mirror of
https://repo.dactyloidae.xyz/Dactyloidae/UXP.git
synced 2026-10-08 16:27:31 +09:00
Update aom to v1.0.0
Update aom to commit id d14c5bb4f336ef1842046089849dee4a301fbbf0.
This commit is contained in:
trav90
Roy Tam
parent
bb61121b44
commit
48f6d2e034
1087 changed files with 154333 additions and 265310 deletions
185
third_party/aom/test/hiprec_convolve_test_util.cc
vendored
185
third_party/aom/test/hiprec_convolve_test_util.cc
vendored
|
|
@ -13,8 +13,8 @@
|
|||
|
||||
#include "av1/common/restoration.h"
|
||||
|
||||
using std::tr1::tuple;
|
||||
using std::tr1::make_tuple;
|
||||
using ::testing::make_tuple;
|
||||
using ::testing::tuple;
|
||||
|
||||
namespace libaom_test {
|
||||
|
||||
|
|
@ -52,8 +52,13 @@ namespace AV1HiprecConvolve {
|
|||
::testing::internal::ParamGenerator<HiprecConvolveParam> BuildParams(
|
||||
hiprec_convolve_func filter) {
|
||||
const HiprecConvolveParam params[] = {
|
||||
make_tuple(8, 8, 50000, filter), make_tuple(64, 64, 1000, filter),
|
||||
make_tuple(32, 8, 10000, filter),
|
||||
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);
|
||||
}
|
||||
|
|
@ -70,14 +75,15 @@ void AV1HiprecConvolveTest::RunCheckOutput(hiprec_convolve_func test_impl) {
|
|||
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 convolve functions always write rows with widths that are multiples of
|
||||
// 8.
|
||||
// So to avoid a buffer overflow, we may need to pad rows to a multiple of 8.
|
||||
int output_n = ((out_w + 7) & ~7) * out_h;
|
||||
// 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];
|
||||
|
||||
|
|
@ -94,10 +100,11 @@ void AV1HiprecConvolveTest::RunCheckOutput(hiprec_convolve_func test_impl) {
|
|||
// 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);
|
||||
aom_convolve8_add_src_hip_c(input + offset_r * w + offset_c, w, output,
|
||||
out_w, hkernel, 16, vkernel, 16, out_w, out_h);
|
||||
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);
|
||||
vkernel, 16, out_w, out_h, &conv_params);
|
||||
|
||||
for (j = 0; j < out_w * out_h; ++j)
|
||||
ASSERT_EQ(output[j], output2[j])
|
||||
|
|
@ -108,9 +115,74 @@ void AV1HiprecConvolveTest::RunCheckOutput(hiprec_convolve_func test_impl) {
|
|||
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
|
||||
|
||||
#if CONFIG_HIGHBITDEPTH
|
||||
namespace AV1HighbdHiprecConvolve {
|
||||
|
||||
::testing::internal::ParamGenerator<HighbdHiprecConvolveParam> BuildParams(
|
||||
|
|
@ -141,13 +213,14 @@ void AV1HighbdHiprecConvolveTest::RunCheckOutput(
|
|||
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 convolve functions always write rows with widths that are multiples of
|
||||
// 8.
|
||||
// So to avoid a buffer overflow, we may need to pad rows to a multiple of 8.
|
||||
int output_n = ((out_w + 7) & ~7) * out_h;
|
||||
// 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];
|
||||
|
||||
|
|
@ -168,11 +241,11 @@ void AV1HighbdHiprecConvolveTest::RunCheckOutput(
|
|||
// 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);
|
||||
aom_highbd_convolve8_add_src_hip_c(input_ptr + offset_r * w + offset_c, w,
|
||||
output_ptr, out_w, hkernel, 16, vkernel,
|
||||
16, out_w, out_h, bd);
|
||||
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, bd);
|
||||
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])
|
||||
|
|
@ -183,6 +256,76 @@ void AV1HighbdHiprecConvolveTest::RunCheckOutput(
|
|||
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
|
||||
#endif // CONFIG_HIGHBITDEPTH
|
||||
} // namespace libaom_test
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue