keras/tests/test_loss_masking.py
François Chollet ea561ba6d8 Add model saving functionality (#3314)
* Add model saving functionality

* Update model saving functionality

* Fix py3 bytes/str issue

* Fix tests
2016-07-26 20:45:28 -07:00

47 lines
1.2 KiB
Python

import numpy as np
import pytest
from keras.models import Sequential
from keras.engine.training import weighted_objective
from keras.layers.core import TimeDistributedDense, Masking
from keras.utils.test_utils import keras_test
from keras import objectives
from keras import backend as K
@keras_test
def test_masking():
np.random.seed(1337)
X = np.array([[[1], [1]],
[[0], [0]]])
model = Sequential()
model.add(Masking(mask_value=0, input_shape=(2, 1)))
model.add(TimeDistributedDense(1, init='one'))
model.compile(loss='mse', optimizer='sgd')
y = np.array([[[1], [1]],
[[1], [1]]])
loss = model.train_on_batch(X, y)
assert loss == 0
@keras_test
def test_loss_masking():
weighted_loss = weighted_objective(objectives.get('mae'))
shape = (3, 4, 2)
X = np.arange(24).reshape(shape)
Y = 2 * X
# Normally the trailing 1 is added by standardize_weights
weights = np.ones((3,))
mask = np.ones((3, 4))
mask[1, 0] = 0
out = K.eval(weighted_loss(K.variable(X),
K.variable(Y),
K.variable(weights),
K.variable(mask)))
if __name__ == '__main__':
pytest.main([__file__])