Keras Embedding + Backwards LSTM

lstm_backwards_embedding.py

from keras.models import Sequential # model used
from keras.layers import Dense, Embedding, LSTM # layers used

batch_size = 2 # how many sequence to process in parallel
time_steps = 3 # lstm length, number of cells, etc.
input_dim = 1 # number of features
embedding_size = 5 # size of embedding vector

model = Sequential()
model.add(Embedding(
    input_dim=input_dim,
    output_dim=embedding_size,
    input_length=time_steps,
    batch_input_shape=(batch_size,time_steps),
    mask_zero=True
))
model.add(LSTM(10,  batch_input_shape=(batch_size,time_steps,embedding_size), return_sequences=False, go_backwards=True))