summaryrefslogtreecommitdiffstats
path: root/third_party/aom/test/hiprec_convolve_test_util.cc
diff options
context:
space:
mode:
Diffstat (limited to 'third_party/aom/test/hiprec_convolve_test_util.cc')
-rw-r--r--third_party/aom/test/hiprec_convolve_test_util.cc331
1 files changed, 331 insertions, 0 deletions
diff --git a/third_party/aom/test/hiprec_convolve_test_util.cc b/third_party/aom/test/hiprec_convolve_test_util.cc
new file mode 100644
index 000000000..2672bcec3
--- /dev/null
+++ b/third_party/aom/test/hiprec_convolve_test_util.cc
@@ -0,0 +1,331 @@
+/*
+ * Copyright (c) 2016, Alliance for Open Media. All rights reserved
+ *
+ * This source code is subject to the terms of the BSD 2 Clause License and
+ * the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License
+ * was not distributed with this source code in the LICENSE file, you can
+ * obtain it at www.aomedia.org/license/software. If the Alliance for Open
+ * Media Patent License 1.0 was not distributed with this source code in the
+ * PATENTS file, you can obtain it at www.aomedia.org/license/patent.
+ */
+
+#include "test/hiprec_convolve_test_util.h"
+
+#include "av1/common/restoration.h"
+
+using ::testing::make_tuple;
+using ::testing::tuple;
+
+namespace libaom_test {
+
+// Generate a random pair of filter kernels, using the ranges
+// of possible values from the loop-restoration experiment
+static void generate_kernels(ACMRandom *rnd, InterpKernel hkernel,
+ InterpKernel vkernel) {
+ hkernel[0] = hkernel[6] =
+ WIENER_FILT_TAP0_MINV +
+ rnd->PseudoUniform(WIENER_FILT_TAP0_MAXV + 1 - WIENER_FILT_TAP0_MINV);
+ hkernel[1] = hkernel[5] =
+ WIENER_FILT_TAP1_MINV +
+ rnd->PseudoUniform(WIENER_FILT_TAP1_MAXV + 1 - WIENER_FILT_TAP1_MINV);
+ hkernel[2] = hkernel[4] =
+ WIENER_FILT_TAP2_MINV +
+ rnd->PseudoUniform(WIENER_FILT_TAP2_MAXV + 1 - WIENER_FILT_TAP2_MINV);
+ hkernel[3] = -(hkernel[0] + hkernel[1] + hkernel[2]);
+ hkernel[7] = 0;
+
+ vkernel[0] = vkernel[6] =
+ WIENER_FILT_TAP0_MINV +
+ rnd->PseudoUniform(WIENER_FILT_TAP0_MAXV + 1 - WIENER_FILT_TAP0_MINV);
+ vkernel[1] = vkernel[5] =
+ WIENER_FILT_TAP1_MINV +
+ rnd->PseudoUniform(WIENER_FILT_TAP1_MAXV + 1 - WIENER_FILT_TAP1_MINV);
+ vkernel[2] = vkernel[4] =
+ WIENER_FILT_TAP2_MINV +
+ rnd->PseudoUniform(WIENER_FILT_TAP2_MAXV + 1 - WIENER_FILT_TAP2_MINV);
+ vkernel[3] = -(vkernel[0] + vkernel[1] + vkernel[2]);
+ vkernel[7] = 0;
+}
+
+namespace AV1HiprecConvolve {
+
+::testing::internal::ParamGenerator<HiprecConvolveParam> BuildParams(
+ hiprec_convolve_func filter) {
+ const HiprecConvolveParam params[] = {
+ make_tuple(8, 8, 50000, filter), make_tuple(8, 4, 50000, filter),
+ make_tuple(64, 24, 1000, filter), make_tuple(64, 64, 1000, filter),
+ make_tuple(64, 56, 1000, filter), make_tuple(32, 8, 10000, filter),
+ make_tuple(32, 28, 10000, filter), make_tuple(32, 32, 10000, filter),
+ make_tuple(16, 34, 10000, filter), make_tuple(32, 34, 10000, filter),
+ make_tuple(64, 34, 1000, filter), make_tuple(8, 17, 10000, filter),
+ make_tuple(16, 17, 10000, filter), make_tuple(32, 17, 10000, filter)
+ };
+ return ::testing::ValuesIn(params);
+}
+
+AV1HiprecConvolveTest::~AV1HiprecConvolveTest() {}
+void AV1HiprecConvolveTest::SetUp() {
+ rnd_.Reset(ACMRandom::DeterministicSeed());
+}
+
+void AV1HiprecConvolveTest::TearDown() { libaom_test::ClearSystemState(); }
+
+void AV1HiprecConvolveTest::RunCheckOutput(hiprec_convolve_func test_impl) {
+ const int w = 128, h = 128;
+ const int out_w = GET_PARAM(0), out_h = GET_PARAM(1);
+ const int num_iters = GET_PARAM(2);
+ int i, j;
+ const ConvolveParams conv_params = get_conv_params_wiener(8);
+
+ uint8_t *input_ = new uint8_t[h * w];
+ uint8_t *input = input_;
+
+ // The AVX2 convolve functions always write rows with widths that are
+ // multiples of 16. So to avoid a buffer overflow, we may need to pad
+ // rows to a multiple of 16.
