Beispiel #1
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def load_imdb(path):
    """
    Deprecated, moved to neon.data.dataloaders.
    """
    logger.error('This function has moved, import from neon.data.dataloaders')
    from neon.data.dataloaders import load_imdb  # noqa
    return load_imdb(path)
Beispiel #2
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args = parser.parse_args(gen_be=False)

# hyperparameters from the reference
args.batch_size = 128
gradient_clip_value = 15
vocab_size = 20000
sentence_length = 128
embedding_dim = 128
hidden_size = 128
reset_cells = True

# setup backend
be = gen_backend(**extract_valid_args(args, gen_backend))

# make dataset
path = load_imdb(path=args.data_dir)
(X_train,
 y_train), (X_test, y_test), nclass = pad_data(path,
                                               vocab_size=vocab_size,
                                               sentence_length=sentence_length)

print "Vocab size - ", vocab_size
print "Sentence Length - ", sentence_length
print "# of train sentences", X_train.shape[0]
print "# of test sentence", X_test.shape[0]

train_set = ArrayIterator(X_train, y_train, nclass=2)
valid_set = ArrayIterator(X_test, y_test, nclass=2)

# weight initialization
uni = Uniform(low=-0.1 / embedding_dim, high=0.1 / embedding_dim)
Beispiel #3
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args = parser.parse_args(gen_be=False)

# hyperparameters from the reference
args.batch_size = 128
gradient_clip_value = 15
vocab_size = 20000
sentence_length = 128
embedding_dim = 128
hidden_size = 128
reset_cells = True

# setup backend
be = gen_backend(**extract_valid_args(args, gen_backend))

# make dataset
path = load_imdb(path=args.data_dir)
(X_train, y_train), (X_test, y_test), nclass = pad_data(path,
                                                        vocab_size=vocab_size,
                                                        sentence_length=sentence_length)

neon_logger.display("Vocab size - {}".format(vocab_size))
neon_logger.display("Sentence Length - {}".format(sentence_length))
neon_logger.display("# of train sentences {}".format(X_train.shape[0]))
neon_logger.display("# of test sentence {}".format(X_test.shape[0]))

train_set = ArrayIterator(X_train, y_train, nclass=2)
valid_set = ArrayIterator(X_test, y_test, nclass=2)

# weight initialization
uni = Uniform(low=-0.1 / embedding_dim, high=0.1 / embedding_dim)
g_uni = GlorotUniform()
def load_imdb(path):
    logger.error('This function has moved, import from neon.data.dataloaders')
    from neon.data.dataloaders import load_imdb  # noqa
    return load_imdb(path)