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33 lines
1.2 KiB
Python
33 lines
1.2 KiB
Python
from typing import Any, Dict, Optional, Union
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import torch
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import torch.distributed
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from .parallel_state import get_tp_group
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def tensor_model_parallel_all_reduce(input_: torch.Tensor) -> torch.Tensor:
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"""All-reduce the input tensor across model parallel group."""
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return get_tp_group().all_reduce(input_)
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def tensor_model_parallel_all_gather(input_: torch.Tensor,
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dim: int = -1) -> torch.Tensor:
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"""All-gather the input tensor across model parallel group."""
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return get_tp_group().all_gather(input_, dim)
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def tensor_model_parallel_gather(input_: torch.Tensor,
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dst: int = 0,
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dim: int = -1) -> torch.Tensor:
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"""Gather the input tensor across model parallel group."""
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return get_tp_group().gather(input_, dst, dim)
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def broadcast_tensor_dict(tensor_dict: Optional[Dict[Any, Union[torch.Tensor,
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Any]]] = None,
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src: int = 0):
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if not torch.distributed.is_initialized():
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return tensor_dict
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return get_tp_group().broadcast_tensor_dict(tensor_dict, src)
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