+ int output_n = ALIGN_POWER_OF_TWO(out_w, 4) * out_h;
+ uint8_t *output = new uint8_t[output_n];
+ uint8_t *output2 = new uint8_t[output_n];
+
+ // Generate random filter kernels
+ DECLARE_ALIGNED(16, InterpKernel, hkernel);
+ DECLARE_ALIGNED(16, InterpKernel, vkernel);
+
+ generate_kernels(&rnd_, hkernel, vkernel);
+
+ for (i = 0; i < h; ++i)
+ for (j = 0; j < w; ++j) input[i * w + j] = rnd_.Rand8();
+
+ for (i = 0; i < num_iters; ++i) {
+ // Choose random locations within the source block
+ int offset_r = 3 + rnd_.PseudoUniform(h - out_h - 7);
+ int offset_c = 3 + rnd_.PseudoUniform(w - out_w - 7);
+ av1_wiener_convolve_add_src_c(input + offset_r * w + offset_c, w, output,
+ out_w, hkernel, 16, vkernel, 16, out_w, out_h,
+ &conv_params);
+ test_impl(input + offset_r * w + offset_c, w, output2, out_w, hkernel, 16,
+ vkernel, 16, out_w, out_h, &conv_params);
+
+ for (j = 0; j < out_w * out_h; ++j)
+ ASSERT_EQ(output[j], output2[j])
+ << "Pixel mismatch at index " << j << " = (" << (j % out_w) << ", "
+ << (j / out_w) << ") on iteration " << i;
+ }
+ delete[] input_;
+ delete[] output;
+ delete[] output2;
+}
+
+void AV1HiprecConvolveTest::RunSpeedTest(hiprec_convolve_func test_impl) {
+ const int w = 128, h = 128;
+ const int out_w = GET_PARAM(0), out_h = GET_PARAM(1);
+ const int num_iters = GET_PARAM(2) / 500;
+ int i, j, k;
+ const ConvolveParams conv_params = get_conv_params_wiener(8);
+
+ uint8_t *input_ = new uint8_t[h * w];
+ uint8_t *input = input_;
+
+ // The AVX2 convolve functions always write rows with widths that are
+ // multiples of 16. So to avoid a buffer overflow, we may need to pad
+ // rows to a multiple of 16.
