wehub-resource-sync
57 lines
1.9 KiB
Python
57 lines
1.9 KiB
Python
# Copyright (c) ModelScope Contributors. All rights reserved.
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import torch.distributed as dist
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from tqdm import tqdm
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from swift.utils import to_device
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class DataLoaderDispatcher:
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def __init__(self, base_dataloader, device=None, skip_batches: int = 0):
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self.base_dataloader = base_dataloader
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self.device = device
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self.skip_batches = skip_batches
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@property
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def rank(self):
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return dist.get_rank(self.group) if dist.is_initialized() else 0
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@property
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def world_size(self):
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return dist.get_world_size(self.group) if dist.is_initialized() else 1
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@property
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def group(self):
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return dist.group.WORLD if dist.is_initialized() else 1
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def _scatter_object_list(self, inputs):
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if not dist.is_initialized():
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return inputs[0]
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outputs = [None]
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global_src_rank = dist.get_global_rank(self.group, 0)
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dist.scatter_object_list(outputs, inputs, global_src_rank, group=self.group)
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return outputs[0]
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def _skip_batches(self, base_iter):
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if self.rank == 0 and self.skip_batches > 0:
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for _ in tqdm(range(self.skip_batches), dynamic_ncols=True, desc='Skip Batches: '):
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[next(base_iter) for _ in range(self.world_size)]
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def __iter__(self):
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base_iter = iter(self.base_dataloader)
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self._skip_batches(base_iter)
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while True:
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if self.rank == 0:
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try:
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data = [next(base_iter) for _ in range(self.world_size)]
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except StopIteration:
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data = [None] * self.world_size
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data = self._scatter_object_list(data)
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else:
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data = self._scatter_object_list(None)
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if data is None:
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break
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if self.device:
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data = to_device(data, self.device)
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yield data
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