code: def stack1(x, filters, blocks, stride1=2, name=None):
      """A set of stacked residual blocks.
  
      Args:
          x: input tensor.
          filters: integer, filters of the bottleneck layer in a block.
          blocks: integer, blocks in the stacked blocks.
          stride1: default 2, stride of the first layer in the first block.
          name: string, stack label.
  
      Returns:
          Output tensor for the stacked blocks.
      """
      x = block1(x, filters, stride=stride1, name=f"{name}_block1")
      for i in range(2, blocks + 1):
          x = block1(
              x,
              filters,
              conv_shortcut=False,
              name=f"{name}_block{str(i)}",
          )
      return x
  
file_path: keras-tuner/keras_tuner/applications/resnet.py
imports: from keras_tuner.api_export import keras_tuner_export
  from keras_tuner.backend import keras
  from keras_tuner.backend import ops
  from keras_tuner.backend.keras import layers
  from keras_tuner.engine import hypermodel
label_desc: Use image node_id 2 for calling a global function with example usage: stack1(x, filters, blocks, stride1, name) and returns: x