+ int output_n = ALIGN_POWER_OF_TWO(out_w, 4) * out_h;
+ uint8_t *output = new uint8_t[output_n];
+ uint8_t *output2 = new uint8_t[output_n];
+
+ // Generate random filter kernels
+ DECLARE_ALIGNED(16, InterpKernel, hkernel);
+ DECLARE_ALIGNED(16, InterpKernel, vkernel);
+
+ generate_kernels(&rnd_, hkernel, vkernel);
+
+ for (i = 0; i < h; ++i)
+ for (j = 0; j < w; ++j) input[i * w + j] = rnd_.Rand8();
+
+ aom_usec_timer ref_timer;
+ aom_usec_timer_start(&ref_timer);
+ for (i = 0; i < num_iters; ++i) {
+ for (j = 3; j < h - out_h - 4; j++) {
+ for (k = 3; k < w - out_w - 4; k++) {
+ av1_wiener_convolve_add_src_c(input + j * w + k, w, output, out_w,
+ hkernel, 16, vkernel, 16, out_w, out_h,
+ &conv_params);
+ }
+ }
+ }
+ aom_usec_timer_mark(&ref_timer);
+ const int64_t ref_time = aom_usec_timer_elapsed(&ref_timer);
+
+ aom_usec_timer tst_timer;
+ aom_usec_timer_start(&tst_timer);
+ for (i = 0; i < num_iters; ++i) {
+ for (j = 3; j < h - out_h - 4; j++) {
+ for (k = 3; k < w - out_w - 4; k++) {
+ test_impl(input + j * w + k, w, output2, out_w, hkernel, 16, vkernel,
+ 16, out_w, out_h, &conv_params);
+ }
+ }
+ }
+ aom_usec_timer_mark(&tst_timer);
+ const int64_t tst_time = aom_usec_timer_elapsed(&tst_timer);
+
+ std::cout << "[ ] C time = " << ref_time / 1000
+ << " ms, SIMD time = " << tst_time / 1000 << " ms\n";
+
+ EXPECT_GT(ref_time, tst_time)
+ << "Error: AV1HiprecConvolveTest.SpeedTest, SIMD slower than C.\n"
+ << "C time: " << ref_time << " us\n"
+ << "SIMD time: " << tst_time << " us\n";
+
+ delete[] input_;
+ delete[] output;
+ delete[] output2;
+}
+} // namespace AV1HiprecConvolve
+
+namespace AV1HighbdHiprecConvolve {
+
+::testing::internal::ParamGenerator<HighbdHiprecConvolveParam> BuildParams(
+ highbd_hiprec_convolve_func filter) {
+ const HighbdHiprecConvolveParam params[] = {
+ make_tuple(8, 8, 50000, 8, filter), make_tuple(64, 64, 1000, 8, filter),
+ make_tuple(32, 8, 10000, 8, filter), make_tuple(8, 8, 50000, 10, filter),
+ make_tuple(64, 64, 1000, 10, filter), make_tuple(32, 8, 10000, 10, filter),
+ make_tuple(8, 8, 50000, 12, filter), make_tuple(64, 64, 1000, 12, filter),
+ make_tuple(32, 8, 10000, 12, filter),
+ };
+ return ::testing::ValuesIn(params);
+}
+
+AV1HighbdHiprecConvolveTest::~AV1HighbdHiprecConvolveTest() {}
+void AV1HighbdHiprecConvolveTest::SetUp() {
+ rnd_.Reset(ACMRandom::DeterministicSeed());
+}
+
+void AV1HighbdHiprecConvolveTest::TearDown() {
+ libaom_test::ClearSystemState();
+}
+
+void AV1HighbdHiprecConvolveTest::RunCheckOutput(
+ highbd_hiprec_convolve_func test_impl) {
+ const int w = 128, h = 128;
+ const int out_w = GET_PARAM(0), out_h = GET_PARAM(1);
+ const int num_iters = GET_PARAM(2);
+ const int bd = GET_PARAM(3);
+ int i, j;
+ const ConvolveParams conv_params = get_conv_params_wiener(bd);
+
+ uint16_t *input = new uint16_t[h * w];
+
+ // The AVX2 convolve functions always write rows with widths that are
+ // multiples of 16. So to avoid a buffer overflow, we may need to pad
+ // rows to a multiple of 16.
