[Example] A2C simplified example #1076
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Apr 24, 2023
examples/a2c/a2c.py
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| with torch.no_grad(): | ||
| test_env.eval() | ||
| actor.eval() | ||
| # Generate a complete episode | ||
| td_test = test_env.rollout( | ||
| policy=actor, | ||
| max_steps=10_000_000, | ||
| auto_reset=True, | ||
| auto_cast_to_device=True, | ||
| break_when_any_done=True, | ||
| ).clone() | ||
| logger.log_scalar( | ||
| "reward_testing", | ||
| td_test["next"]["reward"].sum().item(), | ||
| collected_frames, | ||
| ) | ||
| actor.train() |
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Nit: If we use the Recorder class we can do all of this I guess, but it's a bit of a black box so I'm ok with the explicit calls.
Maybe let's we use td_test["next", "reward"] when we can (same for all the key indexing in the script) :)
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I saw that in Recorder you need to specify a number of steps, and I wanted to record a single test episode, independently of the number of steps. Maybe recorder could accept a number of episodes to records instead of a number steps?
vmoens
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Apr 25, 2023
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Description
Add a simplified version of the A2C code example, including some plot results.
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close #15213if this solves the issue #15213Types of changes
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