenset()) - if current != prev: - added = current - prev - removed = prev - current - logger.info( - "Cache changed on %s: +%d scene(s) %s, -%d scene(s) %s", - address, - len(added), - sorted(added) if added else "[]", - len(removed), - sorted(removed) if removed else "[]", - ) - prev_snapshots = current_snapshots - # --------------------------------------------------------------------------- # Scheduler @@ -405,39 +603,76 @@ def __init__( *, pools: dict[str, AddressPool], runtime: WorkerRuntimeProtocol, - scene_affine_dispatch: bool = True, - cache_refresh_interval_s: float | None = 5.0, + scene_affine_dispatch: SceneAffineDispatchConfig, + max_rollout_retries: int = 2, + rollouts_dir: str | None = None, ) -> None: + if max_rollout_retries < 0: + raise ValueError( + f"max_rollout_retries must be non-negative, got {max_rollout_retries}" + ) + self._pools = pools self._runtime = runtime + self._max_rollout_retries = max_rollout_retries + self._rollouts_dir = rollouts_dir + self._dispatch_lock = asyncio.Lock() self._required_service_names = (*BASE_SERVICE_NAMES, "renderer") self._request_store = RequestStore() renderer_pool = pools["renderer"] - if scene_affine_dispatch: + if scene_affine_dispatch.enabled: self._strategy: DispatchStrategy = SceneAffineDispatch( renderer_pool=renderer_pool, - cache_refresh_interval_s=cache_refresh_interval_s, + max_renderers_per_scene=scene_affine_dispatch.max_renderers_per_scene, + max_scenes_per_renderer=scene_affine_dispatch.max_scenes_per_renderer, ) logger.info("Scene-affine dispatch ENABLED for renderer") else: self._strategy = FifoDispatch(renderer_pool=renderer_pool) logger.info("Scene-affine dispatch DISABLED") + self._cache_refresh_interval_s = scene_affine_dispatch.cache_refresh_interval_s + self._cache_refresh_task: asyncio.Task[None] | None = None self._in_flight: dict[str, _InFlightEntry] = {} self._request_pools: dict[str, dict[str, AddressPool]] = {} self._accepting_requests = True self._dispatch_loop_task = asyncio.create_task(self._dispatch_loop()) async def warm_start(self) -> None: - """Seed the dispatch strategy's cache from NRE servers. + """Seed the strategy's cache from NRE servers and start the refresh loop. Only meaningful for SceneAffineDispatch; no-op for FifoDispatch. Raises ``IntrospectionNotSupportedError`` if the NRE image does not support GetLoadedScenes. """ - if isinstance(self._strategy, SceneAffineDispatch): - await self._strategy.warm_start() + if not isinstance(self._strategy, SceneAffineDispatch): + return + if not self._pools["renderer"].address_order: + return + + await self._strategy.refresh_cache(raise_on_unimplemented=True) + + if self._cache_refresh_interval_s is not None: + self._cache_refresh_task = asyncio.create_task(self._cache_refresh_loop()) + + async def _cache_refresh_loop(self) -> None: + """Periodically re-sync the scene cache from NRE and dispatch on changes. + + Cache changes (e.g. NRE evictions) can unblock pending jobs that no + request or job-result event would re-dispatch, so a changed sync + triggers a dispatch round. + """ + assert isinstance(self._strategy, SceneAffineDispatch) + assert self._cache_refresh_interval_s is not None + logger.info( + "Cache refresh loop started: interval=%.1fs", + self._cache_refresh_interval_s, + ) + while True: + await asyncio.sleep(self._cache_refresh_interval_s) + if await self._strategy.refresh_cache(): + await self.dispatch_once() # ------------------------------------------------------------------ # Public API @@ -471,7 +706,7 @@ async def submit_request( await self._request_store.register_request(request_id, expected_jobs=len(jobs)) for job in jobs: - self._strategy.add_pending(request_id, job) + self._strategy.add_pending(job) await self.dispatch_once() @@ -492,10 +727,10 @@ async def shutdown(self, *, reason: str) -> None: """ self._accepting_requests = False - pending_request_ids = self._strategy.drain_pending_request_ids() - for request_id in pending_request_ids: - self._request_pools.pop(request_id, None) - self._request_store.fail_request(request_id, reason) + if self._cache_refresh_task is not None: + self._cache_refresh_task.cancel() + with suppress(asyncio.CancelledError): + await self._cache_refresh_task self._dispatch_loop_task.cancel() with suppress(asyncio.CancelledError): @@ -503,7 +738,18 @@ async def shutdown(self, *, reason: str) -> None: await self._strategy.shutdown() + async with self._dispatch_lock: + pending_request_ids = self._strategy.drain_pending_request_ids() + for request_id in pending_request_ids: + self._request_pools.pop(request_id, None) + self._request_store.fail_request(request_id, reason) + async def dispatch_once(self) -> None: + """Dispatch all currently eligible jobs, serialized across callers.""" + async with self._dispatch_lock: + await self._dispatch_once_locked() + + async def _dispatch_once_locked(self) -> None: """Greedily dispatch pending jobs via the active strategy. The strategy reserves the best job *and* pre-acquires the renderer @@ -515,7 +761,8 @@ async def dispatch_once(self) -> None: if reservation is None: return - pools = self._request_pools.get(reservation.request_id, self._pools) + job = reservation.job + pools = self._request_pools.get(job.request_id, self._pools) required_pools = { name: pools[name] for name in self._required_service_names } @@ -530,10 +777,10 @@ async def dispatch_once(self) -> None: self._strategy.commit(reservation) assigned = AssignedRolloutJob( - request_id=reservation.request_id, - job_id=reservation.job.job_id, - scene_id=reservation.job.scene_id, - rollout_spec_index=reservation.job.rollout_spec_index, + request_id=job.request_id, + job_id=job.job_id, + scene_id=job.scene_id, + rollout_spec_index=job.rollout_spec_index, endpoints=ServiceEndpoints( driver=acquired["driver"], renderer=acquired["renderer"], @@ -541,11 +788,14 @@ async def dispatch_once(self) -> None: trafficsim=acquired["trafficsim"], controller=acquired["controller"], ), - session_uuid=reservation.job.session_uuid, + dispatch_kind=reservation.dispatch_kind, + scheduler_wait_seconds=max(0.0, monotonic() - job.enqueued_at), + session_uuid=job.session_uuid, ) self._runtime.submit_assigned_job(assigned) self._in_flight[assigned.job_id] = _InFlightEntry( - scene_id=reservation.job.scene_id, + pending_job=job, + dispatch_kind=reservation.dispatch_kind, pools=required_pools, acquired=acquired, ) @@ -555,10 +805,46 @@ def on_result(self, result: JobResult) -> None: if entry is None: raise RuntimeError(f"Unknown job_id in result queue: {result.job_id}") + pending_job = entry.pending_job renderer_addr = entry.acquired["renderer"].address - self._strategy.on_result(entry.scene_id, renderer_addr, result.success) + self._strategy.on_result( + pending_job.scene_id, + renderer_addr, + entry.dispatch_kind, + result.success, + ) release_all(entry.pools, entry.acquired) + + if not result.success and pending_job.retry_attempt < self._max_rollout_retries: + retry_job = replace( + pending_job, + job_id=uuid4().hex, + retry_attempt=pending_job.retry_attempt + 1, + ) + if self._rollouts_dir is not None: + try: + _clear_retry_rollout_dir(retry_job, self._rollouts_dir) + except Exception: # noqa: BLE001 + logger.exception( + "Failed to clear artifacts before retrying rollout; " + "recording the failed attempt instead" + ) + self._request_store.record_result(result) + return + logger.warning( + "Retrying failed rollout: scene=%s failed_job=%s retry_job=%s " + "retry=%d/%d error=%s", + retry_job.scene_id, + result.job_id, + retry_job.job_id, + retry_job.retry_attempt, + self._max_rollout_retries, + result.error, + ) + self._strategy.add_pending(retry_job) + return + self._request_store.record_result(result) try: diff --git a/src/runtime/alpasim_runtime/errors.py b/src/runtime/alpasim_runtime/errors.py index 86066b47..b7da2a3f 100644 --- a/src/runtime/alpasim_runtime/errors.py +++ b/src/runtime/alpasim_runtime/errors.py @@ -3,6 +3,8 @@ """Shared runtime exception types.""" +from alpasim_grpc.v0 import runtime_pb2 + class UnknownSceneError(ValueError): """Raised when a scene_id cannot be resolved to a known data source.""" @@ -10,3 +12,20 @@ class UnknownSceneError(ValueError): def __init__(self, scene_id: str): super().__init__(f"No data source found for scene_id: {scene_id}") self.scene_id = scene_id + + +class RolloutError(Exception): + """Base for rollout failures that carry a RolloutErrorCode for SimulationReturn.""" + + error_code: int = runtime_pb2.ROLLOUT_ERROR_CODE_UNSPECIFIED + + +class InvalidSceneError(RolloutError): + """Raised when scene data is permanently unsuitable for a rollout.""" + + error_code = runtime_pb2.ROLLOUT_ERROR_CODE_INVALID_SCENE + + def __init__(self, scene_id: str, detail: str): + super().__init__(f"INVALID_SCENE: Scene {scene_id!r} is invalid: {detail}") + self.scene_id = scene_id + self.detail = detail diff --git a/src/runtime/alpasim_runtime/event_loop.py b/src/runtime/alpasim_runtime/event_loop.py index 70ff851b..07299784 100644 --- a/src/runtime/alpasim_runtime/event_loop.py +++ b/src/runtime/alpasim_runtime/event_loop.py @@ -577,7 +577,7 @@ async def run(self) -> ScenarioEvalResult | None: rollout_duration = time.perf_counter() - rollout_start_time ctx = try_get_context() if ctx is not None: - ctx.rollout_duration.observe(rollout_duration) + ctx.record_rollout_duration(rollout_duration) eval_result = await self._runtime_evaluator.run_evaluation( self.eval_executor diff --git a/src/runtime/alpasim_runtime/events/policy.py b/src/runtime/alpasim_runtime/events/policy.py index 329c85d8..627865f8 100644 --- a/src/runtime/alpasim_runtime/events/policy.py +++ b/src/runtime/alpasim_runtime/events/policy.py @@ -11,6 +11,7 @@ from __future__ import annotations import logging +import time import numpy as np from alpasim_runtime.events.base import ( @@ -22,6 +23,7 @@ from alpasim_runtime.events.force_gt_utils import controller_reference_trajectory from alpasim_runtime.events.state import RolloutState, ServiceBundle from alpasim_runtime.route_generator import RouteGenerator +from alpasim_runtime.telemetry.telemetry_context import try_get_context from alpasim_utils import geometry logger = logging.getLogger(__name__) @@ -119,7 +121,13 @@ async def run(self, state: RolloutState, queue: EventQueue) -> None: # Barrier: all observations (images + egopose + route + GT) must # reach the driver before we call drive(). + barrier_start = time.perf_counter() await ctx.drain_outstanding_tasks() + telemetry_ctx = try_get_context() + if telemetry_ctx is not None: + telemetry_ctx.record_observation_barrier( + time.perf_counter() - barrier_start + ) state.last_egopose_update_us = step_start_us if ctx.force_gt and state.unbound.skip_driver_during_force_gt: diff --git a/src/runtime/alpasim_runtime/events/step.py b/src/runtime/alpasim_runtime/events/step.py index 08edb874..32890048 100644 --- a/src/runtime/alpasim_runtime/events/step.py +++ b/src/runtime/alpasim_runtime/events/step.py @@ -77,7 +77,7 @@ async def run(self, state: RolloutState, queue: EventQueue) -> None: step_duration = time.perf_counter() - state.step_wall_start telemetry_ctx = try_get_context() if telemetry_ctx is not None: - telemetry_ctx.step_duration.observe(step_duration) + telemetry_ctx.record_step_duration(step_duration) else: # --- Initial case: log initial actor poses --- t0_us = state.unbound.egomotion_context_start_us diff --git a/src/runtime/alpasim_runtime/nre_introspection.py b/src/runtime/alpasim_runtime/nre_introspection.py index 86f0a6cd..fd418058 100644 --- a/src/runtime/alpasim_runtime/nre_introspection.py +++ b/src/runtime/alpasim_runtime/nre_introspection.py @@ -61,8 +61,8 @@ async def get_loaded_scenes( raise IntrospectionNotSupportedError( f"NRE server at {address} does not support GetLoadedScenes " f"(UNIMPLEMENTED). Scene-affine dispatch requires an NRE image " - f"with this RPC. Either upgrade the NRE image or disable " - f"scene_affine_dispatch." + f"with this RPC. Either upgrade the NRE image or set " + f"scene_affine_dispatch.enabled=false." ) from e logger.warning("get_loaded_scenes failed on %s: %s", address, e.details()) return None diff --git a/src/runtime/alpasim_runtime/route_generator.py b/src/runtime/alpasim_runtime/route_generator.py index cc241c21..5e3eb755 100644 --- a/src/runtime/alpasim_runtime/route_generator.py +++ b/src/runtime/alpasim_runtime/route_generator.py @@ -41,7 +41,7 @@ def create( vector_map: VectorMap, route_generator_type: RouteGeneratorType, route_start_offset_m: float = 0.0, - ) -> "RouteGenerator": + ) -> "RouteGenerator | None": """ Factory method to create a RouteGenerator Args: @@ -50,9 +50,11 @@ def create( route_generator_type: the type of route generator to create route_start_offset_m: approximate distance ahead of the ego projection where routes start Returns: - A route generator of the specified type + A route generator of the specified type, or None if route generation is disabled """ - if route_generator_type == RouteGeneratorType.RECORDED: + if route_generator_type == RouteGeneratorType.NONE: + return None + elif route_generator_type == RouteGeneratorType.RECORDED: return RouteGeneratorRecorded( recorded_waypoints_in_local, route_start_offset_m=route_start_offset_m, diff --git a/src/runtime/alpasim_runtime/runtime_context.py b/src/runtime/alpasim_runtime/runtime_context.py index 927fb228..a69d0b0b 100644 --- a/src/runtime/alpasim_runtime/runtime_context.py +++ b/src/runtime/alpasim_runtime/runtime_context.py @@ -13,6 +13,7 @@ BASE_SERVICE_NAMES, CORE_SERVICE_NAMES, NetworkSimulatorConfig, + RenderBundling, RendererKind, SimulatorConfig, UserSimulatorConfig, @@ -146,6 +147,38 @@ def validate_renderer_config(config: SimulatorConfig) -> None: raise ValueError(f"Unknown runtime.renderer.kind: {renderer_kind!r}") +def validate_scene_affinity_config(config: SimulatorConfig) -> None: + """Validate scene-affine dispatch bounds and renderer compatibility.""" + affine = config.user.scene_affine_dispatch + if affine.enabled and config.user.renderer.kind == RendererKind.video_model: + raise ValueError( + "runtime.scene_affine_dispatch.enabled=true is not supported with " + "runtime.renderer.kind=video_model (no per-scene GPU cache); set " + "runtime.scene_affine_dispatch.enabled=false" + ) + render_bundling = config.user.simulation_config.render_bundling + if affine.enabled and render_bundling != RenderBundling.BATCH_RENDER_RGB: + raise ValueError( + "runtime.scene_affine_dispatch.enabled=true requires " + "runtime.simulation_config.render_bundling=BATCH_RENDER_RGB " + f"(got {render_bundling.name}); scene-affine dispatch assumes the " + "NRE batched-render scene cache" + ) + if affine.max_renderers_per_scene <= 0: + raise ValueError( + "runtime.scene_affine_dispatch.max_renderers_per_scene must be positive" + ) + + if ( + affine.max_scenes_per_renderer is not None + and affine.max_scenes_per_renderer <= 0 + ): + raise ValueError( + "runtime.scene_affine_dispatch.max_scenes_per_renderer must be " + "positive or null" + ) + + @dataclass(frozen=True) class RuntimeContext: """Immutable snapshot of all runtime state needed to dispatch simulation jobs. @@ -171,6 +204,7 @@ def parse_simulator_config( network_config = typed_parse_config(network_config_path, NetworkSimulatorConfig) config = SimulatorConfig(user=user_config, network=network_config) validate_renderer_config(config) + validate_scene_affinity_config(config) return config diff --git a/src/runtime/alpasim_runtime/services/sensorsim_service.py b/src/runtime/alpasim_runtime/services/sensorsim_service.py index c40283b8..c8b69a3a 100644 --- a/src/runtime/alpasim_runtime/services/sensorsim_service.py +++ b/src/runtime/alpasim_runtime/services/sensorsim_service.py @@ -37,10 +37,25 @@ from alpasim_utils.geometry import Pose, Trajectory, pose_to_grpc from alpasim_utils.types import ImageWithMetadata +import grpc + logger = logging.getLogger(__name__) WILDCARD_SCENE_ID = "*" -SENSORSIM_UNAVAILABLE_RETRY_DELAYS_S = (0.5, 2.0) +MAX_GRPC_MESSAGE_BYTES = 64 * 1024 * 1024 +SENSORSIM_RETRY_DELAYS_S = (0.5, 2.0) +# NRE loads scene and renderer state lazily. Artifact-fetch races and a first-render +# backend wait exceeding NRE's server-side deadline both succeed once initialization +# finishes, so they are safe to retry. +SENSORSIM_TRANSIENT_ERROR_DETAILS = ( + "A load persistent id instruction was encountered", + "Stopped waiting for backend", +) +# NRE blocks its entire gRPC server (no handshakes, no keepalive acks) for up +# to ~60s while JIT-compiling render kernels on a fresh process's first render. +# wait_for_ready=True queues RPCs until the channel connects instead of failing +# UNAVAILABLE; the deadline bounds the wait for genuinely dead renderers. +SENSORSIM_RPC_TIMEOUT_S = 300.0 class SensorsimService(ServiceBase[SensorsimServiceStub]): @@ -69,6 +84,37 @@ def __init__( def stub_class(self) -> Type[SensorsimServiceStub]: return SensorsimServiceStub + async def _open_connection(self) -> None: + """Open a gRPC connection that supports batched multi-camera images.""" + if self.skip: + return + self.channel = grpc.aio.insecure_channel( + self.address, + options=[ + ("grpc.max_receive_message_length", MAX_GRPC_MESSAGE_BYTES), + ("grpc.max_send_message_length", MAX_GRPC_MESSAGE_BYTES), + ], + ) + self.stub = self.stub_class(self.channel) + + async def _sensorsim_rpc( + self, + method_name: str, + stub_method: Any, + request: Any, + ) -> Any: + """Call a sensorsim RPC with the service's shared retry and timeout policy.""" + return await profiled_rpc_call( + method_name, + "sensorsim", + stub_method, + request, + retry_delays_s=SENSORSIM_RETRY_DELAYS_S, + transient_error_details=SENSORSIM_TRANSIENT_ERROR_DETAILS, + timeout=SENSORSIM_RPC_TIMEOUT_S, + wait_for_ready=True, + ) + def make_initial_render_event(self, **kwargs: Any) -> Any: """Create the initial sensorsim render event for a rollout.""" from alpasim_runtime.events.camera import make_initial_sensorsim_render_event @@ -137,12 +183,10 @@ async def get_available_cameras( ) logger.info(f"Requesting available cameras for {scene_id=}") - response: AvailableCamerasReturn = await profiled_rpc_call( + response: AvailableCamerasReturn = await self._sensorsim_rpc( "get_available_cameras", - "sensorsim", self.stub.get_available_cameras, request, - unavailable_retry_delays_s=SENSORSIM_UNAVAILABLE_RETRY_DELAYS_S, ) await session_info.broadcaster.broadcast( @@ -178,12 +222,10 @@ async def get_available_ego_masks(self) -> AvailableEgoMasksReturn: LogEntry(available_ego_masks_request=request) ) - self._available_ego_masks = await profiled_rpc_call( + self._available_ego_masks = await self._sensorsim_rpc( "get_available_ego_masks", - "sensorsim", self.stub.get_available_ego_masks, request, - unavailable_retry_delays_s=SENSORSIM_UNAVAILABLE_RETRY_DELAYS_S, ) await session_info.broadcaster.broadcast( @@ -418,12 +460,10 @@ async def batch_render( await session_info.broadcaster.broadcast(LogEntry(batch_render_request=request)) - response: BatchRGBRenderReturn = await profiled_rpc_call( + response: BatchRGBRenderReturn = await self._sensorsim_rpc( "batch_render_rgb", - "sensorsim", self.stub.batch_render_rgb, request, - unavailable_retry_delays_s=SENSORSIM_UNAVAILABLE_RETRY_DELAYS_S, ) images_with_metadata = self._batch_return_to_images( @@ -473,12 +513,10 @@ async def aggregated_render( LogEntry(aggregated_render_request=request) ) - response: AggregatedRenderReturn = await profiled_rpc_call( + response: AggregatedRenderReturn = await self._sensorsim_rpc( "render_aggregated", - "sensorsim", self.stub.render_aggregated, request, - unavailable_retry_delays_s=SENSORSIM_UNAVAILABLE_RETRY_DELAYS_S, ) images_with_metadata = [] @@ -537,12 +575,10 @@ async def render( await session_info.broadcaster.broadcast(LogEntry(render_request=request)) - response: RGBRenderReturn = await profiled_rpc_call( + response: RGBRenderReturn = await self._sensorsim_rpc( "render_rgb", - "sensorsim", self.stub.render_rgb, request, - unavailable_retry_delays_s=SENSORSIM_UNAVAILABLE_RETRY_DELAYS_S, ) return ImageWithMetadata( diff --git a/src/runtime/alpasim_runtime/simulate/__main__.py b/src/runtime/alpasim_runtime/simulate/__main__.py index 6b1cc578..e87eebf6 100644 --- a/src/runtime/alpasim_runtime/simulate/__main__.py +++ b/src/runtime/alpasim_runtime/simulate/__main__.py @@ -238,10 +238,11 @@ async def run_simulation(args: argparse.Namespace) -> bool: if len(failed) > 3: logger.error(" ... and %d more", len(failed) - 3) - _generate_metrics_artifacts( - prometheus_url=config.user.prometheus.url, - log_dir=Path(args.log_dir), - ) + if config.user.prometheus.url is not None: + _generate_metrics_artifacts( + prometheus_url=config.user.prometheus.url, + log_dir=Path(args.log_dir), + ) success = all_rollouts_successful diff --git a/src/runtime/alpasim_runtime/telemetry/rpc_wrapper.py b/src/runtime/alpasim_runtime/telemetry/rpc_wrapper.py index a44d33dc..1560197b 100644 --- a/src/runtime/alpasim_runtime/telemetry/rpc_wrapper.py +++ b/src/runtime/alpasim_runtime/telemetry/rpc_wrapper.py @@ -19,11 +19,11 @@ from contextlib import AbstractContextManager from multiprocessing import Manager from multiprocessing.managers import SyncManager -from typing import Any, Awaitable, Callable, MutableMapping +from typing import Any, Callable, MutableMapping import grpc -from .telemetry_context import get_telemetry_tag, try_get_context +from .telemetry_context import try_get_context logger = logging.getLogger(__name__) @@ -33,6 +33,7 @@ # Tuple type for passing shared state between processes SharedRpcTracking = tuple[MutableMapping[str, int], LockLike] + # Module-level state - defaults to local dict, can be upgraded to shared _active_rpc_counts: MutableMapping[str, int] = {} _rpc_lock: LockLike = threading.Lock() @@ -91,17 +92,44 @@ def _decrement_count(service_type: str) -> None: ) +def _is_transient_error( + exc: grpc.aio.AioRpcError, + transient_error_details: Sequence[str], +) -> bool: + """Match transport failures or allowlisted server-side transient details.""" + if exc.code() == grpc.StatusCode.UNAVAILABLE: + return True + if exc.code() not in ( + grpc.StatusCode.UNKNOWN, + grpc.StatusCode.DEADLINE_EXCEEDED, + ): + return False + details = exc.details() or "" + return any(pattern in details for pattern in transient_error_details) + + async def profiled_rpc_call( method_name: str, service_type: str, - stub_call: Callable[..., Awaitable[Any]], + stub_call: Callable[..., grpc.aio.UnaryUnaryCall[Any, Any]], *args: Any, - unavailable_retry_delays_s: Sequence[float] = (), + retry_delays_s: Sequence[float] = (), + transient_error_details: Sequence[str] = (), **kwargs: Any, ) -> Any: """ Wrapper that captures RPC metrics. + Args: + method_name: RPC method name used in metrics and logs. + service_type: Service name used in metrics and logs. + stub_call: gRPC callable to invoke. + *args: Positional arguments forwarded to `stub_call`. + retry_delays_s: Delays before successive transient-error retries. + transient_error_details: Server error detail substrings. An error is + retryable when its details contain any entry in this sequence. + **kwargs: Keyword arguments forwarded to `stub_call`. + Usage: result = await profiled_rpc_call( "drive", "driver", self.stub.Drive, request @@ -109,10 +137,12 @@ async def profiled_rpc_call( If not inside a TelemetryContext, the call still executes but no metrics are recorded. - """ - max_attempts = len(unavailable_retry_delays_s) + 1 - for attempt_idx in range(1, max_attempts + 1): + Each delay in `retry_delays_s` grants one retry after a transient failure: + UNAVAILABLE, or UNKNOWN/DEADLINE_EXCEEDED whose details match an entry in + `transient_error_details` (for known server-side transient failures). + """ + for delay_s in retry_delays_s: try: return await _profiled_rpc_call_once( method_name, @@ -122,29 +152,31 @@ async def profiled_rpc_call( **kwargs, ) except grpc.aio.AioRpcError as exc: - if exc.code() != grpc.StatusCode.UNAVAILABLE or attempt_idx == max_attempts: + if not _is_transient_error(exc, transient_error_details): raise - - delay_s = unavailable_retry_delays_s[attempt_idx - 1] logger.warning( - "%s RPC %s failed with %s on attempt %d/%d; retrying in %.1fs: %s", + "%s RPC %s failed with %s; retrying in %.1fs: %s", service_type, method_name, exc.code().name, - attempt_idx, - max_attempts, delay_s, exc.details(), ) await asyncio.sleep(delay_s) - raise RuntimeError("unreachable") + return await _profiled_rpc_call_once( + method_name, + service_type, + stub_call, + *args, + **kwargs, + ) async def _profiled_rpc_call_once( method_name: str, service_type: str, - stub_call: Callable[..., Awaitable[Any]], + stub_call: Callable[..., grpc.aio.UnaryUnaryCall[Any, Any]], *args: Any, **kwargs: Any, ) -> Any: @@ -178,24 +210,12 @@ def on_done(_: Any) -> None: duration = t_resume - t_start if ctx is not None: - tag = get_telemetry_tag() - worker_id = str(ctx.worker_id) - ctx.rpc_queue_depth_latest.labels( - service=service_type, tag=tag, worker_id=worker_id - ).set(queue_depth_at_start) - ctx.rpc_duration.labels( + ctx.record_rpc( service=service_type, method=method_name, - tag=tag, - worker_id=worker_id, - ).observe(duration) - - # Only record blocking time if callback was successfully registered - if t_done is not None: - blocking = max(0, t_resume - t_done) - ctx.rpc_blocking.labels( - service=service_type, - method=method_name, - tag=tag, - worker_id=worker_id, - ).observe(blocking) + queue_depth_at_start=queue_depth_at_start, + duration_seconds=duration, + blocking_seconds=( + max(0, t_resume - t_done) if t_done is not None else None + ), + ) diff --git a/src/runtime/alpasim_runtime/telemetry/telemetry_context.py b/src/runtime/alpasim_runtime/telemetry/telemetry_context.py index 15108aa2..d853386c 100644 --- a/src/runtime/alpasim_runtime/telemetry/telemetry_context.py +++ b/src/runtime/alpasim_runtime/telemetry/telemetry_context.py @@ -10,11 +10,13 @@ import asyncio import contextlib import logging +import threading from contextvars import ContextVar from dataclasses import dataclass, field from time import perf_counter from types import TracebackType -from typing import Generator, Type +from typing import Callable, Type +from wsgiref.simple_server import WSGIServer from alpasim_runtime.event_loop_idle_profiler import get_event_loop_idle_stats from alpasim_runtime.gc_pressure_profiler import get_gc_pressure_stats @@ -34,8 +36,23 @@ HISTOGRAM_BUCKETS = { "rpc_duration": (0.01, 0.05, 0.1, 0.25, 0.5, 1.0, 2.0, 5.0, 10.0, 20.0), "rpc_blocking": (0.0001, 0.001, 0.005, 0.01, 0.05, 0.1, 0.5, 1.0), - "rollout_duration": list(range(1, 300)), - "step_duration": (0.1, 0.5, 1, 2, 5, 10, 30), + "rollout_duration": (1, 2.5, 5, 10, 25, 50, 100, 250, 500), + "step_duration": (0.05, 0.1, 0.25, 0.5, 1, 2.5, 5, 10, 30), + "observation_barrier": ( + 0.001, + 0.005, + 0.01, + 0.025, + 0.05, + 0.1, + 0.25, + 0.5, + 1, + 2.5, + 5, + 10, + ), + "scheduler_wait": (0.01, 0.1, 0.5, 1, 2.5, 5, 10, 30, 60, 120, 300), } @@ -46,162 +63,255 @@ class TelemetryContext: Use as a context manager for automatic setup/shutdown: - async with TelemetryContext(worker_id) as ctx: + async with TelemetryContext(port=port, worker_id=worker_id) as ctx: # ctx.metrics available here await run_simulation() """ + port: int worker_id: int = 0 bind_host: str = "0.0.0.0" - port: int | None = None refresh_interval_s: float = 1.0 + job_queue_depth_fn: Callable[[], int] | None = None # Metrics (initialized in __post_init__) registry: CollectorRegistry = field(init=False) - rpc_duration: Histogram = field(init=False) - rpc_blocking: Histogram = field(init=False) - rpc_queue_depth_latest: Gauge = field(init=False) - rollout_duration: Histogram = field(init=False) - step_duration: Histogram = field(init=False) + _rpc_duration: Histogram = field(init=False) + _rpc_blocking: Histogram = field(init=False) + _rpc_queue_depth_latest: Gauge = field(init=False) + _rollout_duration: Histogram = field(init=False) + _step_duration: Histogram = field(init=False) + _observation_barrier: Histogram = field(init=False) # Simulation summary metrics - simulation_elapsed_seconds: Gauge = field(init=False) - simulation_rollouts_completed: Counter = field(init=False) + _rollouts: Counter = field(init=False) + _renderer_active_rollouts: Gauge = field(init=False) + _renderer_rollouts_started: Counter = field(init=False) + _renderer_scheduler_wait: Histogram = field(init=False) + _simulation_elapsed_seconds: Gauge = field(init=False) + _job_queue_depth: Gauge = field(init=False) # Event loop gauges - event_loop_idle_seconds: Gauge = field(init=False) - event_loop_poll_seconds: Gauge = field(init=False) - event_loop_work_seconds: Gauge = field(init=False) + _event_loop_idle_seconds: Gauge = field(init=False) + _event_loop_poll_seconds: Gauge = field(init=False) + _event_loop_work_seconds: Gauge = field(init=False) # GC pressure gauges - gc_total_duration_seconds: Gauge = field(init=False) - gc_max_duration_seconds: Gauge = field(init=False) - gc_collection_count: Gauge = field(init=False) + _gc_total_duration_seconds: Gauge = field(init=False) + _gc_max_duration_seconds: Gauge = field(init=False) + _gc_collection_count: Gauge = field(init=False) - _httpd: object | None = field(init=False, default=None) - _http_thread: object | None = field(init=False, default=None) + _httpd: WSGIServer | None = field(init=False, default=None) + _http_thread: threading.Thread | None = field(init=False, default=None) _refresh_task: asyncio.Task[None] | None = field(init=False, default=None) _simulation_started_at: float | None = field(init=False, default=None) def __post_init__(self) -> None: self.registry = CollectorRegistry() worker_labels = {"worker_id": str(self.worker_id)} - # RPC metrics (tag label allows filtering warmup/special operations) - self.rpc_duration = Histogram( + + def worker_gauge(name: str, description: str) -> Gauge: + return Gauge( + name, description, WORKER_LABELS, registry=self.registry + ).labels(**worker_labels) + + # RPC metrics + self._rpc_duration = Histogram( "alpasim_rpc_duration_seconds", "RPC call duration", - ["service", "method", "tag", *WORKER_LABELS], + ["service", "method", *WORKER_LABELS], buckets=HISTOGRAM_BUCKETS["rpc_duration"], registry=self.registry, ) - self.rpc_blocking = Histogram( + self._rpc_blocking = Histogram( "alpasim_rpc_blocking_seconds", "Time between gRPC I/O completion and coroutine resumption", - ["service", "method", "tag", *WORKER_LABELS], + ["service", "method", *WORKER_LABELS], buckets=HISTOGRAM_BUCKETS["rpc_blocking"], registry=self.registry, ) - self.rpc_queue_depth_latest = Gauge( + self._rpc_queue_depth_latest = Gauge( "alpasim_rpc_queue_depth_at_start_latest", "Latest observed queue depth when an RPC was initiated", - ["service", "tag", *WORKER_LABELS], + ["service", *WORKER_LABELS], registry=self.registry, ) # Simulation timing - self.rollout_duration = Histogram( + self._rollout_duration = Histogram( "alpasim_rollout_duration_seconds", "Total rollout execution time", WORKER_LABELS, buckets=HISTOGRAM_BUCKETS["rollout_duration"], registry=self.registry, ).labels(**worker_labels) - self.step_duration = Histogram( + self._step_duration = Histogram( "alpasim_step_duration_seconds", "Per-step execution time", WORKER_LABELS, buckets=HISTOGRAM_BUCKETS["step_duration"], registry=self.registry, ).labels(**worker_labels) + self._observation_barrier = Histogram( + "alpasim_observation_barrier_seconds", + "Wall time awaiting the pre-drive observation barrier", + WORKER_LABELS, + buckets=HISTOGRAM_BUCKETS["observation_barrier"], + registry=self.registry, + ).labels(**worker_labels) # Pre-register simulation summary metrics - self.simulation_elapsed_seconds = Gauge( - "alpasim_simulation_elapsed_seconds", - "Simulation worker elapsed time sampled when rollouts complete", + self._rollouts = Counter( + "alpasim_rollouts", + "Number of rollouts reaching a terminal status", registry=self.registry, - labelnames=WORKER_LABELS, - ).labels(**worker_labels) - self.simulation_rollouts_completed = Counter( - "alpasim_simulation_rollouts_completed", - "Number of completed rollouts", + labelnames=["status", *WORKER_LABELS], + ) + self._renderer_active_rollouts = worker_gauge( + "alpasim_renderer_active_rollouts", + "Renderer-backed rollouts currently executing", + ) + self._renderer_rollouts_started = Counter( + "alpasim_renderer_rollouts_started", + "Renderer-backed rollouts started by scheduling decision", registry=self.registry, - labelnames=WORKER_LABELS, - ).labels(**worker_labels) + labelnames=[ + "kind", + *WORKER_LABELS, + ], + ) + self._renderer_scheduler_wait = Histogram( + "alpasim_renderer_scheduler_wait_seconds", + "Time a renderer-backed rollout waited for scheduler assignment", + registry=self.registry, + labelnames=["kind", *WORKER_LABELS], + buckets=HISTOGRAM_BUCKETS["scheduler_wait"], + ) + self._simulation_elapsed_seconds = worker_gauge( + "alpasim_simulation_elapsed_seconds", + "Simulation worker elapsed time sampled when rollouts finish", + ) + self._job_queue_depth = worker_gauge( + "alpasim_job_queue_depth", + "Runtime rollout jobs waiting for a worker", + ) # Pre-register event loop gauges - self.event_loop_idle_seconds = Gauge( + self._event_loop_idle_seconds = worker_gauge( "alpasim_event_loop_idle_seconds_total", "Total event loop idle time (blocking waits for I/O)", - registry=self.registry, - labelnames=WORKER_LABELS, - ).labels(**worker_labels) - self.event_loop_poll_seconds = Gauge( + ) + self._event_loop_poll_seconds = worker_gauge( "alpasim_event_loop_poll_seconds_total", "Total event loop poll time (non-blocking I/O checks)", - registry=self.registry, - labelnames=WORKER_LABELS, - ).labels(**worker_labels) - self.event_loop_work_seconds = Gauge( + ) + self._event_loop_work_seconds = worker_gauge( "alpasim_event_loop_work_seconds_total", "Total event loop work time (executing Python code)", - registry=self.registry, - labelnames=WORKER_LABELS, - ).labels(**worker_labels) + ) # GC pressure gauges - self.gc_total_duration_seconds = Gauge( + self._gc_total_duration_seconds = worker_gauge( "alpasim_gc_total_duration_seconds", "Total time spent in garbage collection", - registry=self.registry, - labelnames=WORKER_LABELS, - ).labels(**worker_labels) - self.gc_max_duration_seconds = Gauge( + ) + self._gc_max_duration_seconds = worker_gauge( "alpasim_gc_max_duration_seconds", "Longest single garbage collection pause", - registry=self.registry, - labelnames=WORKER_LABELS, - ).labels(**worker_labels) - self.gc_collection_count = Gauge( + ) + self._gc_collection_count = worker_gauge( "alpasim_gc_collection_count_total", "Total number of GC collections", - registry=self.registry, - labelnames=WORKER_LABELS, - ).labels(**worker_labels) + ) - def record_rollout_complete(self) -> None: - """Record one completed rollout in the live simulation summary.""" - self.simulation_rollouts_completed.inc() + def record_rpc( + self, + *, + service: str, + method: str, + queue_depth_at_start: int, + duration_seconds: float, + blocking_seconds: float | None, + ) -> None: + """Record duration and queue depth for one RPC attempt.""" + worker_id = str(self.worker_id) + self._rpc_queue_depth_latest.labels(service=service, worker_id=worker_id).set( + queue_depth_at_start + ) + self._rpc_duration.labels( + service=service, + method=method, + worker_id=worker_id, + ).observe(duration_seconds) + if blocking_seconds is not None: + self._rpc_blocking.labels( + service=service, + method=method, + worker_id=worker_id, + ).observe(blocking_seconds) + + def record_rollout_duration(self, duration_seconds: float) -> None: + """Record one rollout's wall-clock duration.""" + self._rollout_duration.observe(duration_seconds) + + def record_step_duration(self, duration_seconds: float) -> None: + """Record one simulation step's wall-clock duration.""" + self._step_duration.observe(duration_seconds) + + def record_observation_barrier(self, duration_seconds: float) -> None: + """Record one wait at the pre-drive observation barrier.""" + self._observation_barrier.observe(duration_seconds) + + def record_rollout_finished(self, status: str) -> None: + """Record one terminal rollout status in the live simulation summary.""" + self._rollouts.labels( + status=status, + worker_id=str(self.worker_id), + ).inc() if self._simulation_started_at is not None: - self.simulation_elapsed_seconds.set( + self._simulation_elapsed_seconds.set( perf_counter() - self._simulation_started_at ) + def record_renderer_rollout_started( + self, + *, + dispatch_kind: str, + scheduler_wait_seconds: float, + ) -> None: + """Record the scheduling class and begin active-rollout accounting.""" + self._renderer_rollouts_started.labels( + kind=dispatch_kind, + worker_id=str(self.worker_id), + ).inc() + self._renderer_scheduler_wait.labels( + kind=dispatch_kind, + worker_id=str(self.worker_id), + ).observe(scheduler_wait_seconds) + self._renderer_active_rollouts.inc() + + def record_renderer_rollout_stopped(self) -> None: + """Finish active-rollout accounting.""" + self._renderer_active_rollouts.dec() + def refresh_gauges(self) -> None: """Refresh live gauge snapshots for Prometheus scrapes.""" self._refresh_event_loop_gauges() self._refresh_gc_pressure_gauges() + if self.job_queue_depth_fn is not None: + self._job_queue_depth.set(self.job_queue_depth_fn()) def _refresh_event_loop_gauges(self) -> None: idle_stats = get_event_loop_idle_stats() - self.event_loop_idle_seconds.set(idle_stats["idle_seconds"]) - self.event_loop_poll_seconds.set(idle_stats["poll_seconds"]) - self.event_loop_work_seconds.set(idle_stats["work_seconds"]) + self._event_loop_idle_seconds.set(idle_stats["idle_seconds"]) + self._event_loop_poll_seconds.set(idle_stats["poll_seconds"]) + self._event_loop_work_seconds.set(idle_stats["work_seconds"]) def _refresh_gc_pressure_gauges(self) -> None: gc_stats = get_gc_pressure_stats() - self.gc_total_duration_seconds.set(gc_stats["total_duration_s"]) - self.gc_max_duration_seconds.set(gc_stats["max_duration_s"]) - self.gc_collection_count.set(gc_stats["collection_count"]) + self._gc_total_duration_seconds.set(gc_stats["total_duration_s"]) + self._gc_max_duration_seconds.set(gc_stats["max_duration_s"]) + self._gc_collection_count.set(gc_stats["collection_count"]) async def _refresh_gauges_periodically(self) -> None: while True: @@ -209,8 +319,6 @@ async def _refresh_gauges_periodically(self) -> None: await asyncio.sleep(self.refresh_interval_s) async def __aenter__(self) -> "TelemetryContext": - if self.port is None: - raise ValueError(f"Telemetry port missing for worker {self.worker_id}") try: self._httpd, self._http_thread = start_http_server( self.port, @@ -283,32 +391,3 @@ def try_get_context() -> TelemetryContext | None: Use when telemetry is optional, e.g. for functions that might be in tests. """ return _current_context.get() - - -# Task-local tag for labeling telemetry samples (e.g., "warmup") -_current_tag: ContextVar[str] = ContextVar("telemetry_tag", default="default") - - -def get_telemetry_tag() -> str: - """Get current telemetry tag.""" - return _current_tag.get() - - -@contextlib.contextmanager -def tag_telemetry(tag: str) -> Generator[None, None, None]: - """ - Context manager to tag telemetry samples with a label. - - Tagged samples are still recorded but can be filtered in analysis. - Use this for operations like warmup that should be tracked separately. - - Example: - with tag_telemetry("warmup"): - await some_warmup_operation() # Recorded with tag="warmup" - """ - old_tag = _current_tag.get() - _current_tag.set(tag) - try: - yield - finally: - _current_tag.set(old_tag) diff --git a/src/runtime/alpasim_runtime/unbound_rollout.py b/src/runtime/alpasim_runtime/unbound_rollout.py index fea0f66d..6dea6d4f 100644 --- a/src/runtime/alpasim_runtime/unbound_rollout.py +++ b/src/runtime/alpasim_runtime/unbound_rollout.py @@ -20,6 +20,7 @@ SimulationConfig, VehicleConfig, ) +from alpasim_runtime.errors import InvalidSceneError from alpasim_runtime.services.renderer import RendererService from alpasim_runtime.services.sensorsim_service import ImageFormat from alpasim_utils.geometry import Pose, Trajectory @@ -266,7 +267,9 @@ def create( elif data_source.rig.vehicle_config is not None: vehicle = data_source.rig.vehicle_config else: - raise ValueError("No vehicle config provided/found.") + raise InvalidSceneError( + scene_id, "no vehicle config in simulation config or rig" + ) ego_aabb = AABB( x=vehicle.aabb_x_m, @@ -274,6 +277,15 @@ def create( z=vehicle.aabb_z_m, ) + try: + vector_map = data_source.map + except (OSError, MemoryError): + raise + except Exception as exc: + raise InvalidSceneError( + scene_id, f"failed to load vector map: {exc}" + ) from exc + return UnboundRollout( rollout_uuid=session_uuid or str(uuid.uuid1()), scene_id=scene_id, @@ -313,7 +325,7 @@ def create( route_start_offset_m=simulation_config.route_start_offset_m, send_recording_ground_truth=simulation_config.send_recording_ground_truth, vehicle_config=vehicle, - vector_map=data_source.map, + vector_map=vector_map, hidden_traffic_objs=hidden_traffic_objs, render_bundling=simulation_config.render_bundling, ) @@ -325,6 +337,7 @@ def get_log_metadata(self) -> RolloutMetadata.SessionMetadata: batch_size=1, # Always 1 since we only have one rollout n_sim_steps=self.n_sim_steps, start_timestamp_us=self.egomotion_context_start_us, + render_start_timestamp_us=self.render_start_timestamp_us, control_timestep_us=self.control_timestep_us, nre_runid=self.nre_runid, nre_version=self.nre_version, diff --git a/src/runtime/alpasim_runtime/worker/ipc.py b/src/runtime/alpasim_runtime/worker/ipc.py index 6b9fcfdc..576933b0 100644 --- a/src/runtime/alpasim_runtime/worker/ipc.py +++ b/src/runtime/alpasim_runtime/worker/ipc.py @@ -8,8 +8,10 @@ from __future__ import annotations import logging -from dataclasses import dataclass +from dataclasses import dataclass, field from multiprocessing import Queue +from time import monotonic +from typing import Literal from alpasim_grpc.v0.logging_pb2 import RolloutMetadata from alpasim_runtime.address_pool import ServiceAddress @@ -20,6 +22,13 @@ logger = logging.getLogger(__name__) +DispatchKind = Literal[ + "fifo", + "cached_affine", + "cold_initial", + "cold_replica", +] + @dataclass class ServiceEndpoints: @@ -34,8 +43,13 @@ class ServiceEndpoints: @dataclass class PendingRolloutJob: - """Job created by parent before service assignment.""" + """Job created by parent before service assignment. + + Parent-side only; never crosses the worker queue (see AssignedRolloutJob). + """ + # Request identifier for daemon-mode routing and batch compatibility. + request_id: str # Unique identifier for tracking this job in results and logs job_id: str # Scene ID identifying which scene to simulate @@ -44,6 +58,10 @@ class PendingRolloutJob: rollout_spec_index: int # Optional; empty ⇒ runtime generates the UUID. See RolloutSpec in runtime.proto. session_uuid: str = "" + # Number of failed attempts before this pending attempt. + retry_attempt: int = 0 + # Creation time (monotonic clock); basis for scheduler-wait telemetry. + enqueued_at: float = field(default_factory=monotonic) @dataclass @@ -60,6 +78,9 @@ class AssignedRolloutJob: rollout_spec_index: int # Concrete service addresses assigned by the parent dispatch loop. endpoints: ServiceEndpoints + # Bounded scheduler decision metadata for worker-side telemetry. + dispatch_kind: DispatchKind + scheduler_wait_seconds: float # Optional; empty ⇒ runtime generates the UUID. See RolloutSpec in runtime.proto. session_uuid: str = "" @@ -77,6 +98,7 @@ class JobResult: error: str | None error_traceback: str | None # Full traceback for debugging rollout_uuid: str | None + error_code: int = 0 # Evaluation metrics from in-runtime evaluation (if enabled). # Contains timestep_metrics, aggregated_metrics, and metrics_df. # None if evaluation is disabled or failed. @@ -106,10 +128,10 @@ class WorkerArgs: ) log_dir: str # Root directory for outputs (asl/, metrics/, txt-logs/) eval_config: EvalConfig + telemetry_port: int # Port for this worker's Prometheus metrics endpoint # Canonical version IDs computed once by the parent process. version_ids: RolloutMetadata.VersionIds | None = None # For orphan detection in subprocess mode. None disables detection (inline mode). parent_pid: int | None = None # Shared RPC tracking for global queue depth metrics across processes shared_rpc_tracking: SharedRpcTracking | None = None - telemetry_port: int | None = None diff --git a/src/runtime/alpasim_runtime/worker/main.py b/src/runtime/alpasim_runtime/worker/main.py index 474fb649..4d1c357f 100644 --- a/src/runtime/alpasim_runtime/worker/main.py +++ b/src/runtime/alpasim_runtime/worker/main.py @@ -26,9 +26,11 @@ from multiprocessing import Queue from queue import Empty as QueueEmpty +from alpasim_grpc.v0 import runtime_pb2 from alpasim_grpc.v0.logging_pb2 import RolloutMetadata from alpasim_runtime.camera_catalog import CameraCatalog from alpasim_runtime.config import RendererKind, UserSimulatorConfig +from alpasim_runtime.errors import RolloutError from alpasim_runtime.event_loop import create_event_rollout from alpasim_runtime.event_loop_idle_profiler import install_event_loop_idle_profiler from alpasim_runtime.gc_pressure_profiler import setup_gc_pressure_profiler @@ -178,6 +180,11 @@ async def run_single_rollout( error=str(exc), error_traceback=tb, rollout_uuid=rollout.rollout_uuid if rollout else None, + error_code=( + exc.error_code + if isinstance(exc, RolloutError) + else runtime_pb2.ROLLOUT_ERROR_CODE_UNSPECIFIED + ), ) @@ -277,22 +284,32 @@ def _poll_job() -> AssignedRolloutJob | _ShutdownSentinel | None: shutdown_event.set() break - # Process the job - result = await run_single_rollout( - job=job, - user_config=user_config, - data_source=scene_loader.get_data_source(job.scene_id), - camera_catalog=camera_catalog, - version_ids=version_ids, - rollouts_dir=rollouts_dir, - eval_config=eval_config, - eval_executor=eval_executor, - ) + telemetry_ctx = try_get_context() + if telemetry_ctx is not None: + telemetry_ctx.record_renderer_rollout_started( + dispatch_kind=job.dispatch_kind, + scheduler_wait_seconds=job.scheduler_wait_seconds, + ) + try: + result = await run_single_rollout( + job=job, + user_config=user_config, + data_source=scene_loader.get_data_source(job.scene_id), + camera_catalog=camera_catalog, + version_ids=version_ids, + rollouts_dir=rollouts_dir, + eval_config=eval_config, + eval_executor=eval_executor, + ) + finally: + if telemetry_ctx is not None: + telemetry_ctx.record_renderer_rollout_stopped() result_queue.put(result) rollout_count += 1 - telemetry_ctx = try_get_context() if telemetry_ctx is not None: - telemetry_ctx.record_rollout_complete() + telemetry_ctx.record_rollout_finished( + "completed" if result.success else "failed" + ) # Spawn num_consumers consumer tasks -- each handles one job at a time try: @@ -366,8 +383,9 @@ async def worker_async_main(args: WorkerArgs) -> None: # TelemetryContext for live Prometheus scraping. async with TelemetryContext( - worker_id=args.worker_id, port=args.telemetry_port, + worker_id=args.worker_id, + job_queue_depth_fn=args.job_queue.qsize, ): await run_worker_loop( worker_id=args.worker_id, diff --git a/src/runtime/pyproject.toml b/src/runtime/pyproject.toml index a069d3fb..6ab7ea71 100644 --- a/src/runtime/pyproject.toml +++ b/src/runtime/pyproject.toml @@ -5,7 +5,7 @@ build-backend = "setuptools.build_meta" # Trivial comment to trigger CI build-services (for test-slurm dependency). [project] name = "alpasim-runtime" -version = "1.123.0" +version = "1.136.0" description = "Runtime of the Alpamayo Sim" requires-python = ">=3.11,<3.13" authors = [{name = "Michal Tyszkiewicz", email = "mtyszkiewicz@nvidia.com"}] diff --git a/src/runtime/tests/services/test_sensorsim_service.py b/src/runtime/tests/services/test_sensorsim_service.py index 5135d51e..d23f94a0 100644 --- a/src/runtime/tests/services/test_sensorsim_service.py +++ b/src/runtime/tests/services/test_sensorsim_service.py @@ -9,7 +9,10 @@ import pytest from alpasim_grpc.v0.sensorsim_pb2 import BatchRGBRenderReturnItem, RGBRenderReturn -from alpasim_runtime.services.sensorsim_service import SensorsimService +from alpasim_runtime.services.sensorsim_service import ( + MAX_GRPC_MESSAGE_BYTES, + SensorsimService, +) from alpasim_runtime.types import Clock, RuntimeCamera @@ -29,6 +32,40 @@ def _triggers() -> dict[str, Clock.Trigger]: } +@pytest.mark.asyncio +async def test_sensorsim_service_uses_large_grpc_message_limits(monkeypatch): + captured: dict[str, object] = {} + fake_channel = object() + + def fake_insecure_channel(address, options=None): + captured["address"] = address + captured["options"] = options + return fake_channel + + class FakeStub: + def __init__(self, channel): + captured["channel"] = channel + + monkeypatch.setattr( + "alpasim_runtime.services.sensorsim_service.grpc.aio.insecure_channel", + fake_insecure_channel, + ) + monkeypatch.setattr( + "alpasim_runtime.services.sensorsim_service.SensorsimServiceStub", + FakeStub, + ) + + service = SensorsimService("localhost:50051", False, MagicMock()) + await service._open_connection() + + assert captured["address"] == "localhost:50051" + assert captured["channel"] is fake_channel + assert captured["options"] == [ + ("grpc.max_receive_message_length", MAX_GRPC_MESSAGE_BYTES), + ("grpc.max_send_message_length", MAX_GRPC_MESSAGE_BYTES), + ] + + def test_batch_return_maps_images_by_camera_name(): items = [_item("cam_a", b"a"), _item("cam_b", b"b")] diff --git a/src/runtime/tests/services/test_traffic_service.py b/src/runtime/tests/services/test_traffic_service.py new file mode 100644 index 00000000..0a319af3 --- /dev/null +++ b/src/runtime/tests/services/test_traffic_service.py @@ -0,0 +1,45 @@ +# SPDX-License-Identifier: Apache-2.0 +# Copyright (c) 2026 NVIDIA Corporation + +from __future__ import annotations + +import pytest +from alpasim_runtime.services.service_base import SessionInfo +from alpasim_runtime.services.session_configs import TrafficSessionConfig +from alpasim_runtime.services.traffic_service import TrafficService +from alpasim_utils.geometry import Trajectory +from alpasim_utils.scenario import AABB + + +class RecordingBroadcaster: + def __init__(self) -> None: + self.entries = [] + + async def broadcast(self, entry) -> None: + self.entries.append(entry) + + +@pytest.mark.asyncio +async def test_traffic_session_request_uses_scene_id() -> None: + broadcaster = RecordingBroadcaster() + service = TrafficService(address="localhost:0", skip=True) + + await service._initialize_session( + SessionInfo( + uuid="session-1", + broadcaster=broadcaster, + session_config=TrafficSessionConfig( + traffic_objs={}, + scene_id="clipgt-01d503d4-449b-46fc-8d78-9085e70d3554", + ego_aabb=AABB(x=4.5, y=2.0, z=1.7), + gt_ego_aabb_trajectory=Trajectory.create_empty(), + start_timestamp_us=0, + force_gt_duration_us=100_000, + control_timestep_us=100_000, + ), + ) + ) + + assert len(broadcaster.entries) == 1 + request = broadcaster.entries[0].traffic_session_request + assert request.scene_id == "clipgt-01d503d4-449b-46fc-8d78-9085e70d3554" diff --git a/src/runtime/tests/test_address_pool.py b/src/runtime/tests/test_address_pool.py index 0a69984e..4a79fe6d 100644 --- a/src/runtime/tests/test_address_pool.py +++ b/src/runtime/tests/test_address_pool.py @@ -180,13 +180,13 @@ def test_try_acquire_for_address_skip(self): assert slot is not None assert slot.skip is True - def test_all_addresses(self): + def test_address_order(self): pool = AddressPool(["A", "B", "C"], n_concurrent=2, skip=False) - assert pool.all_addresses() == frozenset({"A", "B", "C"}) + assert pool.address_order == ("A", "B", "C") - def test_all_addresses_skip(self): + def test_address_order_skip(self): pool = AddressPool(["A"], n_concurrent=2, skip=True) - assert pool.all_addresses() == frozenset() + assert pool.address_order == () class TestTryAcquireAll: diff --git a/src/runtime/tests/test_config.py b/src/runtime/tests/test_config.py index 10073574..bd0dad80 100644 --- a/src/runtime/tests/test_config.py +++ b/src/runtime/tests/test_config.py @@ -8,6 +8,10 @@ from alpasim_runtime.scene_loader import trajdata_provider_config_to_params +def test_rollout_retry_default() -> None: + assert config.UserSimulatorConfig().max_rollout_retries == 2 + + def test_usdz_provider_config_defaults() -> None: cfg = config.UsdzProviderConfig(data_dir="/data/usdz") diff --git a/src/runtime/tests/test_daemon_engine.py b/src/runtime/tests/test_daemon_engine.py index 4f8f5e65..bb9d9a75 100644 --- a/src/runtime/tests/test_daemon_engine.py +++ b/src/runtime/tests/test_daemon_engine.py @@ -32,8 +32,13 @@ def _make_config() -> SimpleNamespace: smooth_trajectories=True, scenes=[SimpleNamespace(scene_id="clipgt-a")], endpoints=SimpleNamespace(startup_timeout_s=1), - scene_affine_dispatch=False, - cache_refresh_interval_s=5.0, + scene_affine_dispatch=SimpleNamespace( + enabled=False, + cache_refresh_interval_s=5.0, + max_renderers_per_scene=2, + max_scenes_per_renderer=None, + ), + max_rollout_retries=2, ), network=SimpleNamespace(), ) @@ -155,6 +160,8 @@ async def test_engine_startup_gathers_versions_and_validates_scenes( class _FakeScheduler: def __init__(self, *, runtime, **kwargs) -> None: assert runtime is worker_runtime + assert kwargs["max_rollout_retries"] == 2 + assert kwargs["rollouts_dir"] == "/tmp/log/rollouts" async def shutdown(self, *, reason: str) -> None: del reason @@ -541,9 +548,10 @@ def test_build_simulation_return_mixed_results_with_and_without_eval() -> None: job_id="j2", rollout_spec_index=0, success=False, - error="sim crashed", + error="invalid scene", error_traceback=None, rollout_uuid="uuid-2", + error_code=runtime_pb2.ROLLOUT_ERROR_CODE_INVALID_SCENE, eval_result=None, ), ] @@ -557,12 +565,14 @@ def test_build_simulation_return_mixed_results_with_and_without_eval() -> None: # First rollout: has metrics rr0 = ret.rollout_returns[0] assert rr0.success is True + assert rr0.error_code == runtime_pb2.ROLLOUT_ERROR_CODE_NONE assert len(rr0.timestep_metrics) == 2 assert dict(rr0.aggregated_metrics) == {"collision_any": 1.0, "offroad": 0.5} # Second rollout: no metrics rr1 = ret.rollout_returns[1] assert rr1.success is False - assert rr1.error == "sim crashed" + assert rr1.error == "invalid scene" + assert rr1.error_code == runtime_pb2.ROLLOUT_ERROR_CODE_INVALID_SCENE assert len(rr1.timestep_metrics) == 0 assert dict(rr1.aggregated_metrics) == {} diff --git a/src/runtime/tests/test_daemon_request_plumbing.py b/src/runtime/tests/test_daemon_request_plumbing.py index 4428c67d..1d6a5a67 100644 --- a/src/runtime/tests/test_daemon_request_plumbing.py +++ b/src/runtime/tests/test_daemon_request_plumbing.py @@ -9,29 +9,6 @@ from alpasim_runtime.errors import UnknownSceneError -def test_adapter_expands_nr_rollouts() -> None: - req = runtime_pb2.SimulationRequest( - rollout_specs=[runtime_pb2.RolloutSpec(scenario_id="clipgt-a", nr_rollouts=3)] - ) - - jobs = build_pending_jobs_from_request(req, lambda scene_id: scene_id == "clipgt-a") - assert [job.scene_id for job in jobs] == ["clipgt-a", "clipgt-a", "clipgt-a"] - assert [job.rollout_spec_index for job in jobs] == [0, 0, 0] - - -def test_adapter_drops_zero_nr_rollouts_with_warning( - caplog: pytest.LogCaptureFixture, -) -> None: - caplog.set_level("WARNING", logger="alpasim_runtime.daemon.engine") - req = runtime_pb2.SimulationRequest( - rollout_specs=[runtime_pb2.RolloutSpec(scenario_id="clipgt-a")] - ) - - jobs = build_pending_jobs_from_request(req, lambda _scene_id: True) - assert jobs == [] - assert "Dropping rollout spec with nr_rollouts=0" in caplog.text - - def test_adapter_rejects_scene_without_artifact() -> None: req = runtime_pb2.SimulationRequest( rollout_specs=[ @@ -40,7 +17,7 @@ def test_adapter_rejects_scene_without_artifact() -> None: ) with pytest.raises(UnknownSceneError): - build_pending_jobs_from_request(req, lambda _scene_id: False) + build_pending_jobs_from_request(req, "req-1", lambda _scene_id: False) def test_adapter_assigns_rollout_spec_indexes_in_request_order() -> None: @@ -52,7 +29,7 @@ def test_adapter_assigns_rollout_spec_indexes_in_request_order() -> None: ) jobs = build_pending_jobs_from_request( - req, lambda scene_id: scene_id in {"clipgt-a", "clipgt-b"} + req, "req-1", lambda scene_id: scene_id in {"clipgt-a", "clipgt-b"} ) assert len(jobs) == 3 assert [job.scene_id for job in jobs] == ["clipgt-a", "clipgt-b", "clipgt-b"] @@ -68,7 +45,7 @@ def test_adapter_ignores_zero_rollout_specs_when_indexing() -> None: ) jobs = build_pending_jobs_from_request( - req, lambda scene_id: scene_id in {"clipgt-a", "clipgt-b"} + req, "req-1", lambda scene_id: scene_id in {"clipgt-a", "clipgt-b"} ) assert len(jobs) == 2 assert [job.scene_id for job in jobs] == ["clipgt-b", "clipgt-b"] @@ -86,19 +63,10 @@ def test_adapter_propagates_session_uuids_in_order() -> None: ] ) - jobs = build_pending_jobs_from_request(req, lambda _scene_id: True) + jobs = build_pending_jobs_from_request(req, "req-1", lambda _scene_id: True) assert [job.session_uuid for job in jobs] == ["u0", "u1", "u2"] -def test_adapter_omits_session_uuids_when_empty() -> None: - req = runtime_pb2.SimulationRequest( - rollout_specs=[runtime_pb2.RolloutSpec(scenario_id="clipgt-a", nr_rollouts=2)] - ) - - jobs = build_pending_jobs_from_request(req, lambda _scene_id: True) - assert [job.session_uuid for job in jobs] == ["", ""] - - def test_adapter_rejects_mismatched_session_uuids_length() -> None: req = runtime_pb2.SimulationRequest( rollout_specs=[ @@ -111,4 +79,4 @@ def test_adapter_rejects_mismatched_session_uuids_length() -> None: ) with pytest.raises(ValueError, match="session_uuids"): - build_pending_jobs_from_request(req, lambda _scene_id: True) + build_pending_jobs_from_request(req, "req-1", lambda _scene_id: True) diff --git a/src/runtime/tests/test_daemon_scheduler.py b/src/runtime/tests/test_daemon_scheduler.py index 28d9b184..2e3ea034 100644 --- a/src/runtime/tests/test_daemon_scheduler.py +++ b/src/runtime/tests/test_daemon_scheduler.py @@ -4,11 +4,17 @@ from __future__ import annotations import asyncio -from unittest.mock import AsyncMock, patch +from pathlib import Path +from unittest.mock import patch import pytest from alpasim_runtime.address_pool import AddressPool -from alpasim_runtime.daemon.scheduler import DaemonScheduler, SceneAffineDispatch +from alpasim_runtime.config import SceneAffineDispatchConfig +from alpasim_runtime.daemon.scheduler import ( + DaemonScheduler, + SceneAffineDispatch, + _clear_retry_rollout_dir, +) from alpasim_runtime.worker.ipc import JobResult, PendingRolloutJob @@ -34,18 +40,28 @@ def _make_pools(capacity_per_service: int) -> dict[str, AddressPool]: def _make_pools_multi_gpu( n_concurrent: int = 1, + num_renderers: int = 2, ) -> dict[str, AddressPool]: - """Create pools with 2 renderer GPUs for affine tests.""" + """Create pools with multiple renderer GPUs for affine tests.""" + total_capacity = num_renderers * n_concurrent return { - "driver": AddressPool(["driver:50051"], n_concurrent=2, skip=False), + "driver": AddressPool( + ["driver:50051"], n_concurrent=total_capacity, skip=False + ), "renderer": AddressPool( - ["gpu-0:50052", "gpu-1:50052"], + [f"gpu-{i}:50052" for i in range(num_renderers)], n_concurrent=n_concurrent, skip=False, ), - "physics": AddressPool(["physics:50053"], n_concurrent=2, skip=False), - "trafficsim": AddressPool(["trafficsim:50054"], n_concurrent=2, skip=False), - "controller": AddressPool(["controller:50055"], n_concurrent=2, skip=False), + "physics": AddressPool( + ["physics:50053"], n_concurrent=total_capacity, skip=False + ), + "trafficsim": AddressPool( + ["trafficsim:50054"], n_concurrent=total_capacity, skip=False + ), + "controller": AddressPool( + ["controller:50055"], n_concurrent=total_capacity, skip=False + ), } @@ -53,21 +69,29 @@ def _pending( job_id: str, scene_id: str = "scene-a", rollout_spec_index: int = 0, + request_id: str = "req-a", ) -> PendingRolloutJob: return PendingRolloutJob( + request_id=request_id, job_id=job_id, scene_id=scene_id, rollout_spec_index=rollout_spec_index, ) -def _result(request_id: str, job_id: str) -> JobResult: +def _result( + request_id: str, + job_id: str, + *, + success: bool = True, + error: str | None = None, +) -> JobResult: return JobResult( request_id=request_id, job_id=job_id, rollout_spec_index=0, - success=True, - error=None, + success=success, + error=error, error_traceback=None, rollout_uuid=f"uuid-{job_id}", ) @@ -96,435 +120,572 @@ def check_for_crashes(self) -> None: @pytest.mark.asyncio -async def test_scheduler_dispatches_jobs() -> None: +async def test_scheduler_per_request_pool_releases_correctly() -> None: + """Per-request driver pool is used for dispatch and slots release back to it.""" runtime = _FakeRuntime() scheduler = DaemonScheduler( pools=_make_pools(capacity_per_service=1), runtime=runtime, + scene_affine_dispatch=SceneAffineDispatchConfig(enabled=True), ) - await scheduler.submit_request("req-a", [_pending("a1"), _pending("a2")]) - await scheduler.submit_request("req-b", [_pending("b1")]) - await scheduler.dispatch_once() - assert set(scheduler._in_flight) == {"a1"} - assert runtime.submitted_job_ids == ["a1"] + # Custom pool with capacity=1, so second job can only dispatch after first completes + custom_driver = AddressPool(["custom-driver:9999"], n_concurrent=1, skip=False) + await scheduler.submit_request( + "req-custom", + [ + _pending("j1", request_id="req-custom"), + _pending("j2", request_id="req-custom"), + ], + driver_pool=custom_driver, + ) + + # Only j1 dispatched (capacity=1), using the custom pool's address. + assert runtime.submitted_job_ids == ["j1"] + assert runtime.submitted_jobs[0].endpoints.driver.address == "custom-driver:9999" - scheduler.on_result(_result("req-a", "a1")) + # Complete j1 — should release slot and dispatch j2 + scheduler.on_result(_result("req-custom", "j1")) await scheduler.dispatch_once() - assert set(scheduler._in_flight) == {"a2"} - assert runtime.submitted_job_ids == ["a1", "a2"] + assert runtime.submitted_job_ids == ["j1", "j2"] await scheduler.shutdown(reason="test cleanup") +# --------------------------------------------------------------------------- +# Scene-affine dispatch +# --------------------------------------------------------------------------- + + @pytest.mark.asyncio -async def test_scheduler_routes_results_to_request_completion() -> None: +async def test_cold_dispatch_prefers_renderer_with_fewest_active_scenes() -> None: runtime = _FakeRuntime() scheduler = DaemonScheduler( - pools=_make_pools(capacity_per_service=2), + pools=_make_pools_multi_gpu(n_concurrent=4), runtime=runtime, + scene_affine_dispatch=SceneAffineDispatchConfig(enabled=True), ) - await scheduler.submit_request("req-1", [_pending("j1"), _pending("j2")]) + strategy = _affine_strategy(scheduler) + strategy.sync_scene_cache("gpu-0:50052", ["scene-A"]) + strategy.sync_scene_cache("gpu-1:50052", ["scene-B", "scene-C"]) - await scheduler.dispatch_once() - scheduler.on_result(_result("req-1", "j1")) - scheduler.on_result(_result("req-1", "j2")) + # gpu-0 ends up with 3 rollouts of one scene, gpu-1 with 2 rollouts of + # two scenes, so gpu-0 has fewer active scenes but fewer free slots. + await scheduler.submit_request( + "req-1", + [ + _pending("a1", scene_id="scene-A", request_id="req-1"), + _pending("a2", scene_id="scene-A", request_id="req-1"), + _pending("a3", scene_id="scene-A", request_id="req-1"), + _pending("b1", scene_id="scene-B", request_id="req-1"), + _pending("c1", scene_id="scene-C", request_id="req-1"), + ], + ) + a_jobs = [job for job in runtime.submitted_jobs if job.scene_id == "scene-A"] + assert {job.endpoints.renderer.address for job in a_jobs} == {"gpu-0:50052"} - completion = await scheduler.wait_request("req-1") - assert [result.request_id for result in completion] == ["req-1", "req-1"] - assert [result.job_id for result in completion] == ["j1", "j2"] + await scheduler.submit_request( + "req-2", [_pending("d1", scene_id="scene-D", request_id="req-2")] + ) + + d1 = runtime.submitted_jobs[-1] + assert d1.job_id == "d1" + assert d1.dispatch_kind == "cold_initial" + assert d1.endpoints.renderer.address == "gpu-0:50052" await scheduler.shutdown(reason="test cleanup") @pytest.mark.asyncio -async def test_scheduler_uses_per_request_driver_pool() -> None: - """When a per-request driver_pool is provided, dispatch uses it instead of the base pool.""" +async def test_scheduler_retries_any_failure_up_to_configured_limit( + tmp_path: Path, +) -> None: runtime = _FakeRuntime() scheduler = DaemonScheduler( pools=_make_pools(capacity_per_service=1), runtime=runtime, + scene_affine_dispatch=SceneAffineDispatchConfig(enabled=False), + max_rollout_retries=2, + rollouts_dir=str(tmp_path), ) - - custom_driver = AddressPool(["custom-driver:9999"], n_concurrent=1, skip=False) - await scheduler.submit_request( - "req-custom", - [_pending("j1")], - driver_pool=custom_driver, + original = _pending("j1") + original.session_uuid = "requested-session" + await scheduler.submit_request("req-retry", [original]) + + current_job_id = "j1" + for retry_attempt in range(1, 3): + rollout_dir = tmp_path / original.scene_id / original.session_uuid + rollout_dir.mkdir(parents=True) + (rollout_dir / "rollout.asl").write_text("failed attempt") + (rollout_dir / "_complete").touch() + + scheduler.on_result( + _result( + "req-retry", + current_job_id, + success=False, + error=f"failure {retry_attempt}", + ) + ) + assert not rollout_dir.exists() + await scheduler.dispatch_once() + + retry_job = runtime.submitted_jobs[-1] + assert retry_job.job_id != current_job_id + assert retry_job.scene_id == original.scene_id + assert retry_job.rollout_spec_index == original.rollout_spec_index + assert retry_job.session_uuid == "requested-session" + assert ( + scheduler._in_flight[retry_job.job_id].pending_job.retry_attempt + == retry_attempt + ) + current_job_id = retry_job.job_id + + scheduler.on_result( + _result( + "req-retry", + current_job_id, + success=False, + error="final failure", + ) ) + completion = await scheduler.wait_request("req-retry") - assert runtime.submitted_job_ids == ["j1"] + assert len(runtime.submitted_jobs) == 3 + assert len(completion) == 1 + assert completion[0].job_id == current_job_id + assert completion[0].error == "final failure" await scheduler.shutdown(reason="test cleanup") @pytest.mark.asyncio -async def test_scheduler_per_request_pool_releases_correctly() -> None: - """Per-request driver pool slots are released back to the correct pool on result.""" +async def test_scheduler_returns_successful_retry_instead_of_initial_failure() -> None: runtime = _FakeRuntime() scheduler = DaemonScheduler( pools=_make_pools(capacity_per_service=1), runtime=runtime, + scene_affine_dispatch=SceneAffineDispatchConfig(enabled=False), + max_rollout_retries=2, ) + await scheduler.submit_request("req-retry", [_pending("j1")]) - # Custom pool with capacity=1, so second job can only dispatch after first completes - custom_driver = AddressPool(["custom-driver:9999"], n_concurrent=1, skip=False) - await scheduler.submit_request( - "req-custom", - [_pending("j1"), _pending("j2")], - driver_pool=custom_driver, + scheduler.on_result( + _result("req-retry", "j1", success=False, error="transient failure") ) - - # Only j1 dispatched (capacity=1) - assert runtime.submitted_job_ids == ["j1"] - - # Complete j1 — should release slot and dispatch j2 - scheduler.on_result(_result("req-custom", "j1")) await scheduler.dispatch_once() + retry_job = runtime.submitted_jobs[-1] + assert retry_job.session_uuid == "" + retry_job_id = retry_job.job_id + scheduler.on_result(_result("req-retry", retry_job_id)) - assert runtime.submitted_job_ids == ["j1", "j2"] + completion = await scheduler.wait_request("req-retry") + assert len(runtime.submitted_jobs) == 2 + assert len(completion) == 1 + assert completion[0].success is True + assert completion[0].job_id == retry_job_id await scheduler.shutdown(reason="test cleanup") +def test_scheduler_rejects_negative_retry_limit() -> None: + with pytest.raises(ValueError, match="max_rollout_retries must be non-negative"): + DaemonScheduler( + pools=_make_pools(capacity_per_service=1), + runtime=_FakeRuntime(), + scene_affine_dispatch=SceneAffineDispatchConfig(enabled=False), + max_rollout_retries=-1, + ) + + +def test_clear_retry_rollout_dir_rejects_path_traversal(tmp_path: Path) -> None: + outside_dir = tmp_path.parent / f"{tmp_path.name}-outside-session" + outside_dir.mkdir(exist_ok=True) + artifact = outside_dir / "rollout.asl" + artifact.write_text("keep") + pending_job = _pending("j1") + pending_job.session_uuid = f"../../{outside_dir.name}" + + with pytest.raises(ValueError, match="one path component"): + _clear_retry_rollout_dir(pending_job, str(tmp_path)) + + assert artifact.read_text() == "keep" + + @pytest.mark.asyncio -async def test_scheduler_assigns_active_renderer_endpoint() -> None: +async def test_max_scenes_per_renderer_defers_cold_dispatch() -> None: runtime = _FakeRuntime() - pools = _make_pools(capacity_per_service=1) - pools["renderer"] = AddressPool(["video-model:50056"], 1, skip=False) scheduler = DaemonScheduler( - pools=pools, + pools=_make_pools_multi_gpu(n_concurrent=2), runtime=runtime, + scene_affine_dispatch=SceneAffineDispatchConfig( + enabled=True, max_scenes_per_renderer=1 + ), ) - await scheduler.submit_request("req-renderer", [_pending("j1")]) + await scheduler.submit_request( + "req-1", + [ + _pending("a1", scene_id="scene-A", request_id="req-1"), + _pending("b1", scene_id="scene-B", request_id="req-1"), + _pending("c1", scene_id="scene-C", request_id="req-1"), + ], + ) + + assert [job.job_id for job in runtime.submitted_jobs] == ["a1", "b1"] + assert scheduler._strategy.pending_count == 1 + + # Completing scene-A leaves it cached but idle on gpu-0, so gpu-0 is + # eligible again: only loading or executing scenes count toward the cap. + scheduler.on_result(_result("req-1", "a1")) + await scheduler.dispatch_once() - job = runtime.submitted_jobs[0] - assert job.endpoints.renderer.address == "video-model:50056" - assert not hasattr(job.endpoints, "sensorsim") + c1 = runtime.submitted_jobs[-1] + assert c1.job_id == "c1" + assert c1.dispatch_kind == "cold_initial" + assert c1.endpoints.renderer.address == "gpu-0:50052" await scheduler.shutdown(reason="test cleanup") @pytest.mark.asyncio -async def test_scheduler_does_not_acquire_inactive_renderer_pool() -> None: +async def test_max_scenes_per_renderer_does_not_block_cached_affinity() -> None: runtime = _FakeRuntime() scheduler = DaemonScheduler( - pools=_make_pools(capacity_per_service=1), + pools=_make_pools_multi_gpu(n_concurrent=3, num_renderers=1), runtime=runtime, + scene_affine_dispatch=SceneAffineDispatchConfig( + enabled=True, max_scenes_per_renderer=1 + ), ) + strategy = _affine_strategy(scheduler) + strategy.sync_scene_cache("gpu-0:50052", ["scene-A"]) - await scheduler.submit_request("req-renderer", [_pending("j1")]) + await scheduler.submit_request( + "req-1", [_pending("b1", scene_id="scene-B", request_id="req-1")] + ) + await scheduler.submit_request( + "req-2", [_pending("a1", scene_id="scene-A", request_id="req-2")] + ) + await scheduler.submit_request( + "req-3", [_pending("c1", scene_id="scene-C", request_id="req-3")] + ) - assert runtime.submitted_job_ids == ["j1"] - assert runtime.submitted_jobs[0].endpoints.renderer.address == "sensorsim:50052" + assert [job.job_id for job in runtime.submitted_jobs] == ["b1", "a1"] + assert runtime.submitted_jobs[1].dispatch_kind == "cached_affine" + assert scheduler._strategy.pending_count == 1 await scheduler.shutdown(reason="test cleanup") -# --------------------------------------------------------------------------- -# Scene-affine dispatch: tier 1/2/3 job selection -# --------------------------------------------------------------------------- - - @pytest.mark.asyncio -async def test_tier1_prefers_job_for_cached_scene() -> None: - """When a free GPU has scene-A cached, a pending scene-A job is preferred.""" +async def test_cached_affinity_chooses_least_loaded_matching_renderer() -> None: runtime = _FakeRuntime() - pools = _make_pools_multi_gpu() - scheduler = DaemonScheduler(pools=pools, runtime=runtime) - - # Simulate gRPC sync: gpu-0 has scene-A cached. - _affine_strategy(scheduler).sync_scene_cache("gpu-0:50052", ["scene-A"]) + scheduler = DaemonScheduler( + pools=_make_pools_multi_gpu(n_concurrent=2), + runtime=runtime, + scene_affine_dispatch=SceneAffineDispatchConfig(enabled=True), + ) + strategy = _affine_strategy(scheduler) + strategy.sync_scene_cache("gpu-0:50052", ["scene-A", "scene-B"]) + strategy.sync_scene_cache("gpu-1:50052", ["scene-A"]) - # Submit jobs for scene-B (new) and scene-A (cached on gpu-0). await scheduler.submit_request( - "req-1", - [_pending("j2", scene_id="scene-B"), _pending("j3", scene_id="scene-A")], + "req-1", [_pending("b1", scene_id="scene-B", request_id="req-1")] ) - - # Both dispatched (2 GPUs available). j3 (scene-A) should go to gpu-0. - assert len(runtime.submitted_jobs) == 2 - j3_gpu = next( - j.endpoints.renderer.address for j in runtime.submitted_jobs if j.job_id == "j3" + await scheduler.submit_request( + "req-2", [_pending("a1", scene_id="scene-A", request_id="req-2")] ) - assert j3_gpu == "gpu-0:50052" + + assert runtime.submitted_jobs[0].endpoints.renderer.address == "gpu-0:50052" + assert runtime.submitted_jobs[1].endpoints.renderer.address == "gpu-1:50052" await scheduler.shutdown(reason="test cleanup") @pytest.mark.asyncio -async def test_tier2_prefers_new_scene_over_cached_elsewhere() -> None: - """When no free GPU has a matching cache, prefer a scene not cached anywhere. - - Setup: gpu-0 has scene-A cached, gpu-1 has scene-B cached (via sync). - Block gpu-1 with work, leaving gpu-0 (with A) free. - Submit jobs for scene-B (cached on busy gpu-1) and scene-C (new). - Tier 1 fails (gpu-0 has A, not B or C). - Tier 2 should prefer scene-C (not cached anywhere) over scene-B. - """ +async def test_cold_scene_uses_at_most_one_rollout_per_renderer() -> None: runtime = _FakeRuntime() - pools = _make_pools_multi_gpu() - scheduler = DaemonScheduler(pools=pools, runtime=runtime) - - # Seed cache via sync (simulating gRPC introspection). - _affine_strategy(scheduler).sync_scene_cache("gpu-0:50052", ["scene-A"]) - _affine_strategy(scheduler).sync_scene_cache("gpu-1:50052", ["scene-B"]) + scheduler = DaemonScheduler( + pools=_make_pools_multi_gpu(n_concurrent=2), + runtime=runtime, + scene_affine_dispatch=SceneAffineDispatchConfig( + enabled=True, max_renderers_per_scene=2 + ), + ) - # Block gpu-1 with work. await scheduler.submit_request( - "req-block", [_pending("jblock", scene_id="scene-X")] + "req-1", + [_pending(f"a{i}", scene_id="scene-A", request_id="req-1") for i in range(3)], ) - # jblock acquires gpu-0 (FIFO front — tier 1 hit on scene-A? No, scene-X not cached). - # Actually tier 2: scene-X not cached → FIFO slot → gpu-0. - first_gpu = runtime.submitted_jobs[0].endpoints.renderer.address - # Block the other GPU too if first went to gpu-0. - if first_gpu == "gpu-0:50052": - # gpu-1 is free with scene-B cached. Block it. - await scheduler.submit_request( - "req-block2", [_pending("jblock2", scene_id="scene-Y")] - ) - # Release gpu-0 so it's available. - scheduler.on_result(_result("req-block", "jblock")) - else: - # gpu-0 is free with scene-A cached. Good — gpu-1 is busy. - pass - - # Now we need gpu-0 free (with scene-A) and gpu-1 busy. - # Simpler approach: just release and re-block deterministically. + assert [job.dispatch_kind for job in runtime.submitted_jobs] == [ + "cold_initial", + "cold_replica", + ] + assert [job.endpoints.renderer.address for job in runtime.submitted_jobs] == [ + "gpu-0:50052", + "gpu-1:50052", + ] + assert scheduler._strategy.pending_count == 1 + await scheduler.shutdown(reason="test cleanup") - # Re-create with deterministic setup. - runtime = _FakeRuntime() - pools = _make_pools_multi_gpu() - scheduler = DaemonScheduler(pools=pools, runtime=runtime) - _affine_strategy(scheduler).sync_scene_cache("gpu-0:50052", ["scene-A"]) - _affine_strategy(scheduler).sync_scene_cache("gpu-1:50052", ["scene-B"]) - # Acquire gpu-1 slot directly to block it, then submit. - slot = pools["renderer"].try_acquire_for_address("gpu-1:50052") - assert slot is not None # gpu-1 is now busy +@pytest.mark.asyncio +async def test_earlier_scene_replicates_to_bound_before_later_scene_starts() -> None: + runtime = _FakeRuntime() + scheduler = DaemonScheduler( + pools=_make_pools_multi_gpu(n_concurrent=1, num_renderers=3), + runtime=runtime, + scene_affine_dispatch=SceneAffineDispatchConfig( + enabled=True, max_renderers_per_scene=2 + ), + ) - # Submit scene-B (cached on busy gpu-1) and scene-C (new). await scheduler.submit_request( - "req-2", - [_pending("j3", scene_id="scene-B"), _pending("j4", scene_id="scene-C")], + "req-1", + [ + _pending("a1", scene_id="scene-A", request_id="req-1"), + _pending("a2", scene_id="scene-A", request_id="req-1"), + _pending("b1", scene_id="scene-B", request_id="req-1"), + ], ) - # Only gpu-0 is free (has A cached, not B or C → tier 1 fails). - # Tier 2: scene-B is cached (gpu-1), scene-C is not cached → pick scene-C. - dispatched_job = runtime.submitted_jobs[0] - assert dispatched_job.job_id == "j4" - assert dispatched_job.scene_id == "scene-C" + # Scene-A arrived first, so it replicates to max_renderers_per_scene + # before scene-B gets its first location. + assert [(job.job_id, job.dispatch_kind) for job in runtime.submitted_jobs] == [ + ("a1", "cold_initial"), + ("a2", "cold_replica"), + ("b1", "cold_initial"), + ] - pools["renderer"].release(slot) await scheduler.shutdown(reason="test cleanup") @pytest.mark.asyncio -async def test_affine_same_scene_returns_to_same_gpu() -> None: - """A sync-seeded cache directs repeat jobs to the same GPU.""" +async def test_cached_scene_full_starts_only_one_cold_replica() -> None: runtime = _FakeRuntime() - pools = _make_pools_multi_gpu() - scheduler = DaemonScheduler(pools=pools, runtime=runtime) - - # Simulate gRPC sync reporting scene-A on gpu-0. + pools = _make_pools_multi_gpu(n_concurrent=2) + scheduler = DaemonScheduler( + pools=pools, + runtime=runtime, + scene_affine_dispatch=SceneAffineDispatchConfig( + enabled=True, max_renderers_per_scene=2 + ), + ) _affine_strategy(scheduler).sync_scene_cache("gpu-0:50052", ["scene-A"]) + gpu0_slots = [ + pools["renderer"].try_acquire_for_address("gpu-0:50052") for _ in range(2) + ] + assert all(slot is not None for slot in gpu0_slots) - # Submit scene-A job — should hit gpu-0 (tier-1). - await scheduler.submit_request("req-1", [_pending("j1", scene_id="scene-A")]) - first_gpu = runtime.submitted_jobs[0].endpoints.renderer.address - assert first_gpu == "gpu-0:50052" - - # Complete the job. - scheduler.on_result(_result("req-1", "j1")) + await scheduler.submit_request( + "req-1", + [_pending(f"a{i}", scene_id="scene-A", request_id="req-1") for i in range(3)], + ) - # Submit another scene-A job — should still hit gpu-0 (cache still seeded). - await scheduler.submit_request("req-2", [_pending("j2", scene_id="scene-A")]) - second_gpu = runtime.submitted_jobs[1].endpoints.renderer.address - assert second_gpu == first_gpu + assert [(job.job_id, job.dispatch_kind) for job in runtime.submitted_jobs] == [ + ("a0", "cold_replica") + ] + assert runtime.submitted_jobs[0].endpoints.renderer.address == "gpu-1:50052" + assert scheduler._strategy.pending_count == 2 + for slot in gpu0_slots: + assert slot is not None + pools["renderer"].release(slot) await scheduler.shutdown(reason="test cleanup") @pytest.mark.asyncio -async def test_different_scenes_get_different_gpus() -> None: - """Different scenes are routed to different GPUs when possible.""" +async def test_failed_cold_rollout_allows_retry() -> None: runtime = _FakeRuntime() - pools = _make_pools_multi_gpu() - scheduler = DaemonScheduler(pools=pools, runtime=runtime) + scheduler = DaemonScheduler( + pools=_make_pools_multi_gpu(n_concurrent=1), + runtime=runtime, + scene_affine_dispatch=SceneAffineDispatchConfig( + enabled=True, max_renderers_per_scene=1 + ), + ) + await scheduler.submit_request( + "req-1", + [ + _pending("a1", scene_id="scene-A", request_id="req-1"), + _pending("a2", scene_id="scene-A", request_id="req-1"), + ], + ) - # Simulate gRPC sync: gpu-0 has scene-A, gpu-1 has scene-B. - _affine_strategy(scheduler).sync_scene_cache("gpu-0:50052", ["scene-A"]) - _affine_strategy(scheduler).sync_scene_cache("gpu-1:50052", ["scene-B"]) + failed = _result("req-1", "a1") + failed.success = False + scheduler.on_result(failed) + await scheduler.dispatch_once() - # Dispatch scene-A — should hit gpu-0 (tier-1). - await scheduler.submit_request("req-1", [_pending("j1", scene_id="scene-A")]) - gpu_a = runtime.submitted_jobs[0].endpoints.renderer.address - assert gpu_a == "gpu-0:50052" - scheduler.on_result(_result("req-1", "j1")) - - # Dispatch scene-B — should hit gpu-1 (tier-1). - await scheduler.submit_request("req-2", [_pending("j2", scene_id="scene-B")]) - gpu_b = runtime.submitted_jobs[1].endpoints.renderer.address - assert gpu_b == "gpu-1:50052" - scheduler.on_result(_result("req-2", "j2")) - - # Dispatch scene-A again — should still get gpu-0. - await scheduler.submit_request("req-3", [_pending("j3", scene_id="scene-A")]) - gpu_a2 = runtime.submitted_jobs[2].endpoints.renderer.address - assert gpu_a2 == gpu_a - - # Dispatch scene-B again — should still get gpu-1. - scheduler.on_result(_result("req-3", "j3")) - await scheduler.submit_request("req-4", [_pending("j4", scene_id="scene-B")]) - gpu_b2 = runtime.submitted_jobs[3].endpoints.renderer.address - assert gpu_b2 == gpu_b + assert [job.job_id for job in runtime.submitted_jobs] == ["a1", "a2"] + assert runtime.submitted_jobs[-1].dispatch_kind == "cold_initial" await scheduler.shutdown(reason="test cleanup") @pytest.mark.asyncio -async def test_sync_seeded_cache_preserves_diversity() -> None: - """Sync-seeded caches route each scene to its designated GPU. - - gpu-0 has scene-A, gpu-1 has scene-B. Sequential dispatches with - one GPU free at a time should always route to the correct GPU. - """ +async def test_successful_cold_rollout_promotes_affinity_without_refresh() -> None: runtime = _FakeRuntime() - pools = _make_pools_multi_gpu() - scheduler = DaemonScheduler(pools=pools, runtime=runtime) - - # Seed via sync. - _affine_strategy(scheduler).sync_scene_cache("gpu-0:50052", ["A"]) - _affine_strategy(scheduler).sync_scene_cache("gpu-1:50052", ["B"]) - - # Block gpu-1 so only gpu-0 is free. - gpu1_slot = pools["renderer"].try_acquire_for_address("gpu-1:50052") - assert gpu1_slot is not None + scheduler = DaemonScheduler( + pools=_make_pools_multi_gpu(n_concurrent=1), + runtime=runtime, + scene_affine_dispatch=SceneAffineDispatchConfig( + enabled=True, max_renderers_per_scene=1, cache_refresh_interval_s=None + ), + ) + await scheduler.submit_request( + "req-1", + [ + _pending("a1", scene_id="scene-A", request_id="req-1"), + _pending("a2", scene_id="scene-A", request_id="req-1"), + ], + ) - # Submit scene-A — should route to gpu-0 (tier-1 hit). - await scheduler.submit_request("req-1", [_pending("a1", scene_id="A")]) - assert runtime.submitted_jobs[0].endpoints.renderer.address == "gpu-0:50052" + first_address = runtime.submitted_jobs[0].endpoints.renderer.address scheduler.on_result(_result("req-1", "a1")) + await scheduler.dispatch_once() - # Free gpu-1, block gpu-0. - pools["renderer"].release(gpu1_slot) - gpu0_slot = pools["renderer"].try_acquire_for_address("gpu-0:50052") - assert gpu0_slot is not None - - # Submit scene-B — should route to gpu-1 (tier-1 hit). - await scheduler.submit_request("req-2", [_pending("b1", scene_id="B")]) - assert runtime.submitted_jobs[1].endpoints.renderer.address == "gpu-1:50052" - scheduler.on_result(_result("req-2", "b1")) - - # Free gpu-0, submit scene-A again — still hits gpu-0. - pools["renderer"].release(gpu0_slot) - gpu1_slot = pools["renderer"].try_acquire_for_address("gpu-1:50052") - assert gpu1_slot is not None - await scheduler.submit_request("req-3", [_pending("a2", scene_id="A")]) - assert runtime.submitted_jobs[2].endpoints.renderer.address == "gpu-0:50052" + assert runtime.submitted_jobs[-1].dispatch_kind == "cached_affine" + assert runtime.submitted_jobs[-1].endpoints.renderer.address == first_address - pools["renderer"].release(gpu1_slot) await scheduler.shutdown(reason="test cleanup") @pytest.mark.asyncio -async def test_affine_disabled_uses_plain_fifo() -> None: - """With scene_affine_dispatch=False, dispatch is pure FIFO.""" +async def test_empty_cache_snapshot_does_not_clear_loading_location() -> None: runtime = _FakeRuntime() - pools = _make_pools_multi_gpu() scheduler = DaemonScheduler( - pools=pools, runtime=runtime, scene_affine_dispatch=False + pools=_make_pools_multi_gpu(n_concurrent=2), + runtime=runtime, + scene_affine_dispatch=SceneAffineDispatchConfig( + enabled=True, max_renderers_per_scene=1 + ), ) - - # Seed: dispatch scene-A on gpu-0, complete it. - await scheduler.submit_request("req-1", [_pending("j1", scene_id="scene-A")]) - scheduler.on_result(_result("req-1", "j1")) - - # Submit scene-B and scene-A. With affine off, the scheduler just picks - # any job — no preference for scene-A on the cached GPU. await scheduler.submit_request( - "req-2", - [_pending("j2", scene_id="scene-B"), _pending("j3", scene_id="scene-A")], + "req-1", + [ + _pending("a1", scene_id="scene-A", request_id="req-1"), + _pending("a2", scene_id="scene-A", request_id="req-1"), + ], ) + first_address = runtime.submitted_jobs[0].endpoints.renderer.address - # Both should dispatch (2 GPUs), but order is not scene-aware. - assert len(runtime.submitted_jobs) == 3 + _affine_strategy(scheduler).sync_scene_cache(first_address, []) + await scheduler.dispatch_once() + assert [job.job_id for job in runtime.submitted_jobs] == ["a1"] - # FifoDispatch has no affine tracking at all. - assert not hasattr(scheduler._strategy, "_affine_hits") + _affine_strategy(scheduler).sync_scene_cache(first_address, ["scene-A"]) + await scheduler.dispatch_once() + assert [job.job_id for job in runtime.submitted_jobs] == ["a1", "a2"] await scheduler.shutdown(reason="test cleanup") @pytest.mark.asyncio -async def test_warm_started_pool_produces_tier1_hit() -> None: - """A warm-started pool should produce tier-1 hits on the very first dispatch.""" +async def test_cache_snapshot_removes_optimistic_loaded_location() -> None: runtime = _FakeRuntime() - pools = _make_pools_multi_gpu() + scheduler = DaemonScheduler( + pools=_make_pools_multi_gpu(n_concurrent=1), + runtime=runtime, + scene_affine_dispatch=SceneAffineDispatchConfig( + enabled=True, max_renderers_per_scene=1 + ), + ) + await scheduler.submit_request( + "req-1", [_pending("a1", scene_id="scene-A", request_id="req-1")] + ) + first_address = runtime.submitted_jobs[0].endpoints.renderer.address + scheduler.on_result(_result("req-1", "a1")) - scheduler = DaemonScheduler(pools=pools, runtime=runtime) + _affine_strategy(scheduler).sync_scene_cache(first_address, []) + await scheduler.submit_request( + "req-2", [_pending("a2", scene_id="scene-A", request_id="req-2")] + ) - # Pre-seed the strategy's cache as SceneAffineDispatch.warm_start() would. - _affine_strategy(scheduler).sync_scene_cache("gpu-0:50052", ["scene-X"]) - _affine_strategy(scheduler).sync_scene_cache("gpu-1:50052", ["scene-Y"]) + assert runtime.submitted_jobs[-1].dispatch_kind == "cold_initial" - # Submit scene-X — should hit gpu-0 (tier-1: cached + free). - await scheduler.submit_request("req-1", [_pending("j1", scene_id="scene-X")]) - assert runtime.submitted_jobs[0].endpoints.renderer.address == "gpu-0:50052" - assert _affine_strategy(scheduler)._affine_hits == 1 + await scheduler.shutdown(reason="test cleanup") - # Complete and submit scene-Y — should hit gpu-1 (tier-1). - scheduler.on_result(_result("req-1", "j1")) - await scheduler.submit_request("req-2", [_pending("j2", scene_id="scene-Y")]) - assert runtime.submitted_jobs[1].endpoints.renderer.address == "gpu-1:50052" - assert _affine_strategy(scheduler)._affine_hits == 2 - await scheduler.shutdown(reason="test cleanup") +@pytest.mark.asyncio +async def test_failed_service_reservation_does_not_mark_scene_loading() -> None: + runtime = _FakeRuntime() + pools = _make_pools_multi_gpu(n_concurrent=1) + blocked_drivers = [pools["driver"].try_acquire() for _ in range(2)] + assert all(slot is not None for slot in blocked_drivers) + scheduler = DaemonScheduler( + pools=pools, + runtime=runtime, + scene_affine_dispatch=SceneAffineDispatchConfig( + enabled=True, max_renderers_per_scene=1 + ), + ) + await scheduler.submit_request( + "req-1", [_pending("a1", scene_id="scene-A", request_id="req-1")] + ) + assert runtime.submitted_jobs == [] -# --------------------------------------------------------------------------- -# warm_start integration tests -# --------------------------------------------------------------------------- + for slot in blocked_drivers: + assert slot is not None + pools["driver"].release(slot) + await scheduler.dispatch_once() + assert runtime.submitted_jobs[0].dispatch_kind == "cold_initial" + + await scheduler.shutdown(reason="test cleanup") @pytest.mark.asyncio -async def test_warm_start_seeds_cache_and_starts_refresh() -> None: - """warm_start() should query NRE, seed the cache, and start the refresh loop.""" +async def test_earlier_scene_cached_on_busy_renderer_replicates_first() -> None: + """Cold dispatch follows scene arrival order, not cache coverage. + + Setup: gpu-0 has scene-A cached, gpu-1 has scene-B cached (via sync). + Block gpu-1, leaving gpu-0 (with A) free. + Submit jobs for scene-B (cached on busy gpu-1) and scene-C (new). + Tier 1 fails (gpu-0 has A, not B or C). + Scene-B arrived first, so it replicates onto gpu-0 before scene-C + gets its first location. + """ runtime = _FakeRuntime() pools = _make_pools_multi_gpu() + scheduler = DaemonScheduler( + pools=pools, + runtime=runtime, + scene_affine_dispatch=SceneAffineDispatchConfig(enabled=True), + ) + _affine_strategy(scheduler).sync_scene_cache("gpu-0:50052", ["scene-A"]) + _affine_strategy(scheduler).sync_scene_cache("gpu-1:50052", ["scene-B"]) - responses = { - "gpu-0:50052": {"scene-A": 2}, - "gpu-1:50052": {"scene-B": 1}, - } + # Acquire gpu-1 slot directly to block it, then submit. + slot = pools["renderer"].try_acquire_for_address("gpu-1:50052") + assert slot is not None # gpu-1 is now busy - async def _fake_get(address: str, **kwargs): - return responses.get(address, {}) + # Submit scene-B (cached on busy gpu-1) and scene-C (new). + await scheduler.submit_request( + "req-2", + [ + _pending("j3", scene_id="scene-B", request_id="req-2"), + _pending("j4", scene_id="scene-C", request_id="req-2"), + ], + ) - with patch("alpasim_runtime.daemon.scheduler.get_loaded_scenes", _fake_get): - scheduler = DaemonScheduler( - pools=pools, - runtime=runtime, - cache_refresh_interval_s=60.0, - ) - # Before warm_start, no cache and no refresh task. - assert not _affine_strategy(scheduler).is_scene_cached("scene-A") - assert _affine_strategy(scheduler)._cache_refresh_task is None + dispatched_job = runtime.submitted_jobs[0] + assert dispatched_job.job_id == "j3" + assert dispatched_job.dispatch_kind == "cold_replica" + assert dispatched_job.endpoints.renderer.address == "gpu-0:50052" + assert scheduler._strategy.pending_count == 1 - await scheduler.warm_start() + pools["renderer"].release(slot) + await scheduler.shutdown(reason="test cleanup") - # After warm_start, cache is seeded and refresh task is running. - strategy = _affine_strategy(scheduler) - assert strategy.is_scene_cached("scene-A") - assert strategy.is_scene_cached("scene-B") - assert strategy._cache_refresh_task is not None - assert not strategy._cache_refresh_task.done() - await scheduler.shutdown(reason="test cleanup") +# --------------------------------------------------------------------------- +# warm_start integration tests +# --------------------------------------------------------------------------- @pytest.mark.asyncio @@ -546,41 +707,15 @@ async def _fake_get(address: str, **kwargs): scheduler = DaemonScheduler( pools=pools, runtime=runtime, - cache_refresh_interval_s=5.0, + scene_affine_dispatch=SceneAffineDispatchConfig( + enabled=True, cache_refresh_interval_s=5.0 + ), ) with pytest.raises(IntrospectionNotSupportedError): await scheduler.warm_start() # Refresh task should NOT have been started on failure. - assert _affine_strategy(scheduler)._cache_refresh_task is None - - await scheduler.shutdown(reason="test cleanup") - - -@pytest.mark.asyncio -async def test_warm_start_partial_failure_continues() -> None: - """warm_start() should continue if some addresses return None (transient failure).""" - runtime = _FakeRuntime() - pools = _make_pools_multi_gpu() - - async def _fake_get(address: str, **kwargs): - if address == "gpu-0:50052": - return {"scene-A": 1} - return None # gpu-1 is unreachable - - with patch("alpasim_runtime.daemon.scheduler.get_loaded_scenes", _fake_get): - scheduler = DaemonScheduler( - pools=pools, - runtime=runtime, - cache_refresh_interval_s=60.0, - ) - await scheduler.warm_start() - - # Only gpu-0's scenes should be cached. - assert _affine_strategy(scheduler).is_scene_cached("scene-A") - assert not _affine_strategy(scheduler).is_scene_cached("scene-B") - # Refresh task should still start. - assert _affine_strategy(scheduler)._cache_refresh_task is not None + assert scheduler._cache_refresh_task is None await scheduler.shutdown(reason="test cleanup") @@ -591,100 +726,77 @@ async def _fake_get(address: str, **kwargs): @pytest.mark.asyncio -async def test_cache_refresh_updates_routing() -> None: - """The periodic refresh should update the cache so the next dispatch benefits.""" +async def test_cache_refresh_wakes_pending_affine_dispatch() -> None: runtime = _FakeRuntime() - pools = _make_pools_multi_gpu() - - call_count = 0 - responses = { - "gpu-0:50052": {"scene-Z": 2}, - "gpu-1:50052": {"scene-W": 1}, - } + pools = _make_pools_multi_gpu(n_concurrent=2) + refresh_started = False async def _fake_get(address: str, **kwargs): - nonlocal call_count - call_count += 1 - return responses.get(address, {}) + nonlocal refresh_started + del kwargs + if not refresh_started: + return {} + if address == "gpu-0:50052": + return {"scene-A": 1} + return {} with patch("alpasim_runtime.daemon.scheduler.get_loaded_scenes", _fake_get): scheduler = DaemonScheduler( pools=pools, runtime=runtime, - cache_refresh_interval_s=0.05, + scene_affine_dispatch=SceneAffineDispatchConfig( + enabled=True, cache_refresh_interval_s=0.01, max_renderers_per_scene=1 + ), ) - # warm_start seeds the cache and starts the refresh loop. await scheduler.warm_start() - # Let the refresh loop fire at least once after warm_start. - await asyncio.sleep(0.15) + await scheduler.submit_request( + "req-1", + [ + _pending("a1", scene_id="scene-A", request_id="req-1"), + _pending("a2", scene_id="scene-A", request_id="req-1"), + ], + ) + assert [job.job_id for job in runtime.submitted_jobs] == ["a1"] - # The strategy should now know about scene-Z on gpu-0 and scene-W on gpu-1. - assert _affine_strategy(scheduler).is_scene_cached("scene-Z") - assert _affine_strategy(scheduler).is_scene_cached("scene-W") - assert call_count >= 2 # at least one full cycle (2 addresses) + refresh_started = True + for _ in range(20): + if len(runtime.submitted_jobs) == 2: + break + await asyncio.sleep(0.01) - # Dispatch scene-Z — should hit gpu-0 (tier-1). - await scheduler.submit_request("req-1", [_pending("j1", scene_id="scene-Z")]) - assert runtime.submitted_jobs[0].endpoints.renderer.address == "gpu-0:50052" - assert _affine_strategy(scheduler)._affine_hits == 1 + assert [job.job_id for job in runtime.submitted_jobs] == ["a1", "a2"] + assert runtime.submitted_jobs[-1].dispatch_kind == "cached_affine" + assert runtime.submitted_jobs[-1].endpoints.renderer.address == "gpu-0:50052" await scheduler.shutdown(reason="test cleanup") @pytest.mark.asyncio -async def test_cache_refresh_disabled_when_none() -> None: - """cache_refresh_interval_s=None should not create a refresh task.""" +async def test_warm_cache_above_replica_limit_remains_usable() -> None: runtime = _FakeRuntime() - pools = _make_pools_multi_gpu() - scheduler = DaemonScheduler( - pools=pools, + pools=_make_pools_multi_gpu(n_concurrent=1), runtime=runtime, - cache_refresh_interval_s=None, + scene_affine_dispatch=SceneAffineDispatchConfig( + enabled=True, max_renderers_per_scene=1 + ), ) - assert _affine_strategy(scheduler)._cache_refresh_task is None - await scheduler.shutdown(reason="test cleanup") + strategy = _affine_strategy(scheduler) + strategy.sync_scene_cache("gpu-0:50052", ["scene-A"]) + strategy.sync_scene_cache("gpu-1:50052", ["scene-A"]) - -@pytest.mark.asyncio -async def test_cache_refresh_disabled_when_affine_off() -> None: - """With scene_affine_dispatch=False, no refresh task should be created.""" - runtime = _FakeRuntime() - pools = _make_pools_multi_gpu() - - scheduler = DaemonScheduler( - pools=pools, - runtime=runtime, - scene_affine_dispatch=False, - cache_refresh_interval_s=30.0, + await scheduler.submit_request( + "req-1", + [ + _pending("a1", scene_id="scene-A", request_id="req-1"), + _pending("a2", scene_id="scene-A", request_id="req-1"), + ], ) - # FifoDispatch has no cache refresh mechanism. - assert not hasattr(scheduler._strategy, "_cache_refresh_task") - await scheduler.shutdown(reason="test cleanup") - - -@pytest.mark.asyncio -async def test_shutdown_cancels_refresh_task() -> None: - """shutdown() should cleanly cancel the refresh task.""" - runtime = _FakeRuntime() - pools = _make_pools_multi_gpu() - - mock_get = AsyncMock(return_value={"scene-A": 1}) - - with patch("alpasim_runtime.daemon.scheduler.get_loaded_scenes", mock_get): - scheduler = DaemonScheduler( - pools=pools, - runtime=runtime, - cache_refresh_interval_s=60.0, - ) - strategy = _affine_strategy(scheduler) - # Refresh task is not started until warm_start. - assert strategy._cache_refresh_task is None - await scheduler.warm_start() - assert strategy._cache_refresh_task is not None - assert not strategy._cache_refresh_task.done() - - await scheduler.shutdown(reason="test cleanup") + assert {job.endpoints.renderer.address for job in runtime.submitted_jobs} == { + "gpu-0:50052", + "gpu-1:50052", + } + assert all(job.dispatch_kind == "cached_affine" for job in runtime.submitted_jobs) - assert strategy._cache_refresh_task.done() + await scheduler.shutdown(reason="test cleanup") diff --git a/src/runtime/tests/test_event_policy.py b/src/runtime/tests/test_event_policy.py index 6a451961..f4487ec2 100644 --- a/src/runtime/tests/test_event_policy.py +++ b/src/runtime/tests/test_event_policy.py @@ -102,6 +102,7 @@ async def test_first_run_submits_full_initial_egomotion_context( await event.run(rollout_state, EventQueue()) mock_driver.submit_trajectory.assert_awaited_once() + mock_driver.submit_route.assert_not_awaited() trajectory, dynamic_states = mock_driver.submit_trajectory.call_args.args assert trajectory.timestamps_us.tolist() == [0, 100_000, 200_000] assert len(dynamic_states) == 3 diff --git a/src/runtime/tests/test_route_generator.py b/src/runtime/tests/test_route_generator.py index 995d1f3d..d61e890a 100644 --- a/src/runtime/tests/test_route_generator.py +++ b/src/runtime/tests/test_route_generator.py @@ -2,9 +2,11 @@ # Copyright (c) 2025-2026 NVIDIA Corporation import math +from unittest.mock import MagicMock import numpy as np import pytest +from alpasim_runtime.config import RouteGeneratorType from alpasim_runtime.route_generator import ( RouteGenerator, RouteGeneratorMap, @@ -40,6 +42,16 @@ def test_route_generator_invalid_waypoints(): RouteGeneratorRecorded(np.zeros((1, 3))) +def test_route_generator_none_skips_waypoint_validation(): + route_generator = RouteGenerator.create( + np.zeros((1, 3)), + vector_map=MagicMock(), + route_generator_type=RouteGeneratorType.NONE, + ) + + assert route_generator is None + + def test_route_generator_invalid_route_start_offset(rig_waypoints_in_local): with pytest.raises(ValueError, match="route_start_offset_m"): RouteGeneratorRecorded(rig_waypoints_in_local, route_start_offset_m=-1.0) diff --git a/src/runtime/tests/test_telemetry_context.py b/src/runtime/tests/test_telemetry_context.py index 9ef49d91..687a37e4 100644 --- a/src/runtime/tests/test_telemetry_context.py +++ b/src/runtime/tests/test_telemetry_context.py @@ -6,26 +6,48 @@ import alpasim_runtime.telemetry.rpc_wrapper as rpc_wrapper import alpasim_runtime.telemetry.telemetry_context as telemetry_context import pytest +from alpasim_runtime.services.sensorsim_service import SENSORSIM_TRANSIENT_ERROR_DETAILS from alpasim_runtime.telemetry.telemetry_context import TelemetryContext from prometheus_client import generate_latest +import grpc +from grpc.aio import AioRpcError, Metadata -def test_record_rollout_complete_updates_simulation_summary_metrics() -> None: - ctx = TelemetryContext(worker_id=0) + +def _rpc_error(code: grpc.StatusCode, details: str) -> AioRpcError: + return AioRpcError(code, Metadata(), Metadata(), details=details) + + +def test_record_rollout_finished_updates_simulation_summary_metrics( + monkeypatch: pytest.MonkeyPatch, +) -> None: + ctx = TelemetryContext(port=9200, worker_id=0) ctx._simulation_started_at = 10.0 - now = 25.0 + monkeypatch.setattr(telemetry_context, "perf_counter", lambda: 25.0) - with pytest.MonkeyPatch.context() as monkeypatch: - monkeypatch.setattr(telemetry_context, "perf_counter", lambda: now) - ctx.record_rollout_complete() + ctx.record_rollout_finished("completed") metrics = generate_latest(ctx.registry).decode("utf-8") - assert ('alpasim_simulation_rollouts_completed_total{worker_id="0"} 1.0') in metrics + assert ('alpasim_rollouts_total{status="completed",worker_id="0"} 1.0') in metrics assert ('alpasim_simulation_elapsed_seconds{worker_id="0"} 15.0') in metrics +def test_renderer_metrics_exclude_scene_and_renderer_identity() -> None: + """Dispatch metrics must stay bounded: no per-scene or per-renderer labels.""" + ctx = TelemetryContext(port=9200, worker_id=3) + + ctx.record_renderer_rollout_started( + dispatch_kind="cached_affine", + scheduler_wait_seconds=2.5, + ) + + metrics = generate_latest(ctx.registry).decode("utf-8") + assert "scene_id" not in metrics + assert "renderer_address" not in metrics + + def test_refresh_gauges_snapshots_event_loop_and_gc_stats(monkeypatch) -> None: - ctx = TelemetryContext(worker_id=0) + ctx = TelemetryContext(port=9200, worker_id=0) monkeypatch.setattr( telemetry_context, "get_event_loop_idle_stats", @@ -65,7 +87,7 @@ def test_refresh_gauges_snapshots_event_loop_and_gc_stats(monkeypatch) -> None: async def test_profiled_rpc_call_records_latest_queue_depth_gauge( monkeypatch, ) -> None: - ctx = TelemetryContext(worker_id=3) + ctx = TelemetryContext(port=9200, worker_id=3) monkeypatch.setattr(rpc_wrapper, "try_get_context", lambda: ctx) first_done = asyncio.Event() @@ -92,8 +114,7 @@ async def test_profiled_rpc_call_records_latest_queue_depth_gauge( metrics = generate_latest(ctx.registry).decode("utf-8") latest_metric = ( - 'alpasim_rpc_queue_depth_at_start_latest{service="sensorsim",' - 'tag="default",worker_id="3"}' + 'alpasim_rpc_queue_depth_at_start_latest{service="sensorsim",worker_id="3"}' ) assert f"{latest_metric} 1.0" in metrics @@ -102,3 +123,67 @@ async def test_profiled_rpc_call_records_latest_queue_depth_gauge( metrics = generate_latest(ctx.registry).decode("utf-8") assert f"{latest_metric} 0.0" in metrics + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("code", "details"), + [ + ( + grpc.StatusCode.UNKNOWN, + "Exception calling application: A load persistent id instruction " + "was encountered,\nbut no persistent_load function was specified.", + ), + ( + grpc.StatusCode.DEADLINE_EXCEEDED, + "Stopped waiting for backend 'scene-id'", + ), + ], +) +async def test_profiled_rpc_call_retries_known_transient_error( + code: grpc.StatusCode, + details: str, +) -> None: + calls = 0 + + async def flaky() -> str: + nonlocal calls + calls += 1 + if calls == 1: + raise _rpc_error(code, details) + return "ok" + + result = await rpc_wrapper.profiled_rpc_call( + "render", + "sensorsim", + lambda: asyncio.create_task(flaky()), + retry_delays_s=(0,), + transient_error_details=SENSORSIM_TRANSIENT_ERROR_DETAILS, + ) + + assert result == "ok" + assert calls == 2 + + +@pytest.mark.asyncio +async def test_profiled_rpc_call_does_not_retry_unmatched_transient_code() -> None: + calls = 0 + + async def failing() -> str: + nonlocal calls + calls += 1 + raise _rpc_error( + grpc.StatusCode.DEADLINE_EXCEEDED, + "Deadline exceeded while calling an unrelated service", + ) + + with pytest.raises(AioRpcError): + await rpc_wrapper.profiled_rpc_call( + "batch_render_rgb", + "sensorsim", + lambda: asyncio.create_task(failing()), + retry_delays_s=(0,), + transient_error_details=SENSORSIM_TRANSIENT_ERROR_DETAILS, + ) + + assert calls == 1 diff --git a/src/runtime/tests/test_unbound_rollout.py b/src/runtime/tests/test_unbound_rollout.py index d6139deb..a78fc1d5 100644 --- a/src/runtime/tests/test_unbound_rollout.py +++ b/src/runtime/tests/test_unbound_rollout.py @@ -6,6 +6,7 @@ from types import SimpleNamespace import numpy as np +import pytest from alpasim_grpc.v0.logging_pb2 import RolloutMetadata from alpasim_runtime.config import ( PhysicsUpdateMode, @@ -13,6 +14,7 @@ SimulationConfig, VehicleConfig, ) +from alpasim_runtime.errors import InvalidSceneError from alpasim_runtime.services.sensorsim_service import SensorsimService from alpasim_runtime.unbound_rollout import UnboundRollout from alpasim_utils.geometry import Pose, Trajectory @@ -119,7 +121,9 @@ def test_create_uses_rig_start_for_context_and_closed_loop_after_force_gt( assert rollout.first_policy_timestamp_us == 150_000 assert rollout.closed_loop_start_us == 250_000 assert rollout.end_timestamp_us == 350_000 - assert rollout.get_log_metadata().start_timestamp_us == 0 + log_metadata = rollout.get_log_metadata() + assert log_metadata.start_timestamp_us == 0 + assert log_metadata.render_start_timestamp_us == 150_000 assert rollout.force_gt_period == range(150_000, 250_001) assert rollout.first_camera_frame_ranges_us["camera_front"] == range( 170_000, 200_000 @@ -239,3 +243,37 @@ def test_create_keeps_synthetic_first_exposure_inside_rollout_window( assert rollout.first_camera_frame_ranges_us["camera_left"] == range(50_000, 150_000) assert rollout.egomotion_context_start_us == 0 assert rollout.traffic_objs["actor"].trajectory.time_range_us.start == 0 + + +@pytest.mark.parametrize( + ("exception_type", "expected_type"), + [ + pytest.param(ValueError, InvalidSceneError, id="invalid-scene"), + pytest.param(OSError, OSError, id="transient-io"), + pytest.param(MemoryError, MemoryError, id="transient-memory"), + ], +) +def test_create_classifies_vector_map_failures( + tmp_path, + exception_type: type[Exception], + expected_type: type[Exception], +) -> None: + artifact = _artifact() + + class BrokenMapDataSource: + def __getattr__(self, name: str): + return getattr(artifact, name) + + @property + def map(self): + raise exception_type("map-loading failure") + + with pytest.raises(expected_type): + UnboundRollout.create( + simulation_config=_simulation_config(), + scene_id="bad-scene", + version_ids=RolloutMetadata.VersionIds(), + data_source=BrokenMapDataSource(), + rollouts_dir=str(tmp_path), + renderer_service=_sensorsim_renderer(), + ) diff --git a/src/runtime/tests/test_worker_ipc.py b/src/runtime/tests/test_worker_ipc.py index 450219e3..2891900b 100644 --- a/src/runtime/tests/test_worker_ipc.py +++ b/src/runtime/tests/test_worker_ipc.py @@ -37,8 +37,9 @@ class TestPendingRolloutJob: """Tests for PendingRolloutJob dataclass.""" def test_creation(self): - """Pending jobs contain only identity and scene.""" + """Pending jobs include identity, scene, rollout position, and retry state.""" job = PendingRolloutJob( + request_id="req-1", job_id="test-123", scene_id="test-scene", rollout_spec_index=2, @@ -51,6 +52,7 @@ def test_creation(self): def test_pickling(self): """PendingRolloutJob should be picklable.""" job = PendingRolloutJob( + request_id="req-1", job_id="test-123", scene_id="test-scene", rollout_spec_index=1, @@ -61,6 +63,7 @@ def test_pickling(self): assert unpickled.job_id == job.job_id assert unpickled.scene_id == job.scene_id assert unpickled.rollout_spec_index == job.rollout_spec_index + assert unpickled.retry_attempt == 0 class TestAssignedRolloutJob: @@ -75,6 +78,8 @@ def test_creation(self): scene_id="test-scene", rollout_spec_index=0, endpoints=ep, + dispatch_kind="fifo", + scheduler_wait_seconds=0.0, ) assert job.endpoints.driver.address == "driver:50051" @@ -87,6 +92,8 @@ def test_pickling(self): scene_id="test-scene", rollout_spec_index=0, endpoints=ep, + dispatch_kind="fifo", + scheduler_wait_seconds=0.0, ) pickled = pickle.dumps(job) @@ -220,6 +227,7 @@ def test_creation_with_version_ids(self): user_config_path="/tmp/config.yaml", log_dir="/tmp/logs", eval_config=MagicMock(), + telemetry_port=9200, version_ids=version_ids, ) assert args.version_ids is version_ids diff --git a/src/runtime/tests/test_worker_main.py b/src/runtime/tests/test_worker_main.py index b5aff717..168ac79c 100644 --- a/src/runtime/tests/test_worker_main.py +++ b/src/runtime/tests/test_worker_main.py @@ -10,10 +10,12 @@ from unittest.mock import MagicMock import pytest +from alpasim_grpc.v0 import runtime_pb2 from alpasim_grpc.v0.common_pb2 import VersionId from alpasim_grpc.v0.logging_pb2 import RolloutMetadata from alpasim_runtime.address_pool import ServiceAddress from alpasim_runtime.config import RendererConfig, RendererKind, VideoModelConfig +from alpasim_runtime.errors import InvalidSceneError from alpasim_runtime.worker.ipc import ( SHUTDOWN_SENTINEL, AssignedRolloutJob, @@ -21,6 +23,78 @@ ServiceEndpoints, ) from alpasim_runtime.worker.main import run_single_rollout, run_worker_loop +from prometheus_client import generate_latest + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("error", "expected_code"), + [ + ( + InvalidSceneError("bad-scene", "broken map"), + runtime_pb2.ROLLOUT_ERROR_CODE_INVALID_SCENE, + ), + ( + RuntimeError("rollout failed"), + runtime_pb2.ROLLOUT_ERROR_CODE_UNSPECIFIED, + ), + ], +) +async def test_run_single_rollout_reports_error_code( + monkeypatch: pytest.MonkeyPatch, + error: Exception, + expected_code: int, +) -> None: + for service in [ + "DriverService", + "PhysicsService", + "TrafficService", + "ControllerService", + "SensorsimService", + ]: + monkeypatch.setattr( + f"alpasim_runtime.worker.main.{service}", + lambda *args, **kwargs: SimpleNamespace(), + ) + + def _raise(**kwargs): + raise error + + monkeypatch.setattr( + "alpasim_runtime.worker.main.UnboundRollout.create", + _raise, + ) + + result = await run_single_rollout( + job=AssignedRolloutJob( + request_id="req-1", + job_id="job-1", + scene_id="bad-scene", + rollout_spec_index=0, + endpoints=ServiceEndpoints( + driver=ServiceAddress("localhost:10001", skip=False), + renderer=ServiceAddress("localhost:10002", skip=False), + physics=ServiceAddress("localhost:10003", skip=False), + trafficsim=ServiceAddress("localhost:10004", skip=False), + controller=ServiceAddress("localhost:10005", skip=False), + ), + dispatch_kind="fifo", + scheduler_wait_seconds=0.0, + ), + user_config=SimpleNamespace( + renderer=RendererConfig(kind=RendererKind.sensorsim), + simulation_config=MagicMock(), + ), + data_source=MagicMock(), + camera_catalog=MagicMock(), + version_ids=MagicMock(), + rollouts_dir="/tmp", + eval_config=MagicMock(), + eval_executor=MagicMock(), + ) + + assert result.success is False + assert result.error_code == expected_code @pytest.mark.asyncio @@ -78,6 +152,8 @@ async def _fake_run_single_rollout( scene_id="scene-1", rollout_spec_index=0, endpoints=endpoints, + dispatch_kind="fifo", + scheduler_wait_seconds=0.5, ) job_queue: Queue = Queue() @@ -116,6 +192,68 @@ async def _fake_run_single_rollout( assert seen_version_ids is parent_version_ids +@pytest.mark.asyncio +async def test_run_worker_loop_clears_active_metric_when_rollout_raises( + monkeypatch: pytest.MonkeyPatch, +) -> None: + async def _raise(**kwargs) -> JobResult: + del kwargs + raise RuntimeError("rollout failed before producing a result") + + monkeypatch.setattr("alpasim_runtime.worker.main.run_single_rollout", _raise) + + from alpasim_runtime.telemetry.telemetry_context import TelemetryContext + + telemetry = TelemetryContext(port=9200, worker_id=4) + monkeypatch.setattr( + "alpasim_runtime.worker.main.try_get_context", lambda: telemetry + ) + job_queue: Queue = Queue() + job_queue.put( + AssignedRolloutJob( + request_id="req-1", + job_id="job-1", + scene_id="scene-1", + rollout_spec_index=0, + endpoints=ServiceEndpoints( + driver=ServiceAddress("driver", skip=False), + renderer=ServiceAddress("renderer", skip=False), + physics=ServiceAddress("physics", skip=False), + trafficsim=ServiceAddress("trafficsim", skip=False), + controller=ServiceAddress("controller", skip=False), + ), + dispatch_kind="cold_replica", + scheduler_wait_seconds=1.25, + ) + ) + + with pytest.raises(ExceptionGroup): + await run_worker_loop( + worker_id=4, + job_queue=job_queue, + result_queue=Queue(), + num_consumers=1, + user_config=MagicMock(), + scene_loader=MagicMock(), + camera_catalog=MagicMock(), + version_ids=MagicMock(), + rollouts_dir="/tmp", + eval_config=MagicMock(), + parent_pid=None, + ) + + metrics = generate_latest(telemetry.registry).decode("utf-8") + assert 'alpasim_renderer_active_rollouts{worker_id="4"} 0.0' in metrics + assert ( + 'alpasim_renderer_rollouts_started_total{kind="cold_replica",' + 'worker_id="4"} 1.0' + ) in metrics + assert ( + 'alpasim_renderer_scheduler_wait_seconds_sum{kind="cold_replica",' + 'worker_id="4"} 1.25' + ) in metrics + + @pytest.mark.asyncio async def test_run_single_rollout_uses_builtin_video_model_renderer( monkeypatch: pytest.MonkeyPatch, @@ -195,6 +333,8 @@ def _fake_create_event_rollout(**kwargs): trafficsim=ServiceAddress("localhost:10004", skip=False), controller=ServiceAddress("localhost:10005", skip=False), ), + dispatch_kind="fifo", + scheduler_wait_seconds=0.5, ) video_model_config = VideoModelConfig(fps=24) user_config = SimpleNamespace( diff --git a/src/runtime/tests/test_worker_pool.py b/src/runtime/tests/test_worker_pool.py index b56755d7..fc60d460 100644 --- a/src/runtime/tests/test_worker_pool.py +++ b/src/runtime/tests/test_worker_pool.py @@ -64,6 +64,9 @@ def _make_config_mock(nr_workers: int = 1) -> MagicMock: config = MagicMock() config.user.nr_workers = nr_workers config.user.smooth_trajectories = True + config.user.scene_affine_dispatch.enabled = False + config.user.scene_affine_dispatch.max_renderers_per_scene = 2 + config.user.scene_affine_dispatch.max_scenes_per_renderer = None config.user.renderer = RendererConfig(kind=RendererKind.sensorsim) config.user.endpoints.driver.skip = False config.user.endpoints.driver.n_concurrent_rollouts = 2 @@ -320,6 +323,8 @@ def _make_assigned_job(request_id: str, job_id: str) -> AssignedRolloutJob: scene_id="scene-A", rollout_spec_index=0, endpoints=_make_endpoints(), + dispatch_kind="fifo", + scheduler_wait_seconds=0.0, ) diff --git a/src/tools/run-on-slurm/resume_slurm_job.sh b/src/tools/run-on-slurm/resume_slurm_job.sh index e48bbd12..9c37a064 100755 --- a/src/tools/run-on-slurm/resume_slurm_job.sh +++ b/src/tools/run-on-slurm/resume_slurm_job.sh @@ -63,20 +63,7 @@ if [ -n "$SLURM_ARRAY_TASK_ID" ]; then exit 1 fi - # Find the specific log directory for *this* task ID within the original parent directory. - # It looks for a directory whose name matches the pattern __. - TARGET_LOG_DIR_BASENAME=$(ls -1 "$ORIGINAL_DIR" | grep -E "^[0-9]+_${SLURM_ARRAY_TASK_ID}_.*$") - - # Check if exactly one directory was found - MATCH_COUNT=$(echo "$TARGET_LOG_DIR_BASENAME" | wc -l) - - if [ "$MATCH_COUNT" -ne 1 ]; then - echo "ERROR: Expected exactly one log directory for task ${SLURM_ARRAY_TASK_ID} in ${ORIGINAL_DIR}, but found ${MATCH_COUNT}." - ls -1 "$ORIGINAL_DIR" | grep -E "^[0-9]+_${SLURM_ARRAY_TASK_ID}_.