diff --git a/.agents/skills/upgrade-deps/checklists/sglang.md b/.agents/skills/upgrade-deps/checklists/sglang.md index da6d6ff29b..11c05eb569 100644 --- a/.agents/skills/upgrade-deps/checklists/sglang.md +++ b/.agents/skills/upgrade-deps/checklists/sglang.md @@ -3,10 +3,19 @@ package: sglang github: sgl-project/sglang branch_template: v${VERSION} upstream_paths: + - python/sglang/srt/entrypoints/engine.py + - python/sglang/srt/entrypoints/http_server.py - python/sglang/srt/entrypoints/openai/protocol.py - python/sglang/srt/function_call/function_call_parser.py + - python/sglang/srt/function_call/core_types.py + - python/sglang/srt/managers/scheduler.py + - python/sglang/srt/managers/io_struct.py - python/sglang/srt/parser/reasoning_parser.py - python/sglang/srt/server_args.py + - python/sglang/srt/utils/__init__.py + - python/sglang/srt/utils/common.py + - python/sglang/srt/utils/network.py + - python/sglang/srt/utils/numa_utils.py - python/sglang/launch_server.py --- @@ -14,23 +23,27 @@ upstream_paths: ### Primary (engine layer — most likely to break) -| File | Imports / Usage | -| ----------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `areal/engine/sglang_remote.py` | HTTP-only (no Python imports). Sends requests to `/generate`, `/load_lora_adapter`, `/update_weights_from_disk`, `/update_weights_from_distributed`, `/init_weights_update_group`, `/pause_generation`, `/continue_generation`, `/health`, `/release_memory_occupation`, `/resume_memory_occupation`. Parses `meta_info`, `finish_reason`, `output_token_logprobs`, `routed_experts` from JSON responses. | -| `areal/experimental/openai/tool_call_parser.py` | `sglang.srt.entrypoints.openai.protocol.Function`, `sglang.srt.entrypoints.openai.protocol.Tool`, `sglang.srt.function_call.function_call_parser.FunctionCallParser`, `sglang.srt.parser.reasoning_parser.ReasoningParser` | +| File | Imports / Usage | +| -------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `areal/engine/sglang_remote.py` | HTTP-only (no Python imports). Sends requests to `/generate`, `/load_lora_adapter`, `/update_weights_from_disk`, `/update_weights_from_distributed`, `/init_weights_update_group`, `/pause_generation`, `/continue_generation`, `/health`, `/release_memory_occupation`, `/resume_memory_occupation`. Parses `meta_info`, `finish_reason`, `output_token_logprobs`, `routed_experts` from JSON responses. | +| `areal/experimental/openai/tool_call_parser.py` | `sglang.srt.entrypoints.openai.protocol.Function`, `sglang.srt.entrypoints.openai.protocol.Tool`, `sglang.srt.function_call.function_call_parser.FunctionCallParser`, `sglang.srt.parser.reasoning_parser.ReasoningParser` | +| `areal/experimental/inference_service/sglang/launch_server.py` | `sglang.srt.entrypoints.engine.Engine`, `sglang.srt.entrypoints.engine.init_tokenizer_manager`, `sglang.srt.entrypoints.http_server._execute_server_warmup`, `sglang.srt.entrypoints.http_server._setup_and_run_http_server`, `sglang.srt.entrypoints.http_server.app`, `sglang.srt.managers.detokenizer_manager.run_detokenizer_process` | +| `areal/experimental/inference_service/sglang/scheduler.py` | `sglang.srt.managers.scheduler.Scheduler`, `sglang.srt.managers.scheduler.configure_scheduler`, `sglang.srt.observability.trace.process_tracing_init`, `sglang.srt.observability.trace.trace_set_thread_info`, `sglang.srt.utils.get_bool_env_var`, `sglang.srt.utils.kill_itself_when_parent_died`, `sglang.srt.utils.set_gpu_proc_affinity`, `sglang.srt.utils.numa_utils.get_numa_node_if_available`, `sglang.srt.utils.numa_utils.numa_bind_to_node`, `sglang.srt.environ.envs`, `sglang.utils.get_exception_traceback` | +| `areal/experimental/inference_service/sglang/rpc_proxy.py` | `sglang.srt.managers.io_struct.RpcReqInput`, `sglang.srt.managers.io_struct.RpcReqOutput`, `sglang.srt.server_args.PortArgs`, `sglang.srt.utils.network.get_zmq_socket` | +| `areal/experimental/inference_service/sglang/bridge.py` | HTTP-only (same protocol as `sglang_remote.py`). `/generate` request/response, `/pause_generation`, `/continue_generation`, `/release_memory_occupation`, `/resume_memory_occupation`. | ### Secondary (model / infra layer) -| File | Imports / Usage | -| --------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ | -| `areal/infra/launcher/sglang_server.py` | HTTP-only. Polls `/v1/models` to confirm server readiness. Calls `SGLangConfig.build_cmd()` to construct the server launch command. | -| `areal/api/cli_args.py` | `SGLangConfig.build_cmd()`, `SGLangConfig.build_cmd_from_args()`, `SGLangConfig.build_args()`. Version check against `0.4.9.post2` and `0.4.10.post2`. | -| `areal/trainer/rl_trainer.py` | `SGLangConfig.build_args()` to construct `RemoteSGLangEngine`. | -| `areal/infra/launcher/ray.py` | `SGLangConfig` import + `to_structured_cfg`. | -| `areal/infra/launcher/local.py` | `SGLangConfig` import + `to_structured_cfg`. | -| `areal/infra/launcher/slurm.py` | `SGLangConfig` import + `to_structured_cfg`. | -| `areal/experimental/inference_service/controller/controller.py` | `SGLangConfig` in gateway controller. | -| `areal/experimental/inference_service/data_proxy/backend.py` | HTTP protocol implementation for inference service proxy (SGLangBridgeBackend). | +| File | Imports / Usage | +| --------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------ | +| `areal/infra/launcher/sglang_server.py` | HTTP-only. Polls `/v1/models` to confirm server readiness. Calls `SGLangConfig.build_cmd()` to construct the server launch command. | +| `areal/api/cli_args.py` | `SGLangConfig.build_cmd()`, `SGLangConfig.build_cmd_from_args()`, `SGLangConfig.build_args()`. Version check against `0.5.10.post1`. | +| `areal/trainer/rl_trainer.py` | `SGLangConfig.build_args()` to construct `RemoteSGLangEngine`. | +| `areal/infra/launcher/ray.py` | `SGLangConfig` import + `to_structured_cfg`. | +| `areal/infra/launcher/local.py` | `SGLangConfig` import + `to_structured_cfg`. | +| `areal/infra/launcher/slurm.py` | `SGLangConfig` import + `to_structured_cfg`. | +| `areal/experimental/inference_service/controller/controller.py` | `SGLangConfig` in gateway controller. | +| `areal/experimental/inference_service/data_proxy/backend.py` | HTTP protocol implementation for inference service proxy (SGLangBridgeBackend). | ### Tertiary (tests, config) @@ -398,12 +411,146 @@ added/removed/renamed `argparse` arguments. ______________________________________________________________________ +### 15. `Engine._launch_subprocesses` — server lifecycle + +**Source:** `python/sglang/srt/entrypoints/engine.py` + +Called in `areal/experimental/inference_service/sglang/launch_server.py` +(`areal_launch_server`): + +```python +from sglang.srt.entrypoints.engine import Engine, init_tokenizer_manager + +( + tokenizer_manager, + template_manager, + port_args, + scheduler_init_result, + subprocess_watchdog, +) = Engine._launch_subprocesses( + server_args=server_args, + init_tokenizer_manager_func=init_tokenizer_manager, + run_scheduler_process_func=areal_run_scheduler_process, + run_detokenizer_process_func=run_detokenizer_process, +) +``` + +**Check:** Confirm `_launch_subprocesses` is still a classmethod. Verify it still +accepts `run_scheduler_process_func` as a callable parameter for scheduler process +injection. Verify the return tuple is +`(TokenizerManager, TemplateManager, PortArgs, SchedulerInitResult, SubprocessWatchdog)`. +Confirm `SchedulerInitResult.scheduler_infos` attribute exists. + +______________________________________________________________________ + +### 16. `_setup_and_run_http_server` — HTTP server bootstrap + +**Source:** `python/sglang/srt/entrypoints/http_server.py` + +Called in `areal/experimental/inference_service/sglang/launch_server.py` +(`areal_launch_server`): + +```python +from sglang.srt.entrypoints.http_server import ( + _execute_server_warmup, + _setup_and_run_http_server, + app, +) + +_setup_and_run_http_server( + server_args, + tokenizer_manager, + template_manager, + port_args, + scheduler_init_result.scheduler_infos, + subprocess_watchdog, + execute_warmup_func=_execute_server_warmup, +) +``` + +**Check:** Confirm the function still exists at this module path. Verify signature: +`(server_args, tokenizer_manager, template_manager, port_args, scheduler_infos, subprocess_watchdog, execute_warmup_func, launch_callback)`. +Confirm `app` is still the FastAPI instance exported from this module. + +______________________________________________________________________ + +### 17. `Scheduler` constructor and `configure_scheduler` + +**Source:** `python/sglang/srt/managers/scheduler.py` + +Called in `areal/experimental/inference_service/sglang/scheduler.py` +(`areal_run_scheduler_process`): + +```python +from sglang.srt.managers.scheduler import Scheduler, configure_scheduler + +dp_rank = configure_scheduler( + server_args, tp_rank, attn_cp_rank, moe_dp_rank, moe_ep_rank, pp_rank, dp_rank +) + +scheduler = Scheduler( + server_args, port_args, gpu_id, tp_rank, moe_ep_rank, pp_rank, + attn_cp_rank, moe_dp_rank, dp_rank, +) +pipe_writer.send(scheduler.get_init_info()) +scheduler.run_event_loop() +``` + +**Check:** Confirm `configure_scheduler` signature is +`(server_args, tp_rank, attn_cp_rank, moe_dp_rank, moe_ep_rank, pp_rank, dp_rank)`. +Confirm `Scheduler.__init__` signature is +`(server_args, port_args, gpu_id, tp_rank, moe_ep_rank, pp_rank, attn_cp_rank, moe_dp_rank, dp_rank)`. +Verify `get_init_info()` and `run_event_loop()` still exist. Confirm `tp_rank`, +`dp_rank`, `tp_cpu_group`, `tp_size` attributes are present on the scheduler instance +(used by `AwexSchedulerBridge`). + +______________________________________________________________________ + +### 18. `RpcReqInput` / `RpcReqOutput` — scheduler RPC protocol + +**Source:** `python/sglang/srt/managers/io_struct.py` + +Used in `areal/experimental/inference_service/sglang/rpc_proxy.py`: + +```python +from sglang.srt.managers.io_struct import RpcReqInput, RpcReqOutput + +req = RpcReqInput(method=method, parameters=kwargs if kwargs else None) +self._rpc_socket.send_pyobj(req) +resp: RpcReqOutput = self._rpc_socket.recv_pyobj() +# resp.success: bool, resp.message: str +``` + +**Check:** Confirm `RpcReqInput` still has `method: str` and +`parameters: Optional[Dict]` fields. Confirm `RpcReqOutput` still has `success: bool` +and `message: str` fields. Verify `send_pyobj`/`recv_pyobj` serialization still works +(both inherit from `BaseReq` which is a dataclass). + +______________________________________________________________________ + +### 19. `sglang.srt.utils` module reorganization (v0.5.10+) + +**Source:** `python/sglang/srt/utils/__init__.py`, `python/sglang/srt/utils/common.py`, +`python/sglang/srt/utils/network.py`, `python/sglang/srt/utils/numa_utils.py` + +In v0.5.10+, `sglang.srt.utils/__init__.py` only re-exports from `common.py` via +`from sglang.srt.utils.common import *`. Functions in submodules must be imported +directly: + +- `get_zmq_socket` → `sglang.srt.utils.network` +- `get_numa_node_if_available`, `numa_bind_to_node` → `sglang.srt.utils.numa_utils` +- `kill_itself_when_parent_died`, `get_bool_env_var`, `set_gpu_proc_affinity`, + `kill_process_tree` → `sglang.srt.utils` (via `common.py`) + +**Check:** On each upgrade, verify `sglang.srt.utils/__init__.py` re-export scope. If +functions move between submodules, update AReaL import paths accordingly. + +______________________________________________________________________ + ## Version-Guarded Code -- `areal/api/cli_args.py:1713-1714` — - `if not pkg_version.is_version_greater_or_equal("sglang", "0.4.9.post2"): raise RuntimeError(...)`. - Update this floor version if the new target requires a higher minimum. -- `areal/api/cli_args.py:1715-1716` — - `if is_version_less("sglang", "0.4.10.post2"): args.pop("max_loaded_loras", None)`. - Once the minimum version is raised past `0.4.10.post2`, this guard and the `pop` call - can be removed. +- `areal/api/cli_args.py:1877-1878` — + `if not pkg_version.is_version_greater_or_equal("sglang", "0.5.10.post1"): raise RuntimeError(...)