mirror of
https://github.com/vale981/ray
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8b7e4ac701
- Currently not all code under ray-core/doc_code is covered by CI. - tf_example.py and torch_example.py are not used anywhere. Signed-off-by: Jiajun Yao <jeromeyjj@gmail.com>
127 lines
3.2 KiB
Python
127 lines
3.2 KiB
Python
# flake8: noqa
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# fmt: off
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# __init_namespace_start__
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import ray
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ray.init(namespace="hello")
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# __init_namespace_end__
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# fmt: on
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ray.shutdown()
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# fmt: off
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# __actor_namespace_start__
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import subprocess
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import ray
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try:
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subprocess.check_output(["ray", "start", "--head"])
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@ray.remote
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class Actor:
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pass
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# Job 1 creates two actors, "orange" and "purple" in the "colors" namespace.
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with ray.init("ray://localhost:10001", namespace="colors"):
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Actor.options(name="orange", lifetime="detached").remote()
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Actor.options(name="purple", lifetime="detached").remote()
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# Job 2 is now connecting to a different namespace.
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with ray.init("ray://localhost:10001", namespace="fruits"):
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# This fails because "orange" was defined in the "colors" namespace.
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try:
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ray.get_actor("orange")
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except ValueError:
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pass
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# This succceeds because the name "orange" is unused in this namespace.
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Actor.options(name="orange", lifetime="detached").remote()
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Actor.options(name="watermelon", lifetime="detached").remote()
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# Job 3 connects to the original "colors" namespace
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context = ray.init("ray://localhost:10001", namespace="colors")
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# This fails because "watermelon" was in the fruits namespace.
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try:
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ray.get_actor("watermelon")
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except ValueError:
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pass
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# This returns the "orange" actor we created in the first job, not the second.
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ray.get_actor("orange")
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# We are manually managing the scope of the connection in this example.
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context.disconnect()
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finally:
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subprocess.check_output(["ray", "stop", "--force"])
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# __actor_namespace_end__
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# fmt: on
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# fmt: off
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# __specify_actor_namespace_start__
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import subprocess
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import ray
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try:
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subprocess.check_output(["ray", "start", "--head"])
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@ray.remote
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class Actor:
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pass
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ctx = ray.init("ray://localhost:10001")
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# Create an actor with specified namespace.
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Actor.options(name="my_actor", namespace="actor_namespace", lifetime="detached").remote()
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# It is accessible in its namespace.
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ray.get_actor("my_actor", namespace="actor_namespace")
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ctx.disconnect()
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finally:
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subprocess.check_output(["ray", "stop", "--force"])
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# __specify_actor_namespace_end__
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# fmt: on
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# fmt: off
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# __anonymous_namespace_start__
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import subprocess
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import ray
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try:
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subprocess.check_output(["ray", "start", "--head"])
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@ray.remote
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class Actor:
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pass
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# Job 1 connects to an anonymous namespace by default
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with ray.init("ray://localhost:10001"):
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Actor.options(name="my_actor", lifetime="detached").remote()
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# Job 2 connects to a _different_ anonymous namespace by default
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with ray.init("ray://localhost:10001"):
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# This succeeds because the second job is in its own namespace.
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Actor.options(name="my_actor", lifetime="detached").remote()
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finally:
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subprocess.check_output(["ray", "stop", "--force"])
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# __anonymous_namespace_end__
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# fmt: on
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# fmt: off
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# __get_namespace_start__
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import subprocess
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import ray
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try:
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subprocess.check_output(["ray", "start", "--head"])
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ray.init(address="auto", namespace="colors")
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# Will print namespace name "colors".
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print(ray.get_runtime_context().namespace)
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finally:
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subprocess.check_output(["ray", "stop", "--force"])
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# __get_namespace_end__
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# fmt: on
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