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""" |
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Applies the mish function element-wise: |
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mish(x) = x * tanh(softplus(x)) = x * tanh(ln(1 + exp(x))) |
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""" |
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|
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import torch |
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import torch.nn.functional as F |
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from torch import nn |
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|
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@torch.jit.script |
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def mish(input): |
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""" |
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Applies the mish function element-wise: |
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mish(x) = x * tanh(softplus(x)) = x * tanh(ln(1 + exp(x))) |
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See additional documentation for mish class. |
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""" |
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return input * torch.tanh(F.softplus(input)) |
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|
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class Mish(nn.Module): |
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""" |
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Applies the mish function element-wise: |
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mish(x) = x * tanh(softplus(x)) = x * tanh(ln(1 + exp(x))) |
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|
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Shape: |
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- Input: (N, *) where * means, any number of additional |
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dimensions |
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- Output: (N, *), same shape as the input |
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|
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Examples: |
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>>> m = Mish() |
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>>> input = torch.randn(2) |
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>>> output = m(input) |
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|
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Reference: https://pytorch.org/docs/stable/generated/torch.nn.Mish.html |
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""" |
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|
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def __init__(self): |
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""" |
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Init method. |
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""" |
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super().__init__() |
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|
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def forward(self, input): |
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""" |
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Forward pass of the function. |
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""" |
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if torch.__version__ >= "1.9": |
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return F.mish(input) |
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else: |
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return mish(input) |
