Python load_text_label_pairs Examples

Example #1

File: wordvec_lstm_softmax_predict.py Project: vogali/keras-chinese-resume-parser-and-analyzer

def main():
    random_state = 42
    np.random.seed(random_state)

    model_dir_path = './models'
    data_file_path = '../data/training_data'
    text_label_pairs = load_text_label_pairs(data_file_path, label_type='line_label')

    classifier = WordVecLstmSoftmax()
    classifier.load_model(model_dir_path=model_dir_path)

    shuffle(text_label_pairs)

    for i in range(20):
        text, label = text_label_pairs[i]
        print('Output: ', classifier.predict(sentence=text))
        predicted_label = classifier.predict_class(text)
        print('Sentence: ', text)
        print('Predicted: ', predicted_label, 'Actual: ', label)

Example #2

def main():
    random_state = 42
    np.random.seed(random_state)

    output_dir_path = './models'
    data_file_path = '../data/training_data'
    text_data_model = fit_text(data_file_path)
    text_label_pairs = load_text_label_pairs(data_file_path)

    classifier = WordVecLstmSoftmax()
    batch_size = 64
    epochs = 20
    history = classifier.fit(text_data_model=text_data_model,
                             model_dir_path=output_dir_path,
                             text_label_pairs=text_label_pairs,
                             batch_size=batch_size,
                             epochs=epochs,
                             test_size=0.3,
                             random_state=random_state)