class_docstr: Simple GRUModel for testing.
  
  Args:
      output_dim (int): Dimension of the network output.
      hidden_dim (int): Hidden dimension for GRU cell.
      name (str): Model name, also the variable scope.
      args (list): Unused positionl arguments.
      kwargs (dict): Unused keyword arguments.
docstr: Build model given input placeholder(s).
  
  Args:
      obs_input (tf.Tensor): Place holder for entire time-series
          inputs.
      step_obs_input (tf.Tensor): Place holder for step inputs.
      step_hidden (tf.Tensor): Place holder for step hidden state.
      name (str): Inner model name, also the variable scope of the
          inner model, if exist. One example is
          garage.tf.models.Sequential.
  
  Return:
      tf.Tensor: Entire time-series outputs.
      tf.Tensor: Step output.
      tf.Tensor: Step hidden state.
      tf.Tensor: Initial hidden state.
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code: def _build(self, obs_input, step_obs_input, step_hidden, name=None):
      """Build model given input placeholder(s).
  
      Args:
          obs_input (tf.Tensor): Place holder for entire time-series
              inputs.
          step_obs_input (tf.Tensor): Place holder for step inputs.
          step_hidden (tf.Tensor): Place holder for step hidden state.
          name (str): Inner model name, also the variable scope of the
              inner model, if exist. One example is
              garage.tf.models.Sequential.
  
      Return:
          tf.Tensor: Entire time-series outputs.
          tf.Tensor: Step output.
          tf.Tensor: Step hidden state.
          tf.Tensor: Initial hidden state.
  
      """
      del name
      return_var = tf.compat.v1.get_variable(
          "return_var", (), initializer=tf.constant_initializer(0.5)
      )
      outputs = tf.fill(
          (
              tf.shape(obs_input)[0],
              tf.shape(obs_input)[1],
              self.output_dim,
          ),
          return_var,
      )
      output = tf.fill(
          (tf.shape(step_obs_input)[0], self.output_dim), return_var
      )
  
      hidden_init_var = tf.compat.v1.get_variable(
          name="initial_hidden",
          shape=(self.hidden_dim,),
          initializer=tf.zeros_initializer(),
          trainable=False,
          dtype=tf.float32,
      )
  
      return outputs, output, step_hidden, hidden_init_var
  
imports: import tensorflow
  from garage.tf.models import Model
label_desc: Use image node_id 4 for calling the SimpleGRUModel obj's underlying member method code with example usage: obj._build(obs_input, step_obs_input, step_hidden, name) and returns: outputs,  output,  step_hidden,  hidden_init_var