*$" # Show matches/non-matches - exit 1 - fi - - TARGET_LOG_DIR="${ORIGINAL_DIR}${TARGET_LOG_DIR_BASENAME}" + TARGET_LOG_DIR="${ORIGINAL_DIR}task-${SLURM_ARRAY_TASK_ID}" LOG_ID="${SLURM_JOB_ID}_${SLURM_ARRAY_TASK_ID}" diff --git a/src/tools/run-on-slurm/submit.sh b/src/tools/run-on-slurm/submit.sh index cdd88f49..2c65bef1 100755 --- a/src/tools/run-on-slurm/submit.sh +++ b/src/tools/run-on-slurm/submit.sh @@ -21,6 +21,8 @@ #SBATCH --exclusive #SBATCH --job-name alpasim #SBATCH --output=./runs/slurm_output/%j.log +#SBATCH --requeue +#SBATCH --signal=B:USR1@300 # Detect if running on slurm node if [ -z "$SLURM_JOB_ID" ]; then @@ -70,6 +72,13 @@ SCRIPT_PATH=$(scontrol show job "${UNIQUE_JOB_ID}" | awk -F= '/Command=/{print $ SCRIPT_DIR=$(readlink -f "$(dirname $SCRIPT_PATH)") REPO_ROOT_DIR=$(readlink -f "${SCRIPT_DIR}/../../..") +RESTART_COUNT=${SLURM_RESTART_COUNT:-0} +max_requeues=${ALPASIM_MAX_REQUEUES-20} +if [[ ! ${max_requeues} =~ ^[0-9]+$ ]]; then + echo "ALPASIM_MAX_REQUEUES must be a non-negative integer, got: ${max_requeues}" >&2 + exit 1 +fi +max_requeues=$((10#${max_requeues})) # If LOGDIR is not specified, we generate a logdir in the folder where this script lives. If # a relative LOGDIR is specified, we assume the user wants to set the LOGDIR relative to where @@ -77,25 +86,29 @@ REPO_ROOT_DIR=$(readlink -f "${SCRIPT_DIR}/../../..") if [[ -z "$LOGDIR" ]]; then if [ -z "${SLURM_ARRAY_JOB_ID}" ]; then # Non array job - LOGDIR=$SCRIPT_DIR/runs/${SLURM_JOB_ID}_${SLURM_JOB_NAME}_$(date +%Y_%m_%d__%H_%M_%S) + LOGDIR=$SCRIPT_DIR/runs/${SLURM_JOB_ID}_${SLURM_JOB_NAME} ARRAY_JOB_DIR=$LOGDIR else - # Array job, we use a hierarchical logdir to group all array jobs + # Array tasks keep a stable directory across Slurm requeues. ARRAY_JOB_DIR=$SCRIPT_DIR/runs/${SLURM_ARRAY_JOB_ID}_${SLURM_JOB_NAME} - LOGDIR=$ARRAY_JOB_DIR/${SLURM_JOB_ID}_${SLURM_ARRAY_TASK_ID}_$(date +%Y_%m_%d__%H_%M_%S) + LOGDIR=$ARRAY_JOB_DIR/task-${SLURM_ARRAY_TASK_ID} fi else if [[ "$LOGDIR" != /* ]]; then LOGDIR=$(readlink -f "$SLURM_SUBMIT_DIR/$LOGDIR") fi + ARRAY_JOB_DIR=$LOGDIR + if [[ -n "${SLURM_ARRAY_JOB_ID}" ]]; then + LOGDIR=$ARRAY_JOB_DIR/task-${SLURM_ARRAY_TASK_ID} + fi fi # Create txt-logs directory if it doesn't exist mkdir -p ${LOGDIR}/txt-logs # Want the Slurm logs in LOGDIR, but don't know LOGDIR until after job started. -# Copy any early output to our new log file. -cat ./runs/slurm_output/${SLURM_JOB_ID}.log > ${LOGDIR}/txt-logs/slurm.log 2>/dev/null +# Copy any early output to our cumulative log file. +cat "${SCRIPT_DIR}/runs/slurm_output/${SLURM_JOB_ID}.log" > "${LOGDIR}/txt-logs/slurm.log" 2>/dev/null # Redirect all future output to both terminal and the log file exec > >(tee -a "${LOGDIR}/txt-logs/slurm.log") 2>&1 @@ -109,12 +122,12 @@ if [[ -z "${ORIG_ACCOUNT}" ]]; then fi if [ ! -f "${ARRAY_JOB_DIR}/resume.sh" ] && [[ -z "${SLURM_ARRAY_TASK_ID}" || "${SLURM_ARRAY_TASK_ID}" == "${SLURM_ARRAY_TASK_MIN}" ]]; then - cat > ${ARRAY_JOB_DIR}/resume.sh < "${ARRAY_JOB_DIR}/resume.sh" <= max_requeues )); then + echo "Reached automatic requeue limit (${max_requeues})" + [[ -n "${WIZARD_PID}" ]] && kill -TERM "${WIZARD_PID}" 2>/dev/null || true + exit 124 + fi + + echo "Requeueing ${JOB_REFERENCE} with ${RESTART_COUNT} previous restart(s)" + if ! scontrol requeue "${JOB_REFERENCE}"; then + echo "Slurm rejected automatic requeue of ${JOB_REFERENCE}" + [[ -n "${WIZARD_PID}" ]] && kill -TERM "${WIZARD_PID}" 2>/dev/null || true + exit 124 + fi + exit 0 +} + +trap request_requeue USR1 + +RESUME_ARGS=() +if (( RESTART_COUNT > 0 )); then + RESUME_ARGS+=(runtime.enable_autoresume=true) +fi + uv run --project ${REPO_ROOT_DIR}/src/wizard --python 3.12 \ alpasim_wizard \ wizard.log_dir=$LOGDIR \ @@ -134,4 +177,11 @@ uv run --project ${REPO_ROOT_DIR}/src/wizard --python 3.12 \ wizard.latest_symlink=true \ wizard.submitter="$SUBMITTER" \ wizard.description="$DESCRIPTION" \ - "${HYDRA_ARGS[@]}" + "${HYDRA_ARGS[@]}" \ + "${RESUME_ARGS[@]}" & +WIZARD_PID=$! +wait "${WIZARD_PID}" +WIZARD_STATUS=$? +WIZARD_PID= +trap - USR1 +exit "${WIZARD_STATUS}" diff --git a/src/trafficsim/alpasim_trafficsim/catk/batching.py b/src/trafficsim/alpasim_trafficsim/catk/batching.py new file mode 100644 index 00000000..ecc0d05c --- /dev/null +++ b/src/trafficsim/alpasim_trafficsim/catk/batching.py @@ -0,0 +1,131 @@ +# SPDX-License-Identifier: Apache-2.0 +# Copyright (c) 2026 NVIDIA Corporation + +"""Collation helpers for variable-sized CATK inference batches.""" + +from typing import Any + +import torch + + +def collate_model_inputs( + input_data_items: list[dict[str, Any]], +) -> tuple[dict[str, Any], list[int]]: + """Collate variable-sized CATK graph inputs and return output split sizes.""" + if not input_data_items: + raise ValueError("at least one CATK model input is required") + + # Accumulate each variable-sized field before concatenating the batch. + device = input_data_items[0]["agent"]["id"].device + agent_parts: dict[str, list[torch.Tensor]] = {} + freeze_agent_parts: dict[str, list[torch.Tensor]] = {} + map_triplets: list[torch.Tensor] = [] + map_thetas: list[torch.Tensor] = [] + polyline_parts: dict[str, list[torch.Tensor]] = {} + freeze_masks: list[torch.Tensor] = [] + num_obstacles: list[int] = [] + non_ego_agent_counts: list[int] = [] + rb_polylines: list[torch.Tensor] = [] + rb_polylines_batch: list[int] = [] + + for graph_idx, input_data in enumerate(input_data_items): + # Collect active agents and assign them to their source graph. + agent_data = input_data["agent"] + agent_count = int(agent_data["id"].shape[0]) + non_ego_agent_counts.append(int((~agent_data["role"][:, 0]).sum().item())) + num_obstacles.append(agent_count) + for key, value in agent_data.items(): + if key == "batch": + continue + agent_parts.setdefault(key, []).append(value) + agent_parts.setdefault("batch", []).append( + torch.full( + (agent_count,), + graph_idx, + dtype=torch.long, + device=agent_data["id"].device, + ) + ) + + # Collect frozen agents and their masks separately from active agents. + freeze_data = input_data["freeze_agent_data"] + freeze_agents = freeze_data["agent"] + freeze_agent_count = int(freeze_agents["id"].shape[0]) + for key, value in freeze_agents.items(): + if key == "batch": + continue + freeze_agent_parts.setdefault(key, []).append(value) + freeze_agent_parts.setdefault("batch", []).append( + torch.full( + (freeze_agent_count,), + graph_idx, + dtype=torch.long, + device=freeze_agents["id"].device, + ) + ) + freeze_masks.append(input_data["freeze_agent_mask"]) + + # Collect map polylines and assign them to their source graph. + map_data = input_data["map"] + map_triplets.append(map_data["triplets"]) + map_thetas.append(map_data["triplet_thetas"]) + polyline_extras = map_data["polyline_extras"] + polyline_count = int(map_data["triplets"].shape[0]) + for key, value in polyline_extras.items(): + if key == "batch": + continue + polyline_parts.setdefault(key, []).append(value) + polyline_parts.setdefault("batch", []).append( + torch.full( + (polyline_count,), + graph_idx, + dtype=torch.long, + device=map_data["triplets"].device, + ) + ) + + # Preserve variable-length road-boundary polylines as a flat list. + rb_data = map_data.get("rb_data") + if rb_data is not None: + for polyline in rb_data["rb_polylines"]: + rb_polylines.append(polyline) + rb_polylines_batch.append(graph_idx) + + # Concatenate tensor fields into the structure expected by CATK. + collated = { + "agent": {key: torch.cat(values, dim=0) for key, values in agent_parts.items()}, + "num_obstacles": torch.tensor( + num_obstacles, + dtype=torch.long, + device=device, + ), + "num_graphs": len(input_data_items), + "freeze_agent_data": { + "agent": { + key: torch.cat(values, dim=0) + for key, values in freeze_agent_parts.items() + }, + "num_obstacles": torch.tensor( + [ + int(item["freeze_agent_data"]["agent"]["id"].shape[0]) + for item in input_data_items + ], + dtype=torch.long, + device=device, + ), + "num_graphs": len(input_data_items), + }, + "freeze_agent_mask": torch.cat(freeze_masks, dim=0), + "map": { + "triplets": torch.cat(map_triplets, dim=0), + "triplet_thetas": torch.cat(map_thetas, dim=0), + "polyline_extras": { + key: torch.cat(values, dim=0) for key, values in polyline_parts.items() + }, + "rb_data": { + "rb_polylines": rb_polylines, + "rb_polylines_batch": rb_polylines_batch, + }, + }, + } + return collated, non_ego_agent_counts diff --git a/src/trafficsim/alpasim_trafficsim/catk/model_adapter.py b/src/trafficsim/alpasim_trafficsim/catk/model_adapter.py index af11668a..12142a50 100644 --- a/src/trafficsim/alpasim_trafficsim/catk/model_adapter.py +++ b/src/trafficsim/alpasim_trafficsim/catk/model_adapter.py @@ -1,6 +1,7 @@ # SPDX-License-Identifier: Apache-2.0 # Copyright (c) 2026 NVIDIA Corporation +import math import os from typing import Any, Dict @@ -28,6 +29,35 @@ def _token_path(token_pkl_dir: str, token_file: str) -> str: return os.path.abspath(os.path.join(token_pkl_dir, os.path.basename(token_file))) +def _validated_num_obstacles( + input_data: Dict[str, Any], *, device: str +) -> torch.Tensor: + num_obstacles = input_data["num_obstacles"] + num_graphs = int(input_data["num_graphs"]) + agent_count = int(input_data["agent"]["id"].shape[0]) + expected_device = torch.device(device) + device_matches = isinstance(num_obstacles, torch.Tensor) and ( + num_obstacles.device.type == expected_device.type + and ( + expected_device.index is None + or num_obstacles.device.index == expected_device.index + ) + ) + if ( + not isinstance(num_obstacles, torch.Tensor) + or num_obstacles.dtype != torch.long + or not device_matches + or tuple(num_obstacles.shape) != (num_graphs,) + or int(num_obstacles.sum().item()) != agent_count + ): + raise ValueError( + "num_obstacles must be a torch.long tensor on " + f"{expected_device} with shape ({num_graphs},) and total " + f"agent count {agent_count}" + ) + return num_obstacles + + class _BatchDict(dict): def __getattr__(self, name: str) -> Any: try: @@ -43,6 +73,7 @@ def __init__( ckpt_path: str, token_pkl_dir: str, disable_sub_plyline_type: bool, + prediction_steps: int, device: str, use_downsampled_lines: bool = False, ): @@ -51,7 +82,6 @@ def __init__( self.device = device self.model_input_step_num = self.model_config["decoder"]["num_historical_steps"] - self.model_predict_step_num = 5 self.delta_t = self.model_config["token_processor"]["time_step"] map_token_filename = self.model_config["token_processor"]["map_token_file"] @@ -66,6 +96,10 @@ def __init__( self.model = SMART(self.model_config).to(self.device) self.model.eval() + token_stride = self.model.encoder.agent_encoder.shift + self._model_predict_step_num = ( + math.ceil(prediction_steps / token_stride) * token_stride + ) state_dict = torch.load( self.ckpt_path, map_location=self.device, weights_only=False @@ -84,7 +118,9 @@ def create_model_input( ego_xy = env_data["ego"]["xyz"][env_data["env"]["curr_t"]] if filter_map_by_ego and filter_distance_th > 0: filter_map( - env_data=env_data, center_xyz=ego_xy, distance_th=filter_distance_th + env_data=env_data, + center_xyz=ego_xy, + distance_th=filter_distance_th, ) input_data = { @@ -112,15 +148,21 @@ def create_model_input( dt=self.delta_t, device=self.device, ) + input_data["num_obstacles"] = torch.tensor( + (int(input_data["agent"]["id"].shape[0]),), + dtype=torch.long, + device=self.device, + ) assert curr_t >= 1 logger.info( - f"extract frozen agent data in t: [{curr_t}, {curr_t + 1 + self.model_predict_step_num}]" + "extract frozen agent data in t: " + f"[{curr_t}, {curr_t + 1 + self._model_predict_step_num}]" ) freeze_agent_data, freeze_agent_mask = build_freeze_agent_data( env_data, curr_t=curr_t, - target_steps=1 + self.model_predict_step_num, + target_steps=1 + self._model_predict_step_num, dt=self.delta_t, device=self.device, ) @@ -145,8 +187,12 @@ def create_model_input( logger.info(f"[proxy] triplets #:{triplets.shape[0]}") return {"input_data": input_data} - def inference(self, input_data: Dict[str, Any]): - self.model.encoder.agent_encoder.num_future_steps = self.model_predict_step_num + def inference( + self, + input_data: Dict[str, Any], + ): + num_obstacles = _validated_num_obstacles(input_data, device=self.device) + self.model.encoder.agent_encoder.num_future_steps = self._model_predict_step_num sampling_scheme = self.model.validation_rollout_sampling step_current_10hz = self.model.encoder.agent_encoder.num_historical_steps # 10 @@ -157,11 +203,7 @@ def inference(self, input_data: Dict[str, Any]): { "position": None, "agent": input_data["agent"], - "num_obstacles": torch.tensor( - (input_data["agent"]["id"].shape[0],), - device=self.device, - dtype=torch.long, - ).reshape(1), + "num_obstacles": num_obstacles, "traj_pos": None, "traj_theta": None, "map_save": { @@ -199,7 +241,10 @@ def inference(self, input_data: Dict[str, Any]): ) future_xyz = torch.cat( - [output["pred_traj_10hz"], output["pred_z_10hz"].unsqueeze(-1)], + [ + output["pred_traj_10hz"], + output["pred_z_10hz"].unsqueeze(-1), + ], dim=-1, ) future_heading = output["pred_head_10hz"] @@ -210,11 +255,16 @@ def inference(self, input_data: Dict[str, Any]): pos_all = torch.cat([last_hist_pos, future_xyz], dim=1) future_velocity = (pos_all[:, 1:] - pos_all[:, :-1]) / dt - pnum = self.model_predict_step_num actions = { - "agent_future_xyz": future_xyz[~is_ego, :pnum], - "agent_future_heading": future_heading[~is_ego, :pnum], - "agent_future_valid_mask": future_valid[~is_ego, :pnum], - "agent_future_velocity": future_velocity[~is_ego, :pnum, :2], + "agent_future_xyz": future_xyz[~is_ego, : self._model_predict_step_num], + "agent_future_heading": future_heading[ + ~is_ego, : self._model_predict_step_num + ], + "agent_future_valid_mask": future_valid[ + ~is_ego, : self._model_predict_step_num + ], + "agent_future_velocity": future_velocity[ + ~is_ego, : self._model_predict_step_num, :2 + ], } return actions diff --git a/src/trafficsim/alpasim_trafficsim/config/server.yaml b/src/trafficsim/alpasim_trafficsim/config/server.yaml index 249b7ee7..1969a8a3 100644 --- a/src/trafficsim/alpasim_trafficsim/config/server.yaml +++ b/src/trafficsim/alpasim_trafficsim/config/server.yaml @@ -5,7 +5,7 @@ hydra: server: host: 0.0.0.0 port: 6200 - max_workers: 1 + max_workers: 8 log_file: null @@ -18,7 +18,7 @@ catk: usdz_folder: ??? # set via CLI --usdz-folder or wizard volume mount # Service timing controls. num_history_steps: 16 - minimum_future_steps: 5 + prediction_steps: 5 time_step: 0.1 # TarCache-style map preprocessing. diff --git a/src/trafficsim/alpasim_trafficsim/grpc/catk_predictor.py b/src/trafficsim/alpasim_trafficsim/grpc/catk_predictor.py index 75a37905..64b37cd9 100644 --- a/src/trafficsim/alpasim_trafficsim/grpc/catk_predictor.py +++ b/src/trafficsim/alpasim_trafficsim/grpc/catk_predictor.py @@ -2,10 +2,15 @@ # Copyright (c) 2026 NVIDIA Corporation import copy -import math +import queue +import threading +from concurrent.futures import Future +from dataclasses import dataclass from typing import Any import torch +from alpasim_trafficsim.catk.batching import collate_model_inputs +from alpasim_trafficsim.catk.model_adapter import CATK from alpasim_trafficsim.grpc.config import CatkConfig from alpasim_trafficsim.grpc.pipeline.env_builder import ( backfill_static_agent_history, @@ -18,6 +23,10 @@ from alpasim_trafficsim.grpc.service_structures import SessionState, SimEnvData +class CatkPredictionUnavailableError(RuntimeError): + """Raised when CATK cannot produce predictions for the current request.""" + + def _actions_to_env_tensors( actions: dict[str, Any], env_data: SimEnvData, @@ -102,47 +111,6 @@ def _clear_invalid_step_values( step_heading.masked_fill_(invalid_mask, 0.0) -def _fill_static_agent( - processed_xyz: torch.Tensor, - processed_heading: torch.Tensor, - processed_valid: torch.Tensor, - *, - agent_idx: int, - prev_xyz: torch.Tensor, - prev_heading: torch.Tensor, - prev_valid: torch.Tensor, -) -> None: - processed_xyz[agent_idx, :, :] = prev_xyz - processed_heading[agent_idx, :] = prev_heading - processed_valid[agent_idx, :] = prev_valid - - -def _carry_invalid_predictions_forward( - processed_xyz: torch.Tensor, - processed_heading: torch.Tensor, - processed_valid: torch.Tensor, - *, - agent_idx: int, - prev_xyz: torch.Tensor, - prev_heading: torch.Tensor, - prev_valid: torch.Tensor, -) -> None: - last_xyz = prev_xyz - last_heading = prev_heading - last_valid = bool(prev_valid.item()) - for step_offset in range(processed_xyz.shape[1]): - if bool(processed_valid[agent_idx, step_offset].item()): - last_xyz = processed_xyz[agent_idx, step_offset, :] - last_heading = processed_heading[agent_idx, step_offset] - last_valid = True - continue - if not last_valid: - continue - processed_xyz[agent_idx, step_offset, :] = last_xyz - processed_heading[agent_idx, step_offset] = last_heading - processed_valid[agent_idx, step_offset] = True - - def _clone_env_data_for_model(env_data: SimEnvData) -> SimEnvData: model_env_data = dict(env_data) model_env_data["map"] = copy.deepcopy(env_data.get("map", {})) @@ -186,6 +154,65 @@ def _write_predictions_to_env( _clear_invalid_step_values(step_xyz, step_heading, step_valid) +@dataclass +class _PreparedInference: + input_data: dict[str, Any] + future: Future[dict[str, Any]] + + +class _InferenceBatcher: + """Work-conserving CATK inference worker with variable batch sizes.""" + + def __init__(self, model: Any) -> None: + self._model = model + self._queue: queue.Queue[_PreparedInference] = queue.Queue() + self._thread = threading.Thread( + target=self._run, + name="catk-inference-batcher", + daemon=True, + ) + self._thread.start() + + def submit(self, request: _PreparedInference) -> dict[str, Any]: + self._queue.put(request) + return request.future.result() + + def _collect_available_batch(self) -> list[_PreparedInference]: + batch = [self._queue.get()] + + while True: + try: + batch.append(self._queue.get_nowait()) + except queue.Empty: + return batch + + def _run(self) -> None: + while True: + batch = self._collect_available_batch() + try: + self._execute(batch) + except Exception as exc: # noqa: BLE001 - deliver to every waiter + for request in batch: + if not request.future.done(): + request.future.set_exception(exc) + + def _execute(self, batch: list[_PreparedInference]) -> None: + + collated_input, split_sizes = collate_model_inputs( + [request.input_data for request in batch] + ) + actions = self._model.inference(collated_input) + + offset = 0 + for request, split_size in zip(batch, split_sizes, strict=True): + request_actions = { + key: value[offset : offset + split_size] + for key, value in actions.items() + } + offset += split_size + request.future.set_result(request_actions) + + class CATKTrafficPredictor: def __init__(self, catk_cfg: CatkConfig) -> None: self.cfg = catk_cfg @@ -193,10 +220,9 @@ def __init__(self, catk_cfg: CatkConfig) -> None: self.history_window_steps = self.cfg.loader.num_history_steps self.min_valid_history_steps = self.cfg.min_valid_history_steps self.model = self._build_model() - self._token_stride: int = self.model.model.encoder.agent_encoder.shift + self._batcher = _InferenceBatcher(self.model) def _build_model(self) -> Any: - from alpasim_trafficsim.catk.model_adapter import CATK model_cfg = self.cfg.model return CATK( @@ -204,6 +230,7 @@ def _build_model(self) -> Any: ckpt_path=model_cfg.ckpt_path, token_pkl_dir=model_cfg.token_pkl_dir, disable_sub_plyline_type=model_cfg.disable_sub_plyline_type, + prediction_steps=self.cfg.loader.prediction_steps, use_downsampled_lines=model_cfg.use_downsampled_lines, device=self.cfg.device, ) @@ -211,14 +238,7 @@ def _build_model(self) -> Any: def run_inference( self, env_data: SimEnvData, - *, - predict_steps: int, - ) -> dict[str, Any] | None: - if self.model is None or predict_steps <= 0: - return None - # CATK emits full token strides; the caller crops to requested steps. - model_steps = math.ceil(predict_steps / self._token_stride) * self._token_stride - self.model.model_predict_step_num = model_steps + ) -> dict[str, Any]: model_env_data = _clone_env_data_for_model(env_data) backfill_static_agent_history( model_env_data, @@ -232,8 +252,18 @@ def run_inference( filter_distance_th=self.cfg.filter_distance_th, ) if model_input_result is None: - return None - return self.model.inference(model_input_result["input_data"]) + raise CatkPredictionUnavailableError( + "No usable map geometry was found within " + f"{self.cfg.filter_distance_th:g} m of the current ego position; " + "CATK cannot produce predictions" + ) + future: Future[dict[str, Any]] = Future() + return self._batcher.submit( + _PreparedInference( + input_data=model_input_result["input_data"], + future=future, + ) + ) def apply_predictions_to_env( self, @@ -313,41 +343,54 @@ def _postprocess_predictions( ) ) - for agent_idx in range(num_agents): - if bool(frozen_static_mask[agent_idx].item()): - _fill_static_agent( - processed_xyz, - processed_heading, - processed_valid, - agent_idx=agent_idx, - prev_xyz=prev_xyz[agent_idx], - prev_heading=prev_heading[agent_idx], - prev_valid=prev_valid[agent_idx], - ) - continue - - if bool(sparse_history_mask[agent_idx].item()) and bool( - prev_valid[agent_idx].item() - ): - _fill_static_agent( - processed_xyz, - processed_heading, - processed_valid, - agent_idx=agent_idx, - prev_xyz=prev_xyz[agent_idx], - prev_heading=prev_heading[agent_idx], - prev_valid=prev_valid[agent_idx], - ) - continue - - _carry_invalid_predictions_forward( - processed_xyz, - processed_heading, - processed_valid, - agent_idx=agent_idx, - prev_xyz=prev_xyz[agent_idx], - prev_heading=prev_heading[agent_idx], - prev_valid=prev_valid[agent_idx], - ) + force_static_mask = frozen_static_mask | (sparse_history_mask & prev_valid) + + # Treat the current observed pose as time zero, then compute the most + # recent valid source index for every agent and future step at once. + # An index of -1 means that neither the previous pose nor any prediction + # up to that point was valid; those invalid prediction values remain + # untouched + source_xyz = torch.cat((prev_xyz.unsqueeze(1), processed_xyz), dim=1) + source_heading = torch.cat( + (prev_heading.unsqueeze(1), processed_heading), dim=1 + ) + source_valid = torch.cat((prev_valid.unsqueeze(1), processed_valid), dim=1) + source_step_indices = torch.arange( + num_steps + 1, + dtype=torch.long, + device=processed_valid.device, + ).unsqueeze(0) + valid_source_indices = torch.where( + source_valid, + source_step_indices, + torch.full_like(source_step_indices, -1), + ) + last_valid_indices = valid_source_indices.cummax(dim=1).values[:, 1:] + has_valid_source = last_valid_indices >= 0 + safe_indices = last_valid_indices.clamp_min(0) + + carried_xyz = source_xyz.gather( + 1, safe_indices.unsqueeze(-1).expand(-1, -1, source_xyz.shape[-1]) + ) + carried_heading = source_heading.gather(1, safe_indices) + dynamic_mask = ~force_static_mask.unsqueeze(1) + carry_mask = dynamic_mask & has_valid_source + processed_xyz = torch.where( + carry_mask.unsqueeze(-1), carried_xyz, processed_xyz + ) + processed_heading = torch.where(carry_mask, carried_heading, processed_heading) + processed_valid = torch.where(dynamic_mask, has_valid_source, processed_valid) + + # Frozen and sparse-history agents repeat their current observed state + # across the complete prediction horizon. + processed_xyz = torch.where( + force_static_mask[:, None, None], prev_xyz[:, None, :], processed_xyz + ) + processed_heading = torch.where( + force_static_mask[:, None], prev_heading[:, None], processed_heading + ) + processed_valid = torch.where( + force_static_mask[:, None], prev_valid[:, None], processed_valid + ) return processed_xyz, processed_heading, processed_valid diff --git a/src/trafficsim/alpasim_trafficsim/grpc/config.py b/src/trafficsim/alpasim_trafficsim/grpc/config.py index 9caeb2be..bfe2a1b0 100644 --- a/src/trafficsim/alpasim_trafficsim/grpc/config.py +++ b/src/trafficsim/alpasim_trafficsim/grpc/config.py @@ -26,7 +26,7 @@ def _default_map_element_names() -> list[str]: class ServerConfig: host: str = "0.0.0.0" port: int = 6200 - max_workers: int = 1 + max_workers: int = 8 log_file: str | None = None @@ -34,7 +34,7 @@ class ServerConfig: class CatkLoaderConfig: usdz_folder: str = MISSING num_history_steps: int = 16 - minimum_future_steps: int = 5 + prediction_steps: int = 5 time_step: float = 0.1 map_element_names: list[str] | None = field( diff --git a/src/trafficsim/alpasim_trafficsim/grpc/servicer.py b/src/trafficsim/alpasim_trafficsim/grpc/servicer.py index d3f03313..1aafea45 100644 --- a/src/trafficsim/alpasim_trafficsim/grpc/servicer.py +++ b/src/trafficsim/alpasim_trafficsim/grpc/servicer.py @@ -14,7 +14,10 @@ preprocess_runtime_map, ) from alpasim_trafficsim.grpc import API_VERSION_MESSAGE, VersionId -from alpasim_trafficsim.grpc.catk_predictor import CATKTrafficPredictor +from alpasim_trafficsim.grpc.catk_predictor import ( + CatkPredictionUnavailableError, + CATKTrafficPredictor, +) from alpasim_trafficsim.grpc.config import CatkConfig, CatkLoaderConfig from alpasim_trafficsim.grpc.pipeline.env_builder import ( InsufficientEgoTrajectoryError, @@ -72,8 +75,8 @@ def preprocess_session_map( ) -class CatkPredictionUnavailableError(RuntimeError): - """Raised when CATK cannot produce predictions for the current request.""" +class PredictionHorizonExceededError(ValueError): + """Raised when a request advances beyond CATK's fixed prediction horizon.""" class TrafficServiceServicer(traffic_pb2_grpc.TrafficServiceServicer): @@ -86,13 +89,16 @@ def __init__( service_version: str = "simple-traffic-service", ) -> None: self._server = server - self._lock = threading.Lock() + self._registry_lock = threading.Lock() self._sessions: dict[str, SessionState] = {} + self._session_locks: dict[str, threading.Lock] = {} self._service_version = service_version self._time_step_s = catk_config.loader.time_step - self._dt_us = int(round(self._time_step_s * 1e6)) + self._dt_us = round(self._time_step_s * 1e6) self._loader_cfg = catk_config.loader - self._minimum_future_steps = self._loader_cfg.minimum_future_steps + self._prediction_steps = self._loader_cfg.prediction_steps + if self._prediction_steps < 1: + raise ValueError("catk.loader.prediction_steps must be at least 1") self._minimum_history_length = self._loader_cfg.num_history_steps self._scene_loader = SceneLoader( ArtifactSceneProvider.from_path( @@ -181,8 +187,15 @@ def start_session( bool(v) for v in env_data["env"].get("agent_is_static", []) ) - with self._lock: + with self._registry_lock: + if request.session_uuid in self._sessions: + context.set_code(grpc.StatusCode.ALREADY_EXISTS) + context.set_details( + f"Session already exists for session_uuid: {request.session_uuid}" + ) + return common_pb2.SessionRequestStatus() self._sessions[request.session_uuid] = session_state + self._session_locks[request.session_uuid] = threading.Lock() logger.info( "start_session: session={} scene_id={} initial_ts_us={} first_ego_pose_ts_us={} " @@ -208,8 +221,9 @@ def close_session( request: traffic_pb2.TrafficSessionCloseRequest, context: grpc.ServicerContext, ) -> common_pb2.Empty: - with self._lock: + with self._registry_lock: removed = self._sessions.pop(request.session_uuid, None) + self._session_locks.pop(request.session_uuid, None) if removed is None: context.set_code(grpc.StatusCode.NOT_FOUND) @@ -222,27 +236,26 @@ def close_session( def _apply_model_predictions( self, *, - session_uuid: str, - query_ts_us: int, session_state: SessionState, future_step_indices: list[int], ) -> list[int]: if not future_step_indices: return [] + if len(future_step_indices) > self._prediction_steps: + raise PredictionHorizonExceededError( + "traffic request requires " + f"{len(future_step_indices)} future steps, but CATK is configured " + f"for {self._prediction_steps} prediction steps" + ) env_data = session_state.env_data current_step_idx = int(env_data["env"].get("curr_t", 0)) - predict_steps = max(len(future_step_indices), self._minimum_future_steps) - actions = self._catk_predictor.run_inference( - env_data, - predict_steps=predict_steps, - ) - if actions is None: - raise CatkPredictionUnavailableError( - "CATK did not produce predictions for the current request" - ) + actions = self._catk_predictor.run_inference(env_data) - forecast_steps = _prediction_step_count(actions, fallback=predict_steps) + forecast_steps = _prediction_step_count( + actions, + fallback=self._prediction_steps, + ) forecast_step_indices = list( range(current_step_idx + 1, current_step_idx + forecast_steps + 1) ) @@ -283,133 +296,157 @@ def _simulate_logged_replay( session_state.current_ts_us = int(query_ts_us) return result - def simulate( + def _simulate_session( self, request: traffic_pb2.TrafficRequest, context: grpc.ServicerContext, + session_state: SessionState, ) -> traffic_pb2.TrafficReturn: - with self._lock: - query_ts_us = request.time_query_us - session_state = self._sessions.get(request.session_uuid) - if session_state is None: - context.set_code(grpc.StatusCode.NOT_FOUND) - context.set_details(f"Unknown session_uuid: {request.session_uuid}") - return traffic_pb2.TrafficReturn() + query_ts_us = request.time_query_us + merge_object_trajectory_updates( + session_state.closed_loop_trajectories, + request.object_trajectory_updates, + ) - request_update_trajectories = { - update.object_id: trajectory_from_grpc(update.trajectory) - for update in request.object_trajectory_updates - } - merge_object_trajectory_updates( - session_state.closed_loop_trajectories, - request.object_trajectory_updates, + if query_ts_us <= session_state.handover_time_us: + return self._simulate_logged_replay( + session_state=session_state, + session_uuid=request.session_uuid, + query_ts_us=query_ts_us, ) - if query_ts_us <= session_state.handover_time_us: - return self._simulate_logged_replay( - session_state=session_state, - session_uuid=request.session_uuid, - query_ts_us=query_ts_us, - ) + request_update_trajectories = { + update.object_id: trajectory_from_grpc(update.trajectory) + for update in request.object_trajectory_updates + } + history_end_ts_us = int(session_state.current_ts_us) + if history_end_ts_us < session_state.handover_time_us < int(query_ts_us): + history_end_ts_us = session_state.handover_time_us - history_end_ts_us = int(session_state.current_ts_us) - if history_end_ts_us < session_state.handover_time_us < int(query_ts_us): - history_end_ts_us = session_state.handover_time_us + try: + env_data = build_resampled_env_data( + session_state, + end_ts_us=history_end_ts_us, + history_steps=self._minimum_history_length, + dt_us=self._dt_us, + ) + session_state.env_data = env_data + current_step_idx = self._minimum_history_length - 1 - try: - env_data = build_resampled_env_data( - session_state, - end_ts_us=history_end_ts_us, - history_steps=self._minimum_history_length, - dt_us=self._dt_us, - ) - session_state.env_data = env_data - current_step_idx = self._minimum_history_length - 1 + future_step_indices = self._future_step_indices_from_history_window( + current_step_idx=current_step_idx, + current_ts_us=history_end_ts_us, + query_ts_us=query_ts_us, + ) + ego_trajectory = ( + request_update_trajectories.get("EGO") + or session_state.closed_loop_trajectories["EGO"] + ) + populate_ego_future_from_trajectory( + env_data, + ego_trajectory, + current_step_idx=current_step_idx, + requested_timestamp_us=query_ts_us, + future_step_indices=future_step_indices, + dt_us=self._dt_us, + ) - future_step_indices = self._future_step_indices_from_history_window( - current_step_idx=current_step_idx, - current_ts_us=history_end_ts_us, - query_ts_us=query_ts_us, - ) - ego_trajectory = ( - request_update_trajectories.get("EGO") - or session_state.closed_loop_trajectories["EGO"] - ) - populate_ego_future_from_trajectory( - env_data, - ego_trajectory, - current_step_idx=current_step_idx, - requested_timestamp_us=query_ts_us, - future_step_indices=future_step_indices, - dt_us=self._dt_us, - ) + forecast_step_indices = self._apply_model_predictions( + session_state=session_state, + future_step_indices=future_step_indices, + ) - forecast_step_indices = self._apply_model_predictions( - session_uuid=request.session_uuid, - query_ts_us=query_ts_us, - session_state=session_state, - future_step_indices=future_step_indices, - ) + result, _response_current_ts_us = build_simulation_response( + session_uuid=request.session_uuid, + env_data=env_data, + query_ts_us=query_ts_us, + future_step_indices=future_step_indices, + forecast_step_indices=forecast_step_indices, + dt_us=self._dt_us, + minimum_history_length=self._minimum_history_length, + ) + merge_env_step_trajectories( + session_state.closed_loop_trajectories, + env_data, + step_indices=future_step_indices, + dt_us=self._dt_us, + include_ego=True, + ) + merge_env_step_trajectories( + session_state.closed_loop_trajectories, + env_data, + step_indices=forecast_step_indices, + dt_us=self._dt_us, + include_ego=False, + ) + merge_object_trajectory_updates( + session_state.closed_loop_trajectories, + result.object_trajectory_updates, + ) + except CatkPredictionUnavailableError as exc: + logger.warning( + "simulate rejected: session={} query_ts_us={} reason={}", + request.session_uuid, + query_ts_us, + exc, + ) + context.set_code(grpc.StatusCode.FAILED_PRECONDITION) + context.set_details(str(exc)) + return traffic_pb2.TrafficReturn() + except (InsufficientEgoTrajectoryError, PredictionHorizonExceededError) as exc: + logger.warning( + "simulate rejected: session={} query_ts_us={} reason={}", + request.session_uuid, + query_ts_us, + exc, + ) + context.set_code(grpc.StatusCode.INVALID_ARGUMENT) + context.set_details(str(exc)) + return traffic_pb2.TrafficReturn() + except Exception as exc: # noqa: BLE001 - surface as a gRPC status + logger.exception( + "simulate failed: session={} query_ts_us={}", + request.session_uuid, + query_ts_us, + ) + context.set_code(grpc.StatusCode.INTERNAL) + context.set_details(f"simulation step failed: {exc}") + return traffic_pb2.TrafficReturn() - result, _response_current_ts_us = build_simulation_response( - session_uuid=request.session_uuid, - env_data=env_data, - query_ts_us=query_ts_us, - future_step_indices=future_step_indices, - forecast_step_indices=forecast_step_indices, - dt_us=self._dt_us, - minimum_history_length=self._minimum_history_length, - ) - merge_env_step_trajectories( - session_state.closed_loop_trajectories, - env_data, - step_indices=future_step_indices, - dt_us=self._dt_us, - include_ego=True, - ) - merge_env_step_trajectories( - session_state.closed_loop_trajectories, - env_data, - step_indices=forecast_step_indices, - dt_us=self._dt_us, - include_ego=False, - ) - merge_object_trajectory_updates( - session_state.closed_loop_trajectories, - result.object_trajectory_updates, - ) - except CatkPredictionUnavailableError as exc: - logger.warning( - "simulate rejected: session={} query_ts_us={} reason={}", - request.session_uuid, - query_ts_us, - exc, - ) - context.set_code(grpc.StatusCode.FAILED_PRECONDITION) - context.set_details(str(exc)) - return traffic_pb2.TrafficReturn() - except InsufficientEgoTrajectoryError as exc: - logger.warning( - "simulate rejected: session={} query_ts_us={} reason={}", - request.session_uuid, - query_ts_us, - exc, - ) - context.set_code(grpc.StatusCode.INVALID_ARGUMENT) - context.set_details(str(exc)) - return traffic_pb2.TrafficReturn() - except Exception as exc: # noqa: BLE001 - surface as a gRPC status - logger.exception( - "simulate failed: session={} query_ts_us={}", - request.session_uuid, - query_ts_us, + session_state.current_ts_us = int(query_ts_us) + return result + + def simulate( + self, + request: traffic_pb2.TrafficRequest, + context: grpc.ServicerContext, + ) -> traffic_pb2.TrafficReturn: + with self._registry_lock: + session_state = self._sessions.get(request.session_uuid) + session_lock = self._session_locks.get(request.session_uuid) + if session_state is None or session_lock is None: + context.set_code(grpc.StatusCode.NOT_FOUND) + context.set_details(f"Unknown session_uuid: {request.session_uuid}") + return traffic_pb2.TrafficReturn() + + with session_lock: + # close_session removes the entry before waiting for an in-flight + # request. Revalidate after acquiring the lock so a request that was + # queued behind close cannot mutate detached session state. + with self._registry_lock: + session_is_current = ( + self._sessions.get(request.session_uuid) is session_state + and self._session_locks.get(request.session_uuid) is session_lock ) - context.set_code(grpc.StatusCode.INTERNAL) - context.set_details(f"simulation step failed: {exc}") + if not session_is_current: + context.set_code(grpc.StatusCode.NOT_FOUND) + context.set_details(f"Unknown session_uuid: {request.session_uuid}") return traffic_pb2.TrafficReturn() - - session_state.current_ts_us = int(query_ts_us) - return result + return self._simulate_session( + request, + context, + session_state=session_state, + ) def get_metadata( self, diff --git a/src/trafficsim/alpasim_trafficsim/grpc/session/history.py b/src/trafficsim/alpasim_trafficsim/grpc/session/history.py index 2c11a778..6c698ed3 100644 --- a/src/trafficsim/alpasim_trafficsim/grpc/session/history.py +++ b/src/trafficsim/alpasim_trafficsim/grpc/session/history.py @@ -4,21 +4,17 @@ """Traffic session trajectory history and env resampling helpers.""" import numpy as np +import torch from alpasim_trafficsim.grpc.pipeline.env_builder import ( agent_is_static_by_object_id, agent_object_id_to_index, - first_trajectory_pose_at_timestamp, - reset_env_dynamic_state, snapshot_dynamic_env_data, step_idx_to_timestamp_us, - write_pose_to_env, ) from alpasim_trafficsim.grpc.service_structures import SessionState, SimEnvData -from alpasim_utils.geometry import ( - Trajectory, - pose_to_grpc_at_time, - trajectory_from_grpc, -) +from alpasim_utils.geometry import Trajectory, trajectory_from_grpc + +_EGO_OBJECT_ID = "EGO" def _trajectory_from_env_samples( @@ -62,6 +58,12 @@ def merge_object_trajectory_updates( trajectories: dict[str, Trajectory], updates, ) -> None: + """Merge object trajectory updates into an existing trajectory history. + + Args: + trajectories: Input/output mapping updated in place. + updates: Input trajectory updates to merge. + """ for update in updates: merge_trajectory( trajectories, @@ -96,7 +98,7 @@ def merge_env_step_trajectories( if ego_steps: merge_trajectory( trajectories, - object_id="EGO", + object_id=_EGO_OBJECT_ID, trajectory=_trajectory_from_env_samples( [timestamps_by_step_idx[step_idx] for step_idx in ego_steps], env_data["ego"]["xyz"][ego_steps, :], @@ -132,6 +134,60 @@ def merge_env_step_trajectories( ) +def _resample_trajectory_history( + trajectory: Trajectory, + timestamps_us: np.ndarray, + *, + is_static: bool, +) -> tuple[np.ndarray, np.ndarray, np.ndarray]: + """Resample one trajectory over a history window. + + Returns history step indices and matching position/heading arrays. Dynamic + trajectories omit timestamps outside their recorded range. Static + trajectories use their first pose for out-of-range timestamps while still + interpolating any in-range samples. + """ + empty_indices = np.empty((0,), dtype=np.int64) + empty_positions = np.empty((0, 3), dtype=np.float32) + empty_headings = np.empty((0,), dtype=np.float32) + if trajectory.is_empty(): + return empty_indices, empty_positions, empty_headings + + trajectory_start_us, trajectory_end_us = trajectory.get_time_range_tuple() + in_range = (timestamps_us >= trajectory_start_us) & ( + timestamps_us < trajectory_end_us + ) + + if is_static: + first_pose = trajectory.first_pose + positions = np.broadcast_to( + np.asarray(first_pose.vec3, dtype=np.float32), + (len(timestamps_us), 3), + ).copy() + headings = np.full( + (len(timestamps_us),), + first_pose.yaw(), + dtype=np.float32, + ) + step_indices = np.arange(len(timestamps_us), dtype=np.int64) + if bool(in_range.any()): + resampled = trajectory.interpolate(timestamps_us[in_range]) + positions[in_range] = resampled.positions + headings[in_range] = resampled.yaws + return step_indices, positions, headings + + step_indices = np.flatnonzero(in_range).astype(np.int64, copy=False) + if step_indices.size == 0: + return empty_indices, empty_positions, empty_headings + + resampled = trajectory.interpolate(timestamps_us[in_range]) + return ( + step_indices, + np.asarray(resampled.positions, dtype=np.float32), + np.asarray(resampled.yaws, dtype=np.float32), + ) + + def build_resampled_env_data( session_state: SessionState, *, @@ -142,48 +198,78 @@ def build_resampled_env_data( history_steps = max(int(history_steps), 1) end_ts_us = int(end_ts_us) start_ts_us = end_ts_us - ((history_steps - 1) * dt_us) + timestamps_us = start_ts_us + ( + np.arange(history_steps, dtype=np.uint64) * np.uint64(dt_us) + ) resampled_env_data = snapshot_dynamic_env_data(session_state.env_data) - reset_env_dynamic_state( - resampled_env_data, - total_steps=history_steps, - curr_t=history_steps - 1, - sample_start_t_us=start_ts_us, - dt_us=dt_us, - ) + source_ego_xyz = session_state.env_data["ego"]["xyz"] + source_ego_heading = session_state.env_data["ego"]["heading"] + source_agent_xyz = session_state.env_data["agents"]["xyz"] + source_agent_heading = session_state.env_data["agents"]["heading"] + source_agent_valid = session_state.env_data["agents"]["valid_mask"] + num_agents = int(source_agent_xyz.shape[0]) + + ego_xyz = np.zeros((history_steps, 3), dtype=np.float32) + ego_heading = np.zeros((history_steps,), dtype=np.float32) + agent_xyz = np.zeros((num_agents, history_steps, 3), dtype=np.float32) + agent_heading = np.zeros((num_agents, history_steps), dtype=np.float32) + agent_valid = np.zeros((num_agents, history_steps), dtype=np.bool_) static_by_object_id = agent_is_static_by_object_id(resampled_env_data) object_id_to_idx = agent_object_id_to_index(resampled_env_data) object_ids = [ - "EGO", + _EGO_OBJECT_ID, *[str(v) for v in resampled_env_data["env"].get("agent_object_ids", [])], ] for object_id in object_ids: - trajectory = session_state.closed_loop_trajectories.get(str(object_id)) + object_id = str(object_id) + trajectory = session_state.closed_loop_trajectories.get(object_id) if trajectory is None: continue - for step_idx in range(history_steps): - timestamp_us = start_ts_us + (step_idx * dt_us) - try: - pose = pose_to_grpc_at_time( - trajectory.interpolate_pose(int(timestamp_us)), - int(timestamp_us), - ) - except ValueError: - pose = None - if pose is None and static_by_object_id.get(str(object_id), False): - pose = first_trajectory_pose_at_timestamp( - trajectory, - timestamp_us=timestamp_us, - ) - if pose is None: - continue - write_pose_to_env( - resampled_env_data, - object_id=str(object_id), - step_idx=step_idx, - pose_at_time=pose, - agent_object_id_to_idx=object_id_to_idx, - ) + is_static = ( + False if object_id == _EGO_OBJECT_ID else static_by_object_id[object_id] + ) + step_indices, positions, headings = _resample_trajectory_history( + trajectory, + timestamps_us, + is_static=is_static, + ) + if step_indices.size == 0: + continue + + if object_id == _EGO_OBJECT_ID: + ego_xyz[step_indices] = positions + ego_heading[step_indices] = headings + continue + + agent_idx = object_id_to_idx[object_id] + agent_xyz[agent_idx, step_indices] = positions + agent_heading[agent_idx, step_indices] = headings + agent_valid[agent_idx, step_indices] = True + + resampled_env_data["ego"]["xyz"] = torch.as_tensor( + ego_xyz, dtype=source_ego_xyz.dtype, device=source_ego_xyz.device + ) + resampled_env_data["ego"]["heading"] = torch.as_tensor( + ego_heading, dtype=source_ego_heading.dtype, device=source_ego_heading.device + ) + resampled_env_data["agents"]["xyz"] = torch.as_tensor( + agent_xyz, dtype=source_agent_xyz.dtype, device=source_agent_xyz.device + ) + resampled_env_data["agents"]["heading"] = torch.as_tensor( + agent_heading, + dtype=source_agent_heading.dtype, + device=source_agent_heading.device, + ) + resampled_env_data["agents"]["valid_mask"] = torch.as_tensor( + agent_valid, dtype=source_agent_valid.dtype, device=source_agent_valid.device + ) + resampled_env_data["env"]["curr_t"] = history_steps - 1 + resampled_env_data["env"]["sample_start_t_us"] = start_ts_us + resampled_env_data["current_time_us"] = torch.tensor( + [[end_ts_us]], + dtype=torch.long, + ) return resampled_env_data diff --git a/src/trafficsim/tests/test_batching.py b/src/trafficsim/tests/test_batching.py new file mode 100644 index 00000000..9451630e --- /dev/null +++ b/src/trafficsim/tests/test_batching.py @@ -0,0 +1,174 @@ +# SPDX-License-Identifier: Apache-2.0 +# Copyright (c) 2026 NVIDIA Corporation + +from __future__ import annotations + +import threading +from concurrent.futures import Future +from typing import Any + +import pytest +import torch +from alpasim_trafficsim.catk.batching import collate_model_inputs +from alpasim_trafficsim.grpc.catk_predictor import _InferenceBatcher, _PreparedInference + + +def _input_data(*, non_ego_agents: int, triplets: int) -> dict[str, Any]: + total_agents = non_ego_agents + 1 + role = torch.zeros((total_agents, 3), dtype=torch.bool) + role[-1, 0] = True + role[:, 1:] = True + agent = { + "id": torch.arange(total_agents, dtype=torch.long), + "role": role, + "type": torch.zeros((total_agents,), dtype=torch.long), + "valid_mask": torch.ones((total_agents, 2), dtype=torch.bool), + "position": torch.zeros((total_agents, 2, 3)), + "heading": torch.zeros((total_agents, 2)), + "velocity": torch.zeros((total_agents, 2, 2)), + "shape": torch.ones((total_agents, 3)), + "batch": torch.zeros((total_agents,), dtype=torch.long), + } + freeze_agent = {key: value[-1:].clone() for key, value in agent.items()} + freeze_agent["batch"].zero_() + polyline_extras = { + "type": torch.zeros((triplets,), dtype=torch.long), + "pl_type": torch.zeros((triplets,), dtype=torch.long), + "light_type": torch.zeros((triplets,), dtype=torch.long), + "batch": torch.zeros((triplets,), dtype=torch.long), + } + return { + "agent": agent, + "num_graphs": 1, + "freeze_agent_data": { + "agent": freeze_agent, + "num_obstacles": torch.ones((1,), dtype=torch.long), + "num_graphs": 1, + }, + "freeze_agent_mask": role[:, 0].clone(), + "map": { + "triplets": torch.zeros((triplets, 3, 2)), + "triplet_thetas": torch.zeros((triplets,)), + "polyline_extras": polyline_extras, + "rb_data": { + "rb_polylines": [torch.zeros((1, 3, 3))], + "rb_polylines_batch": [0], + }, + }, + } + + +class _ObservedFuture(Future[dict[str, Any]]): + def __init__(self) -> None: + super().