code: def __init__(self, config, *inputs, add_pooling_layer=True, **kwargs):
      super().__init__(config, *inputs, **kwargs)
      self.convnext = TFConvNextMainLayer(
          config, add_pooling_layer=add_pooling_layer, name="convnext"
      )
  
imports: from typing import Dict, Optional, Tuple, Union
  import numpy
  import tensorflow
  from transformers import shape_list
  from ...activations_tf import get_tf_activation
  from ...modeling_tf_outputs import TFBaseModelOutput, TFBaseModelOutputWithPooling, TFSequenceClassifierOutput
  from ...modeling_tf_utils import TFModelInputType, TFPreTrainedModel, TFSequenceClassificationLoss, get_initializer, keras_serializable, unpack_inputs
  from ...utils import add_start_docstrings, add_start_docstrings_to_model_forward, logging, replace_return_docstrings
  from .configuration_convnext import ConvNextConfig
label_desc: Use image node_id 1 to create a new TFConvNextModel object from inherited base classes: TFConvNextPreTrainedModel with example: obj = TFConvNextModel(config)