ops.py 文件源码

def differentiable_backward(self, g):
        if self.normalize_input:
            raise NotImplementedError

        if self.activation is F.leaky_relu:
            g = backward_leaky_relu(self.x, g)
        elif self.activation is F.relu:
            g = backward_relu(self.x, g)
        elif self.activation is F.tanh:
            g = backward_tanh(self.x, g)
        elif self.activation is F.sigmoid:
            g = backward_sigmoid(self.x, g)
        elif not self.activation is None:
            raise NotImplementedError

        if self.norm == 'ln':
            g = backward_layernormalization(self.nx, g, self.n)
        elif not self.norm is None:
            raise NotImplementedError

        if self.nn == 'down_conv' or self.nn == 'conv':
            g = backward_convolution(None, g, self.c)
        elif self.nn == 'linear':
            g = backward_linear(None, g, self.c)
        elif self.nn == 'up_deconv':
            g = backward_deconvolution(None, g, self.c)
        else:
            raise NotImplementedError

        return g