graphlearn_torch/python/distributed/dist_neighbor_loader.py [78:92]:
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               batch_size: int = 1,
               shuffle: bool = False,
               drop_last: bool = False,
               with_edge: bool = False,
               with_weight: bool = False,
               edge_dir: Literal['in', 'out'] = 'out',
               collect_features: bool = False,
               to_device: Optional[torch.device] = None,
               random_seed: Optional[int] = None,
               worker_options: Optional[AllDistSamplingWorkerOptions] = None):

    if isinstance(input_nodes, tuple):
      input_type, input_seeds = input_nodes
    else:
      input_type, input_seeds = None, input_nodes
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graphlearn_torch/python/distributed/dist_subgraph_loader.py [69:82]:
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               batch_size: int = 1,
               shuffle: bool = False,
               drop_last: bool = False,
               with_edge: bool = False,
               with_weight: bool = False,
               edge_dir: Literal['in', 'out'] = 'out',
               collect_features: bool = False,
               to_device: Optional[torch.device] = None,
               random_seed: Optional[int] = None,
               worker_options: Optional[AllDistSamplingWorkerOptions] = None):
    if isinstance(input_nodes, tuple):
      input_type, input_seeds = input_nodes
    else:
      input_type, input_seeds = None, input_nodes
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