def test_gpu_eigh_opt(self):
A = fmatrix("A")
fn = aesara.function([A], eigh(A), mode=mode_with_gpu)
assert any([
isinstance(node.op, GpuMagmaEigh)
for node in fn.maker.fgraph.toposort()
])
def test_jax_basic_multiout():
rng = np.random.default_rng(213234)
M = rng.normal(size=(3, 3))
X = M.dot(M.T)
x = matrix("x")
outs = aet_nlinalg.eig(x)
out_fg = FunctionGraph([x], outs)
def assert_fn(x, y):
np.testing.assert_allclose(x.astype(config.floatX), y, rtol=1e-3)
compare_jax_and_py(out_fg, [X.astype(config.floatX)], assert_fn=assert_fn)
outs = aet_nlinalg.eigh(x)
out_fg = FunctionGraph([x], outs)
compare_jax_and_py(out_fg, [X.astype(config.floatX)], assert_fn=assert_fn)
outs = aet_nlinalg.qr(x, mode="full")
out_fg = FunctionGraph([x], outs)
compare_jax_and_py(out_fg, [X.astype(config.floatX)], assert_fn=assert_fn)
outs = aet_nlinalg.qr(x, mode="reduced")
out_fg = FunctionGraph([x], outs)
compare_jax_and_py(out_fg, [X.astype(config.floatX)], assert_fn=assert_fn)
outs = aet_nlinalg.svd(x)
out_fg = FunctionGraph([x], outs)
compare_jax_and_py(out_fg, [X.astype(config.floatX)], assert_fn=assert_fn)
def test_jax_basic_multiout():
np.random.seed(213234)
M = np.random.normal(size=(3, 3))
X = M.dot(M.T)
x = matrix("x")
outs = aet_nlinalg.eig(x)
out_fg = FunctionGraph([x], outs)
def assert_fn(x, y):
np.testing.assert_allclose(x.astype(config.floatX), y, rtol=1e-3)
compare_jax_and_py(out_fg, [X.astype(config.floatX)], assert_fn=assert_fn)
outs = aet_nlinalg.eigh(x)
out_fg = FunctionGraph([x], outs)
compare_jax_and_py(out_fg, [X.astype(config.floatX)], assert_fn=assert_fn)
outs = aet_nlinalg.qr(x, mode="full")
out_fg = FunctionGraph([x], outs)
compare_jax_and_py(out_fg, [X.astype(config.floatX)], assert_fn=assert_fn)
outs = aet_nlinalg.qr(x, mode="reduced")
out_fg = FunctionGraph([x], outs)
compare_jax_and_py(out_fg, [X.astype(config.floatX)], assert_fn=assert_fn)
outs = aet_nlinalg.svd(x)
out_fg = FunctionGraph([x], outs)
compare_jax_and_py(out_fg, [X.astype(config.floatX)], assert_fn=assert_fn)
# Test that a single output of a multi-output `Op` can be used as input to
# another `Op`
x = dvector()
mx, amx = MaxAndArgmax([0])(x)
out = mx * amx
out_fg = FunctionGraph([x], [out])
compare_jax_and_py(out_fg, [np.r_[1, 2]])