network_pytorch.py 文件源码

def conv(self,
             input,
             k_h, 
             k_w, 
             c_o, 
             s_h,
             s_w,
             name,
             relu=True,
             padding=DEFAULT_PADDING,
             group=1,
             biased=True):
        input = pad_if_needed(input, padding, 'conv2d', k_h, k_w, s_h, s_w)

        result = F.conv2d(input, 
                          self.weights[name + '/weights'], 
                          bias=self.weights[name + '/biases'] if biased else None,
                          padding=0, 
                          groups=group,
                          stride=(s_h, s_w))
        if relu:
            result = F.relu(result)
        return result