File size: 4,198 Bytes
fc0f7bd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 | # Copyright 2019 DeepMind Technologies Limited. All Rights Reserved.
#
# 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
#
# http://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.
# ==============================================================================
"""Tests for optax._src.numerics."""
import functools
import itertools
import re
from absl.testing import absltest
from absl.testing import parameterized
import chex
import jax
import jax.numpy as jnp
import numpy as np
from optax._src import numerics
_ALL_ORDS = [None, np.inf, -np.inf, 'fro', 'nuc', 0, 1, 2, -2, -2, -1.5, 1.5]
int32_array = lambda i: jnp.array(i, dtype=jnp.int32)
float32_array = lambda i: jnp.array(i, dtype=jnp.float32)
def _invalid_ord_axis_inputs(ord_axis_keepdims):
ord_, axis = ord_axis_keepdims[0], ord_axis_keepdims[1]
return any(((ord_ == 0 and axis is None),
(isinstance(ord_, float) and axis is None),
(isinstance(ord_, str) and axis is not None)))
class NumericsTest(chex.TestCase):
@chex.all_variants
def test_safe_int32_increments(self):
inc_fn = self.variant(numerics.safe_int32_increment)
# increment small numbers correctly.
base = int32_array(3)
incremented = inc_fn(base)
np.testing.assert_array_equal(incremented, int32_array(4))
# avoid overflow when incrementing maxint.
base = int32_array(np.iinfo(np.int32).max)
incremented = inc_fn(base)
np.testing.assert_array_equal(incremented, base)
@chex.all_variants
@parameterized.parameters(
itertools.filterfalse(
_invalid_ord_axis_inputs,
itertools.product(_ALL_ORDS, [None, 0, 1], [False, True])))
def test_safe_norm(self, ord, axis, keepdims): # pylint: disable=redefined-builtin
dnorm_dx = self.variant(
jax.jacfwd(
functools.partial(
numerics.safe_norm, ord=ord, axis=axis, keepdims=keepdims),
argnums=0))
# Test gradient is 0. in 0. when zero min norm is used.
g = dnorm_dx(float32_array(jnp.zeros((3, 4))), float32_array(0.))
np.testing.assert_array_equal(g, jnp.zeros_like(g))
# Test gradient is 0. in 0. when non zero min norm is used.
g = dnorm_dx(float32_array(jnp.zeros((3, 4))), float32_array(3.))
np.testing.assert_array_equal(g, jnp.zeros_like(g))
@chex.all_variants
def test_safe_rms(self):
drms_dx = self.variant(jax.grad(numerics.safe_root_mean_squares))
# Test gradient is 0. in 0. when zero min rms is used.
g = drms_dx(float32_array(0.), float32_array(0.))
np.testing.assert_array_equal(g, jnp.zeros_like(g))
# Test gradient is 0. in 0. when non zero min rms is used.
g = drms_dx(float32_array(0.), float32_array(3.))
np.testing.assert_array_equal(g, jnp.zeros_like(g))
def test_complex_vs_real_abs_sqr(self):
# Tests that JAX generates the same HLO from `numerics.abs_sq`,
# `jnp.square(x)`, `x * x`, and `x**2`.
real_sq_fns = (lambda x: x**2, lambda x: x * x, jnp.square)
def _get_hlo_repr(f, x):
hlo_string = jax.jit(f).lower(x).compiler_ir(dialect='hlo').as_hlo_text()
return re.sub('HloModule.*?\n', '',
re.sub('ENTRY.*?{', 'ENTRY XXXX', hlo_string))
# Real arg (same HLO).
for real_sq_fn in real_sq_fns:
for real_x in (3, 3.0, np.array([4, 5.2])):
self.assertEqual(
_get_hlo_repr(real_sq_fn, real_x),
_get_hlo_repr(numerics.abs_sq, real_x))
# Complex arg (different HLOs).
for real_sq_fn in real_sq_fns:
for complex_x in (1j, 3. + 1j, np.array([4 + 1j, 5.2 + 1j])):
self.assertNotEqual(
_get_hlo_repr(real_sq_fn, complex_x),
_get_hlo_repr(numerics.abs_sq, complex_x))
if __name__ == '__main__':
absltest.main()
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