models/actor_critic_lstm.py
def forward_rnn(self, input_dict, state, seq_lens):
        """
        Forward pass through the LSTM.
        :param input_dict: The input tensors.
        :param state: The model state.
        :param seq_lens: LSTM sequence lengths.
        :return: The model output.
        """
        input = [input_dict["curr_obs"], seq_lens] + state

        model_out, self._value_out, h, c = self.rnn_model(input)
        return model_out, self._value_out, h, c

        Forward pass through the LSTM.
        :param input_dict: The input tensors.
        :param state: The model state.
        :param seq_lens: LSTM sequence lengths.
        :return: The model output.
        
Forward pass through the LSTM.
Forward pass through the LSTM .
def forward_rnn(self, input_dict, state, seq_lens):
        input = [input_dict["curr_obs"], seq_lens] + state
        model_out, self._value_out, h, c = self.rnn_model(input)
        return model_out, self._value_out, h, c
def forward_rnn ( self , input_dict , state , seq_lens ) : input = [ input_dict [ "curr_obs" ] , seq_lens ] + state model_out , self . _value_out , h , c = self . rnn_model ( input ) return model_out , self . _value_out , h , c
Forward pass through the LSTM.
Forward pass through the LSTM .
"""
        Forward pass through the LSTM.
        :param input_dict: The input tensors.
        :param state: The model state.
        :param seq_lens: LSTM sequence lengths.
        :return: The model output.
        """
The model output.
The model output .
self
input_dict
The input tensors.
The input tensors .
state
The model state.
The model state .
seq_lens
LSTM sequence lengths.
LSTM sequence lengths .