5d32a2bc0aa033a4a03a005699fd6268bbaa1a7f,src/garage/tf/models/lstm.py,,lstm,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,5

Before Change

            initializer=tf.concat(axis=1,
                                  values=[hidden_init_var_b, cell_init_var_b]),
        )
        hcs = tf.transpose(hcs, (1, 0, 2))
        hs = hcs[:, :, :hidden_dim]
        outputs = output_nonlinearity_layer(hs)

After Change

        cell_init_var_b = tf.broadcast_to(
            cell_init_var, shape=[tf.shape(all_input_var)[0], hidden_dim])

        rnn = tf.keras.layers.RNN(lstm_cell, return_sequences=True)

        hs = rnn(all_input_var,
                 initial_state=[hidden_init_var_b, cell_init_var_b])
        outputs = output_nonlinearity_layer(hs)

Instances