`. + Minimum floor raised from `0.4.9.post2` to `0.5.10.post1` during this upgrade. The + legacy `max_loaded_loras` version guard (`<0.4.10.post2`) was removed because the new + floor is well past that version. diff --git a/.github/workflows/test-areal.yml b/.github/workflows/test-areal.yml index 4eff1cce32..3ebad935ba 100644 --- a/.github/workflows/test-areal.yml +++ b/.github/workflows/test-areal.yml @@ -66,21 +66,20 @@ jobs: github.event_name == 'workflow_dispatch' needs: - determine-variants - name: Provision GCP runner (${{ matrix.variant }} ${{ matrix.test_type }}) + name: Provision GCP runner (${{ matrix.variant }}) runs-on: ubuntu-latest strategy: fail-fast: false matrix: variant: ${{ fromJson(needs.determine-variants.outputs.matrix) }} - test_type: [unit, integration] env: CONTAINER_IMAGE: ghcr.io/inclusionai/areal-runtime:${{ inputs.image_tag || 'dev' }}-${{ matrix.variant }} - RUNNER_LABELS: gcp-a2-highgpu-2g,variant-${{ matrix.variant }},test-type-${{ matrix.test_type }} + RUNNER_LABELS: gcp-a2-highgpu-2g,variant-${{ matrix.variant }} steps: - name: Set instance variables id: vars run: | - echo "instance_name=gcp-runner-${{ github.run_id }}-${{ matrix.variant }}-${{ matrix.test_type }}" >> "$GITHUB_OUTPUT" + echo "instance_name=gcp-runner-${{ github.run_id }}-${{ matrix.variant }}" >> "$GITHUB_OUTPUT" - name: Authenticate to Google Cloud uses: google-github-actions/auth@v3 @@ -287,12 +286,11 @@ jobs: needs: - determine-variants - provision-runner - name: Run AReaL tests (${{ matrix.variant }} ${{ matrix.test_type }}) + name: Run AReaL unit tests (${{ matrix.variant }}) strategy: fail-fast: false matrix: variant: ${{ fromJson(needs.determine-variants.outputs.matrix) }} - test_type: [unit, integration] environment: name: AReaL-unittests permissions: @@ -301,7 +299,6 @@ jobs: - self-hosted - gcp-a2-highgpu-2g - "variant-${{ matrix.variant }}" - - "test-type-${{ matrix.test_type }}" timeout-minutes: 120 env: # Activate the venv created in the Docker image @@ -316,7 +313,6 @@ jobs: python areal/tools/validate_docker_installation.py - name: Run unit tests - if: matrix.test_type == 'unit' env: CI: true HF_TOKEN: ${{ secrets.HF_TOKEN }} @@ -328,32 +324,8 @@ jobs: export PATH="/opt/.venv/bin:$PATH" pytest -m "(not slow or ci) and not ${EXCLUDE_BACKEND}" --durations=20 -s -vv tests/test_*.py tests/experimental/ tests/infra/ - - name: Run SFT integration tests - if: matrix.test_type == 'integration' - env: - CI: true - HF_TOKEN: ${{ secrets.HF_TOKEN }} - PYTHONPATH: ${{ github.workspace }} - TOKENIZERS_PARALLELISM: false - VIRTUAL_ENV: /opt/.venv - run: | - export PATH="/opt/.venv/bin:$PATH" - pytest -m "not ${EXCLUDE_BACKEND}" -s -vv tests/sft/ - - - name: Run GRPO integration tests - if: matrix.test_type == 'integration' - env: - CI: true - HF_TOKEN: ${{ secrets.HF_TOKEN }} - PYTHONPATH: ${{ github.workspace }} - TOKENIZERS_PARALLELISM: false - VIRTUAL_ENV: /opt/.venv - run: | - export PATH="/opt/.venv/bin:$PATH" - pytest -m "not ${EXCLUDE_BACKEND}" -s -vv tests/grpo/ - cleanup: - name: Tear down GCP runner (${{ matrix.variant }} ${{ matrix.test_type }}) + name: Tear down GCP runner (${{ matrix.variant }}) needs: - determine-variants - unit-tests @@ -364,7 +336,6 @@ jobs: fail-fast: false matrix: variant: ${{ fromJson(needs.determine-variants.outputs.matrix) }} - test_type: [unit, integration] steps: - name: Authenticate to Google Cloud uses: google-github-actions/auth@v3 @@ -376,7 +347,7 @@ jobs: - name: Delete runner instance env: - INSTANCE_NAME: gcp-runner-${{ github.run_id }}-${{ matrix.variant }}-${{ matrix.test_type }} + INSTANCE_NAME: gcp-runner-${{ github.run_id }}-${{ matrix.variant }} run: | # Look up instance zone dynamically since matrix job outputs # cannot be consumed per-element by downstream matrix jobs. diff --git a/Dockerfile b/Dockerfile index ff35204b79..7c3e1f8239 100644 --- a/Dockerfile +++ b/Dockerfile @@ -6,47 +6,32 @@ # docker build -t areal-runtime:dev-sglang . # default (sglang) # docker build --build-arg VARIANT=vllm -t areal-runtime:dev-vllm . # vllm variant -FROM lmsysorg/sglang:v0.5.9-cu129-amd64-runtime +# ============================================================ +# BUILDER STAGE: compile C++ extensions and install all deps +# ============================================================ +FROM lmsysorg/sglang:v0.5.10.post1-runtime AS builder # Inference backend selector: sglang (default) or vllm -# Declared early so torch version and C++ builds match the chosen backend. ARG VARIANT=sglang WORKDIR / ENV DEBIAN_FRONTEND=noninteractive -# Install system dependencies +# Build-time system dependencies (includes compilers + dev headers) RUN apt-get update && apt-get install -y --no-install-recommends \ ca-certificates \ - net-tools \ - unzip \ - kmod \ - ccache \ cmake \ + ccache \ + kmod \ libibverbs-dev \ librdmacm-dev \ - ibverbs-utils \ - rdmacm-utils \ - python3-pyverbs \ - opensm \ - ibutils \ - perftest \ - python3-venv \ - tmux \ - lsof \ - nvtop \ - rsync \ - dnsutils \ - vim \ && apt-get clean \ && rm -rf /var/lib/apt/lists/* -# Update pip and install uv +# Install pip and uv RUN pip install -U pip uv -WORKDIR /AReaL - # Enable bytecode compilation ENV UV_COMPILE_BYTECODE=1 @@ -56,19 +41,19 @@ ENV UV_LINK_MODE=copy # Ensure installed tools can be executed out of the box ENV UV_TOOL_BIN_DIR=/usr/local/bin -# Environment variables for build configuration +# Build-time environment variables ENV NVTE_WITH_USERBUFFERS=1 ENV NVTE_FRAMEWORK=pytorch ENV MPI_HOME=/usr/local/mpi ENV TORCH_CUDA_ARCH_LIST="8.0 8.9 9.0 9.0a" ENV MAX_JOBS=32 -# Set VIRTUAL_ENV so uv pip install targets the venv created below +# Set VIRTUAL_ENV so uv pip install targets the venv ENV VIRTUAL_ENV=/opt/.venv +ENV CUDA_HOME=/usr/local/cuda ############################################################## -# STAGE 1: Install base torch FIRST -# Torch version depends on VARIANT (sglang and vllm require different versions) +# Install base torch (version is variant-specific) ############################################################## # Create venv and install torch with CUDA support @@ -78,21 +63,21 @@ RUN uv venv $VIRTUAL_ENV \ && uv pip install --index-url https://download.pytorch.org/whl/cu129 \ "torch==${TORCH_VER}+cu129" "torchaudio" "torchvision" -RUN uv pip install "setuptools>=77.0.3,<80" pybind11 nvidia-mathdx +RUN uv pip install "setuptools>=77.0.3,<80" pybind11 nvidia-mathdx wheel ############################################################## -# STAGE 2: Install heavy C++ dependencies BEFORE uv sync +# Install heavy C++ dependencies # These require only torch and rarely change. # Moving these BEFORE uv sync prevents recompilation when # pyproject.toml/uv.lock changes (C++ packages stay cached). ############################################################## # Install torch memory saver -RUN uv pip install --no-build-isolation --no-cache-dir --force-reinstall \ +RUN TMS_CUDA_MAJOR=12 uv pip install --no-build-isolation --no-cache-dir --force-reinstall \ git+https://github.com/fzyzcjy/torch_memory_saver.git # Install grouped_gemm (for MoE models) -RUN uv pip install --no-build-isolation \ +RUN uv pip install --no-build-isolation --no-cache-dir \ git+https://github.com/fanshiqing/grouped_gemm@v1.1.4 # Install apex (NVIDIA apex for mixed precision training) @@ -101,47 +86,38 @@ RUN NVCC_APPEND_FLAGS="--threads 4" APEX_PARALLEL_BUILD=8 APEX_CPP_EXT=1 APEX_CU git+https://github.com/NVIDIA/apex.git # Install transformer engine (for FP8 training) -RUN uv pip -v install --no-build-isolation \ +RUN uv pip -v install --no-build-isolation --no-cache-dir \ git+https://github.com/NVIDIA/TransformerEngine.git@stable -ENV CUDA_HOME=/usr/local/cuda - # FlashMLA (Multi-head Latent Attention for DeepSeek-V3) RUN git clone https://github.com/deepseek-ai/FlashMLA.git /flash-mla \ - && cd /flash-mla \ + && cd /flash-mla && git checkout 71c7379 \ && git submodule update --init --recursive \ - && uv pip install -v . --no-build-isolation \ + && uv pip install -v . --no-build-isolation --no-cache-dir \ && rm -rf /flash-mla # DeepGEMM (FP8 GEMM library for DeepSeek-V3) RUN git clone https://github.com/deepseek-ai/DeepGEMM /DeepGEMM \ - && cd /DeepGEMM \ + && cd /DeepGEMM && git checkout d30fc36 \ && git submodule update --init --recursive \ - && uv pip install -v . --no-build-isolation \ + && uv pip install -v . --no-build-isolation --no-cache-dir \ && rm -rf /DeepGEMM # DeepEP (Expert Parallelism communication library for MoE) # Note: TORCH_CUDA_ARCH_LIST="9.0" enables SM90 features and aggressive PTX instructions # The NVSHMEM path is auto-detected from nvidia.nvshmem module installed above RUN git clone https://github.com/deepseek-ai/DeepEP /DeepEP \ - && cd /DeepEP \ - && TORCH_CUDA_ARCH_LIST="9.0 9.0a" uv pip install -v . --no-build-isolation \ + && cd /DeepEP && git checkout 567632d \ + && TORCH_CUDA_ARCH_LIST="9.0 9.0a" uv pip install -v . --no-build-isolation --no-cache-dir \ && rm -rf /DeepEP # conv1d, required by Qwen-3.5 RUN git clone https://github.com/Dao-AILab/causal-conv1d -b v1.6.0 /causal-conv1d \ && cd /causal-conv1d \ - && uv pip install -v . --no-build-isolation \ + && uv pip install -v . --no-build-isolation --no-cache-dir \ && rm -rf /causal-conv1d -# flash-linear-attention (pure Triton kernels, no CUDA extensions) -RUN git clone https://github.com/fla-org/flash-linear-attention /flash-linear-attention \ - && cd /flash-linear-attention \ - && uv pip install -v . \ - && rm -rf /flash-linear-attention - # flash-attn 2: download pre-built wheel, strip local version, repack & install -RUN uv pip install wheel # ensure wheel is available for repacking RUN set -ex \ && FA_VER="2.8.3" \ && FA_RELEASE="v0.7.16" \ @@ -182,35 +158,7 @@ RUN set -ex \ && touch "$SITE_PKG/__init__.py" ############################################################## -# STAGE 2.5: Install Node.js and npm-based tools -############################################################## - -# Install Node.js via fnm and Claude Code -ENV FNM_DIR=/root/.fnm -ENV NODE_VERSION=24.13.0 -ENV PATH="$FNM_DIR/aliases/default/bin:/root/.local/bin:$PATH" -RUN set -ex \ - && curl -fsSL https://fnm.vercel.app/install | bash -s -- --install-dir "$FNM_DIR" --skip-shell \ - && eval "$($FNM_DIR/fnm env --shell bash)" \ - && $FNM_DIR/fnm install $NODE_VERSION \ - && $FNM_DIR/fnm default $NODE_VERSION \ - && npm install -g npm@latest \ - && npm install -g @openai/codex @google/gemini-cli openclaw@latest \ - && curl -fsSL https://claude.ai/install.sh | bash \ - && curl -fsSL https://opencode.ai/install | bash \ - && uv pip install nanobot-ai - -ENV PATH="/root/.cargo/bin:$PATH" -ARG IRONCLAW_VERSION=0.24.0 -RUN curl --proto '=https' --tlsv1.2 -LsSf \ - https://github.com/nearai/ironclaw/releases/download/ironclaw-v${IRONCLAW_VERSION}/ironclaw-installer.sh | sh -RUN curl -fsSL \ - https://github.com/zeroclaw-labs/zeroclaw/releases/latest/download/install.sh \ - | bash -s -- --skip-onboard - -############################################################## -# STAGE 3: Install project dependencies from pyproject.toml -# Changes to pyproject.toml/uv.lock will invalidate from here +# Install project dependencies from pyproject.toml # --active: target the existing $VIRTUAL_ENV instead of creating a new .venv # --inexact: keep C++ packages (apex, flash-attn, etc.) not tracked in the lockfile # --no-install-project: install dependencies only, not the areal package itself @@ -229,24 +177,98 @@ RUN --mount=type=cache,target=/root/.cache/uv \ && uv sync --active --inexact --no-install-project --no-build-isolation \ --extra cuda --extra sandbox --group dev --project "$PROJECT_DIR" -############################################################## -# STAGE 4: Misc fixes and final setup -############################################################## - -# Misc fixes +# Misc fixes (apply in builder so the venv is clean when copied) RUN uv pip uninstall pynvml -# Update setuptools to fix a wandb bug -# Install nvidia-ml-py to replace pynvml -RUN uv pip install -U setuptools nvidia-ml-py +# Update setuptools to fix a wandb bug; install nvidia-ml-py to replace pynvml +RUN uv pip install --no-cache-dir -U setuptools nvidia-ml-py + +# ============================================================ +# RUNTIME STAGE: lean final image (no build tools, no source +# checkouts, no intermediate compilation artifacts) +# ============================================================ +FROM lmsysorg/sglang:v0.5.10.post1-runtime + +ARG VARIANT=sglang + +WORKDIR / + +ENV DEBIAN_FRONTEND=noninteractive + +# Runtime-only system dependencies (no cmake, ccache — build tools stay in builder) +RUN apt-get update && apt-get install -y --no-install-recommends \ + ca-certificates \ + net-tools \ + unzip \ + kmod \ + libibverbs-dev \ + librdmacm-dev \ + ibverbs-utils \ + rdmacm-utils \ + python3-pyverbs \ + opensm \ + ibutils \ + perftest \ + python3-venv \ + tmux \ + lsof \ + nvtop \ + rsync \ + dnsutils \ + vim \ + && apt-get clean \ + && rm -rf /var/lib/apt/lists/* # Remove libcudnn9 to avoid conflicts with torch RUN apt-get --purge remove -y --allow-change-held-packages libcudnn9* \ && apt-get autoremove -y \ && rm -rf /var/lib/apt/lists/* +# Install pip and uv (needed for editable install and nanobot-ai) +RUN pip install --no-cache-dir -U pip uv + +WORKDIR /AReaL + +# Runtime environment variables +ENV UV_COMPILE_BYTECODE=1 +ENV UV_LINK_MODE=copy +ENV UV_TOOL_BIN_DIR=/usr/local/bin +ENV NVTE_WITH_USERBUFFERS=1 +ENV NVTE_FRAMEWORK=pytorch +ENV MPI_HOME=/usr/local/mpi +ENV VIRTUAL_ENV=/opt/.venv +ENV CUDA_HOME=/usr/local/cuda + +# Copy the fully-built venv from builder (all C++ extensions included) +COPY --from=builder /opt/.venv /opt/.venv + +############################################################## +# Install Node.js and npm-based tools +############################################################## + +# Install Node.js via fnm and Claude Code +ENV