class_docstr: A ResNet stage composed of stacked layers.
class_docstr_tok: ["A","ResNet","stage","composed","of","stacked","layers","."]
code: def call(
      self, hidden_state: tf.Tensor, training: bool = False
  ) -> tf.Tensor:
      for layer in self.stage_layers:
          hidden_state = layer(hidden_state, training=training)
      return hidden_state
  
imports: from typing import Dict, 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 2 for calling the TFResNetStage obj's underlying member method code with example usage: obj.call(hidden_state, training) and returns: hidden_state