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66c9c8a | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 | # Copyright (c) 2023 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
import unittest
import numpy as np
import warp as wp
from warp.tests.unittest_utils import *
from warp.utils import array_inner, array_sum
wp.init()
def make_test_array_sum(dtype):
N = 1000
def test_array_sum(test, device):
rng = np.random.default_rng(123)
cols = wp.types.type_length(dtype)
values_np = rng.random(size=(N, cols))
values = wp.array(values_np, device=device, dtype=dtype)
vsum = array_sum(values)
ref_vsum = values_np.sum(axis=0)
assert_np_equal(vsum / N, ref_vsum / N, 0.0001)
return test_array_sum
def make_test_array_sum_axis(dtype):
I = 5
J = 10
K = 2
N = I * J * K
def test_array_sum(test, device):
rng = np.random.default_rng(123)
values_np = rng.random(size=(I, J, K))
values = wp.array(values_np, shape=(I, J, K), device=device, dtype=dtype)
for axis in range(3):
vsum = array_sum(values, axis=axis)
ref_vsum = values_np.sum(axis=axis)
assert_np_equal(vsum.numpy() / N, ref_vsum / N, 0.0001)
return test_array_sum
def test_array_sum_empty(test, device):
values = wp.array([], device=device, dtype=wp.vec2)
assert_np_equal(array_sum(values), np.zeros(2))
values = wp.array([], shape=(0, 3), device=device, dtype=float)
assert_np_equal(array_sum(values, axis=0).numpy(), np.zeros(3))
def make_test_array_inner(dtype):
N = 1000
def test_array_inner(test, device):
rng = np.random.default_rng(123)
cols = wp.types.type_length(dtype)
a_np = rng.random(size=(N, cols))
b_np = rng.random(size=(N, cols))
a = wp.array(a_np, device=device, dtype=dtype)
b = wp.array(b_np, device=device, dtype=dtype)
ab = array_inner(a, b)
ref_ab = np.dot(a_np.flatten(), b_np.flatten())
test.assertAlmostEqual(ab / N, ref_ab / N, places=5)
return test_array_inner
def make_test_array_inner_axis(dtype):
I = 5
J = 10
K = 2
N = I * J * K
def test_array_inner(test, device):
rng = np.random.default_rng(123)
a_np = rng.random(size=(I, J, K))
b_np = rng.random(size=(I, J, K))
a = wp.array(a_np, shape=(I, J, K), device=device, dtype=dtype)
b = wp.array(b_np, shape=(I, J, K), device=device, dtype=dtype)
ab = array_inner(a, b, axis=0)
ref_ab = np.einsum(a_np, [0, 1, 2], b_np, [0, 1, 2], [1, 2])
assert_np_equal(ab.numpy() / N, ref_ab / N, 0.0001)
ab = array_inner(a, b, axis=1)
ref_ab = np.einsum(a_np, [0, 1, 2], b_np, [0, 1, 2], [0, 2])
assert_np_equal(ab.numpy() / N, ref_ab / N, 0.0001)
ab = array_inner(a, b, axis=2)
ref_ab = np.einsum(a_np, [0, 1, 2], b_np, [0, 1, 2], [0, 1])
assert_np_equal(ab.numpy() / N, ref_ab / N, 0.0001)
return test_array_inner
def test_array_inner_empty(test, device):
values = wp.array([], device=device, dtype=wp.vec2)
test.assertEqual(array_inner(values, values), 0.0)
values = wp.array([], shape=(0, 3), device=device, dtype=float)
assert_np_equal(array_inner(values, values, axis=0).numpy(), np.zeros(3))
devices = get_test_devices()
class TestArrayReduce(unittest.TestCase):
pass
add_function_test(TestArrayReduce, "test_array_sum_double", make_test_array_sum(wp.float64), devices=devices)
add_function_test(TestArrayReduce, "test_array_sum_vec3", make_test_array_sum(wp.vec3), devices=devices)
add_function_test(TestArrayReduce, "test_array_sum_axis_float", make_test_array_sum_axis(wp.float32), devices=devices)
add_function_test(TestArrayReduce, "test_array_sum_empty", test_array_sum_empty, devices=devices)
add_function_test(TestArrayReduce, "test_array_inner_double", make_test_array_inner(wp.float64), devices=devices)
add_function_test(TestArrayReduce, "test_array_inner_vec3", make_test_array_inner(wp.vec3), devices=devices)
add_function_test(
TestArrayReduce, "test_array_inner_axis_float", make_test_array_inner_axis(wp.float32), devices=devices
)
add_function_test(TestArrayReduce, "test_array_inner_empty", test_array_inner_empty, devices=devices)
if __name__ == "__main__":
wp.build.clear_kernel_cache()
unittest.main(verbosity=2)
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