Introduce pod_spec_from_resources()ray helper function

flytekit/core/resources.py

@@ -1,6 +1,7 @@
-from dataclasses import dataclass
-from typing import List, Optional, Union
+from dataclasses import dataclass, fields
+from typing import Any, List, Optional, Union
 
+from kubernetes.client import V1Container, V1PodSpec, V1ResourceRequirements
 from mashumaro.mixins.json import DataClassJSONMixin
 
 from flytekit.models import task as task_models
@@ -73,7 +74,10 @@ def _convert_resources_to_resource_entries(resources: Resources) -> List[_Resour
         resource_entries.append(_ResourceEntry(name=_ResourceName.GPU, value=str(resources.gpu)))
     if resources.ephemeral_storage is not None:
         resource_entries.append(
-            _ResourceEntry(name=_ResourceName.EPHEMERAL_STORAGE, value=str(resources.ephemeral_storage))
+            _ResourceEntry(
+                name=_ResourceName.EPHEMERAL_STORAGE,
+                value=str(resources.ephemeral_storage),
+            )
         )
     return resource_entries
 
@@ -96,3 +100,48 @@ def convert_resources_to_resource_model(
     if limits is not None:
         limit_entries = _convert_resources_to_resource_entries(limits)
     return task_models.Resources(requests=request_entries, limits=limit_entries)
+
+
+def construct_k8s_pod_spec_from_resources(
+    k8s_pod_name: str,
+    requests: Optional[Resources],
+    limits: Optional[Resources],
+) -> dict[str, Any]:
+    def _construct_k8s_pods_resources(resources: Optional[Resources], k8s_gpu_resource_key: str = "nvidia.com/gpu"):
+        if resources is None:
+            return None
+
+        resources_map = {
+            "cpu": "cpu",
+            "mem": "memory",
+            "gpu": k8s_gpu_resource_key,
+            "ephemeral_storage": "ephemeral-storage",
+        }
+
+        k8s_pod_resources = {}
+
+        for resource in fields(resources):
+            resource_value = getattr(resources, resource.name)
+            if resource_value is not None:
+                k8s_pod_resources[resources_map[resource.name]] = resource_value
+
+        return k8s_pod_resources
+
+    requests = _construct_k8s_pods_resources(resources=requests)
+    limits = _construct_k8s_pods_resources(resources=limits)
+    requests = requests or limits
+    limits = limits or requests
+
+    k8s_pod = V1PodSpec(
+        containers=[
+            V1Container(
+                name=k8s_pod_name,
+                resources=V1ResourceRequirements(
+                    requests=requests,
+                    limits=limits,
+                ),
+            )
+        ]
+    )
+
+    return k8s_pod.to_dict()

plugins/flytekit-ray/flytekitplugins/ray/models.py

@@ -2,8 +2,9 @@
 
 from flyteidl.plugins import ray_pb2 as _ray_pb2
 
+from flytekit.core.resources import Resources, construct_k8s_pod_spec_from_resources
 from flytekit.models import common as _common
-from flytekit.models.task import K8sPod
+from flytekit.models.task import K8sObjectMetadata, K8sPod
 
 
 class WorkerGroupSpec(_common.FlyteIdlEntity):
@@ -14,14 +15,22 @@ def __init__(
         min_replicas: typing.Optional[int] = None,
         max_replicas: typing.Optional[int] = None,
         ray_start_params: typing.Optional[typing.Dict[str, str]] = None,
-        k8s_pod: typing.Optional[K8sPod] = None,
+        requests: typing.Optional[Resources] = None,
+        limits: typing.Optional[Resources] = None,
     ):
         self._group_name = group_name
         self._replicas = replicas
         self._max_replicas = max(replicas, max_replicas) if max_replicas is not None else replicas
         self._min_replicas = min(replicas, min_replicas) if min_replicas is not None else replicas
         self._ray_start_params = ray_start_params
-        self._k8s_pod = k8s_pod
+        self._requests = requests
+        self._limits = limits
+        self._k8s_pod = K8sPod(
+            metadata=K8sObjectMetadata(),
+            pod_spec=construct_k8s_pod_spec_from_resources(
+                k8s_pod_name="ray-worker", requests=self._requests, limits=self._limits
+            ),
+        )
 
