tf_agents.environments.parallel_py_environment.ProcessPyEnvironment

Step a single env in a separate process for lock free paralellism.

tf_agents.environments.parallel_py_environment.ProcessPyEnvironment(
    env_constructor: tf_agents.environments.parallel_py_environment.EnvConstructor,
    flatten: bool = False
)

env_constructor Callable that creates and returns a Python environment.
flatten Boolean, whether to assume flattened actions and time_steps during communication to avoid overhead.

Methods

access

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access(
    name: Text
) -> Any

Access an attribute of the external environment.

This method blocks.

Args
name Name of the attribute to access.

Returns
The attribute value.

action_spec

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action_spec() -> tf_agents.typing.types.NestedArraySpec

call

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call(
    name: Text, *args, **kwargs
) -> tf_agents.environments.parallel_py_environment.Promise

Asynchronously call a method of the external environment.

Args
name Name of the method to call.
*args Positional arguments to forward to the method.
**kwargs Keyword arguments to forward to the method.

Returns
The attribute.

close

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close() -> None

Send a close message to the external process and join it.

observation_spec

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observation_spec() -> tf_agents.typing.types.NestedArraySpec

render

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render(
    mode: Text = 'rgb_array', blocking: bool = True
) -> Union[types.NestedArray, Promise]

Renders the environment.

Args
mode Rendering mode. Only 'rgb_array' is supported.
blocking Whether to wait for the result.

Returns
An ndarray of shape [width, height, 3] denoting an RGB image when blocking. Otherwise, callable that returns the rendered image.

Raises
NotImplementedError If the environment does not support rendering, or any other modes than rgb_array is given.

reset

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reset(
    blocking: bool = True
) -> Union[tf_agents.trajectories.TimeStep, tf_agents.environments.parallel_py_environment.Promise]

Reset the environment.

Args
blocking Whether to wait for the result.

Returns
New observation when blocking, otherwise callable that returns the new observation.

start

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start(
    wait_to_start: bool = True
) -> None

Start the process.

Args
wait_to_start Whether the call should wait for an env initialization.

step

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step(
    action: tf_agents.typing.types.NestedArray,
    blocking: bool = True
) -> Union[tf_agents.trajectories.TimeStep, tf_agents.environments.parallel_py_environment.Promise]

Step the environment.

Args
action The action to apply to the environment.
blocking Whether to wait for the result.

Returns
time step when blocking, otherwise callable that returns the time step.

time_step_spec

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time_step_spec() -> tf_agents.trajectories.TimeStep

wait_start

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wait_start() -> None

Wait for the started process to finish initialization.