def test_basic(self):
utt.verify_grad(xlogy0, [numpy.random.rand(3, 4), numpy.random.rand(3, 4)])
x = as_tensor_variable([1, 0])
y = as_tensor_variable([1, 0])
z = xlogy0(x, y)
f = theano.function([], z)
assert numpy.all(f() == numpy.asarray([0, 0.0]))
def binary_cross_entropy(target, output, sum_axis=1):
XE = xlogy0(target, output) + xlogy0((1 - target), (1 - output))
return -T.sum(XE, axis=sum_axis)
def test3(self):
x = as_tensor_variable([1, 0])
y = as_tensor_variable([1, 0])
z = xlogy0(x, y)
f = theano.function([], z)
self.assertTrue(numpy.all(f() == numpy.asarray([0, 0.])))
def test3(self):
x = as_tensor_variable([1, 0])
y = as_tensor_variable([1, 0])
z = xlogy0(x, y)
f = theano.function([], z)
self.assertTrue(numpy.all(f() == numpy.asarray([0, 0.])))