Add a script to deploy Pathways service as a JobSet

PiperOrigin-RevId: 896092607

Author: guptaaka

pathwaysutils/experimental/shared_pathways_service/deploy_pathways_service.py

@@ -0,0 +1,261 @@
+"""Deploys Pathways service to a Kubernetes cluster using a JobSet template."""
+
+from collections.abc import Callable, Sequence
+import dataclasses
+import logging
+import math
+import os
+import string
+from typing import Any
+from absl import app
+from absl import flags
+from kubernetes import client
+from kubernetes import config
+import yaml
+
+_logger = logging.getLogger(__name__)
+
+# Flag definitions
+FLAGS = flags.FLAGS
+_JOBSET_NAME = flags.DEFINE_string(
+    "jobset_name", "pathways-service", "Name of the JobSet"
+)
+_JAX_VERSION = flags.DEFINE_string(
+    "jax_version", "0.9.0", "JAX version (e.g., 0.9.0)"
+)
+_SERVER_IMAGE = flags.DEFINE_string(
+    "server_image", None, "Full path to the server Docker image"
+)
+_TPU_TYPE = flags.DEFINE_enum(
+    "tpu_type", "v6e", ["v5e", "v5p", "v6e", "tpu7x"], "TPU type"
+)
+_TOPOLOGY = flags.DEFINE_string(
+    "topology", "2x2", "TPU topology (e.g., 4x8, 2x2x2)"
+)
+_NUM_SLICES = flags.DEFINE_integer(
+    "num_slices", 2, "Number of TPU slices"
+)
+_GCS_BUCKET = flags.DEFINE_string(
+    "gcs_bucket",
+    "gs://pathways-test-bucket",
+    "GCS bucket name for scratch space",
+)
+_TEMPLATE_FILE = flags.DEFINE_string(
+    "template_file",
+    os.path.join(
+        os.path.dirname(__file__), "yamls/pw-service-example.yaml",
+    ),
+    "Path to the JobSet YAML template file",
+)
+_DRY_RUN = flags.DEFINE_boolean(
+    "dry_run",
+    False,
+    "If true, only print the generated YAML without deploying.",
+)
+
+
+@dataclasses.dataclass(frozen=True)
+class TPUConfig:
+  """Holds configuration details for a specific TPU type."""
+  machine_type: str
+  chips_per_vm: int
+  accelerator_label: str
+  instance_prefix: str
+
+
+def _validate_topology(topology):
+  """Validates the topology flag format."""
+  try:
+    dims = topology.split("x")
+    if not (2 <= len(dims) <= 3):
+      return False
+    for dim in dims:
+      if not dim.isdigit():
+        return False
+      if int(dim) <= 0:
+        return False
+    return True
+  except ValueError:
+    return False
+
+
+flags.register_validator(
+    "topology",
+    _validate_topology,
+    message=(
+        "--topology must be in the format like 'AxB' or 'AxBxC', where A, B, C"
+        " are positive integers."
+    ),
+)
+
+
+def get_tpu_config(tpu_type: str) -> TPUConfig:
+  """Returns a TPUConfig object containing TPU configuration details."""
+  tpu_configs = {
+      "v5e": TPUConfig(
+          machine_type="ct5lp-hightpu-4t",
+          chips_per_vm=4,
+          accelerator_label="tpu-v5-lite-podslice",
+          instance_prefix="tpuv5e",
+      ),
+      "v5p": TPUConfig(
+          machine_type="ct5p-hightpu-4t",
+          chips_per_vm=4,
+          accelerator_label="tpu-v5p-slice",
+          instance_prefix="tpuv5p",
+      ),
+      "v6e": TPUConfig(
+          machine_type="ct6e-standard-4t",
+          chips_per_vm=4,
+          accelerator_label="tpu-v6e-slice",
+          instance_prefix="tpuv6e",
+      ),
+      "tpu7x": TPUConfig(
+          machine_type="tpu7x-standard-4t",
+          chips_per_vm=4,
+          accelerator_label="tpu-v7-slice",
+          instance_prefix="tpu7x",
+      ),
+  }
+  if tpu_type not in tpu_configs:
+    raise ValueError(
+        f"Unsupported TPU type: {tpu_type}. Supported types are:"
+        f" {list(tpu_configs.keys())}"
+    )
+  return tpu_configs[tpu_type]
+
+
+def calculate_vms_per_slice(topology: str, chips_per_vm: int) -> int:
+  """Calculates the number of VMs per slice based on the topology."""
+  try:
+    dims = [int(d) for d in topology.split("x")]
+    total_chips = math.prod(dims)
+    if total_chips % chips_per_vm != 0:
+      raise ValueError(
