Merge pull request #6 from YiwenAI/main

add ray core tasks

Author: YiwenAI

ray_core_tutorial/ray_core_tasks.py

@@ -0,0 +1,64 @@
+import ray
+import time
+
+
+# A regular Python function.
+def normal_function():
+    return 1
+
+
+# By adding the `@ray.remote` decorator, a regular Python function
+# becomes a Ray remote function.
+@ray.remote
+def my_function():
+    return 1
+
+
+# To invoke this remote function, use the `remote` method.
+# This will immediately return an object ref (a future) and then create
+# a task that will be executed on a worker process.
+obj_ref = my_function.remote()
+
+# The result can be retrieved with ``ray.get``.
+assert ray.get(obj_ref) == 1
+
+
+@ray.remote
+def slow_function():
+    time.sleep(10)
+    return 1
+
+
+# Ray tasks are executed in parallel.
+# All computation is performed in the background, driven by Ray's internal event loop.
+for _ in range(4):
+    # This doesn't block.
+    slow_function.remote()
+
+
+# Specify required resources.
+@ray.remote(num_cpus=4, num_gpus=2)
+def my_function():
+    return 1
+
+
+# Override the default resource requirements.
+my_function.options(num_cpus=3).remote()
+
+
+@ray.remote
+def function_with_an_argument(value):
+    return value + 1
+
+
+obj_ref1 = my_function.remote()
+assert ray.get(obj_ref1) == 1
+
+# You can pass an object ref as an argument to another Ray task.
+obj_ref2 = function_with_an_argument.remote(obj_ref1)
+assert ray.get(obj_ref2) == 2
+
+
+object_refs = [slow_function.remote() for _ in range(2)]
+# Return as soon as one of the tasks finished execution.
+ready_refs, remaining_refs = ray.wait(object_refs, num_returns=1, timeout=None)