code: def __init__(self, config: RegNetConfig, *inputs, **kwargs):
      super().__init__(config, *inputs, **kwargs)
      self.regnet = TFRegNetMainLayer(config, name="regnet")
  
imports: from typing import Dict, Optional, Tuple, Union
  import tensorflow
  from ...activations_tf import ACT2FN
  from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
  from ...modeling_tf_outputs import TFBaseModelOutputWithNoAttention, TFBaseModelOutputWithPoolingAndNoAttention, TFSequenceClassifierOutput
  from ...modeling_tf_utils import TFPreTrainedModel, TFSequenceClassificationLoss, keras_serializable, unpack_inputs
  from ...tf_utils import shape_list
  from ...utils import logging
  from .configuration_regnet import RegNetConfig
label_desc: Use image node_id 1 to create a new TFRegNetModel object from inherited base classes: TFRegNetPreTrainedModel with example: obj = TFRegNetModel(config)