testing the model accuracy on the test set

lstm-test-model.py

# load the weights for the optimal model
lstm_model.load_weights('biLSTM.h5')

# Converts a class vector (integers) to binary class matrix
# for use with categorical_crossentropy
# IMPORTANT for CATEGORICAL_CROSSENTROPY!
y_test = np_utils.to_categorical(y_test, 2)

# generator for validating the LSTM model
test_gen = generate_batch(X_test, y_test, batch_size, expected_frames)

# checks the models performance
accu_test = lstm_model.evaluate(test_gen,
                                steps=len(X_test) // batch_size,
                                verbose=1)

# print the test result
print(f'The test accuracy for this model is {accu_test[1] * 100:0.2f}%')