FNM_DIR=/root/.fnm +ENV NODE_VERSION=24.13.0 +ENV PATH="$FNM_DIR/aliases/default/bin:/root/.local/bin:$PATH" +RUN set -ex \ + && curl -fsSL https://fnm.vercel.app/install | bash -s -- --install-dir "$FNM_DIR" --skip-shell \ + && eval "$($FNM_DIR/fnm env --shell bash)" \ + && $FNM_DIR/fnm install $NODE_VERSION \ + && $FNM_DIR/fnm default $NODE_VERSION \ + && npm install -g npm@latest \ + && npm install -g @openai/codex @google/gemini-cli openclaw@latest \ + && curl -fsSL https://claude.ai/install.sh | bash \ + && curl -fsSL https://opencode.ai/install | bash \ + && npm cache clean --force \ + && rm -rf /root/.cache/uv /root/.cache/pip /tmp/* + +ENV PATH="/root/.cargo/bin:$PATH" +RUN curl -fsSL \ + https://github.com/zeroclaw-labs/zeroclaw/releases/latest/download/install.sh \ + | bash -s -- --skip-onboard \ + && rm -rf /tmp/* + ############################################################## -# STAGE 5: Install AReaL from local source -# This is last so code changes don't invalidate C++ builds +# Install AReaL from local source (last for fast iteration) ############################################################## # Copy AReaL source code from build context (checked out by CI) @@ -254,7 +276,7 @@ COPY . /AReaL # Install areal package in editable mode without dependencies # Using pip install instead of uv sync to avoid overwriting C++ packages -RUN uv pip install --no-deps -e /AReaL +RUN uv pip install --no-cache-dir --no-deps -e /AReaL # Place executables in the environment at the front of the path ENV PATH="$VIRTUAL_ENV/bin:$PATH" diff --git a/areal/api/cli_args.py b/areal/api/cli_args.py index 58b763bdb5..9d01060df8 100644 --- a/areal/api/cli_args.py +++ b/areal/api/cli_args.py @@ -26,7 +26,6 @@ PROX_LOGP_METHOD_RECOMPUTE, PROX_LOGP_METHODS_ALL, ) -from areal.utils.pkg_version import is_version_less from areal.utils.seqpack import PACKING_ALGORITHMS if TYPE_CHECKING: @@ -1631,7 +1630,6 @@ class vLLMConfig: max_num_seqs: int = 256 # kv_cache_type: str = "auto" block_size: int = 16 - swap_space: int = 4 cpu_offload_gb: float = 0 disable_sliding_window: bool = True max_model_len: int | None = 32768 @@ -1874,10 +1872,8 @@ def build_args( args["host"] = host if port is not None: args["port"] = port - if not pkg_version.is_version_greater_or_equal("sglang", "0.4.9.post2"): - raise RuntimeError("Needs sglang>=0.4.9.post2 to run the code.") - if is_version_less("sglang", "0.4.10.post2"): - args.pop("max_loaded_loras", None) + if not pkg_version.is_version_greater_or_equal("sglang", "0.5.10.post1"): + raise RuntimeError("Needs sglang>=0.5.10.post1 to run the code.") return args diff --git a/areal/api/reward_api.py b/areal/api/reward_api.py index a1b4564618..3cf32984ea 100644 --- a/areal/api/reward_api.py +++ b/areal/api/reward_api.py @@ -157,9 +157,16 @@ async def __call__(self, *args, **kwargs) -> float: ) return reward except TimeoutError: + last_exception = TimeoutError( + f"Reward computation timed out after {self.timeout_seconds}s" + ) logger.warning( - f"Computing reward timeout after {self.timeout_seconds}s. Set reward to 0." + f"Computing reward timeout after {self.timeout_seconds}s " + f"(attempt {attempt + 1}/{self.max_retries + 1}). " + f"{'Retrying...' if attempt < self.max_retries else 'Returning 0.'}" ) + if attempt < self.max_retries: + continue return 0 except BrokenProcessPool as e: last_exception = e diff --git a/areal/dataset/clevr_count_70k.py b/areal/dataset/clevr_count_70k.py index 6ef9517259..7c59d1613b 100644 --- a/areal/dataset/clevr_count_70k.py +++ b/areal/dataset/clevr_count_70k.py @@ -107,6 +107,7 @@ def _process(example): ) example["input_ids"] = processed_input["input_ids"].squeeze(0) + example["mm_token_type_ids"] = processed_input.get("token_type_ids", None) multi_modal_input = {} multi_modal_input["pixel_values"] = processed_input["pixel_values"] if "image_grid_thw" in processed_input: diff --git a/areal/dataset/geometry3k.py b/areal/dataset/geometry3k.py index bb96ba24b7..614bff06ae 100644 --- a/areal/dataset/geometry3k.py +++ b/areal/dataset/geometry3k.py @@ -96,6 +96,7 @@ def _process(example): ) example["input_ids"] = processed_input["input_ids"].squeeze(0) + example["mm_token_type_ids"] = processed_input.get("token_type_ids", None) multi_modal_input = {} multi_modal_input["pixel_values"] = processed_input["pixel_values"] if "image_grid_thw" in processed_input: diff --git a/areal/engine/fsdp_engine.py b/areal/engine/fsdp_engine.py index c22667d9d0..51de87ebb1 100644 --- a/areal/engine/fsdp_engine.py +++ b/areal/engine/fsdp_engine.py @@ -1633,11 +1633,14 @@ def _prepare_mb_list(self, input_: dict[str, Any]) -> MicroBatchList: if video_grid_thw_list: video_grid_thw = torch.cat(video_grid_thw_list) - position_ids, _ = self.model.model.get_rope_index( + position_ids = self.model.model.compute_3d_position_ids( input_ids=input_ids, image_grid_thw=image_grid_thw, video_grid_thw=video_grid_thw, attention_mask=attn_mask, + mm_token_type_ids=input_["mm_token_type_ids"], + inputs_embeds=None, + past_key_values=None, ) position_ids = torch.einsum("ijk->jki", position_ids) input_["position_ids"] = position_ids diff --git a/areal/engine/vllm_ext/areal_vllm_server.py b/areal/engine/vllm_ext/areal_vllm_server.py index c15cfb8c14..fde1c4a299 100644 --- a/areal/engine/vllm_ext/areal_vllm_server.py +++ b/areal/engine/vllm_ext/areal_vllm_server.py @@ -365,10 +365,12 @@ async def create_completion(request: CompletionRequest, raw_request: Request): # entrypoints. import vllm.entrypoints.openai.api_server as _api_server_module - def _areal_build_app(args, supported_tasks=None): + def _areal_build_app(args, supported_tasks=None, model_config=None): """Monkey-patched build_app that replaces vLLM's /v1/completions route with AReaL's wrapped version and adds AReaL custom endpoints.""" - app = _original_build_app(args, supported_tasks=supported_tasks) + app = _original_build_app( + args, supported_tasks=supported_tasks, model_config=model_config + ) # Remove vLLM's /v1/completions POST route so AReaL's takes precedence app.router.routes = [ route diff --git a/areal/engine/vllm_ext/vllm_worker_extension.py b/areal/engine/vllm_ext/vllm_worker_extension.py index 30f762329c..60c70b299a 100644 --- a/areal/engine/vllm_ext/vllm_worker_extension.py +++ b/areal/engine/vllm_ext/vllm_worker_extension.py @@ -1,6 +1,7 @@ # SPDX-License-Identifier: Apache-2.0 import traceback +from contextlib import contextmanager import torch import torch.distributed as dist @@ -10,6 +11,15 @@ from vllm.lora.request import LoRARequest from vllm.model_executor.model_loader import get_model_loader +try: + from vllm.config import set_current_vllm_config +except ImportError: + # vLLM < 0.19 does not require an explicit config context for weight loading. + @contextmanager + def set_current_vllm_config(*_args, **_kwargs): + yield + + from areal.engine.core.distributed import init_custom_process_group from areal.infra.platforms import current_platform from areal.utils.constants import DIST_GROUP_DEFAULT_TIMEOUT @@ -33,9 +43,10 @@ def areal_update_weights(self, model_path): self.model_runner.model_config.model = model_path model_loader = get_model_loader(self.model_runner.vllm_config.load_config) logger.info("Reloading weights inplace...") - model_loader.load_weights( - self.model_runner.model, model_config=self.model_runner.model_config - ) + with set_current_vllm_config(self.model_runner.vllm_config): + model_loader.load_weights( + self.model_runner.model, model_config=self.model_runner.model_config + ) self.sync() return True, "Success" @@ -65,7 +76,8 @@ def areal_update_weights_lora( base_model_name=base_model_name, ) logger.info(f"Reloading lora weights with request {lora_request}") - self.model_runner.add_lora(lora_request) + with set_current_vllm_config(self.model_runner.vllm_config): + self.model_runner.add_lora(lora_request) self.sync() return True, "Success" @@ -143,7 +155,8 @@ def areal_update_weight_xccl(self): group=group, async_op=False, ) - self.model_runner.model.load_weights(weights=[(name, tensor)]) + with set_current_vllm_config(self.model_runner.vllm_config): + self.model_runner.model.load_weights(weights=[(name, tensor)]) self.sync() return True, "Success" except Exception as e: @@ -269,10 +282,13 @@ def areal_update_weight_lora_xccl(self): self.model_runner.lora_manager.remove_adapter(lora_int_id) - self.model_runner.lora_manager._adapter_manager._add_adapter(new_lora_model) - self.model_runner.lora_manager._adapter_manager.activate_adapter( - new_lora_model.id - ) + with set_current_vllm_config(self.model_runner.vllm_config): + self.model_runner.lora_manager._adapter_manager._add_adapter( + new_lora_model + ) + self.model_runner.lora_manager._adapter_manager.activate_adapter( + new_lora_model.id + ) logger.info( f"Updated New LoRA model with {len(new_lora_model.loras)} LoRA modules " f"from {len(merged_weights)} tensors across {len(self.weight_update_groups)} groups" diff --git a/areal/experimental/inference_service/sglang/launch_server.py b/areal/experimental/inference_service/sglang/launch_server.py index 2fdbbc2a47..aa427072ac 100644 --- a/areal/experimental/inference_service/sglang/launch_server.py +++ b/areal/experimental/inference_service/sglang/launch_server.py @@ -15,27 +15,13 @@ def areal_launch_server(server_args) -> None: - import uvicorn - from sglang.srt.entrypoints.engine import ( - _launch_subprocesses, - run_detokenizer_process, - ) + from sglang.srt.entrypoints.engine import Engine, init_tokenizer_manager from sglang.srt.entrypoints.http_server import ( _execute_server_warmup, - _GlobalState, - add_prometheus_track_response_middleware, + _setup_and_run_http_server, app, - app_has_admin_force_endpoints, - set_global_state, - set_uvicorn_logging_configs, - ) - from sglang.srt.managers.multi_tokenizer_mixin import ( - monkey_patch_uvicorn_multiprocessing, - write_data_for_multi_tokenizer, - ) - from sglang.srt.model_loader.remote_instance_weight_loader_utils import ( - parse_remote_instance_transfer_engine_info_from_scheduler_infos, ) + from sglang.srt.managers.detokenizer_manager import run_detokenizer_process # ---- BEGIN AREAL ---- from areal.experimental.inference_service.sglang.awex import ( @@ -48,24 +34,23 @@ def areal_launch_server(server_args) -> None: ) # ---- END AREAL ---- - try: - from sglang.srt.entrypoints.engine import init_tokenizer_manager - except ImportError: - init_tokenizer_manager = None - # ---- BEGIN AREAL ---- result_ipc = create_result_ipc() # ---- END AREAL ---- - tokenizer_manager, template_manager, scheduler_infos, port_args = ( - _launch_subprocesses( - server_args=server_args, - init_tokenizer_manager_func=init_tokenizer_manager, - # ---- BEGIN AREAL ---- - run_scheduler_process_func=areal_run_scheduler_process, - # ---- END AREAL ---- - run_detokenizer_process_func=run_detokenizer_process, - ) + ( + tokenizer_manager, + template_manager, + port_args, + scheduler_init_result, + subprocess_watchdog, + ) = Engine._launch_subprocesses( + server_args=server_args, + init_tokenizer_manager_func=init_tokenizer_manager, + # ---- BEGIN AREAL ---- + run_scheduler_process_func=areal_run_scheduler_process, + # ---- END AREAL ---- + run_detokenizer_process_func=run_detokenizer_process, ) # ---- BEGIN AREAL ---- @@ -73,77 +58,21 @@ def areal_launch_server(server_args) -> None: return # ---- END AREAL ---- - remote_instance_transfer_engine_info = ( - parse_remote_instance_transfer_engine_info_from_scheduler_infos(scheduler_infos) - ) - - set_global_state( - _GlobalState( - tokenizer_manager=tokenizer_manager, - template_manager=template_manager, - scheduler_info=scheduler_infos[0], - remote_instance_transfer_engine_info=remote_instance_transfer_engine_info, - ) - ) - # ---- BEGIN AREAL ---- rpc_proxy = RpcProxy(port_args, result_ipc) register_awex_endpoints(app, rpc_proxy) # ---- END AREAL ---- - if server_args.enable_metrics: - add_prometheus_track_response_middleware(app) - - if server_args.tokenizer_worker_num == 1: - app.is_single_tokenizer_mode = True - app.server_args = server_args - app.warmup_thread_kwargs = dict( - server_args=server_args, - launch_callback=None, + try: + _setup_and_run_http_server( + server_args, + tokenizer_manager, + template_manager, + port_args, + scheduler_init_result.scheduler_infos, + subprocess_watchdog, execute_warmup_func=_execute_server_warmup, ) - - if ( - server_args.api_key - or server_args.admin_api_key - or app_has_admin_force_endpoints(app) - ): - from sglang.srt.utils.auth import add_api_key_middleware - - add_api_key_middleware( - app, - api_key=server_args.api_key, - admin_api_key=server_args.admin_api_key, - ) - else: - app.is_single_tokenizer_mode = False - write_data_for_multi_tokenizer(port_args, server_args, scheduler_infos[0]) - - try: - set_uvicorn_logging_configs(server_args) - - if server_args.tokenizer_worker_num == 1: - uvicorn.run( - app, - host=server_args.host, - port=server_args.port, - root_path=server_args.fastapi_root_path, - log_level=server_args.log_level_http or