     @property
     def group_name(self):
@@ -104,10 +113,19 @@ class HeadGroupSpec(_common.FlyteIdlEntity):
     def __init__(
         self,
         ray_start_params: typing.Optional[typing.Dict[str, str]] = None,
-        k8s_pod: typing.Optional[K8sPod] = None,
+        requests: typing.Optional[Resources] = None,
+        limits: typing.Optional[Resources] = None,
     ):
         self._ray_start_params = ray_start_params
-        self._k8s_pod = k8s_pod
+        self._requests = requests
+        self._limits = limits
+
+        self._k8s_pod = K8sPod(
+            metadata=K8sObjectMetadata(),
+            pod_spec=construct_k8s_pod_spec_from_resources(
+                k8s_pod_name="ray-head", requests=self._requests, limits=self._limits
+            ),
+        )
 
     @property
     def ray_start_params(self):

plugins/flytekit-ray/flytekitplugins/ray/task.py

@@ -18,16 +18,17 @@
 from flytekit.configuration import SerializationSettings
 from flytekit.core.context_manager import ExecutionParameters, FlyteContextManager
 from flytekit.core.python_function_task import PythonFunctionTask
+from flytekit.core.resources import Resources
 from flytekit.extend import TaskPlugins
-from flytekit.models.task import K8sPod
 
 ray = lazy_module("ray")
 
 
 @dataclass
 class HeadNodeConfig:
     ray_start_params: typing.Optional[typing.Dict[str, str]] = None
-    k8s_pod: typing.Optional[K8sPod] = None
+    requests: typing.Optional[Resources] = None
+    limits: typing.Optional[Resources] = None
 
 
 @dataclass
@@ -37,7 +38,8 @@ class WorkerNodeConfig:
     min_replicas: typing.Optional[int] = None
     max_replicas: typing.Optional[int] = None
     ray_start_params: typing.Optional[typing.Dict[str, str]] = None
-    k8s_pod: typing.Optional[K8sPod] = None
+    requests: typing.Optional[Resources] = None
+    limits: typing.Optional[Resources] = None
 
 
 @dataclass
@@ -92,7 +94,11 @@ def get_custom(self, settings: SerializationSettings) -> Optional[Dict[str, Any]
         ray_job = RayJob(
             ray_cluster=RayCluster(
                 head_group_spec=(
-                    HeadGroupSpec(cfg.head_node_config.ray_start_params, cfg.head_node_config.k8s_pod)
+                    HeadGroupSpec(
+                        cfg.head_node_config.ray_start_params,
+                        cfg.head_node_config.requests,
+                        cfg.head_node_config.limits,
+                    )
                     if cfg.head_node_config
                     else None
                 ),
@@ -103,7 +109,8 @@ def get_custom(self, settings: SerializationSettings) -> Optional[Dict[str, Any]
                         c.min_replicas,
                         c.max_replicas,
                         c.ray_start_params,
-                        c.k8s_pod,
+                        c.requests,
+                        c.limits,
                     )
                     for c in cfg.worker_node_config
                 ],

plugins/flytekit-ray/tests/test_ray.py

@@ -4,17 +4,31 @@
 import ray
 import yaml
 from flytekitplugins.ray import HeadNodeConfig
-from flytekitplugins.ray.models import RayCluster, RayJob, WorkerGroupSpec, HeadGroupSpec
+from flytekitplugins.ray.models import (
+    RayCluster,
+    RayJob,
+    WorkerGroupSpec,
+    HeadGroupSpec,
+)
 from flytekitplugins.ray.task import RayJobConfig, WorkerNodeConfig
 from google.protobuf.json_format import MessageToDict
-from flytekit.models.task import K8sPod
+from flytekit.core.resources import Resources
 
 from flytekit import PythonFunctionTask, task
 from flytekit.configuration import Image, ImageConfig, SerializationSettings
 
 config = RayJobConfig(
-    worker_node_config=[WorkerNodeConfig(group_name="test_group", replicas=3, min_replicas=0, max_replicas=10, k8s_pod=K8sPod(pod_spec={"str": "worker", "int": 1}))],
-    head_node_config=HeadNodeConfig(k8s_pod=K8sPod(pod_spec={"str": "head", "int": 2})),
+    worker_node_config=[
+        WorkerNodeConfig(
+            group_name="test_group",
+            replicas=3,
+            min_replicas=0,
+            max_replicas=10,
+            requests=Resources(cpu=2, mem="2Gi"),
+            limits=Resources(cpu=2, mem="4Gi"),
+        )
+    ],
+    head_node_config=HeadNodeConfig(requests=Resources(cpu=2)),
     runtime_env={"pip": ["numpy"]},
     enable_autoscaling=True,
     shutdown_after_job_finishes=True,
@@ -44,7 +58,20 @@ def t1(a: int) -> str:
     )
 
