Feat: ff sable Sebulba #1157
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Feat: ff sable Sebulba #1157
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OmaymaMahjoub
requested changes
Feb 12, 2025
| @@ -128,6 +131,7 @@ def step(self, actions: List) -> Tuple[NDArray, NDArray, NDArray, NDArray, Dict] | |||
| else: | |||
| reward = np.array(reward) | |||
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| info["step_count"] = self.step_count | |||
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We need to increment the step count here
| loss_info, grads = grad_fn(params, traj_batch, advantages, targets, entropy_key) | ||
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| # Compute the parallel mean (pmean) over the batch. | ||
| # This pmean could be a regular mean as the batch axis is on the same device. |
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I think it is safe to keep the axis_name for any future, enhancements therefore if you can update the comment and just say it pmean over the learner devices
OmaymaMahjoub
requested changes
Feb 12, 2025
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What?
A FF sable implementation using the Sebulba architecture.