def test_absolute():
X, Y = T.matrix(), T.matrix()
X.tag.test_value = test_X
Y.tag.test_value = test_Y
dist = absolute(X, Y).sum()
f = theano.function([X, Y], dist, mode='FAST_COMPILE')
res = f(test_X, test_Y)
assert res == 0.21, 'absolute loss not working'
def test_absolute_colwise():
X, Y = T.matrix(), T.matrix()
X.tag.test_value = test_X
Y.tag.test_value = test_Y
dist = absolute(X, Y).sum(axis=0)
f = theano.function([X, Y], dist, mode='FAST_COMPILE')
res = f(test_X, test_Y)
correct = np.allclose(res, [0.06, 0.08, 0.07])
assert correct, 'absolute loss colwise not working'
def test_absolute():
X, Y = T.matrix(), T.matrix()
X.tag.test_value = test_X
Y.tag.test_value = test_Y
dist = absolute(X, Y).sum()
f = theano.function([X, Y], dist, mode='FAST_COMPILE')
res = f(test_X, test_Y)
print res
assert np.allclose(res, 0.21), 'absolute loss not working'
def test_absolute_rowwise():
X, Y = T.matrix(), T.matrix()
X.tag.test_value = test_X
Y.tag.test_value = test_Y
dist = absolute(X, Y).sum(axis=1)
f = theano.function([X, Y], dist, mode='FAST_COMPILE')
res = f(test_X, test_Y)
correct = roughly(res, [0.06, 0.15])
assert correct, 'absolute loss rowwise not working'
