class_docstr: A classic ResNet's residual layer composed by two `3x3` convolutions.
class_docstr_tok: ["A","classic","ResNet","'s","residual","layer","composed","by","two","`","3x3","`","convolutions","."]
code: def build(self, input_shape=None):
      if self.built:
          return
      self.built = True
      if getattr(self, "conv1", None) is not None:
          with tf.name_scope(self.conv1.name):
              self.conv1.build(None)
      if getattr(self, "conv2", None) is not None:
          with tf.name_scope(self.conv2.name):
              self.conv2.build(None)
      if getattr(self, "shortcut", None) is not None:
          with tf.name_scope(self.shortcut.name):
              self.shortcut.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 TFResNetBasicLayer obj's underlying member method code with example usage: obj.build(input_shape) without return types