code: def stack_residual_blocks_v2(
      x, filters, blocks, stride1=2, name=None
  ):
      """A set of stacked residual blocks.
  
      Args:
          x: Input tensor.
          filters: Number of filters in the bottleneck layer in a block.
          blocks: Number of blocks in the stacked blocks.
          stride1: Stride of the first layer in the first block. Defaults to `2`.
          name: Stack label.
  
      Returns:
          Output tensor for the stacked blocks.
      """
  
      x = residual_block_v2(
          x, filters, conv_shortcut=True, name=name + "_block1"
      )
      for i in range(2, blocks):
          x = residual_block_v2(
              x, filters, name=name + "_block" + str(i)
          )
      x = residual_block_v2(
          x, filters, stride=stride1, name=name + "_block" + str(blocks)
      )
      return x
  
file_path: keras/keras/applications/resnet.py
imports: from keras import backend
  from keras import layers
  from keras.api_export import keras_export
  from keras.applications import imagenet_utils
  from keras.models import Functional
  from keras.ops import operation_utils
  from keras.utils import file_utils
label_desc: Use image node_id 5 for calling a global function with example usage: stack_residual_blocks_v2(x, filters, blocks, stride1, name) and returns: x