| /* |
| * 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 "aom_ports/aom_timer.h" |
| #include "test/warp_filter_test_util.h" |
| |
| using ::testing::make_tuple; |
| using ::testing::tuple; |
| |
| namespace libaom_test { |
| |
| int32_t random_warped_param(libaom_test::ACMRandom *rnd, int bits) { |
| // 1 in 8 chance of generating zero (arbitrarily chosen) |
| if (((rnd->Rand8()) & 7) == 0) return 0; |
| // Otherwise, enerate uniform values in the range |
| // [-(1 << bits), 1] U [1, 1<<bits] |
| int32_t v = 1 + (rnd->Rand16() & ((1 << bits) - 1)); |
| if ((rnd->Rand8()) & 1) return -v; |
| return v; |
| } |
| |
| void generate_warped_model(libaom_test::ACMRandom *rnd, int32_t *mat, |
| int16_t *alpha, int16_t *beta, int16_t *gamma, |
| int16_t *delta, const int is_alpha_zero, |
| const int is_beta_zero, const int is_gamma_zero, |
| const int is_delta_zero) { |
| while (1) { |
| int rnd8 = rnd->Rand8() & 3; |
| mat[0] = random_warped_param(rnd, WARPEDMODEL_PREC_BITS + 6); |
| mat[1] = random_warped_param(rnd, WARPEDMODEL_PREC_BITS + 6); |
| mat[2] = (random_warped_param(rnd, WARPEDMODEL_PREC_BITS - 3)) + |
| (1 << WARPEDMODEL_PREC_BITS); |
| mat[3] = random_warped_param(rnd, WARPEDMODEL_PREC_BITS - 3); |
| |
| if (rnd8 <= 1) { |
| // AFFINE |
| mat[4] = random_warped_param(rnd, WARPEDMODEL_PREC_BITS - 3); |
| mat[5] = (random_warped_param(rnd, WARPEDMODEL_PREC_BITS - 3)) + |
| (1 << WARPEDMODEL_PREC_BITS); |
| } else if (rnd8 == 2) { |
| mat[4] = -mat[3]; |
| mat[5] = mat[2]; |
| } else { |
| mat[4] = random_warped_param(rnd, WARPEDMODEL_PREC_BITS - 3); |
| mat[5] = (random_warped_param(rnd, WARPEDMODEL_PREC_BITS - 3)) + |
| (1 << WARPEDMODEL_PREC_BITS); |
| if (is_alpha_zero == 1) mat[2] = 1 << WARPEDMODEL_PREC_BITS; |
| if (is_beta_zero == 1) mat[3] = 0; |
| if (is_gamma_zero == 1) mat[4] = 0; |
| if (is_delta_zero == 1) |
| mat[5] = (((int64_t)mat[3] * mat[4] + (mat[2] / 2)) / mat[2]) + |
| (1 << WARPEDMODEL_PREC_BITS); |
| } |
| |
| // Calculate the derived parameters and check that they are suitable |
| // for the warp filter. |
| assert(mat[2] != 0); |
| |
| *alpha = clamp(mat[2] - (1 << WARPEDMODEL_PREC_BITS), INT16_MIN, INT16_MAX); |
| *beta = clamp(mat[3], INT16_MIN, INT16_MAX); |
| *gamma = clamp(((int64_t)mat[4] * (1 << WARPEDMODEL_PREC_BITS)) / mat[2], |
| INT16_MIN, INT16_MAX); |
| *delta = |
| clamp(mat[5] - (((int64_t)mat[3] * mat[4] + (mat[2] / 2)) / mat[2]) - |
| (1 << WARPEDMODEL_PREC_BITS), |
| INT16_MIN, INT16_MAX); |
| |
| if ((4 * abs(*alpha) + 7 * abs(*beta) >= (1 << WARPEDMODEL_PREC_BITS)) || |
| (4 * abs(*gamma) + 4 * abs(*delta) >= (1 << WARPEDMODEL_PREC_BITS))) |
| continue; |
| |
| *alpha = ROUND_POWER_OF_TWO_SIGNED(*alpha, WARP_PARAM_REDUCE_BITS) * |
| (1 << WARP_PARAM_REDUCE_BITS); |
| *beta = ROUND_POWER_OF_TWO_SIGNED(*beta, WARP_PARAM_REDUCE_BITS) * |
| (1 << WARP_PARAM_REDUCE_BITS); |
| *gamma = ROUND_POWER_OF_TWO_SIGNED(*gamma, WARP_PARAM_REDUCE_BITS) * |
| (1 << WARP_PARAM_REDUCE_BITS); |
| *delta = ROUND_POWER_OF_TWO_SIGNED(*delta, WARP_PARAM_REDUCE_BITS) * |
| (1 << WARP_PARAM_REDUCE_BITS); |
| |
| // We have a valid model, so finish |
| return; |
| } |
| } |
| |
| namespace AV1WarpFilter { |
| ::testing::internal::ParamGenerator<WarpTestParams> BuildParams( |
| warp_affine_func filter) { |
| WarpTestParam params[] = { |
| make_tuple(4, 4, 50000, filter), make_tuple(8, 8, 50000, filter), |
| make_tuple(64, 64, 1000, filter), make_tuple(4, 16, 20000, filter), |
| make_tuple(32, 8, 10000, filter), |
| }; |
| return ::testing::Combine(::testing::ValuesIn(params), |
| ::testing::Values(0, 1), ::testing::Values(0, 1), |
| ::testing::Values(0, 1), ::testing::Values(0, 1)); |
| } |
| |
| AV1WarpFilterTest::~AV1WarpFilterTest() {} |
| void AV1WarpFilterTest::SetUp() { rnd_.Reset(ACMRandom::DeterministicSeed()); } |
| |
| void AV1WarpFilterTest::TearDown() { libaom_test::ClearSystemState(); } |
| |
| void AV1WarpFilterTest::RunSpeedTest(warp_affine_func test_impl) { |
