mmcv.cnn.bricks.hsigmoid 源代码

# Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn

from .registry import ACTIVATION_LAYERS

[文档]@ACTIVATION_LAYERS.register_module() class HSigmoid(nn.Module): """Hard Sigmoid Module. Apply the hard sigmoid function: Hsigmoid(x) = min(max((x + bias) / divisor, min_value), max_value) Default: Hsigmoid(x) = min(max((x + 1) / 2, 0), 1) Args: bias (float): Bias of the input feature map. Default: 1.0. divisor (float): Divisor of the input feature map. Default: 2.0. min_value (float): Lower bound value. Default: 0.0. max_value (float): Upper bound value. Default: 1.0. Returns: Tensor: The output tensor. """ def __init__(self, bias=1.0, divisor=2.0, min_value=0.0, max_value=1.0): super(HSigmoid, self).__init__() self.bias = bias self.divisor = divisor assert self.divisor != 0 self.min_value = min_value self.max_value = max_value
[文档] def forward(self, x): x = (x + self.bias) / self.divisor return x.clamp_(self.min_value, self.max_value)