code: def ResNet50(
      include_top=True,
      weights="imagenet",
      input_tensor=None,
      input_shape=None,
      pooling=None,
      classes=1000,
      classifier_activation="softmax",
  ):
      """Instantiates the ResNet50 architecture."""
  
      def stack_fn(x):
          x = stack_residual_blocks_v1(
              x, 64, 3, stride1=1, name="conv2"
          )
          x = stack_residual_blocks_v1(x, 128, 4, name="conv3")
          x = stack_residual_blocks_v1(x, 256, 6, name="conv4")
          return stack_residual_blocks_v1(x, 512, 3, name="conv5")
  
      return ResNet(
          stack_fn,
          False,
          True,
          "resnet50",
          include_top,
          weights,
          input_tensor,
          input_shape,
          pooling,
          classes,
          classifier_activation=classifier_activation,
      )
  
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 6 for calling a global function with example usage: ResNet50(include_top, weights, input_tensor, input_shape, pooling, classes, classifier_activation) and returns: ResNet, stack_residual_blocks_v1