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[Refactor] specs batch size refactoring (#829)
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knowledge_base/PRO-TIPS.md

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@@ -99,3 +99,13 @@ Errors to look for that may be related to this misconception are the following:
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are being used, using vectorized maps and functional programming (through
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functorch) instead of looping over the model configurations can provide a
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significant speedup.
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## Common bugs
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- For bugs related to mujoco (incl. DeepMind Control suite and other libraries),
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refer to the [MUJOCO_INSTALLATION](MUJOCO_INSTALLATION.md) file.
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- `ValueError: bad value(s) in fds_to_keep`: this can have multiple reasons. One that is common in torchrl
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is that you are trying to send a tensor across processes that is a view of another tensor.
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For instance, when sending the tensor `b = tensor.expand(new_shape)` across processes, the reference to the original
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content will be lost (as the `expand` operation keeps the reference to the original tensor).
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To debug this, look for such operations (`view`, `permute`, `expand`, etc.) and call `clone()` or `contiguous()` after
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the call to the function.

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