+ int output_n = ALIGN_POWER_OF_TWO(out_w, 4) * out_h;
+ uint16_t *output = new uint16_t[output_n];
+ uint16_t *output2 = new uint16_t[output_n];
+
+ // Generate random filter kernels
+ DECLARE_ALIGNED(16, InterpKernel, hkernel);
+ DECLARE_ALIGNED(16, InterpKernel, vkernel);
+
+ generate_kernels(&rnd_, hkernel, vkernel);
+
+ for (i = 0; i < h; ++i)
+ for (j = 0; j < w; ++j) input[i * w + j] = rnd_.Rand16() & ((1 << bd) - 1);
+
+ uint8_t *input_ptr = CONVERT_TO_BYTEPTR(input);
+ uint8_t *output_ptr = CONVERT_TO_BYTEPTR(output);
+ uint8_t *output2_ptr = CONVERT_TO_BYTEPTR(output2);
+
+ for (i = 0; i < num_iters; ++i) {
+ // Choose random locations within the source block
+ int offset_r = 3 + rnd_.PseudoUniform(h - out_h - 7);
+ int offset_c = 3 + rnd_.PseudoUniform(w - out_w - 7);
+ av1_highbd_wiener_convolve_add_src_c(
+ input_ptr + offset_r * w + offset_c, w, output_ptr, out_w, hkernel, 16,
+ vkernel, 16, out_w, out_h, &conv_params, bd);
+ test_impl(input_ptr + offset_r * w + offset_c, w, output2_ptr, out_w,
+ hkernel, 16, vkernel, 16, out_w, out_h, &conv_params, bd);
+
+ for (j = 0; j < out_w * out_h; ++j)
+ ASSERT_EQ(output[j], output2[j])
+ << "Pixel mismatch at index " << j << " = (" << (j % out_w) << ", "
+ << (j / out_w) << ") on iteration " << i;
+ }
+ delete[] input;
+ delete[] output;
+ delete[] output2;
+}
+
+void AV1HighbdHiprecConvolveTest::RunSpeedTest(
+ highbd_hiprec_convolve_func test_impl) {
+ const int w = 128, h = 128;
+ const int out_w = GET_PARAM(0), out_h = GET_PARAM(1);
+ const int num_iters = GET_PARAM(2) / 500;
+ const int bd = GET_PARAM(3);
+ int i, j, k;
+ const ConvolveParams conv_params = get_conv_params_wiener(bd);
+
+ uint16_t *input = new uint16_t[h * w];
+
+ // The AVX2 convolve functions always write rows with widths that are
+ // multiples of 16. So to avoid a buffer overflow, we may need to pad
+ // rows to a multiple of 16.
+ int output_n = ALIGN_POWER_OF_TWO(out_w, 4) * out_h;
+ uint16_t *output = new uint16_t[output_n];
+ uint16_t *output2 = new uint16_t[output_n];
+
+ // Generate random filter kernels
+ DECLARE_ALIGNED(16, InterpKernel, hkernel);
+ DECLARE_ALIGNED(16, InterpKernel, vkernel);
+
+ generate_kernels(&rnd_, hkernel, vkernel);
+
+ for (i = 0; i < h; ++i)
+ for (j = 0; j < w; ++j) input[i * w + j] = rnd_.Rand16() & ((1 << bd) - 1);
+
+ uint8_t *input_ptr = CONVERT_TO_BYTEPTR(input);
+ uint8_t *output_ptr = CONVERT_TO_BYTEPTR(output);
+ uint8_t *output2_ptr = CONVERT_TO_BYTEPTR(output2);
+
+ aom_usec_timer ref_timer;
+ aom_usec_timer_start(&ref_timer);
+ for (i = 0; i < num_iters; ++i) {
+ for (j = 3; j < h - out_h - 4; j++) {
+ for (k = 3; k < w - out_w - 4; k++) {
+ av1_highbd_wiener_convolve_add_src_c(
+ input_ptr + j * w + k, w, output_ptr, out_w, hkernel, 16, vkernel,
+ 16, out_w, out_h, &conv_params, bd);
+ }
+ }
+ }
+ aom_usec_timer_mark(&ref_timer);
+ const int64_t ref_time = aom_usec_timer_elapsed(&ref_timer);
+
+ aom_usec_timer tst_timer;
+ aom_usec_timer_start(&tst_timer);
+ for (i = 0; i < num_iters; ++i) {
+ for (j = 3; j < h - out_h - 4; j++) {
+ for (k = 3; k < w - out_w - 4; k++) {
+ test_impl(input_ptr + j * w + k, w, output2_ptr, out_w, hkernel, 16,
+ vkernel, 16, out_w, out_h, &conv_params, bd);
+ }
+ }
+ }
+ aom_usec_timer_mark(&tst_timer);
+ const int64_t tst_time = aom_usec_timer_elapsed(&tst_timer);
+
+ std::cout << "[ ] C time = " << ref_time / 1000
+ << " ms, SIMD time = " << tst_time / 1000 << " ms\n";
+
+ EXPECT_GT(ref_time, tst_time)
+ << "Error: AV1HighbdHiprecConvolveTest.SpeedTest, SIMD slower than C.\n"
+ << "C time: " << ref_time << " us\n"
+ << "SIMD time: " << tst_time << " us\n";
+
+ delete[] input;
+ delete[] output;
+ delete[] output2;
+}
+} // namespace AV1HighbdHiprecConvolve
+} // namespace libaom_test
generated by cgit v1.2.3 (git 2.25.1) at 2024-11-29 02:03:01 +0000