2023-02-27 09:52:16 +00:00
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import torch.nn as nn
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from colossalai.context import ParallelMode, seed
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from ..parallel_1d import *
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from ..utils import get_tensor_parallel_mode
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from ._utils import ColossalaiModule
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class Dropout(ColossalaiModule):
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"""Dropout layer of colossalai.
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Args:
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p (float, optional): probability of an element to be zeroed, defaults 0.5.
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inplace (bool, optional): whether to do dropout in-place, default to be False.
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"""
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def __init__(self, p: float = 0.5, inplace: bool = False) -> None:
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tensor_parallel = get_tensor_parallel_mode()
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if tensor_parallel == "1d":
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drop = Dropout1D(p, inplace)
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else:
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drop = nn.Dropout(p, inplace)
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super().__init__(drop, tensor_parallel=tensor_parallel)
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def forward(self, *args):
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if self.tensor_parallel in [None, '1d']:
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return super().forward(*args)
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else:
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with seed(ParallelMode.TENSOR):
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return super().forward(*args)
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