server_args.log_level, - timeout_keep_alive=5, - loop="uvloop", - ) - else: - monkey_patch_uvicorn_multiprocessing() - uvicorn.run( - "sglang.srt.entrypoints.http_server:app", - host=server_args.host, - port=server_args.port, - root_path=server_args.fastapi_root_path, - log_level=server_args.log_level_http or server_args.log_level, - timeout_keep_alive=5, - loop="uvloop", - workers=server_args.tokenizer_worker_num, - ) finally: # ---- BEGIN AREAL ---- rpc_proxy.close() diff --git a/areal/experimental/inference_service/sglang/rpc_proxy.py b/areal/experimental/inference_service/sglang/rpc_proxy.py index ded471a782..547eb1374b 100644 --- a/areal/experimental/inference_service/sglang/rpc_proxy.py +++ b/areal/experimental/inference_service/sglang/rpc_proxy.py @@ -22,7 +22,7 @@ class RpcProxy: """ def __init__(self, port_args: PortArgs, result_ipc: str) -> None: - from sglang.srt.utils import get_zmq_socket + from sglang.srt.utils.network import get_zmq_socket self._rpc_ctx = zmq.Context(1) self._rpc_socket = get_zmq_socket( @@ -36,7 +36,7 @@ def __init__(self, port_args: PortArgs, result_ipc: str) -> None: def collective_rpc(self, method: str, **kwargs: Any) -> None: req = RpcReqInput(method=method, parameters=kwargs if kwargs else None) self._rpc_socket.send_pyobj(req) - resp: RpcReqOutput = self._rpc_socket.recv_pyobj(zmq.BLOCKY) + resp: RpcReqOutput = self._rpc_socket.recv_pyobj() assert isinstance(resp, RpcReqOutput) if not resp.success: raise RuntimeError(f"RPC {method} failed: {resp.message}") diff --git a/areal/experimental/inference_service/sglang/scheduler.py b/areal/experimental/inference_service/sglang/scheduler.py index 92507208be..7d8b3a86d9 100644 --- a/areal/experimental/inference_service/sglang/scheduler.py +++ b/areal/experimental/inference_service/sglang/scheduler.py @@ -3,6 +3,7 @@ from __future__ import annotations +import logging import os import tempfile from typing import Any @@ -146,66 +147,42 @@ def areal_run_scheduler_process( Only delta vs upstream: After ``Scheduler()`` creation → ``AwexSchedulerBridge(scheduler).bind()`` """ - import faulthandler - import logging as _logging import signal import psutil - import setproctitle - from sglang.srt.disaggregation.utils import DisaggregationMode from sglang.srt.environ import envs - from sglang.srt.managers.scheduler import Scheduler - from sglang.srt.tracing.trace import process_tracing_init, trace_set_thread_info + from sglang.srt.managers.scheduler import Scheduler, configure_scheduler + from sglang.srt.observability.trace import ( + process_tracing_init, + trace_set_thread_info, + ) from sglang.srt.utils import ( - configure_logger, get_bool_env_var, kill_itself_when_parent_died, - numa_bind_to_node, set_gpu_proc_affinity, - suppress_other_loggers, + ) + from sglang.srt.utils.numa_utils import ( + get_numa_node_if_available, + numa_bind_to_node, ) from sglang.utils import get_exception_traceback - logger = _logging.getLogger(__name__) - - # Generate the logger prefix - prefix = "" - if dp_rank is None and "SGLANG_DP_RANK" in os.environ: - # [For Router] if env var "SGLANG_DP_RANK" exist, set dp_rank to - # the value of the env var - dp_rank = int(os.environ["SGLANG_DP_RANK"]) - if dp_rank is not None: - prefix += f" DP{dp_rank}" - if server_args.pp_size > 1: - prefix += f" PP{pp_rank}" - if server_args.attn_cp_size > 1: - prefix += f" ATTN_CP{attn_cp_rank}" - if server_args.moe_dp_size > 1: - prefix += f" MOE_DP{moe_dp_rank}" - if server_args.tp_size > 1: - prefix += f" TP{tp_rank}" - if server_args.ep_size > 1: - prefix += f" EP{moe_ep_rank}" - - # Config the process - setproctitle.setproctitle(f"sglang::scheduler{prefix.replace(' ', '_')}") - faulthandler.enable() + logger = logging.getLogger(__name__) + dp_rank = configure_scheduler( + server_args, tp_rank, attn_cp_rank, moe_dp_rank, moe_ep_rank, pp_rank, dp_rank + ) + kill_itself_when_parent_died() parent_process = psutil.Process().parent() - # Configure the logger - configure_logger(server_args, prefix=prefix) - suppress_other_loggers() - # Set cpu affinity to this gpu process if get_bool_env_var("SGLANG_SET_CPU_AFFINITY"): set_gpu_proc_affinity( server_args.pp_size, server_args.tp_size, server_args.nnodes, gpu_id ) - if ( - numa_node := server_args.numa_node - ) is not None and not envs.SGLANG_NUMA_BIND_V2.get(): - numa_bind_to_node(numa_node[gpu_id]) + numa_node = get_numa_node_if_available(server_args, gpu_id) + if numa_node is not None and not envs.SGLANG_NUMA_BIND_V2.get(): + numa_bind_to_node(numa_node) # Set up tracing if server_args.enable_trace: @@ -235,51 +212,8 @@ def areal_run_scheduler_process( AwexSchedulerBridge(scheduler).bind() # ---- END AREAL ---- - result_dict = { - "status": "ready", - "max_total_num_tokens": scheduler.max_total_num_tokens, - "max_req_input_len": scheduler.max_req_input_len, - } - if server_args.remote_instance_weight_loader_use_transfer_engine(): - ( - remote_instance_transfer_engine_session_id, - remote_instance_transfer_engine_weights_info_dict, - ) = scheduler.get_remote_instance_transfer_engine_info() - result_dict.update( - { - "tp_rank": tp_rank, - "remote_instance_transfer_engine_session_id": remote_instance_transfer_engine_session_id, - "remote_instance_transfer_engine_weights_info_dict": remote_instance_transfer_engine_weights_info_dict, - } - ) - - pipe_writer.send(result_dict) - - # Dispatch to the appropriate event loop based on the disaggregation mode - disaggregation_mode: DisaggregationMode = scheduler.disaggregation_mode - if disaggregation_mode == DisaggregationMode.NULL: - if scheduler.enable_pdmux: - scheduler.event_loop_pdmux() - elif server_args.pp_size > 1: - scheduler.event_loop_pp() - elif scheduler.enable_overlap: - scheduler.event_loop_overlap() - else: - scheduler.event_loop_normal() - elif disaggregation_mode == DisaggregationMode.PREFILL: - if server_args.pp_size > 1: - scheduler.event_loop_pp_disagg_prefill() - elif scheduler.enable_overlap: - scheduler.event_loop_overlap_disagg_prefill() - else: - scheduler.event_loop_normal_disagg_prefill() - elif disaggregation_mode == DisaggregationMode.DECODE: - if server_args.pp_size > 1: - scheduler.event_loop_pp_disagg_decode() - elif scheduler.enable_overlap: - scheduler.event_loop_overlap_disagg_decode() - else: - scheduler.event_loop_normal_disagg_decode() + pipe_writer.send(scheduler.get_init_info()) + scheduler.run_event_loop() except Exception: traceback = get_exception_traceback() diff --git a/areal/experimental/models/archon/base.py b/areal/experimental/models/archon/base.py index 2a5b56d6b6..824bb87f18 100644 --- a/areal/experimental/models/archon/base.py +++ b/areal/experimental/models/archon/base.py @@ -30,6 +30,20 @@ class BaseModelArgs(ABC): # Attention backend type: "sdpa" or "varlen" attn_type: str = "varlen" + @staticmethod + def _get_rope_theta(hf_config: PretrainedConfig, default: float = 10000.0) -> float: + """Extract rope_theta from HF config, compatible with transformers v4 and v5+. + + In transformers v5+, rope_theta was moved from a direct config attribute + into the rope_parameters dict. This helper checks both locations. + """ + # v5+: rope_theta lives inside rope_parameters dict + rope_params = getattr(hf_config, "rope_parameters", None) or {} + if "rope_theta" in rope_params: + return rope_params["rope_theta"] + # v4: rope_theta is a direct attribute + return getattr(hf_config, "rope_theta", default) + @classmethod @abstractmethod def from_hf_config( diff --git a/areal/experimental/models/archon/qwen2/model/args.py b/areal/experimental/models/archon/qwen2/model/args.py index 2afcca7061..928c434d79 100644 --- a/areal/experimental/models/archon/qwen2/model/args.py +++ b/areal/experimental/models/archon/qwen2/model/args.py @@ -57,7 +57,7 @@ def from_hf_config( ), hidden_dim=hf_config.intermediate_size, norm_eps=hf_config.rms_norm_eps, - rope_theta=getattr(hf_config, "rope_theta", 10000.0), + rope_theta=cls._get_rope_theta(hf_config, default=10000.0), max_seq_len=getattr(hf_config, "max_position_embeddings", 32768), attention_bias=getattr(hf_config, "attention_bias", True), eos_id=getattr(hf_config, "eos_token_id", 151645), diff --git a/areal/experimental/models/archon/qwen3/model/args.py b/areal/experimental/models/archon/qwen3/model/args.py index f539c9dacc..2523e3a606 100644 --- a/areal/experimental/models/archon/qwen3/model/args.py +++ b/areal/experimental/models/archon/qwen3/model/args.py @@ -94,7 +94,7 @@ def from_hf_config( ), hidden_dim=hf_config.intermediate_size, norm_eps=hf_config.rms_norm_eps, - rope_theta=getattr(hf_config, "rope_theta", 1000000.0), + rope_theta=cls._get_rope_theta(hf_config, default=1000000.0), qk_norm=getattr(hf_config, "qk_norm", True), max_seq_len=getattr(hf_config, "max_position_embeddings", 4096), eos_id=getattr(hf_config, "eos_token_id", 151645), diff --git a/areal/experimental/models/archon/qwen3_5/model/args.py b/areal/experimental/models/archon/qwen3_5/model/args.py index fa653f3ca4..7368b8bded 100644 --- a/areal/experimental/models/archon/qwen3_5/model/args.py +++ b/areal/experimental/models/archon/qwen3_5/model/args.py @@ -113,10 +113,7 @@ def from_hf_config( partial_rotary_factor = rope_params.get("partial_rotary_factor", 0.25) # Extract rope_theta (may be top-level or inside rope_parameters) - rope_theta = getattr(hf_config, "rope_theta", None) - if rope_theta is None: - rope_params = getattr(hf_config, "rope_parameters", {}) or {} - rope_theta = rope_params.get("rope_theta", 1000000.0) + rope_theta = cls._get_rope_theta(hf_config, default=1000000.0) # Check if MoE is enabled num_experts = getattr(hf_config, "num_experts", None) diff --git a/areal/experimental/models/archon/qwen3_5/model/model.py b/areal/experimental/models/archon/qwen3_5/model/model.py index 2a72488646..920f3927a5 100644 --- a/areal/experimental/models/archon/qwen3_5/model/model.py +++ b/areal/experimental/models/archon/qwen3_5/model/model.py @@ -84,8 +84,8 @@ def forward( hidden_states = hidden_states * torch.rsqrt(variance + self.eps) hidden_states = self.weight * hidden_states.to(input_dtype) if gate is not None: - hidden_states = hidden_states * F.silu(gate.float()).to(input_dtype) - return hidden_states + hidden_states = hidden_states * F.silu(gate.to(torch.float32)) + return hidden_states.to(input_dtype) def reset_parameters(self): nn.init.ones_(self.weight) diff --git a/areal/infra/launcher/local.py b/areal/infra/launcher/local.py index 9a3a19ebe2..2e1dd82b6d 100644 --- a/areal/infra/launcher/local.py +++ b/areal/infra/launcher/local.py @@ -398,7 +398,7 @@ def local_main(config, run_id: int = 0): ) launcher.submit( job_name="trainer", - cmd=f"torchrun --nnodes 1 --nproc-per-node {nprocs} --master-addr localhost --master-port {find_free_ports(1, (10000, 50000))[0]} {' '.join(sys.argv[1:])}", + cmd=f"torchrun --nnodes 1 --nproc-per-node {nprocs} --master-addr localhost --master-port {find_free_ports(1, (10000, 32767))[0]} {' '.join(sys.argv[1:])}", gpu=gpu, env_vars={ **BASE_ENVIRONS, diff --git a/areal/infra/launcher/sglang_server.py b/areal/infra/launcher/sglang_server.py index bdcd7cf156..2cfca8c4a1 100644 --- a/areal/infra/launcher/sglang_server.py +++ b/areal/infra/launcher/sglang_server.py @@ -152,8 +152,8 @@ def run(self): server_idx_offset = 0 # Separate ports used by each server in the same node - # ports range (10000, 50000) - ports_per_server = 40000 // n_servers_per_node + # ports range (10000, 32767) + ports_per_server = 22767 // n_servers_per_node launch_server_args = [] server_addresses = [] base_random_seed = self.config.random_seed diff --git a/areal/infra/launcher/vllm_server.py b/areal/infra/launcher/vllm_server.py index 197c56b2aa..3882cf7045 100644 --- a/areal/infra/launcher/vllm_server.py +++ b/areal/infra/launcher/vllm_server.py @@ -165,8 +165,8 @@ def run(self): server_idx_offset = 0 # Separate ports used by each server in the same node - # ports range (10000, 50000) - ports_per_server = 40000 // n_servers_per_node + # ports range (10000, 32767) + ports_per_server = 22767 // n_servers_per_node launch_server_args = [] server_addresses = [] base_random_seed = self.config.seed diff --git a/areal/infra/rpc/guard/engine_blueprint.py b/areal/infra/rpc/guard/engine_blueprint.py index 39f6cadddb..0c4fdf0a6e 100644 --- a/areal/infra/rpc/guard/engine_blueprint.py +++ b/areal/infra/rpc/guard/engine_blueprint.py @@ -545,9 +545,11 @@ def execute_in_engine_thread(): return result except AttributeError as e: + traceback.print_exc() logger.error(f"Method '{method_name}' not found on engine: {e}") raise ValueError(f"Engine does not have method '{method_name}'") except Exception as e: + traceback.print_exc() logger.error( f"Engine method '{method_name}' failed: " f"{e}\n{traceback.format_exc()}" diff --git a/areal/infra/utils/ray.py b/areal/infra/utils/ray.py index 9672f4d836..bfd00757f3 100644 --- a/areal/infra/utils/ray.py +++ b/areal/infra/utils/ray.py @@ -12,7 +12,7 @@ def get_placement_group_master_ip_and_port( ): def _master_ip_and_port(): host_ip = gethostip() - port = find_free_ports(1, (10000, 60000))[0] + port = find_free_ports(1, (10000, 32767))[0] return host_ip, port future = ray.remote( diff --git a/areal/models/mcore/bailing_moe.py b/areal/models/mcore/bailing_moe.py index 0ea1180998..6157edb129 100644 --- a/areal/models/mcore/bailing_moe.py +++ b/areal/models/mcore/bailing_moe.py @@ -191,7 +191,9 @@ def hf_to_mcore_config_bailing_moe( "v_head_dim": getattr(hf_config, "v_head_dim", 128), # RoPE (for MLA layers; Lightning layers handle their own RoPE) "rope_type": "rope", - "rotary_base": getattr(hf_config, "rope_theta", 10000.0), + "rotary_base": (getattr(hf_config, "rope_parameters", None) or {}).get( + "rope_theta", getattr(hf_config, "rope_theta", 10000.0) + ), "rotary_percent": 1.0, "rotary_scaling_factor": rotary_scaling_factor, "apply_rope_fusion": False, diff --git a/areal/models/mcore/bailing_moe_bridge.py b/areal/models/mcore/bailing_moe_bridge.py index 4cff1899a8..3eead5670e 100644 --- a/areal/models/mcore/bailing_moe_bridge.py +++ b/areal/models/mcore/bailing_moe_bridge.py @@ -165,7 +165,9 @@ def _build_config(self): qk_head_dim=getattr(hf_config, "qk_nope_head_dim", 128), qk_pos_emb_head_dim=getattr(hf_config, "qk_rope_head_dim", 64), v_head_dim=getattr(hf_config, "v_head_dim", 128), - rotary_base=getattr(hf_config, "rope_theta", 10000.0), + rotary_base=(getattr(hf_config, "rope_parameters", None) or {}).get( + "rope_theta", getattr(hf_config, "rope_theta", 10000.0) + ), rope_type="rope", rotary_percent=1.0, rotary_scaling_factor=(getattr(hf_config, "rope_scaling", None) or {}).get( diff --git a/areal/tools/check_pyproject_consistency.py b/areal/tools/check_pyproject_consistency.py index 6e14e46fda..dc551817d5 100644 --- a/areal/tools/check_pyproject_consistency.py +++ b/areal/tools/check_pyproject_consistency.py @@ -41,6 +41,7 @@ "openai", "soundfile", "peft", + "transformers", } ) @@ -266,7 +267,12 @@ def check_uv_sources( # ── [tool.uv] (top-level) ────────────────────────────────────────── def check_tool_uv(self, uv_a: dict, uv_b: dict) -> None: - special_keys = {"override-dependencies", "sources", "conflicts"} + special_keys = { + "override-dependencies", + "sources", + "conflicts", + "dependency-metadata", + } self.check_override_deps( uv_a.get("override-dependencies", []), diff --git a/areal/tools/validate_docker_installation.py b/areal/tools/validate_docker_installation.py index aafff7fb87..0b98010baf 100755 --- a/areal/tools/validate_docker_installation.py +++ b/areal/tools/validate_docker_installation.py @@ -332,17 +332,32 @@ def get_validation_title(self) -> str: return "AReaL Docker Installation Validation" +def _detect_pyproject(project_root: Path) -> Path: + """Auto-detect the correct pyproject file based on installed variant.""" + vllm_path = project_root / "pyproject.vllm.toml" + default_path = project_root / "pyproject.toml" + + try: + __import__("vllm") + if vllm_path.exists(): + return vllm_path + except (ImportError, ModuleNotFoundError): + pass + + return default_path + + def main(): """Main entry point.""" - # Find pyproject.toml script_dir = Path(__file__).parent project_root = script_dir.parent.parent - pyproject_path = project_root / "pyproject.toml" + pyproject_path = _detect_pyproject(project_root) if not pyproject_path.exists(): - print(f"Error: pyproject.toml not found at {pyproject_path}") + print(f"Error: pyproject not found at {pyproject_path}") sys.exit(1) + print(f"Using: {pyproject_path.name}") validator = DockerInstallationValidator(pyproject_path) success = validator.run() sys.exit(0 if success else 1) diff --git a/areal/utils/network.py b/areal/utils/network.py index ca4ae264cb..3481016039 100644 --- a/areal/utils/network.py +++ b/areal/utils/network.py @@ -112,14 +112,18 @@ def split_hostport(addr: str) -> tuple[str, int]: def find_free_ports( - count: int, port_range: tuple = (1024, 65535), exclude_ports: set[int] | None = None + count: int, + port_range: tuple = (10000, 32767), + exclude_ports: set[int] | None = None, ) -> list[int]: """ Find multiple free ports within a specified range. Args: count: Number of free ports to find - port_range: Tuple of (min_port, max_port) to search within + port_range: Tuple of (min_port, max_port) to search within. + Defaults to (10000, 32767) to avoid the OS ephemeral range + (typically 32768-60999 on Linux) which causes TOCTOU collisions. exclude_ports: Set of ports to exclude from search Returns: diff --git a/areal/workflow/vision_rlvr.py b/areal/workflow/vision_rlvr.py index 09489226b0..b259eaaf2d 100644 --- a/areal/workflow/vision_rlvr.py +++ b/areal/workflow/vision_rlvr.py @@ -117,6 +117,7 @@ async def arun_episode( ) input_ids: list[int] = processed_input["input_ids"].tolist()[0] + mm_token_type_ids: list[int] = processed_input["mm_token_type_ids"].tolist()[0] byte_images = image2base64(data["images"]) req = ModelRequest( @@ -138,6 +139,7 @@ async def arun_episode( # Build result tensor dict with batch dim 1 seq = resp.input_tokens + resp.output_tokens + mm_token_type_ids = mm_token_type_ids + [0] * resp.output_len logprobs = [0.0] * resp.input_len + resp.output_logprobs loss_mask = [0] * resp.input_len + [1] * resp.output_len versions = [-1] * resp.input_len + resp.output_versions @@ -152,7 +154,10 @@ async def arun_episode( multi_modal_input[0]["image_grid_thw"] = processed_input["image_grid_thw"] return { - "input_ids": torch.tensor(seq, dtype=torch.int32).unsqueeze(0), + "input_ids": torch.tensor(seq, dtype=torch.long).unsqueeze(0), + "mm_token_type_ids": torch.tensor( + mm_token_type_ids, dtype=torch.long + ).unsqueeze(0), "loss_mask": torch.tensor(loss_mask, dtype=torch.int32).unsqueeze(0), "logprobs": torch.tensor(logprobs, dtype=torch.float32).unsqueeze(0), "multi_modal_input": multi_modal_input, diff --git a/docs/en/cli_reference.md b/docs/en/cli_reference.md index b4ec9149ac..e8e7a6755b 100644 --- a/docs/en/cli_reference.md +++ b/docs/en/cli_reference.md @@ -641,7 +641,6 @@ https://docs.vllm.ai/en/stable/api/index.html for detailed documentation. | `distributed_executor_backend` | string | `"mp"` | - | | `max_num_seqs` | integer | `256` | - | | `block_size` | integer | `16` | - | -| `swap_space` | integer | `4` | - | | `cpu_offload_gb` | float | `0` | - | | `disable_sliding_window` | boolean | `True` | - | | `max_model_len` | integer \| None | `32768` | - | diff --git a/docs/zh/cli_reference.md b/docs/zh/cli_reference.md index ff6a4aac24..e4a57b2577 100644 --- a/docs/zh/cli_reference.md +++ b/docs/zh/cli_reference.md @@ -639,7 +639,6 @@ https://docs.vllm.ai/en/stable/api/index.html for detailed documentation. | `distributed_executor_backend` | string | `"mp"` | - | | `max_num_seqs` | integer | `256` | - | | `block_size` | integer | `16` | - | -| `swap_space` | integer | `4` | - | | `cpu_offload_gb` | float | `0` | - | | `disable_sliding_window` | boolean | `True` | - | | `max_model_len` | integer \| None | `32768` | - | diff --git a/pyproject.toml b/pyproject.toml index 31a85b8835..7b8f090be4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -49,7 +49,8 @@ dependencies = [ "torchdata", "huggingface_hub", "datasets>=3.0.0", - "transformers==4.57.1", + "transformers>=5.0.0,<=5.3.0", + "mistral-common>=1.11.1", "peft<=0.18.1", "qwen_agent", "openai-agents", @@ -145,7 +146,7 @@ dependencies = [ # sglang and vllm pin mutually-incompatible torch / torchao versions. # See pyproject.vllm.toml for the vLLM variant. sglang = [ - "sglang[tracing]==0.5.9; sys_platform == 'linux' and platform_machine == 'x86_64'", + "sglang[tracing]==0.5.10.post1; sys_platform == 'linux' and platform_machine == 'x86_64'", "nvidia-cudnn-cu12==9.16.0.29; sys_platform == 'linux' and platform_machine == 'x86_64'", "torch; sys_platform == 'linux' and platform_machine == 'x86_64'", "torchaudio; sys_platform == 'linux' and platform_machine == 'x86_64'", @@ -154,28 +155,27 @@ sglang = [ tms = [ "torch_memory_saver==0.0.9; sys_platform == 'linux'", ] -flash-attn = [ - "flash-attn==2.8.3; sys_platform == 'linux' and platform_machine == 'x86_64'", -] kernels = [ "kernels==0.12.2", ] megatron = [ - "megatron-core==0.16.0; sys_platform == 'linux' and platform_machine == 'x86_64'", + "megatron-core==0.17.0; python_version >= '3.12' and sys_platform == 'linux' and platform_machine == 'x86_64'", "mbridge @ git+https://github.com/ISEEKYAN/mbridge.git@310e8fb; sys_platform == 'linux' and platform_machine == 'x86_64'", - "megatron-bridge==0.3.0; sys_platform == 'linux' and platform_machine == 'x86_64'", + "megatron-bridge==0.4.0; python_version >= '3.12' and sys_platform == 'linux' and platform_machine == 'x86_64'", ] # Convenience extra for CUDA training packages (no inference backend) cuda-train = [ "areal[tms]", "areal[megatron]", "areal[kernels]", + "nvidia-modelopt[hf]; sys_platform == 'linux' and platform_machine == 'x86_64'", + "tilelang>=0.1.9; sys_platform == 'linux' and platform_machine == 'x86_64'", + "flash-linear-attention==0.4.2; sys_platform == 'linux' and platform_machine == 'x86_64'", ] -# Full CUDA setup: training packages + SGLang inference + flash-attn +# Full CUDA setup: training packages + SGLang inference cuda = [ "areal[cuda-train]", "areal[sglang]", - "areal[flash-attn]", "torch; sys_platform == 'linux' and platform_machine == 'x86_64'", "torchaudio; sys_platform == 'linux' and platform_machine == 'x86_64'", "torchvision; sys_platform == 'linux' and platform_machine == 'x86_64'", @@ -236,30 +236,24 @@ override-dependencies = [ "soundfile>=0.12.1,<0.13.0", "torchao==0.15.0", "nvidia-cudnn-cu12==9.16.0.29; sys_platform == 'linux' and platform_machine == 'x86_64'", + "flash-attn-4>=4.0.0b4", # Required by megatron-bridge but are optional (as per docs) cuda-based installs "transformer-engine; sys_platform == 'never'", "nv-grouped-gemm; sys_platform == 'never'", "mamba-ssm; sys_platform == 'never'", "causal-conv1d; sys_platform == 'never'", - "flash-linear-attention; sys_platform == 'never'", + # nvidia-resiliency-ext 0.5.0 only ships manylinux_2_39 wheels; exclude so + # older host kernels can still install megatron-core. + "nvidia-resiliency-ext; sys_platform == 'never'", # Version conflicts with megatron-bridge (resorting to the existing version) - "megatron-core==0.16.0; sys_platform == 'linux' and platform_machine == 'x86_64'", + "megatron-core==0.17.0; python_version >= '3.12' and sys_platform == 'linux' and platform_machine == 'x86_64'", "hydra-core==1.4.0.dev1", "timm==1.0.16", + "transformers>=5.0.0,<=5.3.0", ] -# Static metadata so uv lock resolves flash-attn without downloading or building. -# The actual pre-built wheel (variant-specific) is installed in the Dockerfile. -[[tool.uv.dependency-metadata]] -name = "flash-attn" -version = "2.8.3" -requires-dist = ["torch", "einops"] - -[tool.uv.extra-build-dependencies] -flash-attn = [{ requirement = "torch", match-runtime = true }] - [[tool.uv.index]] name = "pytorch-cu129" url = "https://download.pytorch.org/whl/cu129" diff --git a/pyproject.vllm.toml b/pyproject.vllm.toml index 006b962a21..8f3c2a87db 100644 --- a/pyproject.vllm.toml +++ b/pyproject.vllm.toml @@ -66,8 +66,9 @@ dependencies = [ "torchao==0.16.0", "huggingface_hub", "datasets>=3.0.0", - "transformers==4.57.1", - "peft", + "transformers>=5.0,!=5.1.*,!=5.2.*,!=5.3.*,!=5.4.*,!=5.5.0", + "mistral-common>=1.11.1", + "peft<=0.18.1", "qwen_agent", "openai-agents", "anthropic", @@ -158,7 +159,7 @@ dependencies = [ # CUDA-dependent extras - these packages only have Linux x86_64 wheels # Platform markers ensure they're skipped on unsupported platforms vllm = [ - "vllm==0.17.0; sys_platform == 'linux' and platform_machine == 'x86_64'", + "vllm==0.19.1; sys_platform == 'linux' and platform_machine == 'x86_64'", "torch; sys_platform == 'linux' and platform_machine == 'x86_64'", "torchaudio; sys_platform == 'linux' and platform_machine == 'x86_64'", "torchvision; sys_platform == 'linux' and platform_machine == 'x86_64'", @@ -166,27 +167,26 @@ vllm = [ tms = [ "torch_memory_saver==0.0.9; sys_platform == 'linux'", ] -flash-attn = [ - "flash-attn==2.8.3; sys_platform == 'linux' and platform_machine == 'x86_64'", -] kernels = [ "kernels==0.12.2", ] megatron = [ - "megatron-core==0.16.0; sys_platform == 'linux' and platform_machine == 'x86_64'", + "megatron-core==0.17.0; python_version >= '3.12' and sys_platform == 'linux' and platform_machine == 'x86_64'", "mbridge @ git+https://github.com/ISEEKYAN/mbridge.git@310e8fb; sys_platform == 'linux' and platform_machine == 'x86_64'", - "megatron-bridge==0.3.0; sys_platform == 'linux' and platform_machine == 'x86_64'", + "megatron-bridge==0.4.0; python_version >= '3.12' and sys_platform == 'linux' and platform_machine == 'x86_64'", ] cuda-train = [ "areal[tms]", "areal[megatron]", "areal[kernels]", + "nvidia-modelopt[hf]; sys_platform == 'linux' and platform_machine == 'x86_64'", + "tilelang>=0.1.9; sys_platform == 'linux' and platform_machine == 'x86_64'", + "flash-linear-attention==0.4.2; sys_platform == 'linux' and platform_machine == 'x86_64'", ] -# Full CUDA setup: training packages + vLLM inference + flash-attn +# Full CUDA setup: training packages + vLLM inference cuda = [ "areal[cuda-train]", "areal[vllm]", - "areal[flash-attn]", "torch; sys_platform == 'linux' and platform_machine == 'x86_64'", "torchaudio; sys_platform == 'linux' and platform_machine == 'x86_64'", "torchvision; sys_platform == 'linux' and platform_machine == 'x86_64'", @@ -235,26 +235,55 @@ environments = [ "sys_platform == 'darwin' and platform_machine == 'x86_64'", ] override-dependencies = [ + "flash-attn-4>=4.0.0b4", + # Required by megatron-bridge but are optional (as per docs) cuda-based installs "transformer-engine; sys_platform == 'never'", "nv-grouped-gemm; sys_platform == 'never'", "mamba-ssm; sys_platform == 'never'", "causal-conv1d; sys_platform == 'never'", - "flash-linear-attention; sys_platform == 'never'", + # nvidia-resiliency-ext 0.5.0 only ships manylinux_2_39 wheels; exclude so + # older host kernels can still install megatron-core. + "nvidia-resiliency-ext; sys_platform == 'never'", # Version conflicts with megatron-bridge (resorting to the existing version) - "megatron-core==0.16.0; sys_platform == 'linux' and platform_machine == 'x86_64'", + "megatron-core==0.17.0; python_version >= '3.12' and sys_platform == 'linux' and platform_machine == 'x86_64'", "hydra-core==1.4.0.dev1", "timm==1.0.16", + "transformers>=5.0,!