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Disable float0 tests that fail under NumPy 1.21. #7096

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Jun 24, 2021
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Disable float0 tests that fail under NumPy 1.21. #7096

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35 changes: 35 additions & 0 deletions tests/api_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -55,6 +55,9 @@
FLAGS = config.FLAGS


numpy_version = tuple(map(int, np.__version__.split('.')[:3]))


class CPPJitTest(jtu.BufferDonationTestCase):
"""Shared tests between the Python and the C++ jax,jit implementations.

Expand Down Expand Up @@ -1484,47 +1487,61 @@ def test_grad_of_int_errors(self):
r"sub-dtype of np.floating or np.complexfloating\), but got int.*."),
lambda: dfn(3))

@unittest.skipIf(numpy_version == (1, 21, 0),
"https://github.com/numpy/numpy/issues/19305")
def test_jvp_of_int_identity(self):
primals = (1,)
tangents = (np.zeros(shape=(), dtype=float0),)

_, out = api.jvp(lambda x: x, primals, tangents)
self.assertEqual(out, np.zeros(shape=(), dtype=float0))

@unittest.skipIf(numpy_version == (1, 21, 0),
"https://github.com/numpy/numpy/issues/19305")
def test_jvp_of_int_add(self):
primals = (2,)
tangents = (np.zeros(shape=(), dtype=float0),)

_, out_tangent = api.jvp(lambda x: x+1, primals, tangents)
self.assertEqual(out_tangent, np.zeros(shape=(), dtype=float0))

@unittest.skipIf(numpy_version == (1, 21, 0),
"https://github.com/numpy/numpy/issues/19305")
def test_jit_jvp_of_int(self):
primals = (2,)
tangents = (np.zeros(shape=(), dtype=float0),)

_, out_tangent = api.jvp(jax.jit(lambda x: x+1), primals, tangents)
self.assertEqual(out_tangent, np.zeros(shape=(), dtype=float0))

@unittest.skipIf(numpy_version == (1, 21, 0),
"https://github.com/numpy/numpy/issues/19305")
def test_vjp_of_int_index(self):
primal, fn_vjp = api.vjp(lambda x, i: x[i], np.ones(2)*2, 1)
tangent_x, tangent_i = fn_vjp(1.)
self.assertEqual(primal, 2.)
self.assertAllClose(tangent_x, jnp.array([0., 1.]))
self.assertEqual(tangent_i, np.zeros(shape=(), dtype=float0))

@unittest.skipIf(numpy_version == (1, 21, 0),
"https://github.com/numpy/numpy/issues/19305")
def test_vjp_of_int_shapes(self):
out, fn_vjp = api.vjp(lambda x: lax.reshape(x, (2, 2)), np.ones((4, 1),
dtype=int))
tangent, = fn_vjp(out)
self.assertArraysEqual(tangent, np.zeros(shape=(4, 1), dtype=float0))

@unittest.skipIf(numpy_version == (1, 21, 0),
"https://github.com/numpy/numpy/issues/19305")
def test_jit_vjp_of_int(self):
primal, fn_vjp = api.vjp(lambda x, y: x+y, 2, 1)
tangent_x, tangent_i = jax.jit(fn_vjp)(1)
self.assertEqual(primal, 3)
self.assertEqual(tangent_x, np.zeros(shape=(), dtype=float0))
self.assertEqual(tangent_i, np.zeros(shape=(), dtype=float0))

@unittest.skipIf(numpy_version == (1, 21, 0),
"https://github.com/numpy/numpy/issues/19305")
def test_vjp_of_int_fulllike(self):
# Regression test for tangent and cotangent mismatch in convert_element_type
# transpose rule wrt a ConstVar
Expand All @@ -1535,30 +1552,40 @@ def test_vjp_of_int_fulllike(self):
self.assertAllClose(tangent_x, jnp.zeros((2, 2)))
self.assertEqual(tangent_y, np.zeros(shape=(), dtype=float0))

@unittest.skipIf(numpy_version == (1, 21, 0),
"https://github.com/numpy/numpy/issues/19305")
def test_grad_of_int(self):
# Need real-valued output, but testing integer input.
out = api.grad(lambda x: x+0., allow_int=True)(1)
self.assertEqual(out, np.zeros(shape=(), dtype=float0))

@unittest.skipIf(numpy_version == (1, 21, 0),
"https://github.com/numpy/numpy/issues/19305")
def test_grad_of_bool(self):
def cond(pred):
return lax.cond(pred, lambda _: 1., lambda _: 2., 1.)
value, grd = api.value_and_grad(cond, allow_int=True)(True)
self.assertEqual(value, 1.)
self.assertEqual(grd, np.zeros(shape=(), dtype=float0))

@unittest.skipIf(numpy_version == (1, 21, 0),
"https://github.com/numpy/numpy/issues/19305")
def test_grad_of_int_index(self):
grad_x, grad_i = api.grad(lambda x, i: x[i], argnums=(0, 1),
allow_int=True)(np.ones(2), 1)
self.assertAllClose(grad_x, jnp.array([0., 1.]))
self.assertEqual(grad_i, np.zeros(shape=(), dtype=float0))

@unittest.skipIf(numpy_version == (1, 21, 0),
"https://github.com/numpy/numpy/issues/19305")
def test_jit_grad_of_int(self):
grad_f = api.grad(lambda x, i: x[i], argnums=(0, 1), allow_int=True)
grad_x, grad_i = jax.jit(grad_f)(np.ones(2), 1)
self.assertAllClose(grad_x, jnp.array([0., 1.]))
self.assertEqual(grad_i, np.zeros(shape=(), dtype=float0))

@unittest.skipIf(numpy_version == (1, 21, 0),
"https://github.com/numpy/numpy/issues/19305")
def test_float0_reshape(self):
# dtype-agnostic operations are supported
float0_array = jax.grad(lambda x: jnp.sum(x+0.),
Expand Down Expand Up @@ -3894,6 +3921,8 @@ def f_jvp(primal, tangent):

api.vmap(sample)(jax.random.split(jax.random.PRNGKey(1), 3)) # don't crash

@unittest.skipIf(numpy_version == (1, 21, 0),
"https://github.com/numpy/numpy/issues/19305")
def test_float0(self):
@api.custom_jvp
def f(x, y):
Expand All @@ -3909,6 +3938,8 @@ def f_jvp(primals, _):
self.assertArraysEqual(api.jvp(f, primals, tangents),
(primals, expected_tangents))

@unittest.skipIf(numpy_version == (1, 21, 0),
"https://github.com/numpy/numpy/issues/19305")
def test_float0_initial_style(self):
@api.custom_jvp
def f(x, y):
Expand Down Expand Up @@ -4837,6 +4868,8 @@ def bwd(y, g):
ans = jax.grad(f)(4.)
self.assertAllClose(ans, -2. * jnp.sin(4.))

@unittest.skipIf(numpy_version == (1, 21, 0),
"https://github.com/numpy/numpy/issues/19305")
def test_float0(self):
@api.custom_vjp
def f(x, _):
Expand All @@ -4853,6 +4886,8 @@ def f_rev(*_):
self.assertEqual(api.grad(f, allow_int=True, argnums=(0, 1))(x, y),
(2., np.zeros(shape=(), dtype=float0)))

@unittest.skipIf(numpy_version == (1, 21, 0),
"https://github.com/numpy/numpy/issues/19305")
def test_float0_initial_style(self):
@api.custom_vjp
def f(x):
Expand Down