     ray_job_pb = RayJob(
-        ray_cluster=RayCluster(worker_group_spec=[WorkerGroupSpec(group_name="test_group", replicas=3, min_replicas=0, max_replicas=10, k8s_pod=K8sPod(pod_spec={"str": "worker", "int": 1}))], head_group_spec=HeadGroupSpec(k8s_pod=K8sPod(pod_spec={"str": "head", "int": 2})), enable_autoscaling=True),
+        ray_cluster=RayCluster(
+            worker_group_spec=[
+                WorkerGroupSpec(
+                    group_name="test_group",
+                    replicas=3,
+                    min_replicas=0,
+                    max_replicas=10,
+                    requests=Resources(cpu=2, mem="2Gi"),
+                    limits=Resources(cpu=2, mem="4Gi"),
+                )
+            ],
+            head_group_spec=HeadGroupSpec(requests=Resources(cpu=2)),
+            enable_autoscaling=True,
+        ),
         runtime_env=base64.b64encode(json.dumps({"pip": ["numpy"]}).encode()).decode(),
         runtime_env_yaml=yaml.dump({"pip": ["numpy"]}),
         shutdown_after_job_finishes=True,

pyproject.toml

@@ -31,6 +31,7 @@ dependencies = [
     "jsonlines",
     "jsonpickle",
     "keyring>=18.0.1",
+    "kubernetes>=12.0.1",
     "markdown-it-py",
     "marshmallow-enum",
     "marshmallow-jsonschema>=0.12.0",

tests/flytekit/unit/core/test_resources.py

@@ -1,10 +1,14 @@
 from typing import Dict
 
 import pytest
+from kubernetes.client import V1Container, V1PodSpec, V1ResourceRequirements
 
 import flytekit.models.task as _task_models
 from flytekit import Resources
-from flytekit.core.resources import convert_resources_to_resource_model
+from flytekit.core.resources import (
+    construct_k8s_pod_spec_from_resources,
+    convert_resources_to_resource_model,
+)
 
 _ResourceName = _task_models.Resources.ResourceName
 
@@ -101,3 +105,53 @@ def test_resources_round_trip():
     json_str = original.to_json()
     result = Resources.from_json(json_str)
     assert original == result
+
+
+def test_construct_k8s_pod_spec_from_resources_requests_limits_set():
+    requests = Resources(cpu="1", mem="1Gi", gpu="1", ephemeral_storage="1Gi")
+    limits = Resources(cpu="4", mem="2Gi", gpu="1", ephemeral_storage="1Gi")
+    k8s_pod_name = "foo"
+
+    expected_pod_spec = V1PodSpec(
+        containers=[
+            V1Container(
+                name=k8s_pod_name,
+                resources=V1ResourceRequirements(
+                    requests={
+                        "cpu": "1",
+                        "memory": "1Gi",
+                        "nvidia.com/gpu": "1",
+                        "ephemeral-storage": "1Gi",
+                    },
+                    limits={
+                        "cpu": "4",
+                        "memory": "2Gi",
+                        "nvidia.com/gpu": "1",
+                        "ephemeral-storage": "1Gi",
+                    },
+                ),
+            )
+        ]
+    )
+    pod_spec = construct_k8s_pod_spec_from_resources(k8s_pod_name=k8s_pod_name, requests=requests, limits=limits)
+    assert expected_pod_spec == V1PodSpec(**pod_spec)
+
+
+def test_construct_k8s_pod_spec_from_resources_requests_set():
+    requests = Resources(cpu="1", mem="1Gi")
+    limits = None
+    k8s_pod_name = "foo"
+
+    expected_pod_spec = V1PodSpec(
+        containers=[
+            V1Container(
+                name=k8s_pod_name,
+                resources=V1ResourceRequirements(
+                    requests={"cpu": "1", "memory": "1Gi"},
+                    limits={"cpu": "1", "memory": "1Gi"},
+                ),
+            )
+        ]
+    )
+    pod_spec = construct_k8s_pod_spec_from_resources(k8s_pod_name=k8s_pod_name, requests=requests, limits=limits)
+    assert expected_pod_spec == V1PodSpec(**pod_spec)