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153 lines
3.7 KiB
153 lines
3.7 KiB
from typing import List
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import torch
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import torch.distributed as dist
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from torch.distributed import ProcessGroup
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from .moe_info import MoeParallelInfo
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def is_moe_tensor(tensor: torch.Tensor) -> bool:
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"""
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Check whether the given tensor is a moe tensor.
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Args:
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tensor (torch.Tensor): The tensor to be checked.
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Returns:
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bool: Whether the given tensor is a moe tensor.
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"""
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return hasattr(tensor, "moe_info")
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def set_moe_tensor_info(tensor: torch.Tensor, moe_info: MoeParallelInfo) -> None:
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"""
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Set moe info for the given tensor.
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Args:
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tensor (torch.Tensor): The tensor to be set.
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moe_info (dict): The moe info to be set.
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"""
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tensor.__setattr__("moe_info", moe_info)
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def get_moe_info(ep_size: int, dp_size: int, pp_size: int, ep_inside: bool) -> MoeParallelInfo:
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"""
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Get moe info for the given tensor.
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Args:
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ep_size (int): The expert parallel size.
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dp_size (int): The data parallel size.
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pp_size (int): The pipeline parallel size.
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ep_inside (bool, optional): Use ep inside dp if True, dp inside ep if Fasle.
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Returns:
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dict: The moe info of the given tensor.
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"""
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return MoeParallelInfo(ep_inside, ep_size, dp_size, pp_size)
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def get_ep_group(tensor: torch.Tensor) -> ProcessGroup:
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"""
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Get the expert parallel group of the given tensor.
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Args:
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tensor (torch.Tensor): The tensor to be checked.
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Returns:
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torch.distributed.ProcessGroup: The expert parallel group of the given tensor.
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"""
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return tensor.moe_info.ep_group
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def get_ep_size(tensor: torch.Tensor) -> int:
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"""
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Get the expert parallel size of the given tensor.
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Args:
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tensor (torch.Tensor): The tensor to be checked.
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Returns:
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int: The expert parallel size of the given tensor.
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"""
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return tensor.moe_info.ep_size
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def get_dp_size(tensor: torch.Tensor) -> int:
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"""
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Get the data parallel size of the given tensor.
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Args:
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tensor (torch.Tensor): The tensor to be checked.
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Returns:
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int: The data parallel size of the given tensor.
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"""
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return tensor.moe_info.dp_size
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def get_dp_group(tensor: torch.Tensor) -> ProcessGroup:
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"""
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Get the data parallel group of the given tensor.
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Args:
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tensor (torch.Tensor): The tensor to be checked.
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Returns:
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torch.distributed.ProcessGroup: The data parallel group of the given tensor.
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"""
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return tensor.moe_info.dp_group
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def get_ep_rank(tensor: torch.Tensor) -> int:
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"""
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Get the expert parallel rank of the given tensor.
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Args:
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tensor (torch.Tensor): The tensor to be checked.
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Returns:
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int: The expert parallel rank of the given tensor.
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"""
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return dist.get_rank(get_ep_group(tensor))
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def get_dp_rank(tensor: torch.Tensor) -> int:
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"""
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Get the data parallel rank of the given tensor.
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Args:
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tensor (torch.Tensor): The tensor to be checked.
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Returns:
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int: The data parallel rank of the given tensor.
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"""
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return dist.get_rank(get_dp_group(tensor))
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def get_ep_group_ranks(tensor: torch.Tensor) -> List[int]:
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"""
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Get the expert parallel group ranks of the given tensor.
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Args:
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tensor (torch.Tensor): The tensor to be checked.
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Returns:
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int: The expert parallel group ranks of the given tensor.
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"""
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return tensor.moe_info.ep_group_ranks
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def get_dp_group_ranks(tensor: torch.Tensor) -> List[int]:
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"""
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Get the data parallel group ranks of the given tensor.
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Args:
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tensor (torch.Tensor): The tensor to be checked.
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Returns:
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int: The data parallel group ranks of the given tensor.
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"""
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return tensor.moe_info.dp_group_ranks
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