refactor: allow training on any supported data type#570
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Consider updating changelogs/pending-changelog.md with a summary of this change for the release notes. This is optional and non-blocking. |
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Consider updating changelogs/pending-changelog.md with a summary of this change for the release notes. This is optional and non-blocking. |
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| ) | ||
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| all_proprio = torch.cat(proprio_list, dim=-1) # (B, actual_state_dim) | ||
| if self.proprio_normalizer is None: |
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I find it confusing, in line 357 it can be none
| Tuple of (images, masks) where images is a list of tensors | ||
| [B, C, H, W] per camera and masks is a list of [B] tensors. | ||
| """ | ||
| if DataType.RGB_IMAGES not in self.input_data_types: |
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If rgb_images are not in the inputs, you can simulate a single all black image otherwise pi0 will raise an error
| Tuple of (images, masks) where images is a list of tensors | ||
| [B, C, H, W] per camera and masks is a list of [B] tensors. | ||
| """ | ||
| if DataType.RGB_IMAGES not in self.input_data_types: |
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