def train_lstm_model():
X_train, X_valid, Y_train, Y_valid = Datasets.make_lstm_data(
data_folder_path)
callbacks = [EarlyStopping(monitor='val_loss', patience=3)]
#ModelCheckpoint(filepath='best_model.h5', monitor='val_loss', save_best_only=True)]
model = lstm_categorical(input_dimension=(7, 120, 160, 3))
model.fit(X_train,
Y_train,
epochs=20,
batch_size=64,
validation_data=(X_valid, Y_valid))
timestamp = datetime.datetime.now().strftime('%Y%m%d%H%M%S')
model.save_weights('saved_models/lstm_categorical_' + timestamp + '.h5',
overwrite=True)
