code: def convolution(self, hidden_state: tf.Tensor) -> tf.Tensor:
      # Pad to match that done in the PyTorch Conv2D model
      height_pad = width_pad = (self.pad_value, self.pad_value)
      hidden_state = tf.pad(
          hidden_state, [(0, 0), height_pad, width_pad, (0, 0)]
      )
      hidden_state = self.conv(hidden_state)
      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 TFResNetConvLayer obj's underlying member method code with example usage: obj.convolution(hidden_state) and returns: hidden_state