class_docstr: GRU Model.
  
  Args:
      output_dim (int): Dimension of the network output.
      hidden_dim (int): Hidden dimension for GRU cell.
      name (str): Policy name, also the variable scope.
      hidden_nonlinearity (callable): Activation function for intermediate
          dense layer(s). It should return a tf.Tensor. Set it to
          None to maintain a linear activation.
      hidden_w_init (callable): Initializer function for the weight
          of intermediate dense layer(s). The function should return a
          tf.Tensor.
      hidden_b_init (callable): Initializer function for the bias
          of intermediate dense layer(s). The function should return a
          tf.Tensor.
      recurrent_nonlinearity (callable): Activation function for recurrent
          layers. It should return a tf.Tensor. Set it to None to
          maintain a linear activation.
      recurrent_w_init (callable): Initializer function for the weight
          of recurrent layer(s). The function should return a
          tf.Tensor.
      output_nonlinearity (callable): Activation function for output dense
          layer. It should return a tf.Tensor. Set it to None to
          maintain a linear activation.
      output_w_init (callable): Initializer function for the weight
          of output dense layer(s). The function should return a
          tf.Tensor.
      output_b_init (callable): Initializer function for the bias
          of output dense layer(s). The function should return a
          tf.Tensor.
      hidden_state_init (callable): Initializer function for the
          initial hidden state. The functino should return a tf.Tensor.
      hidden_state_init_trainable (bool): Bool for whether the initial
          hidden state is trainable.
      layer_normalization (bool): Bool for using layer normalization or not.
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docstr: Object.__setstate__.
  
  Args:
      state (dict): Unpickled state.
docstr_tok: ["Object.__setstate__",".","Args",":","state","(","dict",")",":","Unpickled","state","."]
code: def __setstate__(self, state):
      """Object.__setstate__.
  
      Args:
          state (dict): Unpickled state.
  
      """
      super().__setstate__(state)
      self._initialize()
  
file_path: garage/src/garage/tf/models/gru_model.py
imports: import tensorflow
  from garage.experiment import deterministic
  from garage.tf.models.gru import gru
  from garage.tf.models.model import Model
label_desc: Use image node_id 7 for calling the GRUModel obj's underlying member method code with example usage: obj.__setstate__(state) without return types