lstm.py

import os
import time
import json
import warnings
import numpy as np
from numpy import newaxis
from keras.layers.core import Dense, Activation, Dropout
from keras.layers.recurrent import LSTM
from keras.models import Sequential
from keras.models import load_model

configs = json.loads(open(os.path.join(os.path.dirname(__file__), 'configs.json')).read())
warnings.filterwarnings("ignore") #Hide messy Numpy warnings

def build_network(layers):
    model = Sequential()

    model.add(LSTM(
        input_dim=layers[0],
        output_dim=layers[1],
        return_sequences=True))
    model.add(Dropout(0.2))

    model.add(LSTM(
        layers[2],
        return_sequences=False))
    model.add(Dropout(0.2))

    model.add(Dense(
        output_dim=layers[3]))
    model.add(Activation("tanh"))

    start = time.time()
    model.compile(
        loss=configs['model']['loss_function'],
        optimizer=configs['model']['optimiser_function'])

    print("> Compilation Time : ", time.time() - start)
    return model

def load_network(filename):
    #Load the h5 saved model and weights
    if(os.path.isfile(filename)):
        return load_model(filename)
    else:
        print('ERROR: "' + filename + '" file does not exist as a h5 model')
        return None