From 970d70e328ca991ab72fc505f7400d5269e292d9 Mon Sep 17 00:00:00 2001 From: Jason Parraga Date: Sat, 26 Oct 2024 21:18:44 -0700 Subject: [PATCH] Cleanup ray docs to reflect current functionality Signed-off-by: Jason Parraga --- examples/ray_plugin/README.md | 24 ------------------- examples/ray_plugin/ray_plugin/ray_example.py | 5 ++-- 2 files changed, 2 insertions(+), 27 deletions(-) diff --git a/examples/ray_plugin/README.md b/examples/ray_plugin/README.md index 575c97b50..9fd90b850 100644 --- a/examples/ray_plugin/README.md +++ b/examples/ray_plugin/README.md @@ -29,30 +29,6 @@ To enable the plugin in the backend, refer to the instructions provided in the { ## Implementation details -### Submit a Ray job to existing cluster - -```{eval-rst} -.. testcode:: ray-quickstart-1 - import ray - from flytekit import task - from flytekitplugins.ray import RayJobConfig - - @ray.remote - def f(x): - return x * x - - @task( - task_config=RayJobConfig( - address= - runtime_env={"pip": ["numpy", "pandas"]} - ) - ) - def ray_task() -> typing.List[int]: - futures = [f.remote(i) for i in range(5)] - return ray.get(futures) - -``` - ### Create a Ray cluster managed by Flyte and run a Ray Job on the cluster ```{eval-rst} diff --git a/examples/ray_plugin/ray_plugin/ray_example.py b/examples/ray_plugin/ray_plugin/ray_example.py index 185652b0d..8a432cc82 100644 --- a/examples/ray_plugin/ray_plugin/ray_example.py +++ b/examples/ray_plugin/ray_plugin/ray_example.py @@ -1,8 +1,7 @@ # %% [markdown] # # Running Ray Tasks # -# The Ray task offers the capability to execute a Ray job either on a pre-existing Ray cluster -# or by creating a new Ray cluster using the Ray operator. +# The Ray task offers the capability to execute a Ray job on a dynamically created Ray cluster using the Ray operator. # # :::{Warning} # **Version Compatibility** @@ -51,7 +50,7 @@ def f(x): # Here's a breakdown of the parameters: # # - `ray_start_params`: These are the [parameters](https://docs.ray.io/en/latest/ray-core/api/doc/ray.init.html) -# used in the Ray `init` method, encompassing the address and object-store-memory settings. +# used in the Ray `init` method, encompassing the object-store-memory settings. # - `replicas`: Specifies the desired number of replicas for the worker group. The default is 1. # - `group_name`: A RayCluster can host multiple worker groups, each differentiated by its name. # - `runtime_env`: The [runtime environment](https://docs.ray.io/en/latest/ray-core/handling-dependencies.html#runtime-environments)