def test_perform(self):
x = tensor.matrix()
y = tensor.scalar()
f = function([x, y], fill_diagonal(x, y))
for shp in [(8, 8), (5, 8), (8, 5)]:
a = numpy.random.rand(*shp).astype(config.floatX)
val = numpy.cast[config.floatX](numpy.random.rand())
out = f(a, val)
# We can't use numpy.fill_diagonal as it is bugged.
assert numpy.allclose(numpy.diag(out), val)
assert (out == val).sum() == min(a.shape)
# test for 3d tensor
a = numpy.random.rand(3, 3, 3).astype(config.floatX)
x = tensor.tensor3()
y = tensor.scalar()
f = function([x, y], fill_diagonal(x, y))
val = numpy.cast[config.floatX](numpy.random.rand() + 10)
out = f(a, val)
# We can't use numpy.fill_diagonal as it is bugged.
assert out[0, 0, 0] == val
assert out[1, 1, 1] == val
assert out[2, 2, 2] == val
assert (out == val).sum() == min(a.shape)
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