convnet_builder.py 文件源码

def _conv2d_impl(self, input_layer, num_channels_in, filters, kernel_size,
                   strides, padding, kernel_initializer):
    if self.use_tf_layers:
      return conv_layers.conv2d(input_layer, filters, kernel_size, strides,
                                padding, self.channel_pos,
                                kernel_initializer=kernel_initializer,
                                use_bias=False)
    else:
      weights_shape = [kernel_size[0], kernel_size[1], num_channels_in, filters]
      # We use the name 'conv2d/kernel' so the variable has the same name as its
      # tf.layers equivalent. This way, if a checkpoint is written when
      # self.use_tf_layers == True, it can be loaded when
      # self.use_tf_layers == False, and vice versa.
      weights = self.get_variable('conv2d/kernel', weights_shape,
                                  self.variable_dtype, self.dtype,
                                  initializer=kernel_initializer)
      if self.data_format == 'NHWC':
        strides = [1] + strides + [1]
      else:
        strides = [1, 1] + strides
      return tf.nn.conv2d(input_layer, weights, strides, padding,
                          data_format=self.data_format)