policy.py

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals

import logging

from rasa_core.policies.keras_policy import KerasPolicy

logger = logging.getLogger(__name__)


class OrderPolicy(KerasPolicy):
    def model_architecture(self, num_features, num_actions, max_history_len):
        """Build a Keras model and return a compiled model."""
        from keras.layers import LSTM, Activation, Masking, Dense
        from keras.models import Sequential

        n_hidden = 32  # size of hidden layer in LSTM
        # Build Model
        batch_shape = (None, max_history_len, num_features)

        model = Sequential()
        model.add(Masking(-1, batch_input_shape=batch_shape))
        model.add(LSTM(n_hidden, batch_input_shape=batch_shape))
        model.add(Dense(input_dim=n_hidden, output_dim=num_actions))
        model.add(Activation('softmax'))

        model.compile(loss='categorical_crossentropy',
                      optimizer='adam',
                      metrics=['accuracy'])

        logger.debug(model.summary())
        return model