class_docstr: A ResNet stage composed of stacked layers.
class_docstr_tok: ["A","ResNet","stage","composed","of","stacked","layers","."]
code: def build(self, input_shape=None):
      if self.built:
          return
      self.built = True
      if getattr(self, "stage_layers", None) is not None:
          for layer in self.stage_layers:
              with tf.name_scope(layer.name):
                  layer.build(None)
  
imports: from typing import Optional, Tuple, Union
  import tensorflow
  from ...activations_tf import ACT2FN
  from ...modeling_tf_outputs import TFBaseModelOutputWithNoAttention, TFBaseModelOutputWithPoolingAndNoAttention, TFImageClassifierOutputWithNoAttention
  from ...modeling_tf_utils import TFPreTrainedModel, TFSequenceClassificationLoss, keras_serializable, unpack_inputs
  from ...tf_utils import shape_list
  from ...utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, logging
  from .configuration_resnet import ResNetConfig
label_desc: Use image node_id 3 for calling the TFResNetStage obj's underlying member method code with example usage: obj.build(input_shape) without return types