Keras 1.1.0 - Model

model.py

# Create simple model
model = Sequential()

model.add(TimeDistributed(Convolution2D(32, 3, 3, border_mode='same'), input_shape = batch_input_shape[1:]))
model.add(Activation('relu'))
model.add(TimeDistributed(MaxPooling2D(pool_size = (2,2))))
model.add(BatchNormalization())

model.add(TimeDistributed(Convolution2D(32, 3, 3, border_mode='same')))
model.add(Activation('relu'))
model.add(TimeDistributed(MaxPooling2D(pool_size = (2,2))))
model.add(BatchNormalization())

model.add(TimeDistributed(Convolution2D(32, 3, 3, border_mode='same')))
model.add(Activation('relu'))
model.add(TimeDistributed(MaxPooling2D(pool_size = (2,2))))
model.add(BatchNormalization())

model.add(TimeDistributed(Convolution2D(32, 2, 2, border_mode='same')))
model.add(Activation('relu'))
model.add(TimeDistributed(MaxPooling2D(pool_size = (2,2))))
model.add(BatchNormalization())

model.add(TimeDistributed(Flatten()))

model.add(LSTM(32, stateful = True, return_sequences = False))

model.add(Dense(1))
model.add(Activation('sigmoid'))