import numpy as np
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import LSTM
from keras.layers import Activation
from keras.layers import Masking
from keras.optimizers import RMSprop
from keras import backend as k

# Initialize model
model = Sequential()

# Mask lookback period to fix sequences of varying lengths
model.add(Masking(mask_value=0., input_shape=(max_time, 24)))

# LSTM
model.add(LSTM(50, input_dim=10, return_sequences=True))

# Output
model.add(Dense(1))

#Exponential activation function (coded separately)
model.add(Activation(expactive))


model.compile(loss=custom_loss, optimizer=RMSprop(lr=.001))

def custom_loss(y,h_out,name=None):
    return k.mean(k.pow(h_out - y,2))