__init__() + self.result_entered = threading.Event() + + def result(self, timeout: float | None = None) -> dict[str, Any]: + self.result_entered.set() + return super().result(timeout) + + +def _prepared(input_data: dict[str, Any]) -> _PreparedInference: + return _PreparedInference( + input_data=input_data, + future=_ObservedFuture(), + ) + + +def test_collate_model_inputs_remaps_graph_indices_and_split_sizes() -> None: + first = _input_data(non_ego_agents=2, triplets=3) + second = _input_data(non_ego_agents=1, triplets=2) + + collated, split_sizes = collate_model_inputs([first, second]) + + assert split_sizes == [2, 1] + assert collated["num_graphs"] == 2 + assert collated["num_obstacles"].tolist() == [3, 2] + assert collated["agent"]["batch"].tolist() == [0, 0, 0, 1, 1] + assert collated["freeze_agent_data"]["agent"]["batch"].tolist() == [0, 1] + assert collated["freeze_agent_mask"].tolist() == [False, False, True, False, True] + assert collated["map"]["polyline_extras"]["batch"].tolist() == [0, 0, 0, 1, 1] + assert collated["map"]["rb_data"]["rb_polylines_batch"] == [0, 1] + + +def test_collate_model_inputs_requires_rb_polylines_when_rb_data_is_present() -> None: + input_data = _input_data(non_ego_agents=1, triplets=2) + del input_data["map"]["rb_data"]["rb_polylines"] + + with pytest.raises(KeyError, match="rb_polylines"): + collate_model_inputs([input_data]) + + +class _BlockingBatchModel: + def __init__(self) -> None: + self.prediction_steps = 5 + self.batch_sizes: list[int] = [] + self.first_started = threading.Event() + self.release_first = threading.Event() + + def inference( + self, + input_data: dict[str, Any], + ) -> dict[str, torch.Tensor]: + self.batch_sizes.append(int(input_data["num_graphs"])) + if len(self.batch_sizes) == 1: + self.first_started.set() + if not self.release_first.wait(timeout=3.0): + raise TimeoutError("test did not release first batch") + non_ego = ~input_data["agent"]["role"][:, 0] + graph_ids = input_data["agent"]["batch"][non_ego].float() + num_agents = int(graph_ids.shape[0]) + xyz = torch.zeros((num_agents, self.prediction_steps, 3)) + xyz[:, :, 0] = graph_ids.unsqueeze(1) + return { + "agent_future_xyz": xyz, + "agent_future_heading": torch.zeros((num_agents, self.prediction_steps)), + "agent_future_valid_mask": torch.ones( + (num_agents, self.prediction_steps), dtype=torch.bool + ), + "agent_future_velocity": torch.zeros( + (num_agents, self.prediction_steps, 2) + ), + } + + +def test_batcher_drains_all_available_requests() -> None: + model = _BlockingBatchModel() + batcher = _InferenceBatcher(model) + requests = { + "first": _prepared(_input_data(non_ego_agents=1, triplets=2)), + "second": _prepared(_input_data(non_ego_agents=2, triplets=3)), + "third": _prepared(_input_data(non_ego_agents=1, triplets=4)), + } + results: dict[str, dict[str, torch.Tensor]] = {} + + def submit(name: str) -> None: + results[name] = batcher.submit(requests[name]) + + first_thread = threading.Thread(target=submit, args=("first",)) + first_thread.start() + assert model.first_started.wait(timeout=2.0) + + second_thread = threading.Thread(target=submit, args=("second",)) + third_thread = threading.Thread(target=submit, args=("third",)) + second_thread.start() + third_thread.start() + for name in ("second", "third"): + future = requests[name].future + assert isinstance(future, _ObservedFuture) + assert future.result_entered.wait(timeout=2.0) + + model.release_first.set() + for thread in (first_thread, second_thread, third_thread): + thread.join(timeout=3.0) + assert not thread.is_alive() + + assert model.batch_sizes == [1, 2] + assert results["first"]["agent_future_xyz"].shape[0] == 1 + assert results["second"]["agent_future_xyz"].shape[0] == 2 + assert results["third"]["agent_future_xyz"].shape[0] == 1 + second_ids = set(results["second"]["agent_future_xyz"][:, :, 0].unique().tolist()) + third_ids = set(results["third"]["agent_future_xyz"][:, :, 0].unique().tolist()) + assert len(second_ids) == 1 + assert len(third_ids) == 1 + assert second_ids | third_ids == {0.0, 1.0} diff --git a/src/trafficsim/tests/test_catk_integration.py b/src/trafficsim/tests/test_catk_integration.py index 88666c9d..9e07bab0 100644 --- a/src/trafficsim/tests/test_catk_integration.py +++ b/src/trafficsim/tests/test_catk_integration.py @@ -23,7 +23,6 @@ TRAFFICSIM_TEST_USDZ_DIR — Directory containing ClipGT .usdz files """ - import os from pathlib import Path @@ -292,7 +291,7 @@ def __init__(self) -> None: catk = CATK.__new__(CATK) catk.device = "cpu" catk.model_input_step_num = 16 - catk.model_predict_step_num = 5 + catk._model_predict_step_num = 5 catk.delta_t = 0.1 catk.use_downsampled_lines = False catk.disable_sub_plyline_type = True @@ -303,8 +302,25 @@ def __init__(self) -> None: filter_map_by_ego=False, filter_distance_th=0.0, )["input_data"] + assert input_data["num_obstacles"].dtype == torch.long + assert input_data["num_obstacles"].device.type == "cpu" + assert input_data["num_obstacles"].tolist() == [4] + catk.inference(input_data) + malformed_input = dict(input_data) + del malformed_input["num_obstacles"] + with pytest.raises(KeyError, match="num_obstacles"): + catk.inference(malformed_input) + + malformed_input = {**input_data, "num_obstacles": torch.tensor([4.0])} + with pytest.raises(ValueError, match="torch.long tensor"): + catk.inference(malformed_input) + + malformed_input = {**input_data, "num_obstacles": torch.tensor([3])} + with pytest.raises(ValueError, match="total agent count 4"): + catk.inference(malformed_input) + agent_encoder = catk.model.encoder.agent_encoder assert agent_encoder.captured["freeze_agent_future"] is True assert agent_encoder.captured["freeze_agent_mask"].tolist() == [ @@ -322,6 +338,7 @@ def __init__(self) -> None: @_skip_no_torch_cluster def test_catk_synthetic(): """Load CATK model and run inference on synthetic data (no USDZ needed).""" + from alpasim_trafficsim.catk.batching import collate_model_inputs from alpasim_trafficsim.catk.model_adapter import CATK env_data = _make_synthetic_env_data() @@ -332,6 +349,7 @@ def test_catk_synthetic(): ckpt_path=str(catk_dir / "latest.ckpt"), token_pkl_dir=str(MODELS_DIR / "tokens"), disable_sub_plyline_type=True, + prediction_steps=5, device="cuda", ) @@ -359,6 +377,16 @@ def test_catk_synthetic(): valid_xyz ).all(), "Non-finite positions in valid predictions" + batched_input, split_sizes = collate_model_inputs([input_data, input_data]) + batched_actions = model.inference(batched_input) + assert batched_input["num_graphs"] == 2 + assert split_sizes == [num_agents, num_agents] + assert batched_actions["agent_future_xyz"].shape == ( + num_agents * 2, + num_steps, + 3, + ) + # --------------------------------------------------------------------------- # Tests that require ClipGT USDZ files @@ -425,6 +453,7 @@ def test_catk_inference(): ckpt_path=str(catk_dir / "latest.ckpt"), token_pkl_dir=str(MODELS_DIR / "tokens"), disable_sub_plyline_type=True, + prediction_steps=5, device="cuda", ) diff --git a/src/trafficsim/tests/test_laneline_elevation.py b/src/trafficsim/tests/test_laneline_elevation.py index 4b0daa1b..dd0ffaa4 100644 --- a/src/trafficsim/tests/test_laneline_elevation.py +++ b/src/trafficsim/tests/test_laneline_elevation.py @@ -27,7 +27,6 @@ def _predictor( predictor.history_window_steps = cfg.loader.num_history_steps predictor.min_valid_history_steps = cfg.min_valid_history_steps predictor.model = None - predictor._token_stride = 5 return predictor diff --git a/src/trafficsim/tests/test_service.py b/src/trafficsim/tests/test_service.py index 34f89e29..7ec1da66 100644 --- a/src/trafficsim/tests/test_service.py +++ b/src/trafficsim/tests/test_service.py @@ -10,19 +10,26 @@ from contextlib import contextmanager from typing import Any, Iterator +import numpy as np import pytest import torch from alpasim_grpc.v0 import common_pb2, traffic_pb2, traffic_pb2_grpc from alpasim_runtime.errors import UnknownSceneError +from alpasim_trafficsim.grpc.catk_predictor import CatkPredictionUnavailableError from alpasim_trafficsim.grpc.config import CatkLoaderConfig from alpasim_trafficsim.grpc.servicer import TrafficServiceServicer -from alpasim_trafficsim.grpc.session.history import merge_trajectory +from alpasim_trafficsim.grpc.session import history as history_module +from alpasim_trafficsim.grpc.session.history import ( + _resample_trajectory_history, + merge_trajectory, +) from alpasim_utils.geometry import trajectory_from_grpc import grpc DT_US = 100_000 MIN_HISTORY = 16 +PREDICTION_STEPS = 15 DEFAULT_SCENE_ID = "clipgt-test-scene" @@ -55,29 +62,28 @@ class NoopPredictor: def __init__(self, *, predict_static: bool = True) -> None: self.predict_static = predict_static - def run_inference( - self, env_data: dict[str, Any], *, predict_steps: int - ) -> dict[str, Any] | None: - del env_data, predict_steps - return None + def run_inference(self, env_data: dict[str, Any]) -> dict[str, Any]: + del env_data + raise CatkPredictionUnavailableError( + "No usable map geometry was found within 100 m of the current ego " + "position; CATK cannot produce predictions" + ) class RecordingPredictor: - """Records each run_inference (predict_steps, curr_t); empty predictions.""" + """Records each run_inference (configured steps, curr_t); empty predictions.""" def __init__(self) -> None: self.calls: list[tuple[int, int]] = [] self.predict_static = True - def run_inference( - self, env_data: dict[str, Any], *, predict_steps: int - ) -> dict[str, Any] | None: - self.calls.append((predict_steps, int(env_data["env"].get("curr_t", 0)))) + def run_inference(self, env_data: dict[str, Any]) -> dict[str, Any] | None: + self.calls.append((PREDICTION_STEPS, int(env_data["env"].get("curr_t", 0)))) return { - "agent_future_xyz": torch.zeros((0, predict_steps, 3)), - "agent_future_heading": torch.zeros((0, predict_steps)), + "agent_future_xyz": torch.zeros((0, PREDICTION_STEPS, 3)), + "agent_future_heading": torch.zeros((0, PREDICTION_STEPS)), "agent_future_valid_mask": torch.zeros( - (0, predict_steps), dtype=torch.bool + (0, PREDICTION_STEPS), dtype=torch.bool ), } @@ -102,26 +108,26 @@ def apply_predictions_to_env( class LinearPredictor(RecordingPredictor): """Predicts agent x == future-timestamp-in-seconds (a unique value per step).""" - def run_inference( - self, env_data: dict[str, Any], *, predict_steps: int - ) -> dict[str, Any] | None: + def run_inference(self, env_data: dict[str, Any]) -> dict[str, Any] | None: curr_t = int(env_data["env"].get("curr_t", 0)) - self.calls.append((predict_steps, curr_t)) + self.calls.append((PREDICTION_STEPS, curr_t)) sample_start_t_us = int(env_data["env"]["sample_start_t_us"]) current_ts_us = sample_start_t_us + curr_t * DT_US future_ts_s = torch.tensor( [ (current_ts_us + ((offset + 1) * DT_US)) / 1_000_000.0 - for offset in range(predict_steps) + for offset in range(PREDICTION_STEPS) ], dtype=torch.float32, ) - xyz = torch.zeros((1, predict_steps, 3), dtype=torch.float32) + xyz = torch.zeros((1, PREDICTION_STEPS, 3), dtype=torch.float32) xyz[0, :, 0] = future_ts_s return { "agent_future_xyz": xyz, - "agent_future_heading": torch.zeros((1, predict_steps)), - "agent_future_valid_mask": torch.ones((1, predict_steps), dtype=torch.bool), + "agent_future_heading": torch.zeros((1, PREDICTION_STEPS)), + "agent_future_valid_mask": torch.ones( + (1, PREDICTION_STEPS), dtype=torch.bool + ), } @staticmethod @@ -151,11 +157,9 @@ def __init__(self) -> None: self.second_started = threading.Event() self.release_first = threading.Event() - def run_inference( - self, env_data: dict[str, Any], *, predict_steps: int - ) -> dict[str, Any] | None: + def run_inference(self, env_data: dict[str, Any]) -> dict[str, Any] | None: with self._lock: - self.calls.append((predict_steps, int(env_data["env"].get("curr_t", 0)))) + self.calls.append((PREDICTION_STEPS, int(env_data["env"].get("curr_t", 0)))) call_count = len(self.calls) if call_count == 1: self.first_started.set() @@ -164,10 +168,10 @@ def run_inference( elif call_count == 2: self.second_started.set() return { - "agent_future_xyz": torch.zeros((0, predict_steps, 3)), - "agent_future_heading": torch.zeros((0, predict_steps)), + "agent_future_xyz": torch.zeros((0, PREDICTION_STEPS, 3)), + "agent_future_heading": torch.zeros((0, PREDICTION_STEPS)), "agent_future_valid_mask": torch.zeros( - (0, predict_steps), dtype=torch.bool + (0, PREDICTION_STEPS), dtype=torch.bool ), } @@ -175,9 +179,8 @@ def run_inference( class ExplodingPredictor(NoopPredictor): """Raises during inference to exercise the simulate INTERNAL error path.""" - def run_inference( - self, env_data: dict[str, Any], *, predict_steps: int - ) -> dict[str, Any] | None: + def run_inference(self, env_data: dict[str, Any]) -> dict[str, Any] | None: + del env_data raise RuntimeError("boom: model inference failed") @@ -294,6 +297,58 @@ def test_merge_trajectory_replaces_existing_future_segment() -> None: assert merged.positions[:, 0].tolist() == pytest.approx([1.0, 2.0, 25.0, 35.0]) +def test_vectorized_history_resampling_omits_out_of_range_dynamic_steps() -> None: + trajectory = trajectory_from_grpc( + common_pb2.Trajectory( + poses=[ + _pose(100_000, x=1.0), + _pose(200_000, x=2.0), + _pose(300_000, x=3.0), + ] + ) + ) + timestamps_us = np.asarray( + [0, 100_000, 150_000, 300_000, 400_000], + dtype=np.uint64, + ) + + step_indices, positions, headings = _resample_trajectory_history( + trajectory, + timestamps_us, + is_static=False, + ) + + assert step_indices.tolist() == [1, 2, 3] + assert positions[:, 0].tolist() == pytest.approx([1.0, 1.5, 3.0]) + assert headings.tolist() == pytest.approx([0.0, 0.0, 0.0]) + + +def test_vectorized_history_resampling_preserves_static_fallback() -> None: + trajectory = trajectory_from_grpc( + common_pb2.Trajectory( + poses=[ + _pose(100_000, x=1.0), + _pose(200_000, x=2.0), + _pose(300_000, x=3.0), + ] + ) + ) + timestamps_us = np.asarray( + [0, 100_000, 150_000, 300_000, 400_000], + dtype=np.uint64, + ) + + step_indices, positions, headings = _resample_trajectory_history( + trajectory, + timestamps_us, + is_static=True, + ) + + assert step_indices.tolist() == [0, 1, 2, 3, 4] + assert positions[:, 0].tolist() == pytest.approx([1.0, 1.0, 1.5, 3.0, 1.0]) + assert headings.tolist() == pytest.approx([0.0] * 5) + + def _session_request( *, logged: list[traffic_pb2.ObjectTrajectory], @@ -336,6 +391,20 @@ def session_state(self, session_uuid: str = "session-1") -> Any: return self.servicer._sessions[session_uuid] +class DirectContext: + """Minimal ServicerContext for direct, socket-free service tests.""" + + def __init__(self) -> None: + self.code = grpc.StatusCode.OK + self.details = "" + + def set_code(self, code: grpc.StatusCode) -> None: + self.code = code + + def set_details(self, details: str) -> None: + self.details = details + + def _build_servicer( *, predictor: Any, @@ -345,13 +414,14 @@ def _build_servicer( """Construct a servicer with injected fakes, bypassing loader/model setup.""" servicer = TrafficServiceServicer.__new__(TrafficServiceServicer) servicer._server = None - servicer._lock = threading.Lock() + servicer._registry_lock = threading.Lock() servicer._sessions = {} + servicer._session_locks = {} servicer._service_version = "test-traffic-service" servicer._time_step_s = DT_US / 1e6 servicer._dt_us = DT_US servicer._minimum_history_length = MIN_HISTORY - servicer._minimum_future_steps = 5 + servicer._prediction_steps = PREDICTION_STEPS servicer._loader_cfg = CatkLoaderConfig(usdz_folder="unused") servicer._scene_loader = scene_loader or FakeSceneLoader() servicer._scene_adapter = FakeSceneAdapter(env_data or _make_env_data()) @@ -359,6 +429,49 @@ def _build_servicer( return servicer +def _started_session_state() -> Any: + servicer = _build_servicer(predictor=RecordingPredictor()) + context = DirectContext() + servicer.start_session( + _session_request(logged=[_ego_object(), _moving_object()]), + context, + ) + assert context.code == grpc.StatusCode.OK + return servicer._sessions["session-1"] + + +def test_resampling_requires_static_object_mapping( + monkeypatch: pytest.MonkeyPatch, +) -> None: + state = _started_session_state() + monkeypatch.setattr(history_module, "agent_is_static_by_object_id", lambda _: {}) + + with pytest.raises(KeyError) as exc_info: + history_module.build_resampled_env_data( + state, + end_ts_us=1_500_000, + history_steps=MIN_HISTORY, + dt_us=DT_US, + ) + assert exc_info.value.args == ("moving-1",) + + +def test_resampling_requires_object_index_mapping( + monkeypatch: pytest.MonkeyPatch, +) -> None: + state = _started_session_state() + monkeypatch.setattr(history_module, "agent_object_id_to_index", lambda _: {}) + + with pytest.raises(KeyError) as exc_info: + history_module.build_resampled_env_data( + state, + end_ts_us=1_500_000, + history_steps=MIN_HISTORY, + dt_us=DT_US, + ) + assert exc_info.value.args == ("moving-1",) + + @contextmanager def _serve( predictor: Any | None = None, @@ -411,6 +524,20 @@ def test_start_then_close_session_round_trips(service: RunningService) -> None: traffic_pb2.TrafficSessionCloseRequest(session_uuid="session-1") ) assert "session-1" not in service.servicer._sessions + assert "session-1" not in service.servicer._session_locks + + +def test_start_session_rejects_duplicate_uuid(service: RunningService) -> None: + service.stub.start_session(_session_request(logged=[_ego_object()])) + original_state = service.servicer._sessions["session-1"] + original_lock = service.servicer._session_locks["session-1"] + + with pytest.raises(grpc.RpcError) as exc: + service.stub.start_session(_session_request(logged=[_ego_object()])) + + assert exc.value.code() == grpc.StatusCode.ALREADY_EXISTS + assert service.servicer._sessions["session-1"] is original_state + assert service.servicer._session_locks["session-1"] is original_lock def test_start_session_rejects_empty_uuid(service: RunningService) -> None: @@ -515,7 +642,8 @@ def test_simulate_missing_catk_predictions_returns_failed_precondition() -> None with pytest.raises(grpc.RpcError) as exc: service.stub.simulate(_simulate_request(2_000_000)) assert exc.value.code() == grpc.StatusCode.FAILED_PRECONDITION - assert "CATK did not produce predictions" in exc.value.details() + assert "No usable map geometry was found within 100 m" in exc.value.details() + assert "CATK cannot produce predictions" in exc.value.details() def test_first_simulate_accepts_initial_history_time(service: RunningService) -> None: @@ -552,15 +680,12 @@ def test_dynamic_response_includes_available_prediction_horizon() -> None: assert len(response.object_trajectory_updates) == 1 trajectory = response.object_trajectory_updates[0].trajectory - assert [pose.timestamp_us for pose in trajectory.poses] == [ - 1_600_000, - 1_700_000, - 1_800_000, - 1_900_000, - 2_000_000, + expected_timestamps = [ + 1_600_000 + offset * DT_US for offset in range(PREDICTION_STEPS) ] + assert [pose.timestamp_us for pose in trajectory.poses] == expected_timestamps assert [pose.pose.vec.x for pose in trajectory.poses] == pytest.approx( - [1.6, 1.7, 1.8, 1.9, 2.0] + [timestamp_us / 1_000_000 for timestamp_us in expected_timestamps] ) @@ -600,7 +725,7 @@ def test_logged_traffic_used_until_handover_then_model_runs() -> None: assert pose.pose.vec.x == pytest.approx(1.6) service.stub.simulate(_simulate_request(2_100_000)) - assert predictor.calls == [(5, MIN_HISTORY - 1)] + assert predictor.calls == [(PREDICTION_STEPS, MIN_HISTORY - 1)] def test_off_grid_handover_uses_exact_anchor_for_catk() -> None: @@ -614,13 +739,16 @@ def test_off_grid_handover_uses_exact_anchor_for_catk() -> None: state = service.session_state() service.stub.simulate(_simulate_request(2_060_000)) - assert predictor.calls == [(5, MIN_HISTORY - 1)] + assert predictor.calls == [(PREDICTION_STEPS, MIN_HISTORY - 1)] assert state.current_ts_us == 2_060_000 assert state.env_data["env"]["sample_start_t_us"] == 550_000 assert state.env_data["env"]["curr_t"] == MIN_HISTORY service.stub.simulate(_simulate_request(2_200_000)) - assert predictor.calls == [(5, MIN_HISTORY - 1), (5, MIN_HISTORY - 1)] + assert predictor.calls == [ + (PREDICTION_STEPS, MIN_HISTORY - 1), + (PREDICTION_STEPS, MIN_HISTORY - 1), + ] assert state.env_data["env"]["sample_start_t_us"] == 560_000 assert state.env_data["env"]["curr_t"] == MIN_HISTORY + 1 @@ -723,17 +851,31 @@ def test_handover_resamples_logged_history_before_catk() -> None: assert state.env_data["agents"]["xyz"][0, 16, 0].item() == pytest.approx(2.1) -def test_multi_token_horizon_uses_single_inference_call() -> None: +def test_request_within_fixed_horizon_uses_configured_prediction_steps() -> None: predictor = RecordingPredictor() with _serve(predictor) as service: service.stub.start_session(_session_request(logged=[_ego_object()])) service.stub.simulate(_simulate_request(2_300_000)) assert len(predictor.calls) == 1 - assert predictor.calls[0] == (8, 15) + assert predictor.calls[0] == (PREDICTION_STEPS, 15) assert service.session_state().env_data["env"]["curr_t"] == 23 +def test_request_beyond_fixed_prediction_horizon_is_invalid() -> None: + predictor = RecordingPredictor() + with _serve(predictor) as service: + service.stub.start_session(_session_request(logged=[_ego_object()])) + + with pytest.raises(grpc.RpcError) as exc_info: + service.stub.simulate(_simulate_request(3_100_000)) + + assert exc_info.value.code() == grpc.StatusCode.INVALID_ARGUMENT + assert "requires 16 future steps" in exc_info.value.details() + assert "configured for 15 prediction steps" in exc_info.value.details() + assert predictor.calls == [] + + def test_concurrent_simulate_for_same_session_is_serialized() -> None: predictor = BlockingPredictor() with _serve(predictor, max_workers=4) as service: @@ -761,5 +903,50 @@ def call(timestamp_us: int) -> None: assert not first.is_alive() and not second.is_alive() assert errors == [] - assert predictor.calls == [(5, 15), (5, 15)] + assert predictor.calls == [ + (PREDICTION_STEPS, 15), + (PREDICTION_STEPS, 15), + ] assert service.session_state().current_ts_us == 2_100_000 + + +def test_concurrent_simulate_for_different_sessions_reaches_predictor() -> None: + predictor = BlockingPredictor() + with _serve(predictor, max_workers=4) as service: + service.stub.start_session( + _session_request(logged=[_ego_object()], session_uuid="session-1") + ) + service.stub.start_session( + _session_request(logged=[_ego_object()], session_uuid="session-2") + ) + + errors: list[BaseException] = [] + + def call(session_uuid: str) -> None: + try: + service.stub.simulate( + _simulate_request(2_000_000, session_uuid=session_uuid) + ) + except BaseException as exc: # noqa: BLE001 + errors.append(exc) + + first = threading.Thread(target=call, args=("session-1",)) + second = threading.Thread(target=call, args=("session-2",)) + + first.start() + assert predictor.first_started.wait(timeout=2.0) + second.start() + assert predictor.second_started.wait(timeout=2.0) + + predictor.release_first.set() + first.join(timeout=3.0) + second.join(timeout=3.0) + + assert not first.is_alive() and not second.is_alive() + assert errors == [] + assert predictor.calls == [ + (PREDICTION_STEPS, 15), + (PREDICTION_STEPS, 15), + ] + assert service.session_state("session-1").current_ts_us == 2_000_000 + assert service.session_state("session-2").current_ts_us == 2_000_000 diff --git a/src/trafficsim/tests/test_sparse_history_freeze.py b/src/trafficsim/tests/test_sparse_history_freeze.py index 0932c384..a4c595bd 100644 --- a/src/trafficsim/tests/test_sparse_history_freeze.py +++ b/src/trafficsim/tests/test_sparse_history_freeze.py @@ -7,8 +7,12 @@ from typing import Any +import pytest import torch -from alpasim_trafficsim.grpc.catk_predictor import CATKTrafficPredictor +from alpasim_trafficsim.grpc.catk_predictor import ( + CatkPredictionUnavailableError, + CATKTrafficPredictor, +) from alpasim_trafficsim.grpc.config import CatkConfig @@ -22,7 +26,6 @@ def _predictor(min_valid_history_steps: int | None) -> CATKTrafficPredictor: predictor.history_window_steps = cfg.loader.num_history_steps predictor.min_valid_history_steps = cfg.min_valid_history_steps predictor.model = None - predictor._token_stride = 5 return predictor @@ -127,8 +130,6 @@ def test_threshold_zero_never_freezes_for_sparse_history() -> None: class _EmptyMapModel: - model_predict_step_num = 0 - def create_model_input(self, *args: Any, **kwargs: Any) -> dict[str, Any] | None: del args, kwargs return None @@ -154,11 +155,15 @@ def _env_for_inference() -> dict[str, Any]: } -def test_empty_filtered_map_returns_none_when_prediction_unavailable() -> None: +def test_empty_filtered_map_raises_prediction_unavailable() -> None: predictor = _predictor(min_valid_history_steps=None) predictor.model = _EmptyMapModel() - assert predictor.run_inference(_env_for_inference(), predict_steps=1) is None + with pytest.raises( + CatkPredictionUnavailableError, + match="No usable map geometry was found within 100 m", + ): + predictor.run_inference(_env_for_inference()) def test_model_input_value_error_still_propagates() -> None: @@ -173,7 +178,7 @@ def create_model_input( predictor.model = BrokenModel() try: - predictor.run_inference(_env_for_inference(), predict_steps=1) + predictor.run_inference(_env_for_inference()) except ValueError as exc: assert str(exc) == "different CATK input failure" else: diff --git a/src/utils/alpasim_utils/artifact.py b/src/utils/alpasim_utils/artifact.py index 27abcea3..feb5b3e1 100644 --- a/src/utils/alpasim_utils/artifact.py +++ b/src/utils/alpasim_utils/artifact.py @@ -13,6 +13,7 @@ import numpy as np import yaml +from alpasim_utils.ply_io import load_mesh_vf from alpasim_utils.scenario import Rig, TrafficObjects from alpasim_utils.scene_data_source import SceneDataSource from alpasim_utils.scene_metadata import Metadata @@ -20,12 +21,14 @@ logger = logging.getLogger(__name__) try: + from alpasim_utils.ground_snap import snap_vector_map_to_ground from trajdata.dataset_specific.mads.mads_utils import populate_vector_map from trajdata.dataset_specific.xodr.geo_transform import get_t_rig_enu_from_ecef from trajdata.dataset_specific.xodr.vector_map_export import ( populate_vector_map_from_xodr, ) from trajdata.maps import VectorMap + from trajdata.maps.vec_map_elements import MapElementType except ImportError: logger.warning("Could not import trajdata (missing). Map loading will be disabled.") VectorMap = None @@ -66,6 +69,7 @@ class Artifact(SceneDataSource): _traffic_objects: TrafficObjects | None = None _smooth_trajectories: bool = True _map: VectorMap | None = None + _map_source: str | None = None _attempted_map_load: bool = False _mesh_ply: bytes | None = None @@ -96,6 +100,7 @@ def clear_cache(self) -> None: self._rig = None self._traffic_objects = None self._map = None + self._map_source = None self._attempted_map_load = False self._mesh_ply = None @@ -183,8 +188,9 @@ def map(self) -> VectorMap | None: """Load and return the map data from the USDZ file. Attempts to load map data in the following order: - 1. clipgt/map_data directories (if available) - 2. XODR file (fallback) + 1. map_data or clipgt parquet directories + 2. fastmap parquet directory + 3. XODR file Returns: VectorMap instance or None if no map data is available @@ -210,69 +216,94 @@ def map(self) -> VectorMap | None: "Loading USDZ map data into memory. This will take a few seconds..." ) - self._map = VectorMap(map_id=f"alpasim_usdz:{self.metadata.scene_id}") - - # Try loading map data - map_loaded = False + vector_map = None + map_directory = None with zipfile.ZipFile(self.source, "r") as zip_file: - # Try loading from different sources in order of preference - if self._load_clipgt_map(zip_file): - map_loaded = True - logger.info("Successfully loaded map from clipgt/map_data") - elif self._load_xodr_map(zip_file): - map_loaded = True - logger.info("Successfully loaded map from XODR") - - if not map_loaded: + for candidate in ("map_data", "clipgt", "fastmap"): + vector_map = self._load_parquet_map(zip_file, candidate) + if vector_map is not None: + map_directory = candidate + logger.info("Successfully loaded map from %s", candidate) + break + if vector_map is None: + vector_map = self._load_xodr_map(zip_file) + if vector_map is not None: + map_directory = "xodr" + logger.info("Successfully loaded map from XODR") + + if vector_map is None: logger.warning( - f"No map data (clipgt or XODR) found in {self.source}. " + f"No map data (map_data, clipgt, fastmap, or XODR) found in {self.source}. " "Skipping map loading." ) self._map = None + self._map_source = None # Mark as attempted AFTER setting _map to None (load complete) self._attempted_map_load = True return None + self._map = vector_map + if map_directory == "fastmap": + self._snap_map_z() + # Post-process the loaded map (builds KDTree search indices) self._finalize_map() + self._map_source = map_directory # Mark as attempted AFTER map is fully loaded and finalized self._attempted_map_load = True return self._map - def _load_clipgt_map(self, zip_file: zipfile.ZipFile) -> bool: - """Load map from clipgt/map_data directories. + @property + def map_source(self) -> str | None: + """Return the source used by :attr:`map`. + + Values are ``map_data``, ``clipgt``, ``fastmap``, or ``xodr``. The + property loads the map if needed and returns ``None`` when no usable + map is available. + """ + _ = self.map + return self._map_source + + def _load_parquet_map( + self, zip_file: zipfile.ZipFile, map_directory: str + ) -> VectorMap | None: + """Load a complete parquet map directory. Args: zip_file: Open ZipFile instance + map_directory: Top-level directory containing map parquet files Returns: - True if map was successfully loaded, False otherwise + The loaded map, or None if this directory cannot be loaded """ + prefix = f"{map_directory}/" + members = [name for name in zip_file.namelist() if name.startswith(prefix)] + if not members: + return None + try: with tempfile.TemporaryDirectory() as temp_dir: - # Find and extract map directories - map_dir = self._extract_map_directories(zip_file, temp_dir) - if map_dir is None: - logger.debug("No map_data or clipgt directories found") - return False - - # Load the map data - map_root = os.path.join(temp_dir, map_dir) - populate_vector_map(self._map, map_root) - return True + zip_file.extractall(temp_dir, members) + map_root = os.path.join(temp_dir, map_directory) + vector_map = VectorMap(map_id=f"alpasim_usdz:{self.metadata.scene_id}") + populate_vector_map(vector_map, map_root) + if not vector_map.elements.get(MapElementType.ROAD_LANE): + logger.warning("Could not load map from %s: no road lanes", prefix) + return None + return vector_map except (FileNotFoundError, ValueError, AttributeError) as e: - logger.warning(f"Could not load clipgt map: {e}") - return False + logger.warning("Could not load map from %s: %s", prefix, e) + return None - def _load_xodr_map(self, zip_file: zipfile.ZipFile) -> bool: + def _load_xodr_map(self, zip_file: zipfile.ZipFile) -> VectorMap | None: """Load map from XODR file. Args: zip_file: Open ZipFile instance Returns: - True if map was successfully loaded, False otherwise + The loaded map, or None if the archive has no usable XODR map """ try: # Open XODR file @@ -283,33 +314,14 @@ def _load_xodr_map(self, zip_file: zipfile.ZipFile) -> bool: t_xodr_enu_to_sim = self._get_xodr_transform(zip_file, xodr_xml) # Load the XODR map + vector_map = VectorMap(map_id=f"alpasim_usdz:{self.metadata.scene_id}") populate_vector_map_from_xodr( - self._map, xodr_xml, t_xodr_enu_to_sim=t_xodr_enu_to_sim + vector_map, xodr_xml, t_xodr_enu_to_sim=t_xodr_enu_to_sim ) - return True + return vector_map except (KeyError, FileNotFoundError) as e: logger.debug(f"Could not load XODR map: {e}") - return False - - def _extract_map_directories( - self, zip_file: zipfile.ZipFile, temp_dir: str - ) -> str | None: - """Extract map_data or clipgt directories from the zip file. - - Args: - zip_file: Open ZipFile instance - temp_dir: Temporary directory to extract files to - - Returns: - Name of the extracted directory or None if not found - """ - map_dir = None - for file_name in zip_file.namelist(): - if file_name.startswith(("map_data/", "clipgt/")): - zip_file.extract(file_name, temp_dir) - if map_dir is None: - map_dir = file_name.split("/")[0] - return map_dir + return None def _get_xodr_transform( self, zip_file: zipfile.ZipFile, xodr_xml: str @@ -371,6 +383,15 @@ def _get_xodr_transform( f"This will result in misaligned map and trajectory data. Error: {e}" ) from e + def _snap_map_z(self) -> None: + """Align FastMap geometry with the artifact's ground mesh.""" + assert self._map is not None + logger.info("Snapping FastMap geometry to the ground mesh...") + with zipfile.ZipFile(self.source, "r") as zip_file: + mesh_bytes = zip_file.read("mesh_ground.ply") + vertices, _ = load_mesh_vf(mesh_bytes) + snap_vector_map_to_ground(self._map, vertices) + def _finalize_map(self) -> None: """Finalize the loaded map by setting up data structures.""" self._map.__post_init__() diff --git a/src/utils/alpasim_utils/ground_snap.py b/src/utils/alpasim_utils/ground_snap.py new file mode 100644 index 00000000..2ae51150 --- /dev/null +++ b/src/utils/alpasim_utils/ground_snap.py @@ -0,0 +1,61 @@ +# SPDX-License-Identifier: Apache-2.0 +# Copyright (c) 2026 NVIDIA Corporation + +"""Align vector-map geometry with an AlpaSim ground mesh.""" + +import logging + +import numpy as np +from scipy.spatial import cKDTree +from trajdata.maps import VectorMap +from trajdata.maps.vec_map_elements import RoadEdge, RoadLane, WaitLine + +logger = logging.getLogger(__name__) + + +def snap_vector_map_to_ground( + vector_map: VectorMap, ground_mesh_vertices: np.ndarray +) -> None: + """Snap supported vector-map polylines to the ground mesh in place.""" + if ( + ground_mesh_vertices.ndim != 2 + or ground_mesh_vertices.shape[1] != 3 + or ground_mesh_vertices.shape[0] == 0 + ): + raise ValueError( + "ground_mesh_vertices must be a non-empty array with shape (N, 3), " + f"got {ground_mesh_vertices.shape}" + ) + + ground_tree = cKDTree(ground_mesh_vertices[:, :2]) + ground_z = ground_mesh_vertices[:, 2] + snapped_points = 0 + minimum_height = np.inf + maximum_height = -np.inf + + for element in vector_map.iter_elems(): + polylines: list[np.ndarray] = [] + if isinstance(element, RoadLane): + polylines.extend( + polyline.points + for polyline in (element.center, element.left_edge, element.right_edge) + if polyline is not None + ) + elif isinstance(element, (RoadEdge, WaitLine)): + if element.polyline is not None: + polylines.append(element.polyline.points) + for points in polylines: + if points.shape[0] == 0 or points.shape[1] < 3: + continue + _, indices = ground_tree.query(np.asarray(points[:, :2], dtype=np.float64)) + heights = ground_z[indices] + points[:, 2] = heights + minimum_height = min(minimum_height, float(heights.min())) + maximum_height = max(maximum_height, float(heights.max())) + snapped_points += points.shape[0] + + if snapped_points and vector_map.extent is not None: + vector_map.extent[2] = minimum_height + vector_map.extent[5] = maximum_height + + logger.info("Snapped %d map points to the ground mesh", snapped_points) diff --git a/src/physics/alpasim_physics/ply_io.py b/src/utils/alpasim_utils/ply_io.py similarity index 100% rename from src/physics/alpasim_physics/ply_io.py rename to src/utils/alpasim_utils/ply_io.py diff --git a/src/utils/alpasim_utils/telemetry/alpasim-runtime-dashboard.json b/src/utils/alpasim_utils/telemetry/alpasim-runtime-dashboard.json index 14733109..ca58b025 100644 --- a/src/utils/alpasim_utils/telemetry/alpasim-runtime-dashboard.json +++ b/src/utils/alpasim_utils/telemetry/alpasim-runtime-dashboard.json @@ -92,25 +92,6 @@ "value": "$__all" } }, - { - "type": "query", - "name": "tag", - "datasource": { - "type": "prometheus", - "uid": "Prometheus" - }, - "query": "label_values(alpasim_rpc_duration_seconds_count{run_uuid=~\"$run_uuid\"}, tag)", - "refresh": 1, - "multi": true, - "includeAll": true, - "allValue": ".