Enable Ray Fast Register (#2606)

Signed-off-by: Jan Fiedler <jan@union.ai>

Author: fiedlerNr9

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

@@ -1,16 +1,22 @@
 import base64
 import json
+import os
 import typing
 from dataclasses import dataclass
 from typing import Any, Callable, Dict, Optional
 
 import yaml
-from flytekitplugins.ray.models import HeadGroupSpec, RayCluster, RayJob, WorkerGroupSpec
+from flytekitplugins.ray.models import (
+    HeadGroupSpec,
+    RayCluster,
+    RayJob,
+    WorkerGroupSpec,
+)
 from google.protobuf.json_format import MessageToDict
 
 from flytekit import lazy_module
 from flytekit.configuration import SerializationSettings
-from flytekit.core.context_manager import ExecutionParameters
+from flytekit.core.context_manager import ExecutionParameters, FlyteContextManager
 from flytekit.core.python_function_task import PythonFunctionTask
 from flytekit.extend import TaskPlugins
 
@@ -40,6 +46,7 @@ class RayJobConfig:
     address: typing.Optional[str] = None
     shutdown_after_job_finishes: bool = False
     ttl_seconds_after_finished: typing.Optional[int] = None
+    excludes_working_dir: typing.Optional[typing.List[str]] = None
 
 
 class RayFunctionTask(PythonFunctionTask):
@@ -50,11 +57,30 @@ class RayFunctionTask(PythonFunctionTask):
     _RAY_TASK_TYPE = "ray"
 
     def __init__(self, task_config: RayJobConfig, task_function: Callable, **kwargs):
-        super().__init__(task_config=task_config, task_type=self._RAY_TASK_TYPE, task_function=task_function, **kwargs)
+        super().__init__(
+            task_config=task_config,
+            task_type=self._RAY_TASK_TYPE,
+            task_function=task_function,
+            **kwargs,
+        )
         self._task_config = task_config
 
     def pre_execute(self, user_params: ExecutionParameters) -> ExecutionParameters:
-        ray.init(address=self._task_config.address)
+        init_params = {"address": self._task_config.address}
+
+        ctx = FlyteContextManager.current_context()
+        if not ctx.execution_state.is_local_execution():
+            working_dir = os.getcwd()
+            init_params["runtime_env"] = {
+                "working_dir": working_dir,
+                "excludes": ["script_mode.tar.gz", "fast*.tar.gz"],
+            }
+
+            cfg = self._task_config
+            if cfg.excludes_working_dir:
+                init_params["runtime_env"]["excludes"].extend(cfg.excludes_working_dir)
+
+        ray.init(**init_params)
         return user_params
 
     def get_custom(self, settings: SerializationSettings) -> Optional[Dict[str, Any]]:
@@ -67,12 +93,20 @@ 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) if cfg.head_node_config else None,
+                head_group_spec=(
+                    HeadGroupSpec(cfg.head_node_config.ray_start_params) if cfg.head_node_config else None
+                ),
                 worker_group_spec=[
-                    WorkerGroupSpec(c.group_name, c.replicas, c.min_replicas, c.max_replicas, c.ray_start_params)
+                    WorkerGroupSpec(
+                        c.group_name,
+                        c.replicas,
+                        c.min_replicas,
+                        c.max_replicas,
+                        c.ray_start_params,
+                    )
                     for c in cfg.worker_node_config
                 ],
-                enable_autoscaling=cfg.enable_autoscaling if cfg.enable_autoscaling else False,
+                enable_autoscaling=(cfg.enable_autoscaling if cfg.enable_autoscaling else False),
             ),
             runtime_env=runtime_env,
             runtime_env_yaml=runtime_env_yaml,