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# %%bash
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# pip3 install torchrl mujoco glfw
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- import torchrl
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- import torch
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- import tqdm
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- from typing import Tuple
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-
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# sphinx_gallery_start_ignore
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import warnings
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warnings .filterwarnings ("ignore" )
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+ import multiprocessing
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+ # TorchRL prefers spawn method, that restricts creation of ParallelEnv inside
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+ # `__main__` method call, but for the easy of reading the code switch to fork
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+ # which is also a default spawn method in Google's Colaboratory
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+ multiprocessing .set_start_method ("fork" )
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# sphinx_gallery_end_ignore
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+
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+ import torchrl
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+ import torch
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+ import tqdm
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+ from typing import Tuple
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+
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###############################################################################
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# We will execute the policy on CUDA if available
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device = torch .device ("cuda:0" if torch .cuda .is_available () else "cpu" )
@@ -1219,6 +1225,6 @@ def ceil_div(x, y):
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#
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# To iterate further on this loss module we might consider:
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#
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- # - Using `@dispatch` (see `[Feature] Distpatch IQL loss module <https://github.com/pytorch/rl/pull/1230>`_.
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+ # - Using `@dispatch` (see `[Feature] Distpatch IQL loss module <https://github.com/pytorch/rl/pull/1230>`_.)
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# - Allowing flexible TensorDict keys.
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#
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