Simplest sequence classifier with LSTM & softmax in Keras

simples_lstm_softmax_classifier_keras.py

"""
Classifies sequences of length 10 with 20 features into 2 classes
with a single LSTM layer with 32 neurons.

See also a more involved example:
https://gist.github.com/bzamecnik/dccc1c4fdcf1c7a31757168b19c827a7
"""


from keras.layers import Input, LSTM, Dense
from keras.models import Model

seq_length = 10
feature_count = 20
class_count = 2
rnn_width = 32

input = Input(shape=(seq_length, feature_count))
LSTM(class_count, activation='softmax')(input)
model = Model(input, x)

model.summary()
#____________________________________________________________________________________________________
#Layer (type)                     Output Shape          Param #     Connected to                     
#====================================================================================================
#input_6 (InputLayer)             (None, 10, 20)        0                                            
#____________________________________________________________________________________________________
#lstm_15 (LSTM)                   (None, 2)             184         input_6[0][0]                    
#====================================================================================================
#Total params: 184
#____________________________________________________________________________________________________

model.compile(loss='categorical_crossentropy', optimizer='adam')