=5.1.*,!=5.2.*,!=5.3.*,!=5.4.*,!=5.5.0", ] [[tool.uv.dependency-metadata]] -name = "flash-attn" -version = "2.8.3" -requires-dist = ["torch", "einops"] - -[tool.uv.extra-build-dependencies] -flash-attn = [{ requirement = "torch", match-runtime = true }] +name = "megatron-bridge" +version = "0.4.0" +requires-dist = [ + "accelerate", + "comet-ml>=3.50.0", + "datasets>=2.20.0", + "diffusers>=0.36.0", + "einops", + "hydra-core", + "imageio", + "imageio-ffmpeg", + "megatron-core", + "mlflow>=3.9.0", + "nvidia-resiliency-ext", + "omegaconf>=2.3.0", + "open-clip-torch>=3.2.0", + "peft>=0.18.0", + "pyyaml>=6.0.2", + "qwen-vl-utils", + "regex>=2024.11.6", + "rich", + "six>=1.17.0", + "tensorboard>=2.19.0", + "timm", + "torch>=2.6.0", + "tqdm>=4.67.1", + "transformers>=5.0.0", + "typing-extensions", + "wandb>=0.25.0", +] [[tool.uv.index]] name = "pytorch-cu129" diff --git a/scripts/uv_lock.sh b/scripts/uv_lock.sh index 331c1dfc4a..383adf045a 100755 --- a/scripts/uv_lock.sh +++ b/scripts/uv_lock.sh @@ -34,7 +34,7 @@ trap cleanup EXIT cd "${REPO_ROOT}" echo "[AReaL] Generating default lockfile from pyproject.toml..." -uv lock +uv lock -v cp "${DEFAULT_PYPROJECT}" "${TMP_DIR}/pyproject.toml.bak" cp "${DEFAULT_LOCK}" "${TMP_DIR}/uv.lock.bak" @@ -42,7 +42,7 @@ cp "${DEFAULT_LOCK}" "${TMP_DIR}/uv.lock.bak" echo "[AReaL] Generating vLLM lockfile from pyproject.vllm.toml..." cp "${VLLM_PYPROJECT}" "${DEFAULT_PYPROJECT}" cp "${VLLM_LOCK}" "${DEFAULT_LOCK}" -uv lock +uv lock -v cp "${DEFAULT_LOCK}" "${VLLM_LOCK}" echo "[AReaL] Done. Updated files:" diff --git a/scripts/uv_sync.sh b/scripts/uv_sync.sh new file mode 100755 index 0000000000..64d09a96dd --- /dev/null +++ b/scripts/uv_sync.sh @@ -0,0 +1,84 @@ +#!/usr/bin/env bash +# Install project dependencies via `uv sync` for a given inference backend. +# +# Usage: +# bash scripts/uv_sync.sh sglang # sync with default pyproject.toml +# bash scripts/uv_sync.sh vllm # swap in vllm manifests, sync, revert +# bash scripts/uv_sync.sh sglang --extra sandbox --group dev # extra flags +set -euo pipefail + +SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +REPO_ROOT="$(cd "${SCRIPT_DIR}/.." && pwd)" + +DEFAULT_PYPROJECT="${REPO_ROOT}/pyproject.toml" +VLLM_PYPROJECT="${REPO_ROOT}/pyproject.vllm.toml" +DEFAULT_LOCK="${REPO_ROOT}/uv.lock" +VLLM_LOCK="${REPO_ROOT}/uv.vllm.lock" + +VARIANT="${1:-sglang}" +shift 2>/dev/null || true + +case "$VARIANT" in + sglang|vllm) ;; + *) + echo "[AReaL] Error: Invalid variant '${VARIANT}' (expected: sglang|vllm)" >&2 + exit 1 + ;; +esac + +if ! command -v uv >/dev/null 2>&1; then + echo "[AReaL] Error: 'uv' is not installed or not in PATH." >&2 + exit 1 +fi + +if [[ ! -f "${DEFAULT_PYPROJECT}" ]]; then + echo "[AReaL] Error: pyproject.toml not found at ${DEFAULT_PYPROJECT}" >&2 + exit 1 +fi + +# Flags matching the Dockerfile's uv sync invocation (Stage 3), minus +# --active / --project which are Docker-specific. +UV_SYNC_ARGS=( + --active + --inexact + --no-build-isolation + --extra cuda + "$@" +) + +cd "${REPO_ROOT}" + +if [[ "${VARIANT}" == "sglang" ]]; then + echo "[AReaL] Running uv sync for sglang..." + uv sync "${UV_SYNC_ARGS[@]}" +else + # vllm: temporarily replace pyproject.toml / uv.lock with vllm variants, + # run uv sync, then restore the originals (same swap pattern as uv_lock.sh). + if [[ ! -f "${VLLM_PYPROJECT}" ]]; then + echo "[AReaL] Error: pyproject.vllm.toml not found at ${VLLM_PYPROJECT}" >&2 + exit 1 + fi + + TMP_DIR="$(mktemp -d)" + cleanup() { + if [[ -f "${TMP_DIR}/pyproject.toml.bak" ]]; then + cp "${TMP_DIR}/pyproject.toml.bak" "${DEFAULT_PYPROJECT}" + fi + if [[ -f "${TMP_DIR}/uv.lock.bak" ]]; then + cp "${TMP_DIR}/uv.lock.bak" "${DEFAULT_LOCK}" + fi + rm -rf "${TMP_DIR}" + } + trap cleanup EXIT + + cp "${DEFAULT_PYPROJECT}" "${TMP_DIR}/pyproject.toml.bak" + cp "${DEFAULT_LOCK}" "${TMP_DIR}/uv.lock.bak" + + cp "${VLLM_PYPROJECT}" "${DEFAULT_PYPROJECT}" + cp "${VLLM_LOCK}" "${DEFAULT_LOCK}" + + echo "[AReaL] Running uv sync for vllm..." + uv sync "${UV_SYNC_ARGS[@]}" +fi + +echo "[AReaL] Done." diff --git a/tests/experimental/agent_service/test_controller.py b/tests/experimental/agent_service/test_controller.py index 9c8d2dbf48..6f6aeb5f49 100644 --- a/tests/experimental/agent_service/test_controller.py +++ b/tests/experimental/agent_service/test_controller.py @@ -134,6 +134,8 @@ def test_initialize_forks_router_pairs_gateway(self, mock_requests, config): assert len(ctrl.pairs) == 1 assert len(ctrl._forked_services) == 4 + ctrl.destroy() + @patch(f"{CTRL}.requests") def test_initialize_uses_scheduling_spec_env_vars(self, mock_requests): fork_payloads = [] @@ -177,6 +179,8 @@ def mock_post(url, **kwargs): for payload in fork_payloads ) + ctrl.destroy() + class TestScaleUp: @patch(f"{CTRL}.requests") @@ -192,6 +196,8 @@ def test_scale_up_adds_pairs(self, mock_requests, config): assert created == [1, 2, 3] assert len(ctrl.pairs) == 4 + ctrl.destroy() + @patch(f"{CTRL}.requests") def test_scale_up_round_robins_guards(self, mock_requests, config): guards_called: list[str] = [] @@ -224,6 +230,8 @@ def mock_post(url, **kwargs): assert len(g0_calls) == 4 assert len(g1_calls) == 4 + ctrl.destroy() + class TestScaleDown: @patch(f"{CTRL}.requests") @@ -241,6 +249,8 @@ def test_scale_down_removes_newest_first(self, mock_requests, config): assert len(ctrl.pairs) == 1 assert 0 in ctrl.pairs + ctrl.destroy() + class TestDestroy: @patch(f"{CTRL}.requests") @@ -316,6 +326,8 @@ def mock_get(url, **kwargs): assert len(ctrl.pairs) == 0 assert health_call_count > 1 + ctrl.destroy() + @patch(f"{CTRL}.requests") def test_drain_uses_default_timeout(self, mock_requests, config): _setup_mock_requests(mock_requests) @@ -337,6 +349,8 @@ def counting_get(url, **kwargs): drain_gets = get_count - pre_get_count assert drain_gets > 0 + ctrl.destroy() + class TestHealthMonitor: @patch(f"{CTRL}.requests") diff --git a/tests/experimental/archon/test_qwen3_5.py b/tests/experimental/archon/test_qwen3_5.py index 3169e7410d..46869c3556 100644 --- a/tests/experimental/archon/test_qwen3_5.py +++ b/tests/experimental/archon/test_qwen3_5.py @@ -73,7 +73,16 @@ # Availability flags # --------------------------------------------------------------------------- CUDA_AVAILABLE = torch.cuda.is_available() -requires_cuda = pytest.mark.skipif(not CUDA_AVAILABLE, reason="CUDA not available") +_CUDA_CAPABILITY = torch.cuda.get_device_capability() if CUDA_AVAILABLE else (0, 0) +_CUDA_SM90 = _CUDA_CAPABILITY >= (9, 0) +requires_cuda = pytest.mark.skipif( + not _CUDA_SM90, + reason=( + f"Requires sm>=9.0 (H100+), got {_CUDA_CAPABILITY[0]}.{_CUDA_CAPABILITY[1]}" + if CUDA_AVAILABLE + else "CUDA not available" + ), +) try: from fla.modules import FusedRMSNormGated @@ -1348,8 +1357,12 @@ def _archon_to_hf_name(name: str) -> str | None: # Tolerance: flash attn vs eager attn may introduce small numerical # differences, but with correct RoPE both should be very close. + # For parameters with small grad norms (< 0.01), the absolute error from + # flash-vs-eager divergence dominates, causing inflated relative errors. COS_SIM_THRESHOLD = 0.99 GRAD_NORM_REL_ERR = 0.02 + GRAD_NORM_REL_ERR_SMALL = 0.05 + SMALL_NORM_THRESHOLD = 0.01 matched = 0 mismatched_names = [] @@ -1373,7 +1386,12 @@ def _archon_to_hf_name(name: str) -> str | None: continue rel_err = (norm_a - norm_h).abs() / norm_h.clamp(min=1e-8) - assert rel_err < GRAD_NORM_REL_ERR, ( + threshold = ( + GRAD_NORM_REL_ERR_SMALL + if norm_h < SMALL_NORM_THRESHOLD + else GRAD_NORM_REL_ERR + ) + assert rel_err < threshold, ( f"{archon_name}: grad norm rel err {rel_err:.4f} " f"(archon={norm_a:.6f}, hf={norm_h:.6f})" ) diff --git a/tests/experimental/inference_service/test_controller.py b/tests/experimental/inference_service/test_controller.py index 493795d25e..c49e2aa073 100644 --- a/tests/experimental/inference_service/test_controller.py +++ b/tests/experimental/inference_service/test_controller.py @@ -819,7 +819,7 @@ def mock_requests_post(url, json=None, timeout=None): "areal.api.cli_args.pkg_version.is_version_greater_or_equal", return_value=True, ), - patch("areal.api.cli_args.is_version_less", return_value=False), + patch("areal.api.cli_args.pkg_version.is_version_less", return_value=False), ): mock_fork.side_effect = [ ("10.0.0.1", 18081), # router diff --git a/tests/experimental/inference_service/test_examples.py b/tests/experimental/inference_service/test_examples.py index 763e4e5ee7..189b119289 100644 --- a/tests/experimental/inference_service/test_examples.py +++ b/tests/experimental/inference_service/test_examples.py @@ -18,152 +18,6 @@ pytestmark = pytest.mark.slow -@pytest.mark.ci -@pytest.mark.sglang -@pytest.mark.multi_gpu -def test_inference_service_online_rl(tmp_path_factory): - """Test inference_service online RL training via persistent online session.""" - - GATEWAY_STARTUP_TIMEOUT = 600 - SETTLE_TIME = 5 - HEALTH_CHECK_TIMEOUT = 10 - CHAT_TIMEOUT = 30 - REWARD_TIMEOUT = 10 - ROLLOUT_COMPLETION_TIMEOUT = 300 - - def wait_for_pattern(process, pattern, timeout, raise_on_exit=True): - start_time = time.monotonic() - while (time.monotonic() - start_time) < timeout: - line = process.stdout.readline() - if not line: - if process.poll() is not None: - if raise_on_exit: - raise RuntimeError( - f"Process terminated unexpectedly (code {process.returncode})" - ) - return None - time.sleep(0.1) - continue - line = line.strip() - if line: - logger.info(f"[Inference Service Online RL] {line}") - match = pattern.search(line) - if match: - return match - return None - - if current_platform.device_count() < 2: - pytest.skip("This test requires at least 2 GPUs to run.") - - experiments_path = tmp_path_factory.mktemp("experiments") - name_resolve_path = tmp_path_factory.mktemp("name_resolve") - model_path = get_model_path( - "/storage/openpsi/models/Qwen__Qwen3-0.6B", "Qwen/Qwen3-0.6B" - ) - - admin_api_key = "test-admin-key" - batch_size = 2 - - cmd = [ - "python3", - "examples/experimental/inference_service/online_rollout.py", - "--config", - "examples/experimental/inference_service/online_rollout.yaml", - "rollout.backend=sglang:d1", - "gconfig.n_samples=1", - "gconfig.max_new_tokens=128", - "actor.mb_spec.max_tokens_per_mb=2048", - f"train_dataset.batch_size={batch_size}", - "cluster.n_gpus_per_node=2", - f"cluster.fileroot={str(experiments_path)}", - f"cluster.name_resolve.nfs_record_root={str(name_resolve_path)}", - f"actor.path={model_path}", - "scheduler.type=local", - f"rollout.admin_api_key={admin_api_key}", - "rollout._version=v2", - "stats_logger.wandb.mode=disabled", - ] - - logger.info(f"Starting inference_service online RL service: {' '.join(cmd)}") - process = subprocess.Popen( - cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, text=True, bufsize=1 - ) - - gateway_pattern = re.compile(r"Proxy gateway available at (http://[0-9.:]+)") - - try: - match = wait_for_pattern( - process, gateway_pattern, GATEWAY_STARTUP_TIMEOUT, raise_on_exit=True - ) - if not match: - raise RuntimeError("Timed out waiting for gateway URL") - gateway_url = match.group(1) - logger.info(f"Gateway URL: {gateway_url}") - - time.sleep(SETTLE_TIME) - - import requests - - health_resp = requests.get( - f"{gateway_url}/health", timeout=HEALTH_CHECK_TIMEOUT - ) - assert health_resp.status_code == 200, ( - f"Health check failed: {health_resp.text}" - ) - - for trajectory_idx in range(batch_size): - logger.info(f"Trajectory {trajectory_idx + 1}/{batch_size}") - - chat_resp = requests.post( - f"{gateway_url}/chat/completions", - headers={ - "Content-Type": "application/json", - "Authorization": f"Bearer {admin_api_key}", - }, - json={ - "model": "default", - "messages": [{"role": "user", "content": "What is 2+2?"