Python WordEmbeddingNN.loadの例

コード例 #1

logger = create_logger(__name__)

environment.reproducible()
theano.config.floatX = 'float32'

if not os.path.exists(WORD_EMBEDDING_NN):
    raise EnvironmentError("Can't find NN model. File {} doesn't exist {}."
                           "Probably you haven't train it yet. "
                           "Run `train_word_embedding_nn.py` script.")

logger.info("Reading data")
data = pd.read_csv(REVIEWS_FILE, sep='\t')

logger.info("Loading word embedding NN")
word2vec = WordEmbeddingNN.load(WORD_EMBEDDING_NN)

prepare_data_pipeline = Pipeline([
    ('tokenize_texts', TokenizeText(ignore_stopwords=False)),
    ('ignore_unknown_words', IgnoreUnknownWords(dictionary=word2vec.vocab)),
    ('word_embedding', word2vec),
])

classifier = algorithms.RPROP(
    [
        layers.Relu(100),
        layers.Relu(200),
        layers.Sigmoid(50),
        layers.RoundedOutput(1),
    ],
    error='binary_crossentropy',

コード例 #2

ファイル: train_classifier.py プロジェクト: EdwardBetts/neupy

logger = create_logger(__name__)

environment.reproducible()
theano.config.floatX = 'float32'

if not os.path.exists(WORD_EMBEDDING_NN):
    raise EnvironmentError("Can't find NN model. File {} doesn't exist {}."
                           "Probably you haven't train it yet. "
                           "Run `train_word_embedding_nn.py` script.")

logger.info("Reading data")
data = pd.read_csv(REVIEWS_FILE, sep='\t')

logger.info("Loading word embedding NN")
word2vec = WordEmbeddingNN.load(WORD_EMBEDDING_NN)

prepare_data_pipeline = Pipeline([
    ('tokenize_texts', TokenizeText(ignore_stopwords=False)),
    ('ignore_unknown_words', IgnoreUnknownWords(dictionary=word2vec.vocab)),
    ('word_embedding', word2vec),
])

classifier = algorithms.RPROP(
    [
        layers.Relu(100),
        layers.Relu(200),
        layers.Sigmoid(50),
        layers.RoundedOutput(1),
    ],
    error='binary_crossentropy',