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Fix: check_cached_episodes doesn't check if the requested episode video were downloaded (#2296)

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* In `check_cached_episodes_sufficient` check whether all the requested video files are downloaded

* optimize loop over the video paths

* revert example num_workers

* Apply suggestion from @Copilot

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Signed-off-by: Michel Aractingi <michel.aractingi@huggingface.co>

* set num_workers to zero in example

* style nit

* reintroduce copilot optim

---------

Signed-off-by: Michel Aractingi <michel.aractingi@huggingface.co>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
This commit is contained in:
Michel Aractingi
2025-10-23 17:34:03 +02:00
committed by GitHub
parent df71f3ce24
commit 76a425c600
2 changed files with 25 additions and 16 deletions
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26
examples/dataset/load_lerobot_dataset.py
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@@ -132,17 +132,15 @@ print(f"\n{dataset[0][camera_key].shape=}") # (4, c, h, w)
print(f"{dataset[0]['observation.state'].shape=}") # (6, c)
print(f"{dataset[0]['action'].shape=}\n") # (64, c)
# Finally, our datasets are fully compatible with PyTorch dataloaders and samplers because they are just
# PyTorch datasets.
dataloader = torch.utils.data.DataLoader(
dataset,
num_workers=4,
batch_size=32,
shuffle=True,
)
for batch in dataloader:
print(f"{batch[camera_key].shape=}") # (32, 4, c, h, w)
print(f"{batch['observation.state'].shape=}") # (32, 6, c)
print(f"{batch['action'].shape=}") # (32, 64, c)
break
if __name__ == "__main__":
dataloader = torch.utils.data.DataLoader(
dataset,
num_workers=4,
batch_size=32,
shuffle=True,
)
for batch in dataloader:
print(f"{batch[camera_key].shape=}") # (32, 4, c, h, w)
print(f"{batch['observation.state'].shape=}") # (32, 6, c)
print(f"{batch['action'].shape=}") # (32, 64, c)
break