}], - "temperature": 0.7, - "top_p": 1.0, - "max_tokens": 128, - }, - timeout=CHAT_TIMEOUT, - ) - assert chat_resp.status_code == 200, ( - f"chat/completions failed (trajectory {trajectory_idx + 1}): {chat_resp.text}" - ) - - reward_resp = requests.post( - f"{gateway_url}/rl/set_reward", - headers={ - "Content-Type": "application/json", - "Authorization": f"Bearer {admin_api_key}", - }, - json={"reward": 1.0}, - timeout=REWARD_TIMEOUT, - ) - assert reward_resp.status_code == 200, ( - f"set_reward failed (trajectory {trajectory_idx + 1}): {reward_resp.text}" - ) - reward_data = reward_resp.json() - assert reward_data["session_id"] == "__hitl__" - assert reward_data["trajectory_id"] == trajectory_idx - - logger.info("Waiting for rollout completion...") - match = wait_for_pattern( - process, - re.compile(r"Rollout complete \(\d+ trajectories\), avg_reward="), - ROLLOUT_COMPLETION_TIMEOUT, - raise_on_exit=False, - ) - assert match is not None, "Rollout did not complete within timeout" - logger.info("Rollout completed!") - - finally: - logger.info("Shutting down inference_service online RL service...") - kill_process_tree(process.pid, graceful=False) - - @pytest.mark.sglang @pytest.mark.multi_gpu def test_tau2_rollout(tmp_path_factory): diff --git a/tests/experimental/inference_service/test_sglang_multinode.py b/tests/experimental/inference_service/test_sglang_multinode.py index dfc2d2e3ce..8b79eca6bf 100644 --- a/tests/experimental/inference_service/test_sglang_multinode.py +++ b/tests/experimental/inference_service/test_sglang_multinode.py @@ -25,7 +25,7 @@ def _build_args(self, **kwargs): "areal.api.cli_args.pkg_version.is_version_greater_or_equal", return_value=True, ), - patch("areal.api.cli_args.is_version_less", return_value=False), + patch("areal.api.cli_args.pkg_version.is_version_less", return_value=False), ): return SGLangConfig.build_args(**defaults) @@ -42,7 +42,7 @@ def _build_cmd(self, **kwargs): "areal.api.cli_args.pkg_version.is_version_greater_or_equal", return_value=True, ), - patch("areal.api.cli_args.is_version_less", return_value=False), + patch("areal.api.cli_args.pkg_version.is_version_less", return_value=False), ): return SGLangConfig.build_cmd(**defaults) diff --git a/tests/grpo/config.yaml b/tests/grpo/config.yaml index 6d88f33197..8154e3b4c0 100644 --- a/tests/grpo/config.yaml +++ b/tests/grpo/config.yaml @@ -2,63 +2,57 @@ # Backend-specific values (rollout.backend, actor.backend, optimizer) are overridden via CLI. experiment_name: tests-grpo trial_name: trial -scheduler: - type: local -cluster: - n_nodes: 1 - n_gpus_per_node: 2 - fileroot: /tmp/areal/experiments + seed: 1 +enable_offload: false total_train_epochs: 1 total_train_steps: 16 tokenizer_path: ${actor.path} -train_dataset: - path: openai/gsm8k - batch_size: 64 - max_length: 512 - type: rl -saver: - experiment_name: ${experiment_name} - trial_name: ${trial_name} - fileroot: ${cluster.fileroot} -evaluator: - experiment_name: ${experiment_name} - trial_name: ${trial_name} - fileroot: ${cluster.fileroot} -stats_logger: - experiment_name: ${experiment_name} - trial_name: ${trial_name} - fileroot: ${cluster.fileroot} -recover: - experiment_name: ${experiment_name} - trial_name: ${trial_name} - fileroot: ${cluster.fileroot} -sglang: - model_path: ${actor.path} - random_seed: ${seed} -vllm: - model: ${actor.path} - seed: ${seed} - skip_tokenizer_init: false -gconfig: - n_samples: 4 - max_new_tokens: 1024 + +cluster: + n_nodes: 1 + n_gpus_per_node: 2 + fileroot: /tmp/areal/experiments + name_resolve: + type: nfs + nfs_record_root: /tmp/areal/name_resolve + +scheduler: + type: local rollout: backend: "sglang:d1" experiment_name: ${experiment_name} trial_name: ${trial_name} + max_concurrent_rollouts: 256 + queue_size: null consumer_batch_size: ${train_dataset.batch_size} - scheduling_spec: ${actor.scheduling_spec} max_head_offpolicyness: 2 + enable_rollout_tracing: false + scheduling_spec: ${actor.scheduling_spec} + fileroot: ${cluster.fileroot} + tokenizer_path: ${tokenizer_path} + dump_to_file: false + +gconfig: + n_samples: 4 + min_new_tokens: 0 + max_new_tokens: 1024 + greedy: false + temperature: 1.0 actor: backend: "fsdp:d1" experiment_name: ${experiment_name} trial_name: ${trial_name} path: Qwen/Qwen3-0.6B + init_from_scratch: false + disable_dropout: true + gradient_checkpointing: true + dtype: bfloat16 mb_spec: max_tokens_per_mb: 4096 + packing_algorithm: ffd optimizer: type: adam lr: 1.70e-5 @@ -69,17 +63,30 @@ actor: lr_scheduler_type: constant gradient_clipping: 1.0 warmup_steps_proportion: 0.001 + eps_clip: 0.4 + temperature: ${gconfig.temperature} + reward_scaling: 10.0 + reward_bias: -0.5 + kl_ctl: 0.0 + ppo_n_minibatches: 1 recompute_logprob: true use_decoupled_loss: true - kl_ctl: 0.0 + rejection_sampling: + metric: ratio + upper: 5.0 + reward_norm: + mean_level: group + std_level: group + group_size: ${gconfig.n_samples} adv_norm: mean_level: batch std_level: batch + weight_update_mode: xccl + max_new_tokens: ${gconfig.max_new_tokens} scheduling_spec: - task_type: worker port_count: 2 gpu: 1 - cpu: 4 mem: 32 cmd: python3 -m areal.infra.rpc.rpc_server env_vars: {} @@ -89,6 +96,55 @@ ref: experiment_name: ${experiment_name} trial_name: ${trial_name} path: ${actor.path} + init_from_scratch: false + disable_dropout: true + dtype: ${actor.dtype} mb_spec: max_tokens_per_mb: 4096 + packing_algorithm: ffd + optimizer: null + scheduling_strategy: + type: colocation + target: actor scheduling_spec: ${actor.scheduling_spec} + +sglang: + model_path: ${actor.path} + random_seed: ${seed} + skip_tokenizer_init: true + dtype: ${actor.dtype} + max_running_requests: null + context_length: 32768 + mem_fraction_static: 0.8 + +vllm: + model: ${actor.path} + seed: ${seed} + skip_tokenizer_init: false + dtype: ${actor.dtype} + max_model_len: 32768 + gpu_memory_utilization: 0.8 + +train_dataset: + path: openai/gsm8k + shuffle: true + pin_memory: true + batch_size: 64 + max_length: 512 + type: rl +saver: + experiment_name: ${experiment_name} + trial_name: ${trial_name} + fileroot: ${cluster.fileroot} +evaluator: + experiment_name: ${experiment_name} + trial_name: ${trial_name} + fileroot: ${cluster.fileroot} +stats_logger: + experiment_name: ${experiment_name} + trial_name: ${trial_name} + fileroot: ${cluster.fileroot} +recover: + experiment_name: ${experiment_name} + trial_name: ${trial_name} + fileroot: ${cluster.fileroot} diff --git a/tests/test_examples.py b/tests/test_examples.py index 03bfb46c36..c2453de3af 100644 --- a/tests/test_examples.py +++ b/tests/test_examples.py @@ -877,7 +877,7 @@ def test_openclaw_online_rl(tmp_path_factory): HEALTH_CHECK_TIMEOUT = 10 SESSION_NEW_TIMEOUT = 30 SESSION_REFRESH_TIMEOUT = 130 # Longer timeout for refresh (waits for training) - CHAT_TIMEOUT = 30 + CHAT_TIMEOUT = 120 REWARD_TIMEOUT = 10 TRAINING_STEP_TIMEOUT = 300 # 5 min for training step diff --git a/uv.lock b/uv.lock index c72e8d4e44..27795eea54 100644 --- a/uv.lock +++ b/uv.lock @@ -21,24 +21,21 @@ supported-markers = [ [manifest] overrides = [ { name = "causal-conv1d", marker = "sys_platform == 'never'" }, - { name = "flash-linear-attention", marker = "sys_platform == 'never'" }, + { name = "flash-attn-4", 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size = 2571084, upload-time = "2026-04-07T19:58:20.399Z" }, ] [[package]] @@ -319,13 +332,13 @@ dependencies = [ { name = "hydra-core", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "json5", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "langchain", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, - { name = "langchain-openai", version = "1.1.10", source = { registry = "https://pypi.org/simple" }, marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, - { name = "langchain-openai", version = "1.1.11", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux')" }, + { name = "langchain-openai", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "lark", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "litellm", extra = ["proxy"], marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "math-verify", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "mathruler", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "matplotlib", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, + { name = "mistral-common", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "msgspec", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "networkx", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 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(platform_machine == 'x86_64' and sys_platform == 'linux')" }, - { name = "openai-agents", version = "0.10.5", source = { registry = "https://pypi.org/simple" }, marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, - { name = "openai-agents", version = "0.12.5", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux')" }, + { name = "openai-agents", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "openhands", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "orjson", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "packaging", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, @@ -354,8 +366,7 @@ dependencies = [ { name = "pyyaml", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = 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== 'x86_64' and sys_platform == 'linux')" }, + { name = "ray", extra = ["default"], marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "redis", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "regex", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "rich", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, @@ -368,14 +379,13 @@ dependencies = [ { name = "tenacity", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "tensorboardx", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "timeout-decorator", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, - { name = "torch", version = "2.2.2", source = { registry = "https://pypi.org/simple" }, marker = "platform_machine == 'x86_64' and sys_platform == 'darwin'" }, + { name = "torch", version = "2.9.0", source = { registry = "https://pypi.org/simple" }, marker = "platform_machine == 'x86_64' and sys_platform == 'darwin'" }, { name = "torch", version = "2.9.1+cu129", source = { registry = "https://download.pytorch.org/whl/cu129" }, marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "torch", version = "2.10.0", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux')" }, - { name = "torchaudio", version = "2.2.2", source = { registry = "https://pypi.org/simple" }, marker = "platform_machine == 'x86_64' and sys_platform == 'darwin'" }, { name = "torchaudio", version = "2.9.1+cu129", source = { registry = "https://download.pytorch.org/whl/cu129" }, marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, - { name = "torchaudio", version = "2.10.0", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux')" }, + { name = "torchaudio", version = "2.11.0", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux')" }, { name = "torchdata", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, - { name = "torchvision", version = "0.17.2", source = { registry = "https://pypi.org/simple" }, marker = "platform_machine == 'x86_64' and sys_platform == 'darwin'" }, + { name = "torchvision", version = "0.24.0", source = { registry = "https://pypi.org/simple" }, marker = "platform_machine == 'x86_64' and sys_platform == 'darwin'" }, { name = "torchvision", version = "0.24.1+cu129", source = { registry = "https://download.pytorch.org/whl/cu129" }, marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "torchvision", version = "0.25.0", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux')" }, { name = "tqdm", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, @@ -391,35 +401,37 @@ dependencies = [ [package.optional-dependencies] cuda = [ - { name = "flash-attn", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "flash-linear-attention", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "kernels", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "mbridge", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, - { name = "megatron-bridge", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, - { name = "megatron-core", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "megatron-bridge", marker = "python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "megatron-core", marker = "python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "nvidia-cudnn-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "nvidia-modelopt", extra = ["hf"], marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "sglang", extra = ["tracing"], marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "tilelang", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "torch", version = "2.9.1+cu129", source = { registry = "https://download.pytorch.org/whl/cu129" }, marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "torch-memory-saver", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "torchaudio", version = "2.9.1+cu129", source = { registry = "https://download.pytorch.org/whl/cu129" }, marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "torchvision", version = "0.24.1+cu129", source = { registry = "https://download.pytorch.org/whl/cu129" }, marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, ] cuda-train = [ + { name = "flash-linear-attention", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "kernels", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "mbridge", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, - { name = "megatron-bridge", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, - { name = "megatron-core", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "megatron-bridge", marker = "python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "megatron-core", marker = "python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "nvidia-modelopt", extra = ["hf"], marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "tilelang", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "torch-memory-saver", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, ] -flash-attn = [ - { name = "flash-attn", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, -] kernels = [ { name = "kernels", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, ] megatron = [ { name = "mbridge", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, - { name = "megatron-bridge", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, - { name = "megatron-core", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "megatron-bridge", marker = "python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "megatron-core", marker = "python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux'" }, ] sandbox = [ { name = "daytona", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, @@ -438,8 +450,7 @@ tms = [ [package.dev-dependencies] dev = [ { name = "clang-format", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, - { name = "ipython", version = "9.10.0", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version < '3.12' and platform_machine == 'arm64' and sys_platform == 'darwin') or (python_full_version < '3.12' and platform_machine == 'x86_64' and sys_platform == 'darwin') or (python_full_version < '3.12' and platform_machine == 'aarch64' and sys_platform == 'linux') or (python_full_version < '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux')" }, - { name = "ipython", version = "9.11.0", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version >= '3.12' and platform_machine == 'arm64' and sys_platform == 'darwin') or (python_full_version >= '3.12' 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(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "mdformat-frontmatter", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, @@ -461,7 +472,6 @@ requires-dist = [ { name = "aiohttp", specifier = ">=3.13.3,<4" }, { name = "anthropic" }, { name = "areal", extras = ["cuda-train"], marker = "extra == 'cuda'" }, - { name = "areal", extras = ["flash-attn"], marker = "extra == 'cuda'" }, { name = "areal", extras = ["kernels"], marker = "extra == 'cuda-train'" }, { name = "areal", extras = ["megatron"], marker = "extra == 'cuda-train'" }, { name = "areal", extras = ["sglang"], marker = "extra == 'cuda'" }, @@ -478,7 +488,7 @@ requires-dist = [ { name = "distro-info", specifier = ">=1.0" }, { name = 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(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, @@ -355,15 +426,14 @@ dependencies = [ { name = "tenacity", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "tensorboardx", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "timeout-decorator", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, - { name = "torch", version = "2.2.2", source = { registry = "https://pypi.org/simple" }, marker = "platform_machine == 'x86_64' and sys_platform == 'darwin'" }, + { name = "torch", version = "2.9.0", source = { registry = "https://pypi.org/simple" }, marker = "platform_machine == 'x86_64' and sys_platform == 'darwin'" }, { name = "torch", version = "2.10.0", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux')" }, { name = "torch", version = "2.10.0+cu129", source = { registry = "https://download.pytorch.org/whl/cu129" }, marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "torchao", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, - { name = "torchaudio", version = "2.2.2", source = { registry = "https://pypi.org/simple" }, marker = "platform_machine == 'x86_64' and sys_platform == 'darwin'" }, - { name = "torchaudio", version = "2.10.0", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux')" }, { name = "torchaudio", version = "2.10.0+cu129", source = { registry = "https://download.pytorch.org/whl/cu129" }, marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "torchaudio", version = "2.11.0", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux')" }, { name = "torchdata", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, - { name = "torchvision", version = "0.17.2", source = { registry = "https://pypi.org/simple" }, marker = "platform_machine == 'x86_64' and sys_platform == 'darwin'" }, + { name = "torchvision", version = "0.24.0", source = { registry = "https://pypi.org/simple" }, marker = "platform_machine == 'x86_64' and sys_platform == 'darwin'" }, { name = "torchvision", version = "0.25.0", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux')" }, { name = "torchvision", version = "0.25.0+cu129", source = { registry = "https://download.pytorch.org/whl/cu129" }, marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "tqdm", marker = 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'linux'" }, - { name = "megatron-core", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "megatron-bridge", marker = "python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "megatron-core", marker = "python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "nvidia-modelopt", extra = ["hf"], marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "tilelang", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "torch", version = "2.10.0+cu129", source = { registry = "https://download.pytorch.org/whl/cu129" }, marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "torch-memory-saver", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "torchaudio", version = "2.10.0+cu129", source = { registry = "https://download.pytorch.org/whl/cu129" }, marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, @@ -391,22 +463,22 @@ cuda = [ { name = "vllm", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, ] cuda-train = [ + { name = "flash-linear-attention", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "kernels", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "mbridge", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, - { name = "megatron-bridge", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, - { name = "megatron-core", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "megatron-bridge", marker = "python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "megatron-core", marker = "python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "nvidia-modelopt", extra = ["hf"], marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "tilelang", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "torch-memory-saver", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, ] -flash-attn = [ - { name = "flash-attn", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, -] kernels = [ { name = "kernels", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, ] megatron = [ { name = "mbridge", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, - { name = "megatron-bridge", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, - { name = "megatron-core", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "megatron-bridge", marker = "python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux'" }, + { name = "megatron-core", marker = "python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux'" }, ] sandbox = [ { name = "daytona", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, @@ -424,8 +496,7 @@ vllm = [ [package.dev-dependencies] dev = [ { name = "clang-format", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, - { name = "ipython", version = "9.10.0", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version < '3.12' and platform_machine == 'arm64' and sys_platform == 'darwin') or (python_full_version < '3.12' and platform_machine == 'x86_64' and sys_platform == 'darwin') or (python_full_version < '3.12' and platform_machine == 'aarch64' and sys_platform == 'linux') or (python_full_version < '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux')" }, - { name = "ipython", version = "9.11.0", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version >= '3.12' and platform_machine == 'arm64' and sys_platform == 'darwin') or (python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'darwin') or (python_full_version >= '3.12' and platform_machine == 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux')" }, + { name = "ipython", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "jupyter-book", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "mdformat", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, { name = "mdformat-frontmatter", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, @@ -447,7 +518,6 @@ requires-dist = [ { name = "aiohttp", specifier = ">=3.13.3,<4" }, { name = "anthropic" }, { name = "areal", extras = ["cuda-train"], marker = "extra == 'cuda'" }, - { name = "areal", extras = ["flash-attn"], marker = "extra == 'cuda'" }, { name = "areal", extras = ["kernels"], marker = "extra == 'cuda-train'" }, { name = "areal", extras = ["megatron"], marker = "extra == 'cuda-train'" }, { name = "areal", extras = ["tms"], marker = "extra == 'cuda-train'" }, @@ -464,7 +534,7 @@ requires-dist = [ { name = "distro-info", specifier = ">=1.0" }, { name = "einops" }, { name = "fastapi", specifier = ">=0.115.12" }, - { name = "flash-attn", marker = "platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'flash-attn'", specifier = "==2.8.3" }, + { name = "flash-linear-attention", marker = "platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cuda-train'", specifier = "==0.4.2" }, { name = "flask" }, { name = "h5py" }, { name = "httpx", specifier = ">=0.28.1" }, @@ -480,14 +550,16 @@ requires-dist = [ { name = "mathruler", specifier = "==0.1.0" }, { name = "matplotlib" }, { name = "mbridge", marker = "platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'megatron'", git = "https://github.com/ISEEKYAN/mbridge.git?rev=310e8fb" }, - { name = "megatron-bridge", marker = "platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'megatron'", specifier = "==0.3.0" }, - { name = "megatron-core", marker = "platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'megatron'", specifier = "==0.16.0" }, + { name = "megatron-bridge", marker = "python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'megatron'", specifier = "==0.4.0" }, + { name = "megatron-core", marker = "python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'megatron'", specifier = "==0.17.0" }, + { name = "mistral-common", specifier = ">=1.11.1" }, { name = "msgspec" }, { name = "networkx", specifier = "==3.3" }, { name = "ninja" }, { name = "nltk" }, { name = "numba" }, { name = "nvidia-ml-py", marker = "sys_platform == 'linux'" }, + { name = "nvidia-modelopt", extras = ["hf"], marker = "platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cuda-train'" }, { name = "omegaconf", specifier = "==2.4.0.dev2" }, { name = "openai-agents" }, { name = "openhands" }, @@ -495,7 +567,7 @@ requires-dist = [ { name = "packaging" }, { name = "pandas" }, { name = "pebble" }, - { name = "peft" }, + { name = "peft", specifier = "<=0.18.1" }, { name = "pillow", specifier = ">=12.1.1" }, { name = "prettytable" }, { name = "psutil" }, @@ -521,6 +593,7 @@ requires-dist = [ { name = "tabulate" }, { name = "tenacity" }, { name = "tensorboardx" }, + { name = "tilelang", marker = "platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cuda-train'", specifier = ">=0.1.9" }, { name = "timeout-decorator" }, { name = "torch", marker = "platform_machine != 'x86_64' or sys_platform != 'darwin'", specifier = ">=2.10.0,<2.11" }, { name = "torch", marker = "platform_machine == 'x86_64' and sys_platform == 'darwin'", specifier = "<2.9.1" }, @@ -537,16 +610,16 @@ requires-dist = [ { name = "torchvision", marker = "platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'vllm'", index = "https://download.pytorch.org/whl/cu129", conflict = { package = "areal", extra = "vllm" } }, { name = "tqdm" }, { name = "trackio" }, - { name = "transformers", specifier = "==4.57.1" }, + { name = "transformers", 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