mirror of
https://github.com/ROCm/jax.git
synced 2025-04-14 10:56:06 +00:00
f090074d86
In some environments this appears to import the config module rather than the config object.
128 lines
4.3 KiB
Python
128 lines
4.3 KiB
Python
# Copyright 2019 The JAX Authors.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# https://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
from functools import partial
|
|
|
|
import numpy as np
|
|
from scipy.sparse import csgraph, csr_matrix
|
|
|
|
from absl.testing import absltest
|
|
|
|
import jax
|
|
from jax._src import dtypes
|
|
from jax import numpy as jnp
|
|
from jax._src import test_util as jtu
|
|
|
|
jax.config.parse_flags_with_absl()
|
|
|
|
|
|
all_dtypes = jtu.dtypes.floating + jtu.dtypes.integer + jtu.dtypes.complex
|
|
|
|
|
|
# TODO: these tests fail without fixed PRNG seeds.
|
|
|
|
|
|
class TestPolynomial(jtu.JaxTestCase):
|
|
|
|
def assertSetsAllClose(self, x, y, rtol=None, atol=None, check_dtypes=True):
|
|
"""Assert that x and y contain permutations of the same approximate set of values.
|
|
|
|
For non-complex inputs, this is accomplished by comparing the sorted inputs.
|
|
For complex, such an approach can be confounded by numerical errors. In this case,
|
|
we compute the structural rank of the pairwise comparison matrix: if the structural
|
|
rank is full, it implies that the matrix can be permuted so that the diagonal is
|
|
non-zero, which implies a one-to-one approximate match between the permuted sets.
|
|
"""
|
|
x = np.asarray(x).ravel()
|
|
y = np.asarray(y).ravel()
|
|
|
|
atol = max(jtu.tolerance(x.dtype, atol), jtu.tolerance(y.dtype, atol))
|
|
rtol = max(jtu.tolerance(x.dtype, rtol), jtu.tolerance(y.dtype, rtol))
|
|
|
|
if not (np.issubdtype(x.dtype, np.complexfloating) or
|
|
np.issubdtype(y.dtype, np.complexfloating)):
|
|
return self.assertAllClose(np.sort(x), np.sort(y), atol=atol, rtol=rtol,
|
|
check_dtypes=check_dtypes)
|
|
|
|
if check_dtypes:
|
|
self.assertEqual(x.dtype, y.dtype)
|
|
self.assertEqual(x.size, y.size)
|
|
|
|
pairwise = np.isclose(x[:, None], x[None, :],
|
|
atol=atol, rtol=rtol, equal_nan=True)
|
|
rank = csgraph.structural_rank(csr_matrix(pairwise))
|
|
self.assertEqual(rank, x.size)
|
|
|
|
|
|
@jtu.sample_product(
|
|
dtype=all_dtypes,
|
|
length=[0, 3, 5],
|
|
leading=[0, 2],
|
|
trailing=[0, 2],
|
|
)
|
|
# TODO(phawkins): no nonsymmetric eigendecomposition implementation on GPU.
|
|
@jtu.run_on_devices("cpu")
|
|
def testRoots(self, dtype, length, leading, trailing):
|
|
rng = jtu.rand_some_zero(self.rng())
|
|
|
|
def args_maker():
|
|
p = rng((length,), dtype)
|
|
return [jnp.concatenate(
|
|
[jnp.zeros(leading, p.dtype), p, jnp.zeros(trailing, p.dtype)])]
|
|
|
|
jnp_fun = jnp.roots
|
|
def np_fun(arg):
|
|
return np.roots(arg).astype(dtypes.to_complex_dtype(arg.dtype))
|
|
|
|
# Note: outputs have no defined order, so we need to use a special comparator.
|
|
args = args_maker()
|
|
np_roots = np_fun(*args)
|
|
jnp_roots = jnp_fun(*args)
|
|
self.assertSetsAllClose(np_roots, jnp_roots)
|
|
|
|
@jtu.sample_product(
|
|
dtype=all_dtypes,
|
|
length=[0, 3, 5],
|
|
leading=[0, 2],
|
|
trailing=[0, 2],
|
|
)
|
|
# TODO(phawkins): no nonsymmetric eigendecomposition implementation on GPU.
|
|
@jtu.run_on_devices("cpu")
|
|
def testRootsNoStrip(self, dtype, length, leading, trailing):
|
|
rng = jtu.rand_some_zero(self.rng())
|
|
|
|
def args_maker():
|
|
p = rng((length,), dtype)
|
|
return [jnp.concatenate(
|
|
[jnp.zeros(leading, p.dtype), p, jnp.zeros(trailing, p.dtype)])]
|
|
|
|
jnp_fun = partial(jnp.roots, strip_zeros=False)
|
|
def np_fun(arg):
|
|
roots = np.roots(arg).astype(dtypes.to_complex_dtype(arg.dtype))
|
|
if len(roots) < len(arg) - 1:
|
|
roots = np.pad(roots, (0, len(arg) - len(roots) - 1),
|
|
constant_values=complex(np.nan, np.nan))
|
|
return roots
|
|
|
|
# Note: outputs have no defined order, so we need to use a special comparator.
|
|
args = args_maker()
|
|
np_roots = np_fun(*args)
|
|
jnp_roots = jnp_fun(*args)
|
|
self.assertSetsAllClose(np_roots, jnp_roots)
|
|
self._CompileAndCheck(jnp_fun, args_maker)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
absltest.main(testLoader=jtu.JaxTestLoader())
|