code: def call(self, hidden_states: tf.Tensor) -> tf.Tensor:
      hidden_states = self.fc_in(hidden_states)
      hidden_states = self.act(hidden_states)
      hidden_states = self.fc_out(hidden_states)
      hidden_states = self.dropout(hidden_states)
      return hidden_states
  
imports: from __future__ import annotations
  from typing import Optional, Tuple, Union
  import numpy
  import tensorflow
  from ...activations_tf import get_tf_activation
  from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
  from ...modeling_tf_outputs import TFBaseModelOutputWithPast, TFCausalLMOutputWithPast, TFQuestionAnsweringModelOutput, TFSequenceClassifierOutputWithPast
  from ...modeling_tf_utils import TFCausalLanguageModelingLoss, TFModelInputType, TFPreTrainedModel, TFQuestionAnsweringLoss, TFSequenceClassificationLoss, TFSharedEmbeddings, get_initializer, keras_serializable, unpack_inputs
  from ...tf_utils import check_embeddings_within_bounds, shape_list, stable_softmax
  from ...utils import logging
  from .configuration_gptj import GPTJConfig
label_desc: Use image node_id 2 for calling the TFGPTJMLP obj's underlying member method code with example usage: obj.call(hidden_states) and returns: hidden_states