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Fix PyTorch DDP sampler epoch forwarding in the data loader wrappers #1017

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Fix PyTorch DDP sampler epoch forwarding in the data loader wrappers #1017

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17 changes: 17 additions & 0 deletions src/openpi/training/data_loader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -424,6 +424,7 @@ def __init__(
jax.sharding.PartitionSpec("B"),
)
self._num_batches = num_batches
self._sampler = sampler

mp_context = None
if num_workers > 0:
Expand All @@ -449,6 +450,15 @@ def __init__(
def torch_loader(self) -> torch.utils.data.DataLoader:
return self._data_loader

def set_epoch(self, epoch: int) -> None:
if hasattr(self._sampler, "set_epoch"):
self._sampler.set_epoch(epoch)

def __len__(self) -> int:
if self._num_batches is not None:
return self._num_batches
return len(self._data_loader)

def __iter__(self):
num_items = 0
while True:
Expand Down Expand Up @@ -535,6 +545,13 @@ def __init__(self, data_config: _config.DataConfig, data_loader: TorchDataLoader
def data_config(self) -> _config.DataConfig:
return self._data_config

def set_epoch(self, epoch: int) -> None:
if hasattr(self._data_loader, "set_epoch"):
self._data_loader.set_epoch(epoch)

def __len__(self) -> int:
return len(self._data_loader)

def __iter__(self):
for batch in self._data_loader:
yield _model.Observation.from_dict(batch), batch["actions"]