code: def bottleneck_block_v1(cnn, depth, depth_bottleneck, stride):
      
      input_layer = cnn.top_layer
      in_size = cnn.top_size
      name_key = "resnet_v1"
      name = name_key + str(cnn.counts[name_key])
      cnn.counts[name_key] += 1
  
      with tf.variable_scope(name):
          if depth == in_size:
              if stride == 1:
                  shortcut = input_layer
              else:
                  shortcut = cnn.apool(
                      1,
                      1,
                      stride,
                      stride,
                      input_layer=input_layer,
                      num_channels_in=in_size)
          else:
              shortcut = cnn.conv(
                  depth,
                  1,
                  1,
                  stride,
                  stride,
                  activation=None,
                  use_batch_norm=True,
                  input_layer=input_layer,
                  num_channels_in=in_size,
                  bias=None)
          cnn.conv(
              depth_bottleneck,
              1,
              1,
              stride,
              stride,
              input_layer=input_layer,
              num_channels_in=in_size,
              use_batch_norm=True,
              bias=None)
          cnn.conv(
              depth_bottleneck,
              3,
              3,
              1,
              1,
              mode="SAME_RESNET",
              use_batch_norm=True,
              bias=None)
          res = cnn.conv(
              depth, 1, 1, 1, 1, activation=None, use_batch_norm=True, bias=None)
          output = tf.nn.relu(shortcut + res)
          cnn.top_layer = output
          cnn.top_size = depth
docs: Bottleneck block with identity short-cut for ResNet v1.
  
    Args:
      cnn: the network to append bottleneck blocks.
      depth: the number of output filters for this bottleneck block.
      depth_bottleneck: the number of bottleneck filters for this block.
      stride: Stride used in the first layer of the bottleneck block.