*", - "hide": 2, - "current": { - "selected": true, - "text": "All", - "value": "$__all" - } - }, { "type": "query", "name": "node", @@ -185,7 +166,7 @@ }, { "type": "timeseries", - "title": "RPC duration p95", + "title": "RPC duration", "gridPos": { "x": 0, "y": 1, @@ -193,15 +174,126 @@ "h": 8 }, "targets": [ + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "min by (run_uuid, run_name, method) (sum by (run_uuid, run_name, method, worker_id) (rate(alpasim_rpc_duration_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",method=~\"run_controller_and_vehicle|drive|submit_egomotion_observation|submit_image_observation|submit_route|ground_intersection|render_rgb\"}[5m])) / sum by (run_uuid, run_name, method, worker_id) (rate(alpasim_rpc_duration_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",method=~\"run_controller_and_vehicle|drive|submit_egomotion_observation|submit_image_observation|submit_route|ground_intersection|render_rgb\"}[5m])))", + "legendFormat": "{{method}} min", + "refId": "B" + }, + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "avg by (run_uuid, run_name, method) (sum by (run_uuid, run_name, method, worker_id) (rate(alpasim_rpc_duration_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",method=~\"run_controller_and_vehicle|drive|submit_egomotion_observation|submit_image_observation|submit_route|ground_intersection|render_rgb\"}[5m])) / sum by (run_uuid, run_name, method, worker_id) (rate(alpasim_rpc_duration_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",method=~\"run_controller_and_vehicle|drive|submit_egomotion_observation|submit_image_observation|submit_route|ground_intersection|render_rgb\"}[5m])))", + "legendFormat": "{{method}} avg", + "refId": "A" + }, + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "quantile by (run_uuid, run_name, method) (0.90, sum by (run_uuid, run_name, method, worker_id) (rate(alpasim_rpc_duration_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",method=~\"run_controller_and_vehicle|drive|submit_egomotion_observation|submit_image_observation|submit_route|ground_intersection|render_rgb\"}[5m])) / sum by (run_uuid, run_name, method, worker_id) (rate(alpasim_rpc_duration_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",method=~\"run_controller_and_vehicle|drive|submit_egomotion_observation|submit_image_observation|submit_route|ground_intersection|render_rgb\"}[5m])))", + "legendFormat": "{{method}} p90", + "refId": "D" + }, + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "max by (run_uuid, run_name, method) (sum by (run_uuid, run_name, method, worker_id) (rate(alpasim_rpc_duration_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",method=~\"run_controller_and_vehicle|drive|submit_egomotion_observation|submit_image_observation|submit_route|ground_intersection|render_rgb\"}[5m])) / sum by (run_uuid, run_name, method, worker_id) (rate(alpasim_rpc_duration_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",method=~\"run_controller_and_vehicle|drive|submit_egomotion_observation|submit_image_observation|submit_route|ground_intersection|render_rgb\"}[5m])))", + "legendFormat": "{{method}} max", + "refId": "C" + }, { "datasource": { "type": "prometheus", "uid": "Prometheus" }, "expr": "alpasim:rpc_duration_seconds:p95{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}", - "legendFormat": "p95 {{method}}" + "legendFormat": "{{method}} pooled event p95", + "refId": "E" } - ] + ], + "fieldConfig": { + "defaults": { + "unit": "s" + }, + "overrides": [ + { + "matcher": { + "id": "byFrameRefID", + "options": "B" + }, + "properties": [ + { + "id": "custom.lineWidth", + "value": 1 + }, + { + "id": "custom.lineStyle", + "value": { + "dash": [ + 2, + 4 + ], + "fill": "dash" + } + } + ] + }, + { + "matcher": { + "id": "byFrameRefID", + "options": "C" + }, + "properties": [ + { + "id": "custom.lineWidth", + "value": 1 + }, + { + "id": "custom.lineStyle", + "value": { + "dash": [ + 10, + 10 + ], + "fill": "dash" + } + } + ] + }, + { + "matcher": { + "id": "byFrameRefID", + "options": "D" + }, + "properties": [ + { + "id": "custom.lineWidth", + "value": 1 + }, + { + "id": "custom.lineStyle", + "value": { + "dash": [ + 8, + 4 + ], + "fill": "dash" + } + } + ] + } + ] + }, + "description": "Per-worker five-minute event mean summarized by method as min, equal-worker average, worker p90, and max, plus the solid p95 pooled across all RPC events." }, { "type": "histogram", @@ -245,7 +337,7 @@ }, { "type": "timeseries", - "title": "RPC blocking p95", + "title": "RPC blocking duration", "gridPos": { "x": 6, "y": 33, @@ -253,15 +345,126 @@ "h": 8 }, "targets": [ + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "min by (run_uuid, run_name, method) (sum by (run_uuid, run_name, method, worker_id) (rate(alpasim_rpc_blocking_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",method=~\"run_controller_and_vehicle|drive|submit_egomotion_observation|submit_image_observation|submit_route|ground_intersection|render_rgb\"}[5m])) / sum by (run_uuid, run_name, method, worker_id) (rate(alpasim_rpc_blocking_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",method=~\"run_controller_and_vehicle|drive|submit_egomotion_observation|submit_image_observation|submit_route|ground_intersection|render_rgb\"}[5m])))", + "legendFormat": "{{method}} min", + "refId": "B" + }, + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "avg by (run_uuid, run_name, method) (sum by (run_uuid, run_name, method, worker_id) (rate(alpasim_rpc_blocking_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",method=~\"run_controller_and_vehicle|drive|submit_egomotion_observation|submit_image_observation|submit_route|ground_intersection|render_rgb\"}[5m])) / sum by (run_uuid, run_name, method, worker_id) (rate(alpasim_rpc_blocking_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",method=~\"run_controller_and_vehicle|drive|submit_egomotion_observation|submit_image_observation|submit_route|ground_intersection|render_rgb\"}[5m])))", + "legendFormat": "{{method}} avg", + "refId": "A" + }, + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "quantile by (run_uuid, run_name, method) (0.90, sum by (run_uuid, run_name, method, worker_id) (rate(alpasim_rpc_blocking_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",method=~\"run_controller_and_vehicle|drive|submit_egomotion_observation|submit_image_observation|submit_route|ground_intersection|render_rgb\"}[5m])) / sum by (run_uuid, run_name, method, worker_id) (rate(alpasim_rpc_blocking_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",method=~\"run_controller_and_vehicle|drive|submit_egomotion_observation|submit_image_observation|submit_route|ground_intersection|render_rgb\"}[5m])))", + "legendFormat": "{{method}} p90", + "refId": "D" + }, + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "max by (run_uuid, run_name, method) (sum by (run_uuid, run_name, method, worker_id) (rate(alpasim_rpc_blocking_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",method=~\"run_controller_and_vehicle|drive|submit_egomotion_observation|submit_image_observation|submit_route|ground_intersection|render_rgb\"}[5m])) / sum by (run_uuid, run_name, method, worker_id) (rate(alpasim_rpc_blocking_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",method=~\"run_controller_and_vehicle|drive|submit_egomotion_observation|submit_image_observation|submit_route|ground_intersection|render_rgb\"}[5m])))", + "legendFormat": "{{method}} max", + "refId": "C" + }, { "datasource": { "type": "prometheus", "uid": "Prometheus" }, "expr": "alpasim:rpc_blocking_seconds:p95{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}", - "legendFormat": "p95 {{method}}" + "legendFormat": "{{method}} pooled event p95", + "refId": "E" } - ] + ], + "fieldConfig": { + "defaults": { + "unit": "s" + }, + "overrides": [ + { + "matcher": { + "id": "byFrameRefID", + "options": "B" + }, + "properties": [ + { + "id": "custom.lineWidth", + "value": 1 + }, + { + "id": "custom.lineStyle", + "value": { + "dash": [ + 2, + 4 + ], + "fill": "dash" + } + } + ] + }, + { + "matcher": { + "id": "byFrameRefID", + "options": "C" + }, + "properties": [ + { + "id": "custom.lineWidth", + "value": 1 + }, + { + "id": "custom.lineStyle", + "value": { + "dash": [ + 10, + 10 + ], + "fill": "dash" + } + } + ] + }, + { + "matcher": { + "id": "byFrameRefID", + "options": "D" + }, + "properties": [ + { + "id": "custom.lineWidth", + "value": 1 + }, + { + "id": "custom.lineStyle", + "value": { + "dash": [ + 8, + 4 + ], + "fill": "dash" + } + } + ] + } + ] + }, + "description": "Per-worker five-minute event mean summarized by method as min, equal-worker average, worker p90, and max, plus the solid p95 pooled across all blocking events." }, { "type": "timeseries", @@ -278,7 +481,7 @@ "type": "prometheus", "uid": "Prometheus" }, - "expr": "sum by (method) (rate(alpasim_rpc_duration_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",worker_id=~\"$worker_id\",method=~\"$method\",tag=~\"$tag\"}[1m]))", + "expr": "sum by (method) (rate(alpasim_rpc_duration_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",worker_id=~\"$worker_id\",method=~\"$method\"}[1m]))", "legendFormat": "{{method}}" } ] @@ -316,8 +519,8 @@ "type": "prometheus", "uid": "Prometheus" }, - "expr": "avg_over_time(alpasim:rpc_queue_depth_at_start_latest:max{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[10m])", - "legendFormat": "{{service}} max 10m avg", + "expr": "avg_over_time(alpasim:rpc_queue_depth_at_start_latest:max{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])", + "legendFormat": "{{service}} max 5m avg", "refId": "C" }, { @@ -325,8 +528,8 @@ "type": "prometheus", "uid": "Prometheus" }, - "expr": "avg_over_time(alpasim:rpc_queue_depth_at_start_latest:min{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[10m])", - "legendFormat": "{{service}} min 10m avg", + "expr": "avg_over_time(alpasim:rpc_queue_depth_at_start_latest:min{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])", + "legendFormat": "{{service}} min 5m avg", "refId": "D" } ], @@ -500,23 +703,321 @@ }, { "matcher": { - "id": "byRegexp", - "options": "^video_model min.*" + "id": "byRegexp", + "options": "^video_model min.*" + }, + "properties": [ + { + "id": "color", + "value": { + "fixedColor": "light-red", + "mode": "fixed" + } + } + ] + }, + { + "matcher": { + "id": "byRegexp", + "options": ".* (max|min)$" + }, + "properties": [ + { + "id": "custom.lineWidth", + "value": 1 + }, + { + "id": "custom.lineStyle", + "value": { + "dash": [ + 10, + 10 + ], + "fill": "dash" + } + }, + { + "id": "custom.showPoints", + "value": "never" + } + ] + }, + { + "matcher": { + "id": "byRegexp", + "options": ".* 5m avg$" + }, + "properties": [ + { + "id": "custom.lineWidth", + "value": 2 + }, + { + "id": "custom.showPoints", + "value": "never" + } + ] + } + ] + } + }, + { + "type": "histogram", + "title": "RPC queue depth histogram", + "gridPos": { + "x": 6, + "y": 9, + "w": 6, + "h": 8 + }, + "targets": [ + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "alpasim:rpc_queue_depth_at_start_latest:max{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}", + "legendFormat": "{{service}} max" + } + ], + "options": { + "bucketCount": 30, + "combine": false, + "legend": { + "displayMode": "list", + "placement": "bottom", + "showLegend": true + }, + "tooltip": { + "mode": "single", + "sort": "none" + } + }, + "fieldConfig": { + "defaults": { + "unit": "short" + }, + "overrides": [] + } + }, + { + "type": "timeseries", + "title": "Rollout duration", + "gridPos": { + "x": 12, + "y": 9, + "w": 6, + "h": 8 + }, + "targets": [ + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "min by (run_uuid, run_name) (sum by (run_uuid, run_name, worker_id) (rate(alpasim_rollout_duration_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])) / sum by (run_uuid, run_name, worker_id) (rate(alpasim_rollout_duration_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])))", + "legendFormat": "{{run_name}} min", + "refId": "B" + }, + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "avg by (run_uuid, run_name) (sum by (run_uuid, run_name, worker_id) (rate(alpasim_rollout_duration_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])) / sum by (run_uuid, run_name, worker_id) (rate(alpasim_rollout_duration_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])))", + "legendFormat": "{{run_name}} avg", + "refId": "A" + }, + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "quantile by (run_uuid, run_name) (0.90, sum by (run_uuid, run_name, worker_id) (rate(alpasim_rollout_duration_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])) / sum by (run_uuid, run_name, worker_id) (rate(alpasim_rollout_duration_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])))", + "legendFormat": "{{run_name}} p90", + "refId": "D" + }, + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "max by (run_uuid, run_name) (sum by (run_uuid, run_name, worker_id) (rate(alpasim_rollout_duration_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])) / sum by (run_uuid, run_name, worker_id) (rate(alpasim_rollout_duration_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])))", + "legendFormat": "{{run_name}} max", + "refId": "C" + }, + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "alpasim:rollout_duration_seconds:p95{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}", + "legendFormat": "{{run_name}} pooled event p95", + "refId": "E" + } + ], + "fieldConfig": { + "defaults": { + "unit": "s" + }, + "overrides": [ + { + "matcher": { + "id": "byFrameRefID", + "options": "B" + }, + "properties": [ + { + "id": "custom.lineWidth", + "value": 1 + }, + { + "id": "custom.lineStyle", + "value": { + "dash": [ + 2, + 4 + ], + "fill": "dash" + } + } + ] + }, + { + "matcher": { + "id": "byFrameRefID", + "options": "C" + }, + "properties": [ + { + "id": "custom.lineWidth", + "value": 1 + }, + { + "id": "custom.lineStyle", + "value": { + "dash": [ + 10, + 10 + ], + "fill": "dash" + } + } + ] + }, + { + "matcher": { + "id": "byFrameRefID", + "options": "D" + }, + "properties": [ + { + "id": "custom.lineWidth", + "value": 1 + }, + { + "id": "custom.lineStyle", + "value": { + "dash": [ + 8, + 4 + ], + "fill": "dash" + } + } + ] + } + ] + }, + "description": "Per-worker five-minute event mean rollout duration summarized as min, equal-worker average, worker p90, and max, plus the solid p95 pooled across all events." + }, + { + "type": "timeseries", + "title": "Step duration", + "gridPos": { + "x": 18, + "y": 9, + "w": 6, + "h": 8 + }, + "targets": [ + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "min by (run_uuid, run_name) (sum by (run_uuid, run_name, worker_id) (rate(alpasim_step_duration_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])) / sum by (run_uuid, run_name, worker_id) (rate(alpasim_step_duration_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])))", + "legendFormat": "{{run_name}} min", + "refId": "B" + }, + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "avg by (run_uuid, run_name) (sum by (run_uuid, run_name, worker_id) (rate(alpasim_step_duration_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])) / sum by (run_uuid, run_name, worker_id) (rate(alpasim_step_duration_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])))", + "legendFormat": "{{run_name}} avg", + "refId": "A" + }, + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "quantile by (run_uuid, run_name) (0.90, sum by (run_uuid, run_name, worker_id) (rate(alpasim_step_duration_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])) / sum by (run_uuid, run_name, worker_id) (rate(alpasim_step_duration_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])))", + "legendFormat": "{{run_name}} p90", + "refId": "D" + }, + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "max by (run_uuid, run_name) (sum by (run_uuid, run_name, worker_id) (rate(alpasim_step_duration_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])) / sum by (run_uuid, run_name, worker_id) (rate(alpasim_step_duration_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])))", + "legendFormat": "{{run_name}} max", + "refId": "C" + }, + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "alpasim:step_duration_seconds:p95{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}", + "legendFormat": "{{run_name}} pooled event p95", + "refId": "E" + } + ], + "fieldConfig": { + "defaults": { + "unit": "s" + }, + "overrides": [ + { + "matcher": { + "id": "byFrameRefID", + "options": "B" }, "properties": [ { - "id": "color", + "id": "custom.lineWidth", + "value": 1 + }, + { + "id": "custom.lineStyle", "value": { - "fixedColor": "light-red", - "mode": "fixed" + "dash": [ + 2, + 4 + ], + "fill": "dash" } } ] }, { "matcher": { - "id": "byRegexp", - "options": ".* (max|min)$" + "id": "byFrameRefID", + "options": "C" }, "properties": [ { @@ -532,110 +1033,34 @@ ], "fill": "dash" } - }, - { - "id": "custom.showPoints", - "value": "never" } ] }, { "matcher": { - "id": "byRegexp", - "options": ".* 10m avg$" + "id": "byFrameRefID", + "options": "D" }, "properties": [ { "id": "custom.lineWidth", - "value": 2 + "value": 1 }, { - "id": "custom.showPoints", - "value": "never" + "id": "custom.lineStyle", + "value": { + "dash": [ + 8, + 4 + ], + "fill": "dash" + } } ] } ] - } - }, - { - "type": "histogram", - "title": "RPC queue depth histogram", - "gridPos": { - "x": 6, - "y": 9, - "w": 6, - "h": 8 - }, - "targets": [ - { - "datasource": { - "type": "prometheus", - "uid": "Prometheus" - }, - "expr": "alpasim:rpc_queue_depth_at_start_latest:max{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}", - "legendFormat": "{{service}} max" - } - ], - "options": { - "bucketCount": 30, - "combine": false, - "legend": { - "displayMode": "list", - "placement": "bottom", - "showLegend": true - }, - "tooltip": { - "mode": "single", - "sort": "none" - } - }, - "fieldConfig": { - "defaults": { - "unit": "short" - }, - "overrides": [] - } - }, - { - "type": "timeseries", - "title": "Rollout duration p95", - "gridPos": { - "x": 12, - "y": 9, - "w": 6, - "h": 8 - }, - "targets": [ - { - "datasource": { - "type": "prometheus", - "uid": "Prometheus" - }, - "expr": "alpasim:rollout_duration_seconds:p95{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}", - "legendFormat": "p95" - } - ] - }, - { - "type": "timeseries", - "title": "Step duration p95", - "gridPos": { - "x": 18, - "y": 9, - "w": 6, - "h": 8 }, - "targets": [ - { - "datasource": { - "type": "prometheus", - "uid": "Prometheus" - }, - "expr": "alpasim:step_duration_seconds:p95{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}", - "legendFormat": "p95" - } - ] + "description": "Per-worker five-minute event mean step duration summarized as min, equal-worker average, worker p90, and max, plus the solid p95 pooled across all events." }, { "type": "timeseries", @@ -661,8 +1086,8 @@ "type": "prometheus", "uid": "Prometheus" }, - "expr": "avg_over_time(alpasim:process_cpu_utilization_percent:max_by_group:rate30s{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[10m])", - "legendFormat": "10m avg {{groupname}}", + "expr": "avg_over_time(alpasim:process_cpu_utilization_percent:max_by_group:rate30s{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])", + "legendFormat": "5m avg {{groupname}}", "refId": "B" } ], @@ -877,8 +1302,8 @@ "type": "prometheus", "uid": "Prometheus" }, - "expr": "avg_over_time(alpasim:gpu_utilization_percent:avg{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[10m])", - "legendFormat": "gpu {{gpu}} % 10m avg", + "expr": "avg_over_time(alpasim:gpu_utilization_percent:avg{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\"}[5m])", + "legendFormat": "gpu {{gpu}} % 5m avg", "refId": "B" } ], @@ -1517,7 +1942,7 @@ }, { "type": "row", - "title": "Detailed telemetry", + "title": "Renderer scheduling", "collapsed": false, "gridPos": { "x": 0, @@ -1529,30 +1954,170 @@ }, { "type": "timeseries", - "title": "Rollout duration p95 by worker", + "title": "Renderer active rollouts", + "gridPos": { + "x": 0, + "y": 58, + "w": 6, + "h": 8 + }, + "targets": [ + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "sum by (run_uuid, run_name) (alpasim_renderer_active_rollouts{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",worker_id=~\"$worker_id\"})", + "legendFormat": "{{run_name}} active" + } + ], + "fieldConfig": { + "defaults": { + "unit": "short", + "min": 0 + }, + "overrides": [] + }, + "description": "Total executing renderer-backed rollouts across selected workers." + }, + { + "type": "timeseries", + "title": "Rollout starts by dispatch class", + "gridPos": { + "x": 6, + "y": 58, + "w": 6, + "h": 8 + }, + "targets": [ + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "sum by (run_uuid, run_name, kind) (rate(alpasim_renderer_rollouts_started_total{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",worker_id=~\"$worker_id\"}[5m]))", + "legendFormat": "{{kind}}" + } + ], + "fieldConfig": { + "defaults": { + "min": 0 + }, + "overrides": [] + }, + "description": "Five-minute rollout-start rate split by scheduler decision." + }, + { + "type": "timeseries", + "title": "Scene replication effectiveness", "gridPos": { "x": 12, "y": 58, + "w": 6, + "h": 8 + }, + "targets": [ + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "sum by (run_uuid, run_name) (rate(alpasim_renderer_rollouts_started_total{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",worker_id=~\"$worker_id\",kind=\"cold_replica\"}[5m])) / sum by (run_uuid, run_name) (rate(alpasim_renderer_rollouts_started_total{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",worker_id=~\"$worker_id\",kind=\"cold_initial\"}[5m]))", + "legendFormat": "cold replica / initial" + } + ], + "fieldConfig": { + "defaults": { + "unit": "percentunit", + "min": 0 + }, + "overrides": [] + }, + "description": "Cold-replica overhead relative to initial scene loads." + }, + { + "type": "timeseries", + "title": "Scheduler wait p95", + "gridPos": { + "x": 18, + "y": 58, + "w": 6, + "h": 8 + }, + "targets": [ + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "histogram_quantile(0.95, sum by (run_uuid, run_name, le, kind) (rate(alpasim_renderer_scheduler_wait_seconds_bucket{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",worker_id=~\"$worker_id\"}[5m])))", + "legendFormat": "{{kind}}" + } + ], + "fieldConfig": { + "defaults": { + "unit": "s", + "min": 0 + }, + "overrides": [] + }, + "description": "Five-minute p95 time from scheduler insertion to successful renderer assignment." + }, + { + "type": "row", + "title": "Detailed telemetry", + "collapsed": false, + "gridPos": { + "x": 0, + "y": 66, + "w": 24, + "h": 1 + }, + "panels": [] + }, + { + "type": "timeseries", + "title": "Rollout duration by worker", + "gridPos": { + "x": 12, + "y": 67, "w": 12, "h": 8 }, "targets": [ + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "sum by (run_uuid, run_name, worker_id) (rate(alpasim_rollout_duration_seconds_sum{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",worker_id=~\"$worker_id\"}[5m])) / sum by (run_uuid, run_name, worker_id) (rate(alpasim_rollout_duration_seconds_count{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",worker_id=~\"$worker_id\"}[5m]))", + "legendFormat": "worker {{worker_id}} mean", + "refId": "A" + }, { "datasource": { "type": "prometheus", "uid": "Prometheus" }, "expr": "alpasim:rollout_duration_seconds:p95_by_worker{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",worker_id=~\"$worker_id\"}", - "legendFormat": "worker {{worker_id}}" + "legendFormat": "worker {{worker_id}} event p95", + "refId": "E" } - ] + ], + "fieldConfig": { + "defaults": { + "unit": "s" + }, + "overrides": [] + }, + "description": "Five-minute event mean and event p95 for each AlpaSim worker." }, { "type": "timeseries", "title": "Process top memory", "gridPos": { "x": 0, - "y": 66, + "y": 75, "w": 12, "h": 8 }, @@ -1573,7 +2138,7 @@ "collapsed": false, "gridPos": { "x": 0, - "y": 74, + "y": 83, "w": 24, "h": 1 }, @@ -1584,7 +2149,7 @@ "title": "Node CPU utilization", "gridPos": { "x": 0, - "y": 75, + "y": 84, "w": 8, "h": 8 }, @@ -1604,7 +2169,7 @@ "title": "Host memory available", "gridPos": { "x": 8, - "y": 75, + "y": 84, "w": 8, "h": 8 }, @@ -1644,7 +2209,7 @@ "title": "GPU utilization by node", "gridPos": { "x": 0, - "y": 83, + "y": 92, "w": 8, "h": 8 }, @@ -1664,7 +2229,7 @@ "title": "GPU memory pressure", "gridPos": { "x": 8, - "y": 83, + "y": 92, "w": 8, "h": 8 }, @@ -1679,12 +2244,32 @@ } ] }, + { + "type": "timeseries", + "title": "GPU SM active by node", + "gridPos": { + "x": 0, + "y": 100, + "w": 8, + "h": 8 + }, + "targets": [ + { + "datasource": { + "type": "prometheus", + "uid": "Prometheus" + }, + "expr": "100 * DCGM_FI_PROF_SM_ACTIVE{run_uuid=~\"$run_uuid\",run_name=~\"$run_name\",node=~\"$node\",gpu=~\"$gpu\"}", + "legendFormat": "{{node}} gpu {{gpu}} %" + } + ] + }, { "type": "timeseries", "title": "Process exporter scrape duration", "gridPos": { "x": 16, - "y": 83, + "y": 92, "w": 8, "h": 8 }, @@ -1704,7 +2289,7 @@ "title": "GC time spent rate", "gridPos": { "x": 0, - "y": 91, + "y": 108, "w": 8, "h": 8 }, @@ -1724,7 +2309,7 @@ "title": "GC worst pause so far", "gridPos": { "x": 8, - "y": 91, + "y": 108, "w": 8, "h": 8 }, @@ -1744,7 +2329,7 @@ "title": "GC collection rate", "gridPos": { "x": 16, - "y": 91, + "y": 108, "w": 8, "h": 8 }, diff --git a/src/utils/alpasim_utils/telemetry/metrics_plot_recording_rules.yml b/src/utils/alpasim_utils/telemetry/metrics_plot_recording_rules.yml index a3e35313..16e32a50 100644 --- a/src/utils/alpasim_utils/telemetry/metrics_plot_recording_rules.yml +++ b/src/utils/alpasim_utils/telemetry/metrics_plot_recording_rules.yml @@ -32,19 +32,19 @@ groups: - record: alpasim:driver_drive_rpc_duration_seconds_bucket:sum expr: >- sum by (run_uuid, run_name, le) - (alpasim_rpc_duration_seconds_bucket{service="driver",method="drive",tag="default"}) + (alpasim_rpc_duration_seconds_bucket{service="driver",method="drive"}) - record: alpasim:driver_drive_rpc_duration_seconds_bucket:rate1m expr: >- sum by (run_uuid, run_name, le) - (rate(alpasim_rpc_duration_seconds_bucket{service="driver",method="drive",tag="default"}[1m])) + (rate(alpasim_rpc_duration_seconds_bucket{service="driver",method="drive"}[1m])) - record: alpasim:nre_render_rpc_duration_seconds_bucket:sum expr: >- sum by (run_uuid, run_name, le) - (alpasim_rpc_duration_seconds_bucket{service="sensorsim",method=~"render_rgb|batch_render_rgb|render_aggregated",tag="default"}) + (alpasim_rpc_duration_seconds_bucket{service="sensorsim",method=~"render_rgb|batch_render_rgb|render_aggregated"}) - record: alpasim:nre_render_rpc_duration_seconds_bucket:rate1m expr: >- sum by (run_uuid, run_name, le) - (rate(alpasim_rpc_duration_seconds_bucket{service="sensorsim",method=~"render_rgb|batch_render_rgb|render_aggregated",tag="default"}[1m])) + (rate(alpasim_rpc_duration_seconds_bucket{service="sensorsim",method=~"render_rgb|batch_render_rgb|render_aggregated"}[1m])) - record: alpasim:rpc_duration_seconds:p95 expr: >- histogram_quantile(0.95, @@ -91,19 +91,19 @@ groups: - record: alpasim:simulation_rollouts_completed:sum expr: >- sum by (run_uuid, run_name) - (alpasim_simulation_rollouts_completed_total) + (alpasim_rollouts_total) - record: alpasim:simulation_seconds_per_rollout:avg expr: >- ( max by (run_uuid, run_name) (alpasim_simulation_elapsed_seconds) / sum by (run_uuid, run_name) - (alpasim_simulation_rollouts_completed_total) + (alpasim_rollouts_total) ) and on (run_uuid, run_name) ( sum by (run_uuid, run_name) - (alpasim_simulation_rollouts_completed_total) > 0 + (alpasim_rollouts_total) > 0 ) - record: alpasim:simulation_seconds_per_rollout:rate5m expr: >- @@ -111,12 +111,12 @@ groups: max by (run_uuid, run_name) (increase(alpasim_simulation_elapsed_seconds[5m])) / sum by (run_uuid, run_name) - (increase(alpasim_simulation_rollouts_completed_total[5m])) + (increase(alpasim_rollouts_total[5m])) ) and on (run_uuid, run_name) ( sum by (run_uuid, run_name) - (increase(alpasim_simulation_rollouts_completed_total[5m])) > 0 + (increase(alpasim_rollouts_total[5m])) > 0 ) - record: alpasim:process_cpu_utilization_percent:rate30s expr: >- diff --git a/src/utils/tests/test_artifact.py b/src/utils/tests/test_artifact.py index 4bbe980d..48238f85 100644 --- a/src/utils/tests/test_artifact.py +++ b/src/utils/tests/test_artifact.py @@ -1,7 +1,34 @@ # SPDX-License-Identifier: Apache-2.0 -# Copyright (c) 2025 NVIDIA Corporation +# Copyright (c) 2025-2026 NVIDIA Corporation +import zipfile +from types import SimpleNamespace + +import numpy as np +import pytest +from alpasim_utils import artifact as artifact_module from alpasim_utils.artifact import Artifact +from trajdata.maps import VectorMap +from trajdata.maps.vec_map_elements import Polyline, RoadLane + + +def _artifact_with_metadata(path) -> Artifact: + artifact = Artifact(source=str(path)) + artifact._metadata = SimpleNamespace(scene_id="clipgt-test") + return artifact + + +def _write_map_directory(archive: zipfile.ZipFile, directory: str) -> None: + archive.writestr(f"{directory}/lane.parquet", b"") + + +def _add_test_lane(vector_map: VectorMap) -> None: + vector_map.add_map_element( + RoadLane( + id="lane_0", + center=Polyline(np.array([[0.0, 0.0, 0.0], [1.0, 0.0, 0.0]])), + ) + ) def test_artifact_no_map(): @@ -10,6 +37,7 @@ def test_artifact_no_map(): # expect that the map is None (no exceptions) assert artifact.map is None + assert artifact.map_source is None def test_xodr_artifact(): @@ -18,7 +46,138 @@ def test_xodr_artifact(): # expect that the map is not None (no exceptions) assert artifact.map is not None + assert artifact.map_source == "xodr" assert ( artifact.map.map_id == "alpasim_usdz:clipgt-026d6a39-bd8f-4175-bc61-fe50ed0403a3" ) + + +def test_loads_fastmap_directory(tmp_path, monkeypatch) -> None: + path = tmp_path / "artifact.usdz" + with zipfile.ZipFile(path, "w") as archive: + _write_map_directory(archive, "fastmap") + + loaded_roots = [] + + def populate(vector_map, map_root): + loaded_roots.append(map_root) + _add_test_lane(vector_map) + + monkeypatch.setattr(artifact_module, "populate_vector_map", populate) + artifact = _artifact_with_metadata(path) + + with zipfile.ZipFile(path) as archive: + vector_map = artifact._load_parquet_map(archive, "fastmap") + + assert vector_map is not None + assert vector_map.map_id == "alpasim_usdz:clipgt-test" + assert len(loaded_roots) == 1 + assert loaded_roots[0].endswith("/fastmap") + + +def test_fastmap_precedes_xodr_and_snaps_to_ground(tmp_path, monkeypatch) -> None: + path = tmp_path / "artifact.usdz" + with zipfile.ZipFile(path, "w"): + pass + artifact = _artifact_with_metadata(path) + calls = [] + + def load_parquet(_archive, directory): + calls.append(directory) + if directory == "fastmap": + return VectorMap(map_id="alpasim_usdz:clipgt-test") + return None + + monkeypatch.setattr(artifact, "_load_parquet_map", load_parquet) + monkeypatch.setattr( + artifact, + "_load_xodr_map", + lambda _archive: pytest.fail("XODR should not be loaded"), + ) + monkeypatch.setattr(artifact, "_snap_map_z", lambda: calls.append("snap")) + monkeypatch.setattr(artifact, "_finalize_map", lambda: None) + + assert artifact.map is not None + assert calls == ["map_data", "clipgt", "fastmap", "snap"] + assert artifact.map_source == "fastmap" + + +def test_complete_map_data_precedes_fastmap(tmp_path, monkeypatch) -> None: + path = tmp_path / "artifact.usdz" + with zipfile.ZipFile(path, "w"): + pass + artifact = _artifact_with_metadata(path) + calls = [] + + def load_parquet(_archive, directory): + calls.append(directory) + return VectorMap(map_id="alpasim_usdz:clipgt-test") + + monkeypatch.setattr(artifact, "_load_parquet_map", load_parquet) + monkeypatch.setattr( + artifact, + "_snap_map_z", + lambda: pytest.fail("preferred map must not be ground-snapped"), + ) + monkeypatch.setattr(artifact, "_finalize_map", lambda: None) + + assert artifact.map is not None + assert calls == ["map_data"] + assert artifact.map_source == "map_data" + + +def test_failed_map_source_does_not_leak_partial_state(tmp_path, monkeypatch) -> None: + path = tmp_path / "artifact.usdz" + with zipfile.ZipFile(path, "w") as archive: + _write_map_directory(archive, "map_data") + _write_map_directory(archive, "clipgt") + artifact = _artifact_with_metadata(path) + + def populate(vector_map, map_root): + if map_root.endswith("/map_data"): + vector_map.failed_source_marker = True + raise ValueError("broken map") + _add_test_lane(vector_map) + + monkeypatch.setattr(artifact_module, "populate_vector_map", populate) + monkeypatch.setattr(artifact, "_finalize_map", lambda: None) + + vector_map = artifact.map + + assert vector_map is not None + assert not hasattr(vector_map, "failed_source_marker") + assert artifact.map_source == "clipgt" + + +def test_empty_map_source_falls_back_to_fastmap(tmp_path, monkeypatch) -> None: + path = tmp_path / "artifact.usdz" + with zipfile.ZipFile(path, "w") as archive: + _write_map_directory(archive, "map_data") + _write_map_directory(archive, "fastmap") + artifact = _artifact_with_metadata(path) + calls = [] + + def populate(vector_map, map_root): + calls.append(map_root.rsplit("/", 1)[-1]) + if map_root.endswith("/fastmap"): + _add_test_lane(vector_map) + + monkeypatch.setattr(artifact_module, "populate_vector_map", populate) + monkeypatch.setattr(artifact, "_snap_map_z", lambda: calls.append("snap")) + monkeypatch.setattr(artifact, "_finalize_map", lambda: None) + + assert artifact.map is not None + assert calls == ["map_data", "fastmap", "snap"] + assert artifact.map_source == "fastmap" + + +def test_fastmap_requires_ground_mesh(tmp_path) -> None: + path = tmp_path / "artifact.usdz" + with zipfile.ZipFile(path, "w"): + pass + artifact = _artifact_with_metadata(path) + artifact._map = VectorMap(map_id="alpasim_usdz:clipgt-test") + + with pytest.raises(KeyError, match=r"mesh_ground\.ply"): + artifact._snap_map_z() diff --git a/src/utils/tests/test_ground_snap.py b/src/utils/tests/test_ground_snap.py new file mode 100644 index 00000000..23b6f66d --- /dev/null +++ b/src/utils/tests/test_ground_snap.py @@ -0,0 +1,77 @@ +# SPDX-License-Identifier: Apache-2.0 +# Copyright (c) 2026 NVIDIA Corporation + +import numpy as np +import pytest +from alpasim_utils.ground_snap import snap_vector_map_to_ground +from trajdata.maps.vec_map import VectorMap +from trajdata.maps.vec_map_elements import MapElementType, Polyline, RoadEdge, RoadLane + + +def _flat_mesh(z: float = 0.0, extent: float = 10.0) -> np.ndarray: + return np.array( + [ + [-extent, -extent, z], + [extent, -extent, z], + [extent, extent, z], + [-extent, extent, z], + [0.0, 0.0, z], + ], + dtype=np.float64, + ) + + +def test_snap_vector_map_to_ground_rejects_invalid_vertices() -> None: + vector_map = VectorMap(map_id="test:test") + + with pytest.raises(ValueError, match="shape"): + snap_vector_map_to_ground(vector_map, np.zeros((10, 2))) + with pytest.raises(ValueError, match="non-empty"): + snap_vector_map_to_ground(vector_map, np.zeros((0, 3))) + + +def test_snap_vector_map_to_ground_updates_lane_geometry() -> None: + vector_map = VectorMap(map_id="test:test") + vector_map.extent = np.array([-1.0, -1.0, -99.0, 1.0, 1.0, -99.0]) + lane = RoadLane( + id="lane_0", + center=Polyline( + np.array([[0.0, 0.0, -99.0], [1.0, 0.0, -99.0]], dtype=np.float64) + ), + left_edge=Polyline( + np.array([[0.0, 0.5, -99.0], [1.0, 0.5, -99.0]], dtype=np.float64) + ), + right_edge=Polyline( + np.array([[0.0, -0.5, -99.0], [1.0, -0.5, -99.0]], dtype=np.float64) + ), + ) + vector_map.elements[MapElementType.ROAD_LANE][lane.id] = lane + + snap_vector_map_to_ground(vector_map, _flat_mesh(z=1.0)) + + np.testing.assert_allclose(lane.center.points[:, 2], 1.0) + np.testing.assert_allclose(lane.left_edge.points[:, 2], 1.0) + np.testing.assert_allclose(lane.right_edge.points[:, 2], 1.0) + np.testing.assert_allclose(vector_map.extent[[2, 5]], 1.0) + + +def test_snap_vector_map_to_ground_uses_nearest_mesh_vertex() -> None: + vector_map = VectorMap(map_id="test:test") + edge = RoadEdge( + id="edge_0", + polyline=Polyline( + np.array( + [[0.1, 0.1, -50.0], [4.9, 0.1, -50.0], [0.1, 4.9, -50.0]], + dtype=np.float64, + ) + ), + ) + vector_map.elements[MapElementType.ROAD_EDGE][edge.id] = edge + vertices = np.array( + [[0.0, 0.0, 1.0], [5.0, 0.0, 2.0], [0.0, 5.0, 3.0]], + dtype=np.float64, + ) + + snap_vector_map_to_ground(vector_map, vertices) + + np.testing.assert_allclose(edge.polyline.points[:, 2], [1.0, 2.0, 3.0]) diff --git a/src/utils/tests/test_grpc_boundary_rs.py b/src/utils/tests/test_grpc_boundary_rs.py new file mode 100644 index 00000000..4a9395ec --- /dev/null +++ b/src/utils/tests/test_grpc_boundary_rs.py @@ -0,0 +1,152 @@ +# SPDX-License-Identifier: Apache-2.0 +# Copyright (c) 2026 NVIDIA Corporation + +"""Tests for gRPC-boundary helpers in the utils_rs extension.""" + +import numpy as np +import pytest + +from utils_rs import ( + build_drive_response_bytes, + pack_route_array, + pack_trajectory_arrays, +) + + +def _require_generated_common_pb2() -> object: + """Import generated common_pb2, skipping when protos have not been compiled.""" + common_pb2 = pytest.importorskip("alpasim_grpc.v0.common_pb2") + if not hasattr(common_pb2.Trajectory().poses, "add"): + pytest.skip("requires generated alpasim protobufs") + return common_pb2 + + +def _require_generated_egodriver_pb2() -> object: + """Import generated egodriver_pb2, skipping when protos have not been compiled.""" + egodriver_pb2 = pytest.importorskip("alpasim_grpc.v0.egodriver_pb2") + if not hasattr(egodriver_pb2.DriveResponse(), "ParseFromString"): + pytest.skip("requires generated alpasim protobufs") + return egodriver_pb2 + + +def test_build_drive_response_bytes_rejects_shape_mismatch() -> None: + """The native encoder rejects arrays that cannot map to trajectory rows.""" + xyz = np.zeros((2, 3), dtype=np.float32) + quat_wxyz = np.zeros((3, 4), dtype=np.float32) + dt_us = np.zeros((2,), dtype=np.int64) + + with pytest.raises(ValueError, match="mismatched leading dims"): + build_drive_response_bytes(1_000, xyz, quat_wxyz, dt_us) + + +def test_build_drive_response_bytes_matches_empty_generated_proto() -> None: + """An empty horizon leaves the trajectory field unset.""" + egodriver_pb2 = _require_generated_egodriver_pb2() + + payload = build_drive_response_bytes( + 1_000, + np.empty((0, 3), dtype=np.float32), + np.empty((0, 4), dtype=np.float32), + np.empty((0,), dtype=np.int64), + ) + + assert payload == egodriver_pb2.DriveResponse().SerializeToString( + deterministic=True + ) + + +def test_build_drive_response_bytes_matches_generated_proto_serialization() -> None: + """Native bytes match generated protobuf serialization exactly.""" + common_pb2 = _require_generated_common_pb2() + egodriver_pb2 = _require_generated_egodriver_pb2() + xyz = np.array( + [ + [1.25, 0.0, -3.5], + [-0.0, 5.0, 6.0], + [0.0, 0.0, 0.0], + ], + dtype=np.float32, + ) + quat_wxyz = np.array( + [ + [1.0, 0.0, 0.0, 0.0], + [0.0, 1.0, 0.0, -0.5], + [0.0, 0.0, 0.0, 0.0], + ], + dtype=np.float32, + ) + dt_us = np.array([0, 100_000, 200_000], dtype=np.int64) + + payload = build_drive_response_bytes(0, xyz, quat_wxyz, dt_us) + expected = egodriver_pb2.DriveResponse() + for dt_us_value, xyz_row, quat_row in zip(dt_us, xyz, quat_wxyz, strict=True): + pose_at_time = common_pb2.PoseAtTime(timestamp_us=int(dt_us_value)) + pose_at_time.pose.vec.x = float(xyz_row[0]) + pose_at_time.pose.vec.y = float(xyz_row[1]) + pose_at_time.pose.vec.z = float(xyz_row[2]) + pose_at_time.pose.quat.w = float(quat_row[0]) + pose_at_time.pose.quat.x = float(quat_row[1]) + pose_at_time.pose.quat.y = float(quat_row[2]) + pose_at_time.pose.quat.z = float(quat_row[3]) + expected.trajectory.poses.append(pose_at_time) + + assert payload == expected.SerializeToString(deterministic=True) + + +def test_pack_trajectory_arrays_sorts_and_preserves_pose_fields() -> None: + """Trajectory packing returns timestamp-sorted numeric arrays.""" + common_pb2 = _require_generated_common_pb2() + trajectory = common_pb2.Trajectory() + for timestamp_us, x in ((30, 3.0), (10, 1.0), (20, 2.0)): + pose_at_time = trajectory.poses.add() + pose_at_time.timestamp_us = timestamp_us + pose_at_time.pose.vec.x = x + pose_at_time.pose.vec.y = x + 0.5 + pose_at_time.pose.vec.z = x + 1.0 + pose_at_time.pose.quat.w = 1.0 + pose_at_time.pose.quat.x = x * 0.1 + + timestamps_us, xyz, quat_wxyz = pack_trajectory_arrays(trajectory) + + np.testing.assert_array_equal(timestamps_us, np.array([10, 20, 30], dtype=np.int64)) + np.testing.assert_allclose( + xyz, + np.array( + [ + [1.0, 1.5, 2.0], + [2.0, 2.5, 3.0], + [3.0, 3.5, 4.0], + ], + dtype=np.float32, + ), + ) + np.testing.assert_allclose( + quat_wxyz, + np.array( + [ + [1.0, 0.1, 0.0, 0.0], + [1.0, 0.2, 0.0, 0.0], + [1.0, 0.3, 0.0, 0.0], + ], + dtype=np.float32, + ), + ) + + +def test_pack_route_array_preserves_timestamp_and_waypoints() -> None: + """Route packing returns the route timestamp plus waypoint xyz rows.""" + egodriver_pb2 = _require_generated_egodriver_pb2() + route = egodriver_pb2.Route(timestamp_us=123) + for x, y, z in ((1.0, 2.0, 3.0), (4.0, 5.0, 6.0)): + waypoint = route.waypoints.add() + waypoint.x = x + waypoint.y = y + waypoint.z = z + + timestamp_us, waypoints_xyz = pack_route_array(route) + + assert timestamp_us == 123 + np.testing.assert_allclose( + waypoints_xyz, + np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], dtype=np.float32), + ) diff --git a/src/physics/tests/test_ply_io.py b/src/utils/tests/test_ply_io.py similarity index 94% rename from src/physics/tests/test_ply_io.py rename to src/utils/tests/test_ply_io.py index 3db2bb90..8adc1d1e 100644 --- a/src/physics/tests/test_ply_io.py +++ b/src/utils/tests/test_ply_io.py @@ -6,7 +6,7 @@ import numpy as np import pytest -from alpasim_physics.ply_io import load_mesh_vf, save_mesh_vf +from alpasim_utils.ply_io import load_mesh_vf, save_mesh_vf # --------------------------------------------------------------------------- # Helpers @@ -321,20 +321,3 @@ def test_unknown_format(self) -> None: ) with pytest.raises(ValueError, match="Unsupported PLY format"): load_mesh_vf(header.encode("ascii")) - - -# --------------------------------------------------------------------------- -# Tests — loading the existing binary test fixture -# --------------------------------------------------------------------------- - - -class TestExistingFixture: - """Verify we can load the binary LE PLY fixture used by test_backend.""" - - def test_load_mesh_ground_ply(self) -> None: - data = open("tests/data/mesh_ground.ply", "rb").read() - verts, faces = load_mesh_vf(data) - assert verts.shape == (1688260, 3) - assert faces.shape == (3376506, 3) - assert verts.dtype == np.float64 - assert faces.dtype == np.int32 diff --git a/src/utils_rs/src/grpc_boundary.rs b/src/utils_rs/src/grpc_boundary.rs new file mode 100644 index 00000000..e906c1d1 --- /dev/null +++ b/src/utils_rs/src/grpc_boundary.rs @@ -0,0 +1,224 @@ +// SPDX-License-Identifier: Apache-2.0 +// Copyright (c) 2026 NVIDIA Corporation + +use numpy::ndarray::Array2; +use numpy::{PyArray1, PyArray2, PyReadonlyArray1, PyReadonlyArray2, PyUntypedArrayMethods}; +use pyo3::exceptions::PyValueError; +use pyo3::prelude::*; +use pyo3::types::{PyAny, PyBytes}; + +const WIRE_FIXED64: u32 = 1; +const WIRE_LENGTH_DELIMITED: u32 = 2; +const WIRE_FIXED32: u32 = 5; + +#[pyfunction] +pub fn build_drive_response_bytes<'py>( + py: Python<'py>, + time_now_us: i64, + xyz: PyReadonlyArray2<'_, f32>, + quat_wxyz: PyReadonlyArray2<'_, f32>, + dt_us: PyReadonlyArray1<'_, i64>, +) -> PyResult> { + let xyz_shape = xyz.shape(); + let quat_shape = quat_wxyz.shape(); + let dt_shape = dt_us.shape(); + if xyz_shape.len() != 2 || xyz_shape[1] != 3 { + return Err(PyValueError::new_err(format!