n_valid = count_datasets_total(valid_csvs)
print(f'# of training set: {n_train}')
print(f'# of validation set: {n_valid}')
word_encoder, countrycode_encoder = get_encoders(csvs)
with tf.Session() as sess:
K.set_session(sess)
convnet = ConvNet(
word_encoder,
countrycode_encoder,
)
model = convnet.get_model()
model.summary()
hist = model.fit_generator(
convnet.get_generator(
train_csvs,
batch_size=BATCH_SIZE,
),
steps_per_epoch=np.ceil(n_train / BATCH_SIZE).astype('int'),
epochs=EPOCHS,
validation_data=convnet.get_generator(
valid_csvs,
batch_size=BATCH_SIZE,
),
validation_steps=np.ceil(n_valid / BATCH_SIZE).astype('int'),
callbacks=convnet.get_callbacks(),
)