+          f"Total chips ({total_chips}) in topology {topology} is not divisible"
+          f" by chips_per_vm ({chips_per_vm})"
+      )
+    return total_chips // chips_per_vm
+  except ValueError as e:
+    raise ValueError(
+        f"Invalid topology format: {topology}. Expected format like 'AxB' or"
+        f" 'AxBxC'. {e}"
+    ) from e
+
+
+def load_and_substitute_template(
+    template_path: str, context: dict[str, Any]
+) -> dict[str, Any]:
+  """Loads and substitutes the string.Template from the given path."""
+  try:
+    with open(template_path, "r") as f:
+      template_str = f.read()
+  except OSError as err:
+    raise ValueError(
+        f"Could not read template file: {template_path}: {err}"
+    ) from err
+
+  _logger.info("Template file: %s", template_path)
+  _logger.info("Context: %s", context)
+  template = string.Template(template_str)
+  _logger.info("Template: %s", template)
+  substituted_yaml = template.substitute(context)
+  return yaml.safe_load(substituted_yaml)
+
+
+def deploy_jobset(jobset_yaml: dict[str, Any]) -> None:
+  """Deploys the JobSet to the current Kubernetes cluster."""
+  try:
+    config.load_kube_config()
+    api = client.CustomObjectsApi()
+    api.create_namespaced_custom_object(
+        group="jobset.x-k8s.io",
+        version="v1alpha2",
+        namespace=jobset_yaml["metadata"]["namespace"],
+        body=jobset_yaml,
+        plural="jobsets",
+    )
+    _logger.info(
+        "JobSet '%s' created successfully.", jobset_yaml["metadata"]["name"]
+    )
+  except client.rest.ApiException:
+    _logger.exception("Error creating JobSet")
+  except config.ConfigException:
+    _logger.exception("Error loading Kubernetes configuration")
+
+
+def run_deployment(
+    tpu_type,
+    topology,
+    num_slices,
+    jobset_name,
+    gcs_bucket,
+    server_image,
+    template_file,
+    dry_run,
+    deploy_func: Callable[[dict[str, Any]], None] = deploy_jobset,
+) -> None:
+  """Executes the deployment logic."""
+  tpu_config = get_tpu_config(tpu_type)
+  vms_per_slice = calculate_vms_per_slice(topology, tpu_config.chips_per_vm)
+
+  context = {
+      "JOBSET_NAME": jobset_name,
+      "SERVER_IMAGE": server_image,
+      "GCS_SCRATCH_LOCATION": gcs_bucket,
+      "NUM_SLICES": num_slices,
+      "INSTANCE_TYPE": f"{tpu_config.instance_prefix}:{topology}",
+      "VMS_PER_SLICE": vms_per_slice,
+      "CHIPS_PER_VM": tpu_config.chips_per_vm,
+      "ACCELERATOR_LABEL": tpu_config.accelerator_label,
+      "TOPOLOGY": topology,
+  }
+
+  jobset_config = load_and_substitute_template(template_file, context)
+
+  _logger.info("--- Generated JobSet YAML ---")
+  _logger.info("\n%s", yaml.dump(jobset_config))
+
+  if not dry_run:
+    _logger.info("Deploying JobSet...")
+    deploy_func(jobset_config)
+  else:
+    _logger.info("Dry run mode, not deploying.")
+
+
+def main(argv: Sequence[str]) -> None:
+  if len(argv) > 1:
+    raise app.UsageError("Too many command-line arguments.")
+
+  try:
+    if (
+        flags.FLAGS["jax_version"].present
+        and flags.FLAGS["server_image"].present
+    ):
+      raise ValueError("Cannot provide both --jax_version and --server_image")
+
+    if _SERVER_IMAGE.value:
+      server_image = _SERVER_IMAGE.value
+    else:
+      server_image = f"us-docker.pkg.dev/cloud-tpu-v2-images/pathways/server:jax-{_JAX_VERSION.value}"
+
+    run_deployment(
+        tpu_type=_TPU_TYPE.value,
+        topology=_TOPOLOGY.value,
+        num_slices=_NUM_SLICES.value,
+        jobset_name=_JOBSET_NAME.value,
+        gcs_bucket=_GCS_BUCKET.value,
+        server_image=server_image,
+        template_file=_TEMPLATE_FILE.value,
+        dry_run=_DRY_RUN.value,
+    )
+  except ValueError as e:
+    _logger.exception("Error: %s", e)
+  except FileNotFoundError:
+    _logger.exception(
+        "Error: Template file not found at %s", _TEMPLATE_FILE.value
+    )
+
+
+if __name__ == "__main__":
+  app.run(main)