( + "xyz must have shape (N, 3), got {:?}", + xyz_shape + ))); + } + if quat_shape.len() != 2 || quat_shape[1] != 4 { + return Err(PyValueError::new_err(format!( + "quat_wxyz must have shape (N, 4), got {:?}", + quat_shape + ))); + } + if dt_shape.len() != 1 { + return Err(PyValueError::new_err(format!( + "dt_us must have shape (N,), got {:?}", + dt_shape + ))); + } + + let horizon = xyz_shape[0]; + if quat_shape[0] != horizon || dt_shape[0] != horizon { + return Err(PyValueError::new_err(format!( + "mismatched leading dims: xyz={:?}, quat_wxyz={:?}, dt_us={:?}", + xyz_shape, quat_shape, dt_shape + ))); + } + + let xyz = xyz.as_slice()?; + let quat_wxyz = quat_wxyz.as_slice()?; + let dt_us = dt_us.as_slice()?; + + let mut trajectory = Vec::with_capacity(horizon * 96); + for i in 0..horizon { + let timestamp_us = checked_timestamp_us(time_now_us, dt_us[i])?; + let pose = encode_pose(&xyz[i * 3..i * 3 + 3], &quat_wxyz[i * 4..i * 4 + 4]); + let mut pose_at_time = Vec::with_capacity(pose.len() + 16); + put_message_field(&mut pose_at_time, 1, &pose); + put_fixed64_field(&mut pose_at_time, 2, timestamp_us); + put_message_field(&mut trajectory, 1, &pose_at_time); + } + + let mut response = Vec::with_capacity(trajectory.len() + 8); + if !trajectory.is_empty() { + put_message_field(&mut response, 2, &trajectory); + } + Ok(PyBytes::new(py, &response)) +} + +#[pyfunction] +pub fn pack_trajectory_arrays<'py>( + py: Python<'py>, + trajectory: &Bound<'py, PyAny>, +) -> PyResult<( + Bound<'py, PyArray1>, + Bound<'py, PyArray2>, + Bound<'py, PyArray2>, +)> { + let poses = trajectory.getattr("poses")?; + let pose_count = poses.len()?; + let mut rows = Vec::with_capacity(pose_count); + for i in 0..pose_count { + let pose_at_time = poses.get_item(i)?; + let timestamp_us = pose_at_time.getattr("timestamp_us")?.extract::()?; + let pose = pose_at_time.getattr("pose")?; + let vec = pose.getattr("vec")?; + let quat = pose.getattr("quat")?; + rows.push(PoseRow { + timestamp_us, + xyz: [ + vec.getattr("x")?.extract::()?, + vec.getattr("y")?.extract::()?, + vec.getattr("z")?.extract::()?, + ], + quat_wxyz: [ + quat.getattr("w")?.extract::()?, + quat.getattr("x")?.extract::()?, + quat.getattr("y")?.extract::()?, + quat.getattr("z")?.extract::()?, + ], + }); + } + rows.sort_by_key(|row| row.timestamp_us); + + let mut timestamps = Vec::with_capacity(pose_count); + let mut xyz = Vec::with_capacity(pose_count * 3); + let mut quat_wxyz = Vec::with_capacity(pose_count * 4); + for row in rows { + timestamps.push(row.timestamp_us); + xyz.extend_from_slice(&row.xyz); + quat_wxyz.extend_from_slice(&row.quat_wxyz); + } + + Ok(( + PyArray1::from_vec(py, timestamps), + array2_from_shape_vec(py, pose_count, 3, xyz)?, + array2_from_shape_vec(py, pose_count, 4, quat_wxyz)?, + )) +} + +#[pyfunction] +pub fn pack_route_array<'py>( + py: Python<'py>, + route: &Bound<'py, PyAny>, +) -> PyResult<(i64, Bound<'py, PyArray2>)> { + let waypoints = route.getattr("waypoints")?; + let waypoint_count = waypoints.len()?; + let mut xyz = Vec::with_capacity(waypoint_count * 3); + for i in 0..waypoint_count { + let waypoint = waypoints.get_item(i)?; + xyz.push(waypoint.getattr("x")?.extract::()?); + xyz.push(waypoint.getattr("y")?.extract::()?); + xyz.push(waypoint.getattr("z")?.extract::()?); + } + Ok(( + route.getattr("timestamp_us")?.extract::()?, + array2_from_shape_vec(py, waypoint_count, 3, xyz)?, + )) +} + +struct PoseRow { + timestamp_us: i64, + xyz: [f32; 3], + quat_wxyz: [f32; 4], +} + +fn array2_from_shape_vec<'py>( + py: Python<'py>, + rows: usize, + cols: usize, + values: Vec, +) -> PyResult>> { + let array = Array2::from_shape_vec((rows, cols), values) + .map_err(|error| PyValueError::new_err(error.to_string()))?; + Ok(PyArray2::from_owned_array(py, array)) +} + +fn checked_timestamp_us(time_now_us: i64, dt_us: i64) -> PyResult { + let timestamp_us = time_now_us + .checked_add(dt_us) + .ok_or_else(|| PyValueError::new_err("timestamp_us overflow"))?; + if timestamp_us < 0 { + return Err(PyValueError::new_err(format!( + "timestamp_us must be non-negative, got {}", + timestamp_us + ))); + } + Ok(timestamp_us as u64) +} + +fn encode_pose(xyz: &[f32], quat_wxyz: &[f32]) -> Vec { + let mut vec3 = Vec::with_capacity(15); + put_float_field(&mut vec3, 1, xyz[0]); + put_float_field(&mut vec3, 2, xyz[1]); + put_float_field(&mut vec3, 3, xyz[2]); + + let mut quat = Vec::with_capacity(20); + put_float_field(&mut quat, 1, quat_wxyz[0]); + put_float_field(&mut quat, 2, quat_wxyz[1]); + put_float_field(&mut quat, 3, quat_wxyz[2]); + put_float_field(&mut quat, 4, quat_wxyz[3]); + + let mut pose = Vec::with_capacity(vec3.len() + quat.len() + 8); + put_message_field(&mut pose, 1, &vec3); + put_message_field(&mut pose, 2, &quat); + pose +} + +fn put_float_field(buf: &mut Vec, field_number: u32, value: f32) { + if value.to_bits() == 0 { + return; + } + put_key(buf, field_number, WIRE_FIXED32); + buf.extend_from_slice(&value.to_le_bytes()); +} + +fn put_fixed64_field(buf: &mut Vec, field_number: u32, value: u64) { + if value == 0 { + return; + } + put_key(buf, field_number, WIRE_FIXED64); + buf.extend_from_slice(&value.to_le_bytes()); +} + +fn put_message_field(buf: &mut Vec, field_number: u32, value: &[u8]) { + put_key(buf, field_number, WIRE_LENGTH_DELIMITED); + put_varint(buf, value.len() as u64); + buf.extend_from_slice(value); +} + +fn put_key(buf: &mut Vec, field_number: u32, wire_type: u32) { + put_varint(buf, ((field_number << 3) | wire_type) as u64); +} + +fn put_varint(buf: &mut Vec, mut value: u64) { + while value >= 0x80 { + buf.push((value as u8) | 0x80); + value >>= 7; + } + buf.push(value as u8); +} diff --git a/src/utils_rs/src/lib.rs b/src/utils_rs/src/lib.rs index de2f30d5..f137f014 100644 --- a/src/utils_rs/src/lib.rs +++ b/src/utils_rs/src/lib.rs @@ -10,10 +10,14 @@ use pyo3::prelude::*; mod array_utils; mod dynamic_trajectory; +mod grpc_boundary; mod polyline; mod pose; mod trajectory; +pub use grpc_boundary::{ + build_drive_response_bytes, pack_route_array, pack_trajectory_arrays, +}; pub use dynamic_trajectory::DynamicTrajectory; pub use polyline::Polyline; pub use pose::Pose; @@ -33,5 +37,8 @@ fn utils_rs(m: &Bound<'_, PyModule>) -> PyResult<()> { m.add_class::()?; m.add_class::()?; m.add_function(wrap_pyfunction!(version, m)?)?; + m.add_function(wrap_pyfunction!(build_drive_response_bytes, m)?)?; + m.add_function(wrap_pyfunction!(pack_trajectory_arrays, m)?)?; + m.add_function(wrap_pyfunction!(pack_route_array, m)?)?; Ok(()) } diff --git a/src/utils_rs/utils_rs.pyi b/src/utils_rs/utils_rs.pyi index 3a53ee68..00a92c96 100644 --- a/src/utils_rs/utils_rs.pyi +++ b/src/utils_rs/utils_rs.pyi @@ -5,6 +5,8 @@ from __future__ import annotations +from typing import Any + import numpy as np from numpy.typing import NDArray @@ -12,6 +14,37 @@ def version() -> str: """Returns the version of this Rust extension.""" ... +def build_drive_response_bytes( + time_now_us: int, + xyz: NDArray[np.float32], + quat_wxyz: NDArray[np.float32], + dt_us: NDArray[np.int64], +) -> bytes: + """ + Build serialized egodriver DriveResponse bytes from trajectory arrays. + + :param time_now_us: Base simulator timestamp in microseconds. + :param xyz: Array of shape (N, 3) with position rows. + :param quat_wxyz: Array of shape (N, 4) with proto-order quaternions. + :param dt_us: Array of shape (N,) with timestamp offsets in microseconds. + """ + ... + +def pack_trajectory_arrays( + trajectory: Any, +) -> tuple[NDArray[np.int64], NDArray[np.float32], NDArray[np.float32]]: + """ + Pack a proto-like trajectory into timestamp, xyz, and quat_wxyz arrays. + + Returned rows are sorted by timestamp, and quaternions are in proto order + [w, x, y, z]. + """ + ... + +def pack_route_array(route: Any) -> tuple[int, NDArray[np.float32]]: + """Pack a proto-like route into its timestamp and waypoint xyz array.""" + ... + class Pose: """ A single rigid transform: position + quaternion rotation. diff --git a/src/wizard/alpasim_wizard/configuration.py b/src/wizard/alpasim_wizard/configuration.py index 93a5e0fd..002e5ecd 100644 --- a/src/wizard/alpasim_wizard/configuration.py +++ b/src/wizard/alpasim_wizard/configuration.py @@ -114,7 +114,11 @@ def _generate_runtime_config( runtime_config["simulation_config"] = simulation_config runtime_config["prometheus"] = { "worker_ports": list(telemetry_ports.workers), - "url": f"http://{prometheus_host}:{telemetry_ports.prometheus}", + "url": ( + f"http://{prometheus_host}:{telemetry_ports.prometheus}" + if cfg.wizard.prometheus.start_prometheus + else None + ), } # Write flat scene list @@ -301,7 +305,11 @@ def _load_or_create_run_metadata(self, cfg: Any) -> dict[str, Any]: run_metadata.setdefault("run_uuid", str(uuid.uuid4())) return run_metadata - run_uuid = uuid.uuid4() + run_uuid = ( + uuid.UUID(cfg.wizard.prometheus.run_uuid) + if cfg.wizard.prometheus.run_uuid + else uuid.uuid4() + ) run_name = ( cfg.wizard.run_name or os.environ.get("SLURM_JOB_NAME", None) diff --git a/src/wizard/alpasim_wizard/context.py b/src/wizard/alpasim_wizard/context.py index 9160f7d6..949ee9e3 100644 --- a/src/wizard/alpasim_wizard/context.py +++ b/src/wizard/alpasim_wizard/context.py @@ -198,10 +198,11 @@ def create(cfg: AlpasimConfig) -> WizardContext: artifact_list=artifact_list, num_gpus=detect_gpus(), ) - logger.info( - "Prometheus UI: http://localhost:%d", - telemetry_ports.prometheus, - ) + if cfg.wizard.prometheus.start_prometheus: + logger.info( + "Prometheus UI: http://localhost:%d", + telemetry_ports.prometheus, + ) logger.info( "Prometheus file-SD dir: %s", cfg.wizard.prometheus.file_sd_dir, diff --git a/src/wizard/alpasim_wizard/deployment/slurm.py b/src/wizard/alpasim_wizard/deployment/slurm.py index e735883d..ab0f4106 100644 --- a/src/wizard/alpasim_wizard/deployment/slurm.py +++ b/src/wizard/alpasim_wizard/deployment/slurm.py @@ -42,11 +42,65 @@ def deploy_all_services(self) -> None: ) containers = list(self.container_set.sim) containers.append(self.container_set.prometheus) - self.deploy( - containers=containers, - containers_to_start_last=containers_to_start_last, + if self.context.cfg.wizard.enable_mps: + self._start_mps_daemon() + try: + self.deploy( + containers=containers, + containers_to_start_last=containers_to_start_last, + ) + finally: + if self.context.cfg.wizard.enable_mps: + self._stop_mps_daemon() + + def _mps_pipe_dir(self) -> str: + """Job-scoped CUDA MPS pipe directory. + + Lives under /tmp rather than the run log dir because Unix socket paths + are capped at ~108 characters, which Lustre log paths exceed. Scoped by + job id so daemons of jobs sharing a node cannot collide. + """ + return f"/tmp/nvidia-mps-{self.context.cfg.wizard.slurm_job_id}" + + def _start_mps_daemon(self) -> None: + """Start the CUDA MPS control daemon on the host for this job.""" + cfg = self.context.cfg.wizard + pipe_dir = self._mps_pipe_dir() + mps_log_dir = f"{cfg.log_dir}/mps" + # Remove a stale pipe dir (e.g. from a requeued job) so the daemon + # does not fail on leftover sockets. + dispatch_command( + f"rm -rf {pipe_dir} && mkdir -p {pipe_dir} {mps_log_dir} && " + f"CUDA_MPS_PIPE_DIRECTORY={pipe_dir} CUDA_MPS_LOG_DIRECTORY={mps_log_dir} " + "nvidia-cuda-mps-control -d", + log_dir=Path(cfg.log_dir), + dry_run=cfg.dry_run, + blocking=True, ) + def _stop_mps_daemon(self) -> None: + """Stop the CUDA MPS control daemon and remove its pipe directory.""" + cfg = self.context.cfg.wizard + pipe_dir = self._mps_pipe_dir() + try: + try: + dispatch_command( + f"echo quit | CUDA_MPS_PIPE_DIRECTORY={pipe_dir} " + "nvidia-cuda-mps-control", + log_dir=Path(cfg.log_dir), + dry_run=cfg.dry_run, + blocking=True, + ) + finally: + dispatch_command( + f"rm -rf {pipe_dir}", + log_dir=Path(cfg.log_dir), + dry_run=cfg.dry_run, + blocking=True, + ) + except Exception as e: + logger.warning("Failed to stop MPS daemon: %s", e) + def deploy( self, containers: List[Any], @@ -175,9 +229,10 @@ def _to_slurm_run( ), "SLURM environment not detected" slurm_job_id = container.context.cfg.wizard.slurm_job_id + restart_count = os.environ.get("SLURM_RESTART_COUNT", "0") s_log = ( f"{container.context.cfg.wizard.log_dir}/txt-logs/" - f"out-{slurm_job_id}-{container.uuid}-log.txt" + f"out-{slurm_job_id}-attempt-{restart_count}-{container.uuid}-log.txt" ) sqsh = ensure_sqsh_path( @@ -188,11 +243,14 @@ def _to_slurm_run( # Note that we cannot use --export=CUDA_VISIBLE_DEVICES=... with srun because SLURM # overrides CUDA_VISIBLE_DEVICES even when exported as an environment variable. # Instead we set it in the command line. Use export to allow chaining commands with &&. - s_gpu = ( - f"export CUDA_VISIBLE_DEVICES={container.gpu};" - if container.gpu is not None - else "" + mps_enabled = ( + container.context.cfg.wizard.enable_mps and container.gpu is not None ) + s_gpu = "" + if container.gpu is not None: + s_gpu = f"export CUDA_VISIBLE_DEVICES={container.gpu};" + if mps_enabled: + s_gpu += f"export CUDA_MPS_PIPE_DIRECTORY={self._mps_pipe_dir()};" # Separate environment variables: # - 'VAR=value' format to export in bash. The value will be logged, not secure for secrets. # - 'VAR' format pass-through from host. The value will not be logged, secure for secrets. @@ -215,7 +273,12 @@ def _to_slurm_run( # isolated, while preserving the job id needed for Slurm-scoped telemetry. s_env_export_arg = f"--export={','.join(env_passthrough_set)} " - s_mnt = ",".join([v.to_str() for v in container.volumes]) + mounts = [v.to_str() for v in container.volumes] + if mps_enabled: + # enroot containers have an isolated rootfs; the MPS pipe directory + # must be mounted explicitly for clients to reach the daemon. + mounts.append(f"{self._mps_pipe_dir()}:{self._mps_pipe_dir()}") + s_mnt = ",".join(mounts) # Pin child srun steps to the wizard's node so services are co-located # and reachable via localhost. Without --nodelist, SLURM may schedule diff --git a/src/wizard/alpasim_wizard/scenes/csv_utils.py b/src/wizard/alpasim_wizard/scenes/csv_utils.py index f8b4940a..95cf6a22 100644 --- a/src/wizard/alpasim_wizard/scenes/csv_utils.py +++ b/src/wizard/alpasim_wizard/scenes/csv_utils.py @@ -39,7 +39,7 @@ def __str__(self) -> str: "artifact_repository", "hf_revision", ] -SUITES_COLUMNS = ["test_suite_id", "scene_id"] +SUITES_COLUMNS = ["test_suite_id", "scene_id", "uuid"] # Validation patterns # Matches ISO-format timestamps: "YYYY-MM-DD HH:MM:SS" (e.g., "2024-12-05 14:30:00") @@ -113,7 +113,7 @@ def merge_suites_csv( dry_run: bool = False, ) -> tuple[int, int]: """ - Merge new suite rows into existing CSV, deduplicating by (test_suite_id, scene_id). + Merge new suite rows into existing CSV, deduplicating by (test_suite_id, uuid). Args: csv_path: Path to the suites CSV file. @@ -135,15 +135,15 @@ def merge_suites_csv( existing_pairs = set( zip( existing["test_suite_id"].to_list(), - existing["scene_id"].to_list(), + existing["uuid"].to_list(), ) ) else: existing_pairs = set() new_only = new_rows.filter( - pl.struct(["test_suite_id", "scene_id"]).map_elements( - lambda x: (x["test_suite_id"], x["scene_id"]) not in existing_pairs, + pl.struct(["test_suite_id", "uuid"]).map_elements( + lambda x: (x["test_suite_id"], x["uuid"]) not in existing_pairs, return_dtype=pl.Boolean, ) ) @@ -181,12 +181,12 @@ def validate_csvs(scenes_csv: str, suites_csv: str | None = None) -> None: - No empty/null values in required fields (uuid, scene_id, nre_version_string, path) Suites CSV (if provided): - - Required columns present (test_suite_id, scene_id) - - No duplicate (test_suite_id, scene_id) pairs + - Required columns present (test_suite_id, scene_id, uuid) + - No duplicate (test_suite_id, uuid) pairs - No empty/null values in any column Cross-file (if suites_csv provided): - - All scene_ids referenced in suites exist in scenes + - All (scene_id, uuid) pairs referenced in suites exist in scenes Raises: CSVValidationError: If any validation check fails. @@ -315,18 +315,18 @@ def validate_csvs(scenes_csv: str, suites_csv: str | None = None) -> None: errors.append(f"Suites CSV missing columns: {missing_cols}") if suites_df.height > 0 and not missing_cols: - # Check for duplicate (test_suite_id, scene_id) pairs + # Check for duplicate (test_suite_id, uuid) pairs dup_pairs = suites_df.filter( - pl.struct(["test_suite_id", "scene_id"]).is_duplicated() + pl.struct(["test_suite_id", "uuid"]).is_duplicated() ) if dup_pairs.height > 0: dup_list = list( zip( dup_pairs["test_suite_id"].to_list()[:3], - dup_pairs["scene_id"].to_list()[:3], + dup_pairs["uuid"].to_list()[:3], ) ) - errors.append(f"Duplicate (test_suite_id, scene_id) pairs: {dup_list}") + errors.append(f"Duplicate (test_suite_id, uuid) pairs: {dup_list}") # Check for empty values for col in SUITES_COLUMNS: @@ -341,16 +341,27 @@ def validate_csvs(scenes_csv: str, suites_csv: str | None = None) -> None: # --- Cross-file validation --- - if suites_df.height > 0 and scenes_df.height > 0: - # Check that all scene_ids in suites exist in scenes - suite_scene_ids = set(suites_df["scene_id"].to_list()) - scenes_scene_ids = set(scenes_df["scene_id"].to_list()) - missing_in_scenes = suite_scene_ids - scenes_scene_ids - if missing_in_scenes: - missing_list = list(missing_in_scenes)[:5] + if ( + suites_df.height > 0 + and {"scene_id", "uuid"}.issubset(suites_df.columns) + and {"scene_id", "uuid"}.issubset(scenes_df.columns) + ): + missing_in_scenes = ( + suites_df.select(["scene_id", "uuid"]) + .unique() + .join( + scenes_df.select(["scene_id", "uuid"]).unique(), + on=["scene_id", "uuid"], + how="anti", + ) + .sort(["scene_id", "uuid"]) + ) + if missing_in_scenes.height > 0: + missing_list = missing_in_scenes.head(5).rows() errors.append( - f"Suites reference scene_ids not in scenes CSV: {missing_list}" - f"{'...' if len(missing_in_scenes) > 5 else ''}" + "Suites reference (scene_id, uuid) pairs not in scenes CSV: " + f"{missing_list}" + f"{'...' if missing_in_scenes.height > 5 else ''}" ) # Raise if any errors diff --git a/src/wizard/alpasim_wizard/scenes/sceneset.py b/src/wizard/alpasim_wizard/scenes/sceneset.py index e67e95d8..568ab8f0 100644 --- a/src/wizard/alpasim_wizard/scenes/sceneset.py +++ b/src/wizard/alpasim_wizard/scenes/sceneset.py @@ -175,6 +175,7 @@ def scan_local_usdz_directory(usdz_dir: str) -> tuple[pl.DataFrame, pl.DataFrame { "test_suite_id": str(ArtifactRepository.LOCAL), "scene_id": scene_id, + "uuid": uuid, } ) @@ -244,7 +245,7 @@ def from_cfg(cls, cfg: ScenesConfig) -> Self: else: sim_scenes = _load_and_merge_csvs(cfg.scenes_csv, dedup_key="uuid") sim_suites = _load_and_merge_csvs( - cfg.suites_csv, dedup_key=["test_suite_id", "scene_id"] + cfg.suites_csv, dedup_key=["test_suite_id", "uuid"] ) cache_dir = cfg.scene_cache @@ -298,28 +299,27 @@ def query_by_suite_id(self, test_suite_id: str) -> list[SceneIdAndUuid]: df = suite_scenes.join( self.sim_scenes, - on="scene_id", + on=["scene_id", "uuid"], how="left", - ).select(["uuid", "scene_id", "nre_version_string", "last_modified"]) + ).select(["uuid", "scene_id", "nre_version_string"]) if df.height == 0: raise USDZQueryError(f"Failed to find any scenes for {test_suite_id=}.") - if df["uuid"].null_count() > 0: - missing = df.filter(pl.col("uuid").is_null())["scene_id"].to_list() + if df["nre_version_string"].null_count() > 0: + missing = ( + df.filter(pl.col("nre_version_string").is_null()) + .select(["scene_id", "uuid"]) + .to_dicts() + ) raise USDZQueryError( f"Failed to find some scenes for scene suite {test_suite_id}. " - f"Missing: {missing}." - "A sceneset is expected to contain a valid artifact for each scene_id." + f"Missing (scene_id, uuid) pairs: {missing}." ) - _warn_duplicate_scenes(df) - deduplicated = _deduplicate(df) - logger.info( - f"Scenes: \n{deduplicated.select(['scene_id', 'nre_version_string'])}" - ) + logger.info(f"Scenes: \n{df.select(['scene_id', 'nre_version_string'])}") - return SceneIdAndUuid.list_from_df(deduplicated) + return SceneIdAndUuid.list_from_df(df) def get_paths(self, uuids: list[str]) -> dict[str, str]: """Get artifact paths for given UUIDs.""" diff --git a/src/wizard/alpasim_wizard/schema.py b/src/wizard/alpasim_wizard/schema.py index 49111676..492e9bc5 100644 --- a/src/wizard/alpasim_wizard/schema.py +++ b/src/wizard/alpasim_wizard/schema.py @@ -87,8 +87,12 @@ class RunMode(Enum): @dataclass class WizardPrometheusConfig: + """Prometheus ownership, identity, and discovery settings.""" + scrape_interval: str = "5s" file_sd_dir: str | None = None + start_prometheus: bool = True + run_uuid: str | None = None @dataclass @@ -137,6 +141,11 @@ class WizardConfig: # allocations on CI nodes), otherwise overlapping steps are killed. slurm_cpu_bind_none: bool = False + # Run GPU services through CUDA MPS so kernels from co-located processes + # execute concurrently instead of time-slicing between CUDA contexts. + # Starts a per-job MPS control daemon on the node. SLURM only. + enable_mps: bool = False + # External service addresses for services running outside the deployment. # Maps service name to list of addresses (e.g., {"driver": ["localhost:6789"]}). # These addresses are added to generated-network-config.yaml so the runtime diff --git a/src/wizard/alpasim_wizard/services.py b/src/wizard/alpasim_wizard/services.py index c8bed682..e2df4307 100644 --- a/src/wizard/alpasim_wizard/services.py +++ b/src/wizard/alpasim_wizard/services.py @@ -27,6 +27,10 @@ def resolve_prometheus_command(context: WizardContext) -> str: ) for name, port in context.telemetry_ports.prometheus_service_ports().items(): command = command.replace(f"{{prometheus_ports.{name}}}", str(port)) + command = command.replace( + "{start_prometheus}", + str(context.cfg.wizard.prometheus.start_prometheus).lower(), + ) return command @@ -445,14 +449,10 @@ def build_service_containers( build_service_containers(name, config, cfg.runtime) ) - prometheus_container = _build_prometheus_container( - cfg, - context, - use_address_string, - ) + prometheus_container = _build_prometheus_container(cfg, context, use_address_string) logger.info("Built %d simulation containers", len(sim_containers)) - logger.info("Built Prometheus container %s", prometheus_container.uuid) + logger.info("Built telemetry container %s", prometheus_container.uuid) return ContainerSet( sim=sim_containers, @@ -469,7 +469,9 @@ def _build_prometheus_container( name = "prometheus" config = cfg.services.prometheus prometheus_ports = context.telemetry_ports.prometheus_service_ports() - readiness_port = prometheus_ports["prometheus"] + readiness_port = prometheus_ports[ + "prometheus" if cfg.wizard.prometheus.start_prometheus else "node_exporter" + ] uuid = f"{name}-0" address = ContainerDefinition._build_address( readiness_port, diff --git a/src/wizard/alpasim_wizard/telemetry/prometheus.py b/src/wizard/alpasim_wizard/telemetry/prometheus.py index 7c06dea0..4d632c84 100644 --- a/src/wizard/alpasim_wizard/telemetry/prometheus.py +++ b/src/wizard/alpasim_wizard/telemetry/prometheus.py @@ -26,6 +26,7 @@ PROMETHEUS_TARGETS = f"{TELEMETRY_LOG_DIR}/prometheus/targets" PROMETHEUS_RULES = f"{TELEMETRY_LOG_DIR}/prometheus/rules" PROCESS_EXPORTER_CONFIG = f"{TELEMETRY_LOG_DIR}/prometheus/process-exporter.yml" +DCGM_COUNTERS_CONFIG = f"{TELEMETRY_LOG_DIR}/prometheus/dcgm-counters.csv" PROMETHEUS_DATA = f"{TELEMETRY_LOG_DIR}/prometheus/data" FILE_SD_CLEANUP_MIN_AGE_S = 5 * 60 * 60 @@ -71,14 +72,6 @@ def generate_prometheus_configs( file-SD publication is disabled. """ cfg = context.cfg - prometheus_config_path = _host_log_path(log_dir, PROMETHEUS_CONFIG) - targets_dir = _host_log_path(log_dir, PROMETHEUS_TARGETS) - data_dir = _host_log_path(log_dir, PROMETHEUS_DATA) - rules_dir = _host_log_path(log_dir, PROMETHEUS_RULES) - targets_dir.mkdir(parents=True, exist_ok=True) - data_dir.mkdir(parents=True, exist_ok=True) - rules_dir.mkdir(parents=True, exist_ok=True) - write_json( { "process_names": [ @@ -92,63 +85,73 @@ def generate_prometheus_configs( }, _host_log_path(log_dir, PROCESS_EXPORTER_CONFIG), ) - - local_targets = _build_file_sd_targets(run_metadata, cfg, context, local=True) - write_json(local_targets, targets_dir / "alpasim.json") - - central_file_sd_path = None - file_sd_root = ( - Path(cfg.wizard.prometheus.file_sd_dir) - if cfg.wizard.prometheus.file_sd_dir - else None + dcgm_counters_path = _host_log_path(log_dir, DCGM_COUNTERS_CONFIG) + dcgm_counters_path.parent.mkdir(parents=True, exist_ok=True) + dcgm_counters_path.write_text( + resource_files("alpasim_wizard") + .joinpath("telemetry/resources/dcgm-counters.csv") + .read_text(encoding="utf-8"), + encoding="utf-8", ) - if file_sd_root: - _cleanup_stale_file_sd(file_sd_root) - central_path = file_sd_root / f"{run_metadata['run_uuid']}.json" + central_file_sd_path = None + if cfg.wizard.prometheus.file_sd_dir: + file_sd_root = Path(cfg.wizard.prometheus.file_sd_dir) file_sd_root.mkdir(parents=True, exist_ok=True) + if file_sd_root.stat().st_mode & 0o7777 != 0o2777: + file_sd_root.chmod(0o2777) + _cleanup_stale_file_sd(file_sd_root) + central_file_sd_path = file_sd_root / f"{run_metadata['run_uuid']}.json" write_json( - _build_file_sd_targets(run_metadata, cfg, context, local=False), - central_path, + _build_file_sd_targets(run_metadata, context, local=False), + central_file_sd_path, + mode=0o666, ) - central_file_sd_path = central_path - prometheus_config = { - "global": { - "scrape_interval": str(cfg.wizard.prometheus.scrape_interval), - "evaluation_interval": str(cfg.wizard.prometheus.scrape_interval), - }, - "rule_files": [f"{PROMETHEUS_RULES}/*.yml"], - "scrape_configs": [ - { - "job_name": "alpasim", - "file_sd_configs": [ - { - "files": [f"{PROMETHEUS_TARGETS}/*.json"], - "refresh_interval": "5s", - } - ], - } - ], - } - recording_rules = resource_files("alpasim_utils.telemetry").joinpath( - "metrics_plot_recording_rules.yml" - ) - (rules_dir / "alpasim-recording-rules.yml").write_text( - recording_rules.read_text(encoding="utf-8"), - encoding="utf-8", - ) - write_yaml(prometheus_config, str(prometheus_config_path)) + if cfg.wizard.prometheus.start_prometheus: + _host_log_path(log_dir, PROMETHEUS_DATA).mkdir(parents=True, exist_ok=True) + write_json( + _build_file_sd_targets(run_metadata, context, local=True), + _host_log_path(log_dir, PROMETHEUS_TARGETS) / "alpasim.json", + ) + prometheus_config = { + "global": { + "scrape_interval": str(cfg.wizard.prometheus.scrape_interval), + "evaluation_interval": str(cfg.wizard.prometheus.scrape_interval), + }, + "rule_files": [f"{PROMETHEUS_RULES}/*.yml"], + "scrape_configs": [ + { + "job_name": "alpasim", + "file_sd_configs": [ + { + "files": [f"{PROMETHEUS_TARGETS}/*.json"], + "refresh_interval": "5s", + } + ], + } + ], + } + recording_rules = resource_files("alpasim_utils.telemetry").joinpath( + "metrics_plot_recording_rules.yml" + ) + rules_dir = _host_log_path(log_dir, PROMETHEUS_RULES) + rules_dir.mkdir(parents=True, exist_ok=True) + (rules_dir / "alpasim-recording-rules.yml").write_text( + recording_rules.read_text(encoding="utf-8"), + encoding="utf-8", + ) + write_yaml(prometheus_config, str(_host_log_path(log_dir, PROMETHEUS_CONFIG))) return central_file_sd_path def _build_file_sd_targets( run_metadata: dict[str, Any], - cfg: Any, context: WizardContext, *, local: bool, ) -> list[dict[str, Any]]: """Build Prometheus file-SD target groups for local or central scraping.""" + cfg = context.cfg labels = _base_file_sd_labels(run_metadata, cfg) if local: runtime_host = ( @@ -167,7 +170,11 @@ def _build_file_sd_targets( return [ { "targets": [f"{runtime_host}:{port}" for port in telemetry_ports.workers], - "labels": {**labels, "job": "alpasim-runtime-worker"}, + "labels": { + **labels, + "job": "alpasim-runtime-worker", + "component": "runtime", + }, }, { "targets": [f"{exporter_host}:{prometheus_ports['node_exporter']}"], @@ -194,44 +201,23 @@ def _central_scrape_host() -> str: def _cleanup_stale_file_sd(file_sd_dir: Path) -> None: - """Delete stale central file-SD files whose targets are unreachable. - - Central file-SD entries are meant to exist only while a run is active. This - cleanup prevents old runs from staying discoverable if the wizard process - exited before `cleanup_central_file_sd` could remove its own entry. - - Args: - file_sd_dir: Root directory containing Prometheus file-SD JSON files. - """ + """Delete stale central file-SD files whose targets are unreachable.""" now = time.time() for path in file_sd_dir.glob("*.json"): try: if now - path.stat().st_mtime < FILE_SD_CLEANUP_MIN_AGE_S: continue - with open(path, encoding="utf-8") as f: - groups = json.load(f) - if not isinstance(groups, list): - raise TypeError("expected a list of file-SD target groups") - targets: list[str] = [] - for group in groups: - if not isinstance(group, dict): - raise TypeError("expected each file-SD target group to be a dict") - group_targets = group.get("targets") - if not isinstance(group_targets, list): - raise TypeError( - "expected file-SD target group targets to be a list" - ) - if not all(isinstance(target, str) for target in group_targets): - raise TypeError("expected all file-SD targets to be strings") - targets.extend(group_targets) + with open(path, encoding="utf-8") as stream: + groups = json.load(stream) + targets = [target for group in groups for target in group["targets"]] with ThreadPoolExecutor( max_workers=FILE_SD_CLEANUP_MAX_WORKERS ) as executor: if any(executor.map(_target_reachable, targets)): continue - except (OSError, json.JSONDecodeError, TypeError, ValueError) as exc: + except (OSError, AttributeError, KeyError, TypeError, ValueError) as exc: logger.warning("Skipping invalid file-SD file %s: %s", path, exc) continue diff --git a/src/wizard/alpasim_wizard/telemetry/resources/dcgm-counters.csv b/src/wizard/alpasim_wizard/telemetry/resources/dcgm-counters.csv new file mode 100644 index 00000000..d995561e --- /dev/null +++ b/src/wizard/alpasim_wizard/telemetry/resources/dcgm-counters.csv @@ -0,0 +1,18 @@ +# DCGM fields exported by dcgm-exporter (passed via -f in prometheus_sidecar.sh). +# This replaces the exporter's built-in default set, so every field used by +# dashboards or recording rules must be listed here. +# Format: DCGM field, Prometheus metric type, help message + +DCGM_FI_DEV_GPU_UTIL, gauge, GPU utilization (in %). +DCGM_FI_DEV_FB_TOTAL, gauge, Total framebuffer memory (in MiB). +DCGM_FI_DEV_FB_USED, gauge, Used framebuffer memory (in MiB). +DCGM_FI_DEV_FB_FREE, gauge, Free framebuffer memory (in MiB). +DCGM_FI_DEV_FB_RESERVED, gauge, Reserved framebuffer memory (in MiB). + +# Profiling (DCP) fields; measure real SM/memory usage rather than the coarse +# "any kernel resident" signal of DCGM_FI_DEV_GPU_UTIL. Unsupported fields are +# skipped by dcgm-exporter with a warning on GPUs without profiling support. +DCGM_FI_PROF_SM_ACTIVE, gauge, Ratio of cycles at least one warp was resident on an SM, averaged over all SMs. +DCGM_FI_PROF_SM_OCCUPANCY, gauge, Ratio of resident warps to maximum resident warps, averaged over all SMs. +DCGM_FI_PROF_PIPE_TENSOR_ACTIVE, gauge, Ratio of cycles the tensor core pipe was active. +DCGM_FI_PROF_DRAM_ACTIVE, gauge, Ratio of cycles the device memory interface was active. diff --git a/src/wizard/alpasim_wizard/telemetry/resources/prometheus_sidecar.sh b/src/wizard/alpasim_wizard/telemetry/resources/prometheus_sidecar.sh index 06d101e6..b04fd4fd 100644 --- a/src/wizard/alpasim_wizard/telemetry/resources/prometheus_sidecar.sh +++ b/src/wizard/alpasim_wizard/telemetry/resources/prometheus_sidecar.sh @@ -1,10 +1,14 @@ set -euo pipefail -if command -v prometheus >/dev/null 2>&1; then - PROMETHEUS_BIN=prometheus -else - echo "prometheus binary not found" >&2 - exit 1 +START_PROMETHEUS={start_prometheus} +PROMETHEUS_BIN= +if [[ "$START_PROMETHEUS" == "true" ]]; then + if command -v prometheus >/dev/null 2>&1; then + PROMETHEUS_BIN=prometheus + else + echo "prometheus binary not found" >&2 + exit 1 + fi fi if command -v node_exporter >/dev/null 2>&1; then @@ -33,12 +37,16 @@ start_slurm_process_exporter() { PROCESS_PID=$! } +# hwmon/nvme sysfs reads issue live NVMe admin commands; a wedged controller +# blocks them in uninterruptible sleep and kills the whole /metrics endpoint. $NODE_EXPORTER_BIN \ --web.listen-address=0.0.0.0:{prometheus_ports.node_exporter} \ --path.procfs=/host/proc \ --path.sysfs=/host/sys \ --path.rootfs=/rootfs \ - --no-collector.systemd & + --no-collector.systemd \ + --no-collector.hwmon \ + --no-collector.nvme & NODE_PID=$! if [[ -n "${SLURM_JOB_ID:-}" ]]; then @@ -56,7 +64,7 @@ else fi if command -v dcgm-exporter >/dev/null 2>&1; then - dcgm-exporter -a :{prometheus_ports.dcgm_exporter} & + dcgm-exporter -f /mnt/log_dir/prometheus/dcgm-counters.csv -a :{prometheus_ports.dcgm_exporter} & DCGM_PID=$! else echo "dcgm-exporter binary not found; GPU exporter disabled" >&2 @@ -65,8 +73,12 @@ fi trap 'kill "$NODE_PID" "$PROCESS_PID" "$DCGM_PID" 2>/dev/null || true' TERM INT -exec $PROMETHEUS_BIN \ - --config.file=/mnt/log_dir/prometheus/prometheus.yml \ - --storage.tsdb.path=/mnt/log_dir/prometheus/data \ - --enable-feature=promql-at-modifier \ - --web.listen-address=0.0.0.0:{prometheus_ports.prometheus} +if [[ "$START_PROMETHEUS" == "true" ]]; then + exec $PROMETHEUS_BIN \ + --config.file=/mnt/log_dir/prometheus/prometheus.yml \ + --storage.tsdb.path=/mnt/log_dir/prometheus/data \ + --enable-feature=promql-at-modifier \ + --web.listen-address=0.0.0.0:{prometheus_ports.prometheus} +fi + +wait diff --git a/src/wizard/alpasim_wizard/telemetry/slurm_process_exporter.py b/src/wizard/alpasim_wizard/telemetry/slurm_process_exporter.py index bd27de98..28f5d16d 100644 --- a/src/wizard/alpasim_wizard/telemetry/slurm_process_exporter.py +++ b/src/wizard/alpasim_wizard/telemetry/slurm_process_exporter.py @@ -33,16 +33,17 @@ @dataclass -class ProcessSample: +class GroupUsage: cpu_seconds: float = 0.0 resident_bytes: int = 0 @dataclass(frozen=True) -class ProcessMetric: +class ProcessSample: pid: str group: str port: str + gpu_indices: tuple[int, ...] cpu_seconds: float resident_bytes: int @@ -92,6 +93,14 @@ def _port_for_cmdline(cmdline: str) -> str: return match.group(1) if match else "" +def _gpu_indices_for_environ(environ: Sequence[str]) -> tuple[int, ...]: + for entry in environ: + key, separator, value = entry.partition("=") + if separator and key == "CUDA_VISIBLE_DEVICES": + return tuple(int(device) for device in value.split(",") if device) + return () + + def _run_command(command: Sequence[str]) -> subprocess.CompletedProcess[str]: return subprocess.run(command, check=True, capture_output=True, text=True) @@ -185,16 +194,7 @@ def discover_pids( return pids | discover_procfs_pids(procfs, job_id) -def collect(procfs: Path, pids: Iterable[str]) -> dict[str, ProcessSample]: - samples: dict[str, ProcessSample] = {} - for process in collect_processes(procfs, pids): - sample = samples.setdefault(process.group, ProcessSample()) - sample.cpu_seconds += process.cpu_seconds - sample.resident_bytes += process.resident_bytes - return samples - - -def collect_processes(procfs: Path, pids: Iterable[str]) -> list[ProcessMetric]: +def collect_processes(procfs: Path, pids: Iterable[str]) -> list[ProcessSample]: samples = [] for pid in pids: pid_dir = procfs / pid @@ -204,10 +204,11 @@ def collect_processes(procfs: Path, pids: Iterable[str]) -> list[ProcessMetric]: if group is None: continue samples.append( - ProcessMetric( + ProcessSample( pid=pid, group=group, port=_port_for_cmdline(cmdline), + gpu_indices=_gpu_indices_for_environ(_read_environ(pid_dir)), cpu_seconds=_read_cpu_seconds(pid_dir), resident_bytes=_read_resident_bytes(pid_dir), ) @@ -222,19 +223,24 @@ def _label_value(value: str) -> str: def render_metrics( - samples: dict[str, ProcessSample], + process_samples: Sequence[ProcessSample], duration: float, - process_samples: Sequence[ProcessMetric] = (), ) -> bytes: + usage_by_group: dict[str, GroupUsage] = {} + for process in process_samples: + usage = usage_by_group.setdefault(process.group, GroupUsage()) + usage.cpu_seconds += process.cpu_seconds + usage.resident_bytes += process.resident_bytes + lines = [ "# HELP namedprocess_namegroup_cpu_seconds_total Cpu usage in seconds", "# TYPE namedprocess_namegroup_cpu_seconds_total counter", ] - for group, sample in samples.items(): + for group, usage in usage_by_group.items(): label = _label_value(group) lines.append( f'namedprocess_namegroup_cpu_seconds_total{{groupname="{label}"}} ' - f"{sample.cpu_seconds}" + f"{usage.cpu_seconds}" ) lines.extend( [ @@ -242,16 +248,15 @@ def render_metrics( "# TYPE namedprocess_namegroup_memory_bytes gauge", ] ) - for group, sample in samples.items(): + for group, usage in usage_by_group.items(): label = _label_value(group) lines.append( f'namedprocess_namegroup_memory_bytes{{groupname="{label}",' - f'memtype="resident"}} {sample.resident_bytes}' + f'memtype="resident"}} {usage.resident_bytes}' ) lines.extend( [ - "# HELP alpasim_process_cpu_seconds_total " - "Cpu usage in seconds by process", + "# HELP alpasim_process_cpu_seconds_total Cpu usage in seconds by process", "# TYPE alpasim_process_cpu_seconds_total counter", ] ) @@ -263,6 +268,16 @@ def render_metrics( f'alpasim_process_cpu_seconds_total{{groupname="{group}",' f'pid="{pid}",port="{port}"}} {process.cpu_seconds}' ) + lines.extend( + [ + "# HELP alpasim_gpu_workload_info Physical GPUs owned by AlpaSim processes", + "# TYPE alpasim_gpu_workload_info gauge", + ] + ) + for gpu_index in sorted( + {gpu_index for process in process_samples for gpu_index in process.gpu_indices} + ): + lines.append(f'alpasim_gpu_workload_info{{gpu="{gpu_index}"}} 1') lines.extend( [ "# HELP alpasim_slurm_process_exporter_scrape_duration_seconds " @@ -288,17 +303,8 @@ def do_GET(self) -> None: started = time.monotonic() pids = discover_pids(server.job_id, server.procfs, server.cgroupfs) process_samples = collect_processes(server.procfs, pids) - samples: dict[str, ProcessSample] = {} - for process in process_samples: - sample = samples.setdefault(process.group, ProcessSample()) - sample.cpu_seconds += process.cpu_seconds - sample.resident_bytes += process.resident_bytes duration = time.monotonic() - started - MetricsHandler.cache_body = render_metrics( - samples, - duration, - process_samples, - ) + MetricsHandler.cache_body = render_metrics(process_samples, duration) MetricsHandler.cache_until = now + server.cache_seconds self.send_response(200) self.send_header("Content-Type", "text/plain; version=0.0.4") @@ -317,13 +323,6 @@ class MetricsServer(http.server.HTTPServer): cache_seconds: float -def _job_id_from_env() -> str: - job_id = os.environ.get("SLURM_JOB_ID") - if not job_id: - raise RuntimeError("SLURM_JOB_ID is required") - return job_id - - def main() -> None: parser = argparse.ArgumentParser() parser.add_argument("--job-id", default=None) @@ -334,7 +333,7 @@ def main() -> None: args = parser.parse_args() server = MetricsServer(("0.0.0.0", args.port), MetricsHandler) - server.job_id = args.job_id or _job_id_from_env() + server.job_id = args.job_id or os.environ["SLURM_JOB_ID"] server.procfs = args.procfs server.cgroupfs = args.cgroupfs server.cache_seconds = args.cache_seconds diff --git a/src/wizard/alpasim_wizard/utils.py b/src/wizard/alpasim_wizard/utils.py index 57b35f73..0cc85c28 100644 --- a/src/wizard/alpasim_wizard/utils.py +++ b/src/wizard/alpasim_wizard/utils.py @@ -7,6 +7,7 @@ import re import subprocess import sys +import uuid from enum import Enum from pathlib import Path from typing import Any, cast @@ -44,12 +45,24 @@ def represent_literal_str(dumper: yaml.Dumper, data: LiteralStr) -> yaml.ScalarN yaml.dump(data, stream, Dumper=IndentedListDumper, sort_keys=False) -def write_json(data: Any, file_path: str | Path) -> None: - """Write indented JSON, creating the parent directory first.""" +def write_json(data: Any, file_path: str | Path, *, mode: int | None = None) -> None: + """Atomically write indented JSON, creating the parent directory first. + + Writes to a temporary file and renames it into place so concurrent readers + (e.g. an external Prometheus watching file-SD target files) never observe + partially written JSON. + """ path = Path(file_path) path.parent.mkdir(parents=True, exist_ok=True) - with open(path, "w", encoding="utf-8") as f: - json.dump(data, f, indent=2) + temporary_path = path.with_name(f".