55 lines
1.4 KiB
Python
55 lines
1.4 KiB
Python
import torch
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from torch import nn
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class LayerScale(nn.Module):
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""" LayerScale on tensors with channels in last-dim.
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"""
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def __init__(
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self,
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dim: int,
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init_values: float = 1e-5,
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inplace: bool = False,
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device=None,
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dtype=None,
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) -> None:
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super().__init__()
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self.init_values = init_values
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self.inplace = inplace
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self.gamma = nn.Parameter(torch.empty(dim, device=device, dtype=dtype))
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self.reset_parameters()
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def reset_parameters(self):
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torch.nn.init.constant_(self.gamma, self.init_values)
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def forward(self, x: torch.Tensor) -> torch.Tensor:
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return x.mul_(self.gamma) if self.inplace else x * self.gamma
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class LayerScale2d(nn.Module):
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""" LayerScale for tensors with torch 2D NCHW layout.
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"""
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def __init__(
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self,
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dim: int,
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init_values: float = 1e-5,
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inplace: bool = False,
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device=None,
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dtype=None,
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):
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super().__init__()
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self.init_values = init_values
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self.inplace = inplace
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self.gamma = nn.Parameter(torch.empty(dim, device=device, dtype=dtype))
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self.reset_parameters()
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def reset_parameters(self):
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torch.nn.init.constant_(self.gamma, self.init_values)
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def forward(self, x):
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gamma = self.gamma.view(1, -1, 1, 1)
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return x.mul_(gamma) if self.inplace else x * gamma
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