chore: import upstream snapshot with attribution

python/ray/_private/workers/setup_worker.py

@@ -0,0 +1,33 @@
+import argparse
+import logging
+
+from ray._private.ray_constants import LOGGER_FORMAT, LOGGER_LEVEL
+from ray._private.ray_logging import setup_logger
+from ray._private.runtime_env.context import RuntimeEnvContext
+from ray.core.generated.common_pb2 import Language
+
+logger = logging.getLogger(__name__)
+
+parser = argparse.ArgumentParser(
+    description=("Set up the environment for a Ray worker and launch the worker.")
+)
+
+parser.add_argument(
+    "--serialized-runtime-env-context",
+    type=str,
+    help="the serialized runtime env context",
+)
+
+parser.add_argument("--language", type=str, help="the language type of the worker")
+
+
+if __name__ == "__main__":
+    setup_logger(LOGGER_LEVEL, LOGGER_FORMAT)
+    args, remaining_args = parser.parse_known_args()
+    # NOTE(edoakes): args.serialized_runtime_env_context is only None when
+    # we're starting the main Ray client proxy server. That case should
+    # probably not even go through this codepath.
+    runtime_env_context = RuntimeEnvContext.deserialize(
+        args.serialized_runtime_env_context or "{}"
+    )
+    runtime_env_context.exec_worker(remaining_args, Language.Value(args.language))