{path.name}.{uuid.uuid4().hex}.tmp") + try: + with open(temporary_path, "w", encoding="utf-8") as stream: + if mode is not None: + os.fchmod(stream.fileno(), mode) + json.dump(data, stream, indent=2) + os.replace(temporary_path, path) + finally: + temporary_path.unlink(missing_ok=True) def nre_image_to_nre_version(image: str) -> str: diff --git a/src/wizard/alpasim_wizard/wizard.py b/src/wizard/alpasim_wizard/wizard.py index 4df12647..e76180bf 100644 --- a/src/wizard/alpasim_wizard/wizard.py +++ b/src/wizard/alpasim_wizard/wizard.py @@ -87,6 +87,12 @@ def cast(self) -> None: config_manager = ConfigurationManager(self.context.cfg.wizard.log_dir) config_manager.generate_all(container_set, self.context) + if ( + self.context.cfg.wizard.enable_mps + and self.context.cfg.wizard.run_method != RunMethod.SLURM + ): + raise ValueError("wizard.enable_mps is only supported on SLURM") + # Handle different run methods try: if self.context.cfg.wizard.run_method == RunMethod.SLURM: diff --git a/src/wizard/configs/base_config.yaml b/src/wizard/configs/base_config.yaml index 6c804f6c..258f8a90 100644 --- a/src/wizard/configs/base_config.yaml +++ b/src/wizard/configs/base_config.yaml @@ -7,7 +7,7 @@ defaults: - driver: null # Must be overridden (e.g., driver=vavam, driver=alpamayo1) - driver_source: null # Optional: external_static or external_dynamic. Omit for managed drivers. - topology: null # Must be overridden (e.g., topology=1gpu) - - trafficsim: null # Optional override + - trafficsim: disabled # Disabled unless an implementation is selected (e.g., trafficsim=catk) - controller: default # Defaults to linear MPC; override with controller=nonlinear etc. - renderer: null # Optional override - optional scenes_catalog: internal # auto-override when internal plugin installed @@ -33,6 +33,14 @@ defines: renderer_entrypoint: "/app/internal/scripts/pycena/runtime/pycena_nrm_full" nre_max_workers: 4 + # Maximum backends a single scene ID may occupy inside one NRE server + # (concurrent rollouts of the same scene each check out a backend; one render + # request covers all cameras). Requests beyond the cap queue on the NRE side + # instead of spawning more backends. Must be <= nre_cache_size; size the cache + # as nre_cache_size >= min(n_concurrent_rollouts, max_scenes_per_renderer) + # * nre_max_backends_per_scene. Only consumed by renderer images whose command + # passes --max-backends-per-scene (e.g. renderer=internal_nre). + nre_max_backends_per_scene: 1 helper: scripts vscode: sources/remote-vscode-server physics_cache_size: 16 # should match or exceed concurrent scenes to avoid cache thrashing @@ -97,6 +105,10 @@ wizard: log_level: INFO prometheus: scrape_interval: 5s + # Exporters always run; disable this when an external Prometheus scrapes them. + start_prometheus: true + # Optional parent identity supplied by an orchestrator such as AlpaGym. + run_uuid: null # Central Prometheus file-SD publication directory. Deploy configs resolve # `defines.filesystem`; override this to publish elsewhere. file_sd_dir: "${defines.filesystem}/prometheus/file-sd" @@ -246,6 +258,9 @@ services: runtime: # nr_workers and endpoints.*.n_concurrent_rollouts are set by topology configs. + # Number of times to retry a rollout after a failed attempt. + max_rollout_retries: 2 + # Scene provider configuration for a single backend family. scene_provider: kind: usdz @@ -313,7 +328,7 @@ runtime: physics_update_mode: "EGO_ONLY" - route_generator_type: "MAP" # "MAP" or "RECORDED" + route_generator_type: "MAP" # "NONE", "MAP", or "RECORDED" route_start_offset_m: 0.0 # Along-route distance ahead of ego where submitted routes start vehicle: null # use values from the .usdz file (original dimensions) @@ -369,6 +384,8 @@ eval: min_timesteps: 5 image: camera_logical_id: camera_front_wide_120fov + open_loop_collision: + horizon_s: 3.0 aggregation_modifiers: max_dist_to_gt_trajectory: 4.0 diff --git a/src/wizard/configs/driver/alpamayo1.yaml b/src/wizard/configs/driver/alpamayo1.yaml index 3604787c..095e8fd8 100644 --- a/src/wizard/configs/driver/alpamayo1.yaml +++ b/src/wizard/configs/driver/alpamayo1.yaml @@ -19,6 +19,7 @@ model: # # Alternative local path to a pre-downloaded model # checkpoint_path: "/mnt/drivers/alpamayo1/Alpamayo-R1-10B" device: "cuda" + force_determinism: false # Server configuration host: "0.0.0.0" diff --git a/src/wizard/configs/topology/1gpu.yaml b/src/wizard/configs/topology/1gpu.yaml index d4c73138..2643e512 100644 --- a/src/wizard/configs/topology/1gpu.yaml +++ b/src/wizard/configs/topology/1gpu.yaml @@ -4,6 +4,10 @@ defines: nre_cache_size: 5 # renderer.n_concurrent_rollouts + 1 +trafficsim: + server: + max_workers: 4 + services: renderer: replicas_per_container: 1 @@ -44,4 +48,3 @@ runtime: n_concurrent_rollouts: 4 trafficsim: n_concurrent_rollouts: 4 - skip: true diff --git a/src/wizard/configs/topology/2gpu.yaml b/src/wizard/configs/topology/2gpu.yaml index cbd6f462..af6783bf 100644 --- a/src/wizard/configs/topology/2gpu.yaml +++ b/src/wizard/configs/topology/2gpu.yaml @@ -4,6 +4,10 @@ defines: nre_cache_size: 13 # renderer.n_concurrent_rollouts + 1 +trafficsim: + server: + max_workers: 6 + services: renderer: replicas_per_container: 1 @@ -33,6 +37,7 @@ runtime: # DRIV: 1 x 3 x 4 = 12 # PHYS: 2 x 1 x 6 = 12 # CONT: 1 (CPU) x 6 x 2 = 12 + # TRAF: 2 x 1 x 6 = 12 renderer: n_concurrent_rollouts: 12 driver: @@ -44,4 +49,4 @@ runtime: controller: n_concurrent_rollouts: 2 trafficsim: - skip: true + n_concurrent_rollouts: 6 diff --git a/src/wizard/configs/topology/8gpu_12rollouts.yaml b/src/wizard/configs/topology/8gpu_12rollouts.yaml index 52b8fb3e..ab3d09d5 100644 --- a/src/wizard/configs/topology/8gpu_12rollouts.yaml +++ b/src/wizard/configs/topology/8gpu_12rollouts.yaml @@ -5,6 +5,10 @@ defines: nre_cache_size: 16 # (renderer.n_concurrent_rollouts(=3) + buffer(=1)) x expected_camera_count (=4) physics_cache_size: 16 +trafficsim: + server: + max_workers: 6 + services: renderer: replicas_per_container: 1 @@ -34,6 +38,7 @@ runtime: # DRIV: 4 x 1 x 3 = 12 # PHYS: 6 x 1 x 2 = 12 # CONT: 1 (CPU) x 2 x 6 = 12 + # TRAF: 2 x 1 x 6 = 12 renderer: n_concurrent_rollouts: 3 driver: @@ -44,4 +49,4 @@ runtime: controller: n_concurrent_rollouts: 6 trafficsim: - skip: true + n_concurrent_rollouts: 6 diff --git a/src/wizard/configs/topology/8gpu_64rollouts.yaml b/src/wizard/configs/topology/8gpu_64rollouts.yaml index 891253b2..c9d62f91 100644 --- a/src/wizard/configs/topology/8gpu_64rollouts.yaml +++ b/src/wizard/configs/topology/8gpu_64rollouts.yaml @@ -5,6 +5,10 @@ defines: nre_cache_size: 17 # renderer.n_concurrent_rollouts + 1 physics_cache_size: 6 +trafficsim: + server: + max_workers: 16 + eval: num_processes: 32 @@ -26,8 +30,10 @@ services: gpus: null trafficsim: + # CATK loads a complete model per replica. Keep one model per GPU; four + # replicas per GPU exhaust node memory before the runtime can start. replicas_per_container: 1 - gpus: [0, 1] + gpus: [0, 1, 2, 3] runtime: nr_workers: 8 @@ -37,6 +43,7 @@ runtime: # DRIV: 4 x 8 x 2 = 64 # PHYS: 4 x 4 x 4 = 64 # CONT: 1 (CPU) x 16 x 4 = 64 + # TRAF: 4 x 1 x 16 = 64 renderer: n_concurrent_rollouts: 16 driver: @@ -48,4 +55,4 @@ runtime: controller: n_concurrent_rollouts: 4 trafficsim: - skip: true + n_concurrent_rollouts: 16 diff --git a/src/wizard/configs/topology/8gpu_no_replicas.yaml b/src/wizard/configs/topology/8gpu_no_replicas.yaml index 3094b1b7..fce94af7 100644 --- a/src/wizard/configs/topology/8gpu_no_replicas.yaml +++ b/src/wizard/configs/topology/8gpu_no_replicas.yaml @@ -7,6 +7,10 @@ defines: nre_cache_size: 3 # renderer.n_concurrent_rollouts + 1 +trafficsim: + server: + max_workers: 10 + services: renderer: gpus: [3, 4, 5, 6, 7] @@ -52,4 +56,3 @@ runtime: trafficsim: n_concurrent_rollouts: 10 - skip: false diff --git a/src/wizard/configs/topology/daemon.yaml b/src/wizard/configs/topology/daemon.yaml index 64278002..41e7cb10 100644 --- a/src/wizard/configs/topology/daemon.yaml +++ b/src/wizard/configs/topology/daemon.yaml @@ -7,6 +7,10 @@ defines: nre_cache_size: 5 +trafficsim: + server: + max_workers: 1 + services: renderer: replicas_per_container: 1 @@ -38,4 +42,4 @@ runtime: controller: n_concurrent_rollouts: 1 trafficsim: - skip: true + n_concurrent_rollouts: 1 diff --git a/src/wizard/configs/trafficsim/catk.yaml b/src/wizard/configs/trafficsim/catk.yaml index 64c0d6d9..e4384f96 100644 --- a/src/wizard/configs/trafficsim/catk.yaml +++ b/src/wizard/configs/trafficsim/catk.yaml @@ -19,6 +19,11 @@ runtime: services: trafficsim: image: ${services.runtime.image} + environments: + # Request-level concurrency already keeps the CPU busy. Prevent each + # small PyTorch CPU operation from recruiting a node-sized thread pool. + - OMP_NUM_THREADS=1 + - MKL_NUM_THREADS=1 volumes: - "${scenes.scene_cache}:/mnt/nre-data" - "${defines.trafficsim_models}:/mnt/trafficsim-models" @@ -35,11 +40,10 @@ trafficsim: hydra: job: chdir: false - server: + server: # parameters set by the wizard host: 0.0.0.0 port: 6200 - max_workers: 1 - log_file: /mnt/log_dir/txt-logs/trafficsim.log + log_file: null catk: device: cuda filter_distance_th: 100.0 @@ -49,7 +53,7 @@ trafficsim: usdz_folder: /mnt/nre-data time_step: 0.1 num_history_steps: 16 - minimum_future_steps: 45 + prediction_steps: 15 model: config_path: /mnt/trafficsim-models/catk_v120/config.yaml ckpt_path: /mnt/trafficsim-models/catk_v120/latest.ckpt diff --git a/src/wizard/configs/trafficsim/disabled.yaml b/src/wizard/configs/trafficsim/disabled.yaml new file mode 100644 index 00000000..5134dd04 --- /dev/null +++ b/src/wizard/configs/trafficsim/disabled.yaml @@ -0,0 +1,7 @@ +# @package _global_ +# Traffic simulation is opt-in; implementation configs enable their endpoint. + +runtime: + endpoints: + trafficsim: + skip: true diff --git a/src/wizard/pyproject.toml b/src/wizard/pyproject.toml index c577b9c7..76f14643 100644 --- a/src/wizard/pyproject.toml +++ b/src/wizard/pyproject.toml @@ -43,7 +43,7 @@ asyncio_default_fixture_loop_scope = "function" include = ["alpasim_wizard*", "hydra_plugins*"] [tool.setuptools.package-data] -alpasim_wizard = ["telemetry/resources/*.sh"] +alpasim_wizard = ["telemetry/resources/*.sh", "telemetry/resources/*.csv"] [project.scripts] alpasim_wizard = "alpasim_wizard.__main__:main" diff --git a/src/wizard/tests/test_runtime_server_mode.py b/src/wizard/tests/test_runtime_server_mode.py index 2741b400..84b852c2 100644 --- a/src/wizard/tests/test_runtime_server_mode.py +++ b/src/wizard/tests/test_runtime_server_mode.py @@ -91,6 +91,8 @@ def _cfg( prometheus=SimpleNamespace( scrape_interval="5s", file_sd_dir=None, + start_prometheus=True, + run_uuid=None, ), slurm_job_id=0, run_name="test-run", @@ -238,6 +240,7 @@ def test_prometheus_configs_publish_runtime_targets_and_recording_rules( assert worker_target["labels"]["run_uuid"] == run_metadata["run_uuid"] assert worker_target["labels"]["run_name"] == "test-run" assert "worker_id" not in worker_target["labels"] + assert "instance" not in worker_target["labels"] prometheus_config = yaml.safe_load( (tmp_path / "prometheus/prometheus.yml").read_text() @@ -247,10 +250,17 @@ def test_prometheus_configs_publish_runtime_targets_and_recording_rules( rules = yaml.safe_load( (tmp_path / "prometheus/rules/alpasim-recording-rules.yml").read_text() ) - rule_names = {rule["record"] for rule in rules["groups"][0]["rules"]} + rules_by_name = { + rule["record"]: rule["expr"] for rule in rules["groups"][0]["rules"] + } + rule_names = set(rules_by_name) assert "alpasim:rpc_queue_depth_at_start_latest:max" in rule_names assert "alpasim:rpc_queue_depth_at_start_latest:min" in rule_names assert "alpasim:simulation_rollouts_completed:sum" in rule_names + throughput_rule = rules_by_name["alpasim:simulation_seconds_per_rollout:avg"] + assert "alpasim_simulation_elapsed_seconds" in throughput_rule + assert "alpasim_rollouts_total" in throughput_rule + assert "alpasim_rollout_duration_seconds" not in throughput_rule assert "alpasim:process_cpu_utilization_percent:max_by_group:rate30s" in rule_names assert "alpasim:gpu_memory_pressure_percent:avg" in rule_names @@ -277,6 +287,43 @@ def test_run_metadata_is_loaded_for_resume(tmp_path: Path) -> None: assert run_metadata == existing_metadata +def test_parent_run_uuid_and_disabled_prometheus_keep_exporter_discovery( + tmp_path: Path, +) -> None: + """An orchestrator can own Prometheus while AlpaSim runs its exporters.""" + cfg = _cfg(tmp_path) + cfg.wizard.prometheus.start_prometheus = False + cfg.wizard.prometheus.run_uuid = "4ed94022-fc8d-409b-a0d8-745e6bdb44ab" + cfg.wizard.prometheus.file_sd_dir = str(tmp_path / "file-sd") + context = _context(cfg, baseport=6100) + container_set = build_container_set(context, "uuid") + manager = ConfigurationManager(str(tmp_path)) + + assert "START_PROMETHEUS=false" in container_set.prometheus.command + assert container_set.prometheus.service_instances[0].port == 6103 + run_metadata = manager._load_or_create_run_metadata(cfg) + manager._generate_runtime_config(cfg, [], context) + prometheus.generate_prometheus_configs(tmp_path, run_metadata, context) + runtime_config = yaml.safe_load( + (tmp_path / "generated-user-config-0.yaml").read_text() + ) + targets = json.loads( + (tmp_path / "file-sd" / f"{run_metadata['run_uuid']}.json").read_text() + ) + + assert run_metadata["run_uuid"] == cfg.wizard.prometheus.run_uuid + assert runtime_config["prometheus"]["url"] is None + assert not (tmp_path / "prometheus/prometheus.yml").exists() + assert (tmp_path / "prometheus/process-exporter.yml").exists() + assert len(targets) == 4 + assert {target["labels"]["job"] for target in targets} == { + "alpasim-runtime-worker", + "alpasim-node", + "alpasim-process", + "alpasim-dcgm", + } + + def test_file_sd_cleanup_removes_old_unreachable_files( tmp_path: Path, monkeypatch: pytest.MonkeyPatch, @@ -320,6 +367,7 @@ def test_central_file_sd_publication_is_removed_on_cleanup( ) central_path = file_sd_dir / f"{run_metadata['run_uuid']}.json" assert central_path.exists() + assert central_path.stat().st_mode & 0o7777 == 0o666 central_targets = json.loads(central_path.read_text()) assert central_targets[0]["targets"] == ["192.0.2.10:6100", "192.0.2.10:6101"] assert central_targets[0]["labels"]["node"] != "192.0.2.10" diff --git a/src/wizard/tests/test_scene_csvs.py b/src/wizard/tests/test_scene_csvs.py index 65ece62b..0555a733 100644 --- a/src/wizard/tests/test_scene_csvs.py +++ b/src/wizard/tests/test_scene_csvs.py @@ -5,8 +5,13 @@ from pathlib import Path +import polars as pl import pytest -from alpasim_wizard.scenes.csv_utils import CSVValidationError, validate_csvs +from alpasim_wizard.scenes.csv_utils import ( + CSVValidationError, + merge_suites_csv, + validate_csvs, +) def get_repo_root() -> Path: @@ -23,9 +28,18 @@ def get_repo_root() -> Path: REPO_ROOT = get_repo_root() SCENES_CSV = REPO_ROOT / "data" / "scenes" / "sim_scenes.csv" SUITES_CSV = REPO_ROOT / "data" / "scenes" / "sim_suites.csv" - - -def test_scene_csvs_are_valid(): +LEGACY_SCENES_CSV = REPO_ROOT / "data" / "scenes" / "sim_scenes_2505.csv" +LEGACY_SUITES_CSV = REPO_ROOT / "data" / "scenes" / "sim_suites_2505.csv" + + +@pytest.mark.parametrize( + ("scenes_csv", "suites_csv"), + [ + (SCENES_CSV, SUITES_CSV), + (LEGACY_SCENES_CSV, LEGACY_SUITES_CSV), + ], +) +def test_scene_csvs_are_valid(scenes_csv: Path, suites_csv: Path): """ Validate that the repository's scene and suite CSV files are well-formed. @@ -33,14 +47,31 @@ def test_scene_csvs_are_valid(): - Duplicate entries - Missing required columns - Invalid formats (UUIDs, timestamps, scene_ids) - - Orphaned suite references (scene_ids not in scenes file) + - Suite artifact pairs that do not exist in the scenes file """ try: - validate_csvs(str(SCENES_CSV), str(SUITES_CSV)) + validate_csvs(str(scenes_csv), str(suites_csv)) except CSVValidationError as e: pytest.fail(f"Scene CSV validation failed:\n{e}") +@pytest.mark.parametrize( + ("suite_id", "hf_revision"), + [("public_2601", "26.01"), ("public_2604", "26.04")], +) +def test_public_suite_pins_its_release(suite_id: str, hf_revision: str): + """A versioned public suite selects artifacts from that release.""" + scenes = pl.read_csv(SCENES_CSV, infer_schema_length=0) + suite = pl.read_csv(SUITES_CSV, infer_schema_length=0).filter( + pl.col("test_suite_id") == suite_id + ) + + selected = suite.join(scenes, on=["scene_id", "uuid"], how="inner") + + assert selected.height == suite.height + assert selected["hf_revision"].unique().to_list() == [hf_revision] + + def test_validate_csvs_catches_duplicate_uuids(tmp_path): """Verify validation catches duplicate UUIDs.""" scenes = tmp_path / "scenes.csv" @@ -51,28 +82,41 @@ def test_validate_csvs_catches_duplicate_uuids(tmp_path): "dup-uuid,clipgt-aaa,0.2.220,path/a,2025-01-01 00:00:00,swiftstack,\n" "dup-uuid,clipgt-bbb,0.2.220,path/b,2025-01-01 00:00:00,swiftstack,\n" # duplicate! ) - suites.write_text("test_suite_id,scene_id\n") + suites.write_text("test_suite_id,scene_id,uuid\n") with pytest.raises(CSVValidationError, match="Duplicate UUIDs"): validate_csvs(str(scenes), str(suites)) def test_validate_csvs_catches_orphaned_suite_references(tmp_path): - """Verify validation catches suite entries referencing non-existent scenes.""" + """Verify validation catches suite entries referencing non-existent artifacts.""" scenes = tmp_path / "scenes.csv" suites = tmp_path / "suites.csv" scenes.write_text( "uuid,scene_id,nre_version_string,path,last_modified,artifact_repository,hf_revision\n" - "uuid-1,clipgt-exists,0.2.220,path/a,2025-01-01 00:00:00,swiftstack,\n" ) suites.write_text( - "test_suite_id,scene_id\n" - "my-suite,clipgt-exists\n" - "my-suite,clipgt-missing\n" # not in scenes! + "test_suite_id,scene_id,uuid\n" "my-suite,clipgt-missing,uuid-missing\n" + ) + + with pytest.raises(CSVValidationError, match="pairs not in scenes CSV"): + validate_csvs(str(scenes), str(suites)) + + +def test_validate_csvs_catches_mismatched_scene_and_uuid(tmp_path): + """Verify a suite UUID must belong to the scene ID beside it.""" + scenes = tmp_path / "scenes.csv" + suites = tmp_path / "suites.csv" + + scenes.write_text( + "uuid,scene_id,nre_version_string,path,last_modified,artifact_repository,hf_revision\n" + "uuid-1,clipgt-aaa,0.2.220,path/a,2025-01-01 00:00:00,swiftstack,\n" + "uuid-2,clipgt-bbb,0.2.220,path/b,2025-01-01 00:00:00,swiftstack,\n" ) + suites.write_text("test_suite_id,scene_id,uuid\n" "my-suite,clipgt-aaa,uuid-2\n") - with pytest.raises(CSVValidationError, match="scene_ids not in scenes CSV"): + with pytest.raises(CSVValidationError, match="pairs not in scenes CSV"): validate_csvs(str(scenes), str(suites)) @@ -85,7 +129,7 @@ def test_validate_csvs_catches_invalid_timestamp_format(tmp_path): "uuid,scene_id,nre_version_string,path,last_modified,artifact_repository,hf_revision\n" "uuid-1,clipgt-aaa,0.2.220,path/a,01/15/2025 10:30:00,swiftstack,\n" # wrong format! ) - suites.write_text("test_suite_id,scene_id\n") + suites.write_text("test_suite_id,scene_id,uuid\n") with pytest.raises(CSVValidationError, match="Invalid last_modified format"): validate_csvs(str(scenes), str(suites)) @@ -100,7 +144,7 @@ def test_validate_csvs_catches_invalid_scene_id_format(tmp_path): "uuid,scene_id,nre_version_string,path,last_modified,artifact_repository,hf_revision\n" "uuid-1,invalid-scene-id,0.2.220,path/a,2025-01-01 00:00:00,swiftstack,\n" # missing clipgt- prefix ) - suites.write_text("test_suite_id,scene_id\n") + suites.write_text("test_suite_id,scene_id,uuid\n") with pytest.raises(CSVValidationError, match="Invalid scene_id format"): validate_csvs(str(scenes), str(suites)) @@ -115,14 +159,29 @@ def test_validate_csvs_catches_missing_columns(tmp_path): "uuid,scene_id\n" # missing nre_version_string, path, last_modified, artifact_repository "uuid-1,clipgt-aaa\n" ) - suites.write_text("test_suite_id,scene_id\n") + suites.write_text("test_suite_id,scene_id,uuid\n") with pytest.raises(CSVValidationError, match="missing columns"): validate_csvs(str(scenes), str(suites)) +def test_validate_csvs_requires_suite_uuid(tmp_path): + """Verify suite rows must pin an artifact UUID.""" + scenes = tmp_path / "scenes.csv" + suites = tmp_path / "suites.csv" + + scenes.write_text( + "uuid,scene_id,nre_version_string,path,last_modified,artifact_repository,hf_revision\n" + "uuid-1,clipgt-aaa,0.2.220,path/a,2025-01-01 00:00:00,swiftstack,\n" + ) + suites.write_text("test_suite_id,scene_id\nmy-suite,clipgt-aaa\n") + + with pytest.raises(CSVValidationError, match="Suites CSV missing columns"): + validate_csvs(str(scenes), str(suites)) + + def test_validate_csvs_catches_duplicate_suite_entries(tmp_path): - """Verify validation catches duplicate (test_suite_id, scene_id) pairs.""" + """Verify validation catches duplicate (test_suite_id, uuid) pairs.""" scenes = tmp_path / "scenes.csv" suites = tmp_path / "suites.csv" @@ -131,15 +190,40 @@ def test_validate_csvs_catches_duplicate_suite_entries(tmp_path): "uuid-1,clipgt-aaa,0.2.220,path/a,2025-01-01 00:00:00,swiftstack,\n" ) suites.write_text( - "test_suite_id,scene_id\n" - "my-suite,clipgt-aaa\n" - "my-suite,clipgt-aaa\n" # duplicate! + "test_suite_id,scene_id,uuid\n" + "my-suite,clipgt-aaa,uuid-1\n" + "my-suite,clipgt-aaa,uuid-1\n" ) with pytest.raises(CSVValidationError, match="Duplicate"): validate_csvs(str(scenes), str(suites)) +def test_merge_suites_csv_uses_uuid_as_artifact_identity(tmp_path): + """A suite can contain two artifacts for one scene, but not one UUID twice.""" + suites = tmp_path / "suites.csv" + suites.write_text("test_suite_id,scene_id,uuid\n" "my-suite,clipgt-aaa,uuid-1\n") + new_rows = pl.DataFrame( + [ + { + "test_suite_id": "my-suite", + "scene_id": "clipgt-aaa", + "uuid": "uuid-1", + }, + { + "test_suite_id": "my-suite", + "scene_id": "clipgt-aaa", + "uuid": "uuid-2", + }, + ] + ) + + added, duplicates = merge_suites_csv(str(suites), new_rows) + + assert (added, duplicates) == (1, 1) + assert pl.read_csv(suites)["uuid"].to_list() == ["uuid-1", "uuid-2"] + + def test_validate_csvs_catches_invalid_artifact_repository(tmp_path): """Verify validation catches invalid artifact_repository values.""" scenes = tmp_path / "scenes.csv" @@ -149,7 +233,7 @@ def test_validate_csvs_catches_invalid_artifact_repository(tmp_path): "uuid,scene_id,nre_version_string,path,last_modified,artifact_repository,hf_revision\n" "uuid-1,clipgt-aaa,0.2.220,path/a,2025-01-01 00:00:00,invalid_repo,\n" # invalid! ) - suites.write_text("test_suite_id,scene_id\n") + suites.write_text("test_suite_id,scene_id,uuid\n") with pytest.raises(CSVValidationError, match="Invalid artifact_repository"): validate_csvs(str(scenes), str(suites)) @@ -164,7 +248,7 @@ def test_validate_csvs_catches_missing_hf_revision(tmp_path): "uuid,scene_id,nre_version_string,path,last_modified,artifact_repository,hf_revision\n" "uuid-1,clipgt-aaa-bbb-ccc,0.2.220-abc123,path/to/file.usdz,2025-01-01 00:00:00,huggingface,\n" ) - suites.write_text("test_suite_id,scene_id\n") + suites.write_text("test_suite_id,scene_id,uuid\n") with pytest.raises(CSVValidationError, match="hf_revision"): validate_csvs(str(scenes), str(suites)) @@ -181,10 +265,10 @@ def test_validate_csvs_passes_for_valid_data(tmp_path): "uuid-2,clipgt-ddd-eee-fff,0.2.220-abc123,alpasim/path/to/file2.usdz,2025-01-02 12:30:45,huggingface,v1\n" ) suites.write_text( - "test_suite_id,scene_id\n" - "my-suite,clipgt-aaa-bbb-ccc\n" - "my-suite,clipgt-ddd-eee-fff\n" - "another-suite,clipgt-aaa-bbb-ccc\n" + "test_suite_id,scene_id,uuid\n" + "my-suite,clipgt-aaa-bbb-ccc,uuid-1\n" + "my-suite,clipgt-ddd-eee-fff,uuid-2\n" + "another-suite,clipgt-aaa-bbb-ccc,uuid-1\n" ) # Should not raise diff --git a/src/wizard/tests/test_sceneset.py b/src/wizard/tests/test_sceneset.py index f6fdd87e..a3f2e218 100644 --- a/src/wizard/tests/test_sceneset.py +++ b/src/wizard/tests/test_sceneset.py @@ -53,10 +53,13 @@ def test_csvs(tmp_path: Path) -> tuple[Path, Path]: # Create suites CSV with test data suites_csv.write_text( - "test_suite_id,scene_id\n" - "dev.alpasim.unit_tests.v0,clipgt-c045249c-2c01-45b0-87f5-6f631f71f1f1\n" - "dev.alpasim.unit_tests.v0,clipgt-c370a6ff-e319-4757-8282-09a67fad614e\n" - "dev.alpasim.unit_tests.v0,clipgt-c1ba971e-260f-4a7d-90b1-f60a9caf6acb\n" + "test_suite_id,scene_id,uuid\n" + "dev.alpasim.unit_tests.v0,clipgt-c045249c-2c01-45b0-87f5-6f631f71f1f1," + "stripped-2b8f88d4-8348-4faf-9dd3-78564fddde78\n" + "dev.alpasim.unit_tests.v0,clipgt-c370a6ff-e319-4757-8282-09a67fad614e," + "stripped-90db43dd-e5d2-41c4-9a69-400f6c33fb45\n" + "dev.alpasim.unit_tests.v0,clipgt-c1ba971e-260f-4a7d-90b1-f60a9caf6acb," + "stripped-c146251f-16d0-43eb-8905-3f0c037028cb\n" ) return scenes_csv, suites_csv @@ -227,25 +230,25 @@ def test_load_and_merge_csvs_duplicate_raises(tmp_path: Path): def test_load_and_merge_csvs_composite_key_duplicate_raises(tmp_path: Path): """Duplicate composite keys across suite files raise ValueError.""" csv_a = tmp_path / "a.csv" - csv_a.write_text("test_suite_id,scene_id\nsuite-1,clipgt-aaa\n") + csv_a.write_text("test_suite_id,scene_id,uuid\nsuite-1,clipgt-aaa,uuid-1\n") csv_b = tmp_path / "b.csv" - csv_b.write_text("test_suite_id,scene_id\nsuite-1,clipgt-aaa\n") + csv_b.write_text("test_suite_id,scene_id,uuid\nsuite-1,clipgt-aaa,uuid-1\n") with pytest.raises(ValueError, match="duplicate"): _load_and_merge_csvs( [str(csv_a), str(csv_b)], - dedup_key=["test_suite_id", "scene_id"], + dedup_key=["test_suite_id", "uuid"], ) def test_load_and_merge_csvs_suites_no_overlap(tmp_path: Path): """Suite CSVs with different suites merge successfully.""" csv_a = tmp_path / "a.csv" - csv_a.write_text("test_suite_id,scene_id\nsuite-public,clipgt-aaa\n") + csv_a.write_text("test_suite_id,scene_id,uuid\nsuite-public,clipgt-aaa,uuid-1\n") csv_b = tmp_path / "b.csv" - csv_b.write_text("test_suite_id,scene_id\nsuite-internal,clipgt-bbb\n") + csv_b.write_text("test_suite_id,scene_id,uuid\nsuite-internal,clipgt-bbb,uuid-2\n") merged = _load_and_merge_csvs( [str(csv_a), str(csv_b)], - dedup_key=["test_suite_id", "scene_id"], + dedup_key=["test_suite_id", "uuid"], ) assert merged.height == 2 @@ -263,9 +266,9 @@ def test_from_cfg_multiple_csvs(tmp_path: Path): "uuid-2,clipgt-bbb,0.1,path/b,2025-01-01 00:00:00,swiftstack,\n" ) suites_a = tmp_path / "suites_a.csv" - suites_a.write_text("test_suite_id,scene_id\nsuite-pub,clipgt-aaa\n") + suites_a.write_text("test_suite_id,scene_id,uuid\nsuite-pub,clipgt-aaa,uuid-1\n") suites_b = tmp_path / "suites_b.csv" - suites_b.write_text("test_suite_id,scene_id\nsuite-int,clipgt-bbb\n") + suites_b.write_text("test_suite_id,scene_id,uuid\nsuite-int,clipgt-bbb,uuid-2\n") config = ScenesConfig( scene_cache=str(tmp_path), scenes_csv=[str(scenes_a), str(scenes_b)], @@ -376,6 +379,7 @@ def test_scan_local_usdz_directory(local_usdz_dir: Path): # Check suites DataFrame - all scenes should be in the "local" suite assert sim_suites.height == 3 + assert set(sim_suites.columns) == {"test_suite_id", "scene_id", "uuid"} suite_ids = set(sim_suites["test_suite_id"].to_list()) assert suite_ids == {LOCAL_SUITE_ID} @@ -414,7 +418,7 @@ def test_usdz_manager_from_cfg_with_local_usdz_dir( scenes_csv.write_text( "uuid,scene_id,nre_version_string,path,last_modified,artifact_repository,hf_revision\n" ) - suites_csv.write_text("test_suite_id,scene_id\n") + suites_csv.write_text("test_suite_id,scene_id,uuid\n") config = ScenesConfig( local_usdz_dir=str(local_usdz_dir), @@ -445,7 +449,7 @@ def test_usdz_manager_query_by_scene_ids_with_local( scenes_csv.write_text( "uuid,scene_id,nre_version_string,path,last_modified,artifact_repository,hf_revision\n" ) - suites_csv.write_text("test_suite_id,scene_id\n") + suites_csv.write_text("test_suite_id,scene_id,uuid\n") config = ScenesConfig( local_usdz_dir=str(local_usdz_dir), @@ -472,7 +476,7 @@ def test_get_artifact_info_local(local_usdz_dir: Path, tmp_path: Path): scenes_csv.write_text( "uuid,scene_id,nre_version_string,path,last_modified,artifact_repository,hf_revision\n" ) - suites_csv.write_text("test_suite_id,scene_id\n") + suites_csv.write_text("test_suite_id,scene_id,uuid\n") config = ScenesConfig( local_usdz_dir=str(local_usdz_dir), @@ -498,7 +502,7 @@ def test_get_artifact_info_includes_hf_revision(tmp_path: Path): "uuid,scene_id,nre_version_string,path,last_modified,artifact_repository,hf_revision\n" "uuid-hf,clipgt-hf-scene,1.0,sample_set/26.01/file.usdz,2025-01-01 00:00:00,huggingface,26.01\n" ) - suites_csv.write_text("test_suite_id,scene_id\n") + suites_csv.write_text("test_suite_id,scene_id,uuid\n") config = ScenesConfig( scene_cache=str(tmp_path), scenes_csv=[str(scenes_csv)], @@ -520,7 +524,7 @@ def test_query_by_scene_ids_duplicate_nre_versions_warns(tmp_path: Path, caplog) "uuid-aaa,clipgt-scene-1,1.0.0-aaaa,path/a,2025-01-01 00:00:00,swiftstack,\n" "uuid-bbb,clipgt-scene-1,2.0.0-bbbb,path/b,2025-01-02 00:00:00,swiftstack,\n" ) - suites_csv.write_text("test_suite_id,scene_id\n") + suites_csv.write_text("test_suite_id,scene_id,uuid\n") config = ScenesConfig( scene_cache=str(tmp_path), scenes_csv=[str(scenes_csv)], @@ -537,8 +541,8 @@ def test_query_by_scene_ids_duplicate_nre_versions_warns(tmp_path: Path, caplog) assert "multiple NRE versions" in caplog.text -def test_query_by_suite_id_duplicate_nre_versions_warns(tmp_path: Path, caplog): - """Warning when a suite scene has multiple NRE versions; newest is picked.""" +def test_query_by_suite_id_selects_pinned_artifact(tmp_path: Path): + """A suite selects its pinned artifact when a scene has several versions.""" scenes_csv = tmp_path / "sim_scenes.csv" suites_csv = tmp_path / "sim_suites.csv" scenes_csv.write_text( @@ -548,7 +552,9 @@ def test_query_by_suite_id_duplicate_nre_versions_warns(tmp_path: Path, caplog): "uuid-ccc,clipgt-scene-2,1.0.0-aaaa,path/c,2025-01-01 00:00:00,swiftstack,\n" ) suites_csv.write_text( - "test_suite_id,scene_id\nsuite-1,clipgt-scene-1\nsuite-1,clipgt-scene-2\n" + "test_suite_id,scene_id,uuid\n" + "suite-1,clipgt-scene-1,uuid-aaa\n" + "suite-1,clipgt-scene-2,uuid-ccc\n" ) config = ScenesConfig( scene_cache=str(tmp_path), @@ -557,11 +563,31 @@ def test_query_by_suite_id_duplicate_nre_versions_warns(tmp_path: Path, caplog): ) manager = USDZManager.from_cfg(config) - with caplog.at_level(logging.WARNING, logger="alpasim_wizard"): - results = manager.query_by_suite_id(test_suite_id="suite-1") + results = manager.query_by_suite_id(test_suite_id="suite-1") assert len(results) == 2 - # clipgt-scene-1 should use newest artifact scene1 = next(r for r in results if r.scene_id == "clipgt-scene-1") - assert scene1.uuid == "uuid-bbb" - assert "clipgt-scene-1" in caplog.text + assert scene1.uuid == "uuid-aaa" + + +def test_query_by_suite_id_rejects_mismatched_scene_and_uuid(tmp_path: Path): + """A suite UUID must belong to the scene ID beside it.""" + scenes_csv = tmp_path / "sim_scenes.csv" + suites_csv = tmp_path / "sim_suites.csv" + scenes_csv.write_text( + "uuid,scene_id,nre_version_string,path,last_modified,artifact_repository,hf_revision\n" + "uuid-aaa,clipgt-scene-1,1.0.0-aaaa,path/a,2025-01-01 00:00:00,swiftstack,\n" + "uuid-bbb,clipgt-scene-2,1.0.0-aaaa,path/b,2025-01-01 00:00:00,swiftstack,\n" + ) + suites_csv.write_text( + "test_suite_id,scene_id,uuid\n" "suite-1,clipgt-scene-1,uuid-bbb\n" + ) + config = ScenesConfig( + scene_cache=str(tmp_path), + scenes_csv=[str(scenes_csv)], + suites_csv=[str(suites_csv)], + ) + manager = USDZManager.from_cfg(config) + + with pytest.raises(USDZQueryError, match=r"Missing \(scene_id, uuid\) pairs"): + manager.query_by_suite_id(test_suite_id="suite-1") diff --git a/src/wizard/tests/test_slurm_deployment.py b/src/wizard/tests/test_slurm_deployment.py index 7a5f8431..b7008c8e 100644 --- a/src/wizard/tests/test_slurm_deployment.py +++ b/src/wizard/tests/test_slurm_deployment.py @@ -13,7 +13,9 @@ from alpasim_wizard.schema import DebugFlags, RunMode -def _context(tmp_path: Path, *, dry_run: bool = False) -> WizardContext: +def _context( + tmp_path: Path, *, dry_run: bool = False, enable_mps: bool = False +) -> WizardContext: cfg = SimpleNamespace( wizard=SimpleNamespace( log_dir=str(tmp_path), @@ -24,6 +26,7 @@ def _context(tmp_path: Path, *, dry_run: bool = False) -> WizardContext: slurm_job_id=123, sqshcaches=[], slurm_cpu_bind_none=False, + enable_mps=enable_mps, debug_flags=DebugFlags(use_localhost=False), ) ) @@ -42,9 +45,11 @@ def _context(tmp_path: Path, *, dry_run: bool = False) -> WizardContext: ) -def _deployment(tmp_path: Path, *, dry_run: bool = False) -> SlurmDeployment: +def _deployment( + tmp_path: Path, *, dry_run: bool = False, enable_mps: bool = False +) -> SlurmDeployment: deployment = SlurmDeployment.__new__(SlurmDeployment) - deployment.context = _context(tmp_path, dry_run=dry_run) + deployment.context = _context(tmp_path, dry_run=dry_run, enable_mps=enable_mps) return deployment @@ -288,3 +293,94 @@ def fake_dispatch(command, *, log_dir, dry_run, blocking): deployment.deploy([driver], containers_to_start_last=[runtime]) assert commands == [False, True] + + +def test_slurm_run_mps_env_and_mount( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + deployment = _deployment(tmp_path, enable_mps=True) + monkeypatch.setattr( + "alpasim_wizard.deployment.slurm.ensure_sqsh_path", + lambda image, caches: f"{image}.sqsh", + ) + + gpu_command = deployment._to_slurm_run( + _slurm_container(deployment, gpu=1), RunMode.ONESHOT + ) + assert "export CUDA_MPS_PIPE_DIRECTORY=/tmp/nvidia-mps-123;" in gpu_command + assert "--container-mounts=/tmp/nvidia-mps-123:/tmp/nvidia-mps-123" in gpu_command + + cpu_command = deployment._to_slurm_run( + _slurm_container(deployment, gpu=None), RunMode.ONESHOT + ) + assert "nvidia-mps" not in cpu_command + + +def test_slurm_run_without_mps_has_no_mps_plumbing( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + deployment = _deployment(tmp_path) + monkeypatch.setattr( + "alpasim_wizard.deployment.slurm.ensure_sqsh_path", + lambda image, caches: f"{image}.sqsh", + ) + + command = deployment._to_slurm_run( + _slurm_container(deployment, gpu=1), RunMode.ONESHOT + ) + assert "nvidia-mps" not in command + + +def test_mps_daemon_start_and_stop_commands( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + deployment = _deployment(tmp_path, enable_mps=True) + commands = [] + + def fake_dispatch(command, *, log_dir, dry_run, blocking): + del log_dir, dry_run, blocking + commands.append(command) + return "" + + monkeypatch.setattr( + "alpasim_wizard.deployment.slurm.dispatch_command", + fake_dispatch, + ) + + deployment._start_mps_daemon() + deployment._stop_mps_daemon() + + start, stop, cleanup = commands + assert "nvidia-cuda-mps-control -d" in start + assert "CUDA_MPS_PIPE_DIRECTORY=/tmp/nvidia-mps-123" in start + assert f"CUDA_MPS_LOG_DIRECTORY={tmp_path}/mps" in start + assert stop.startswith("echo quit |") + assert cleanup == "rm -rf /tmp/nvidia-mps-123" + + +def test_mps_pipe_dir_cleanup_runs_when_daemon_shutdown_fails( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + deployment = _deployment(tmp_path, enable_mps=True) + commands = [] + + def fake_dispatch(command, *, log_dir, dry_run, blocking): + del log_dir, dry_run, blocking + commands.append(command) + if command.startswith("echo quit |"): + raise RuntimeError("MPS shutdown failed") + return "" + + monkeypatch.setattr( + "alpasim_wizard.deployment.slurm.dispatch_command", + fake_dispatch, + ) + + deployment._stop_mps_daemon() + + assert len(commands) == 2 + assert commands[1] == "rm -rf /tmp/nvidia-mps-123" diff --git a/src/wizard/tests/test_slurm_process_exporter.py b/src/wizard/tests/test_slurm_process_exporter.py index d574b434..a3f9ccf1 100644 --- a/src/wizard/tests/test_slurm_process_exporter.py +++ b/src/wizard/tests/test_slurm_process_exporter.py @@ -7,7 +7,6 @@ import pytest from alpasim_wizard.telemetry.slurm_process_exporter import ( - collect, collect_processes, discover_pids, render_metrics, @@ -133,20 +132,16 @@ def test_render_metrics_omits_unobserved_groups(tmp_path: Path) -> None: tmp_path, "101", cmdline=( - "uv run physics_server --port=6116 " - "--artifact-glob=/mnt/nre-data/**/*.usdz" + "uv run physics_server --port=6116 --artifact-glob=/mnt/nre-data/**/*.usdz" ), utime=100, stime=50, resident_pages=10, + environ=["CUDA_VISIBLE_DEVICES=3"], ) process_samples = collect_processes(tmp_path, {"101"}) - payload = render_metrics( - collect(tmp_path, {"101"}), - duration=0.125, - process_samples=process_samples, - ).decode("utf-8") + payload = render_metrics(process_samples, duration=0.125).decode("utf-8") assert 'namedprocess_namegroup_cpu_seconds_total{groupname="physics"}' in payload assert ( @@ -162,4 +157,5 @@ def test_render_metrics_omits_unobserved_groups(tmp_path: Path) -> None: 'namedprocess_namegroup_memory_bytes{groupname="driver",memtype="resident"}' not in payload ) + assert 'alpasim_gpu_workload_info{gpu="3"} 1' in payload assert "alpasim_slurm_process_exporter_scrape_duration_seconds 0.125" in payload