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We will cover six crucial components of TorchRL:
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- * `environments <https://pytorch.org/rl/reference/envs.html>`__
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- * `transforms <https://pytorch.org/rl/reference/envs.html#transforms>`__
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- * `models (policy and value function) <https://pytorch.org/rl/reference/modules.html>`__
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- * `loss modules <https://pytorch.org/rl/reference/objectives.html>`__
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- * `data collectors <https://pytorch.org/rl/reference/collectors.html>`__
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- * `replay buffers <https://pytorch.org/rl/reference/data.html#replay-buffers>`__
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+ * `environments <https://docs. pytorch.org/rl/stable /reference/envs.html>`__
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+ * `transforms <https://docs. pytorch.org/rl/stable /reference/envs.html#transforms>`__
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+ * `models (policy and value function) <https://docs. pytorch.org/rl/stable /reference/modules.html>`__
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+ * `loss modules <https://docs. pytorch.org/rl/stable /reference/objectives.html>`__
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+ * `data collectors <https://docs. pytorch.org/rl/stable /reference/collectors.html>`__
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+ * `replay buffers <https://docs. pytorch.org/rl/stable /reference/data.html#replay-buffers>`__
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"""
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# Data collector
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# --------------
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#
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- # TorchRL provides a set of `DataCollector classes <https://pytorch.org/rl/reference/collectors.html>`__.
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+ # TorchRL provides a set of `DataCollector classes <https://docs. pytorch.org/rl/stable /reference/collectors.html>`__.
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# Briefly, these classes execute three operations: reset an environment,
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# compute an action given the latest observation, execute a step in the environment,
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# and repeat the last two steps until the environment signals a stop (or reaches
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