From here: https://github.com/fchollet/keras/issues/4870

keras_test.py

import numpy as np

from keras.models import Sequential
from keras.layers import Dense
from keras.layers import LSTM

# This does work by using only one sample:
data = [[0,0,0,0,0,0,0,0,0,2,1]]
data = np.array(data, dtype=float)
target = [0,0,0,0,0,0,0,0,2,1,0]
target = np.array(target, dtype=float)

data = data.reshape((1, 1, 11)) # Single batch, 1 time steps, 11 dimentions
target = target.reshape((-1, 11)) # Corresponds to shape (None, 11)


# Build Model
model = Sequential()  
model.add(LSTM(11, input_shape=(1, 11), unroll=False))
model.add(Dense(11))
model.compile(loss='mean_absolute_error', optimizer='adam')
model.fit(data, target, nb_epoch=1000, batch_size=1, verbose=2)

# Do the output values match the target values?
predict = model.predict(data)
print(repr(data))
print(repr(predict))