| const int w = 128, h = 128; |
| const int border = 16; |
| const int stride = w + 2 * border; |
| WarpTestParam params = GET_PARAM(0); |
| const int out_w = ::testing::get<0>(params), |
| out_h = ::testing::get<1>(params); |
| const int is_alpha_zero = GET_PARAM(1); |
| const int is_beta_zero = GET_PARAM(2); |
| const int is_gamma_zero = GET_PARAM(3); |
| const int is_delta_zero = GET_PARAM(4); |
| int sub_x, sub_y; |
| const int bd = 8; |
| |
| uint8_t *input_ = new uint8_t[h * stride]; |
| uint8_t *input = input_ + border; |
| |
| // The warp 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; |
| uint8_t *output = new uint8_t[output_n]; |
| int32_t mat[8]; |
| int16_t alpha, beta, gamma, delta; |
| ConvolveParams conv_params = get_conv_params(0, 0, bd); |
| CONV_BUF_TYPE *dsta = new CONV_BUF_TYPE[output_n]; |
| generate_warped_model(&rnd_, mat, &alpha, &beta, &gamma, &delta, |
| is_alpha_zero, is_beta_zero, is_gamma_zero, |
| is_delta_zero); |
| |
| for (int r = 0; r < h; ++r) |
| for (int c = 0; c < w; ++c) input[r * stride + c] = rnd_.Rand8(); |
| for (int r = 0; r < h; ++r) { |
| memset(input + r * stride - border, input[r * stride], border); |
| memset(input + r * stride + w, input[r * stride + (w - 1)], border); |
| } |
| |
| sub_x = 0; |
| sub_y = 0; |
| int do_average = 0; |
| |
| conv_params = get_conv_params_no_round(do_average, 0, dsta, out_w, 1, bd); |
| conv_params.use_dist_wtd_comp_avg = 0; |
| |
| const int num_loops = 1000000000 / (out_w + out_h); |
| aom_usec_timer timer; |
| aom_usec_timer_start(&timer); |
| for (int i = 0; i < num_loops; ++i) |
| test_impl(mat, input, w, h, stride, output, 32, 32, out_w, out_h, out_w, |
| sub_x, sub_y, &conv_params, alpha, beta, gamma, delta); |
| |
| aom_usec_timer_mark(&timer); |
| const int elapsed_time = static_cast<int>(aom_usec_timer_elapsed(&timer)); |
| printf("warp %3dx%-3d: %7.2f ns\n", out_w, out_h, |
| 1000.0 * elapsed_time / num_loops); |
| |
| delete[] input_; |
| delete[] output; |
| delete[] dsta; |
| } |
| |
| void AV1WarpFilterTest::RunCheckOutput(warp_affine_func test_impl) { |
| const int w = 128, h = 128; |
| const int border = 16; |
| const int stride = w + 2 * border; |
| WarpTestParam params = GET_PARAM(0); |
| const int is_alpha_zero = GET_PARAM(1); |
| const int is_beta_zero = GET_PARAM(2); |
| const int is_gamma_zero = GET_PARAM(3); |
| const int is_delta_zero = GET_PARAM(4); |
| const int out_w = ::testing::get<0>(params), |
| out_h = ::testing::get<1>(params); |
| const int num_iters = ::testing::get<2>(params); |
| int i, j, sub_x, sub_y; |
| const int bd = 8; |
| |
| // The warp 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; |
| uint8_t *input_ = new uint8_t[h * stride]; |
| uint8_t *input = input_ + border; |
| uint8_t *output = new uint8_t[output_n]; |
| uint8_t *output2 = new uint8_t[output_n]; |
| int32_t mat[8]; |
| int16_t alpha, beta, gamma, delta; |
| ConvolveParams conv_params = get_conv_params(0, 0, bd); |
| CONV_BUF_TYPE *dsta = new CONV_BUF_TYPE[output_n]; |
| CONV_BUF_TYPE *dstb = new CONV_BUF_TYPE[output_n]; |
| for (int i = 0; i < output_n; ++i) output[i] = output2[i] = rnd_.Rand8(); |
| |
| for (i = 0; i < num_iters; ++i) { |
| // Generate an input block and extend its borders horizontally |
| for (int r = 0; r < h; ++r) |
| for (int c = 0; c < w; ++c) input[r * stride + c] = rnd_.Rand8(); |
| for (int r = 0; r < h; ++r) { |
| memset(input + r * stride - border, input[r * stride], border); |
| memset(input + r * stride + w, input[r * stride + (w - 1)], border); |
| } |
| const int use_no_round = rnd_.Rand8() & 1; |
| for (sub_x = 0; sub_x < 2; ++sub_x) |
| for (sub_y = 0; sub_y < 2; ++sub_y) { |
| generate_warped_model(&rnd_, mat, &alpha, &beta, &gamma, &delta, |
| is_alpha_zero, is_beta_zero, is_gamma_zero, |
| is_delta_zero); |
| |
| for (int ii = 0; ii < 2; ++ii) { |
| for (int jj = 0; jj < 5; ++jj) { |
| for (int do_average = 0; do_average <= 1; ++do_average) { |
| if (use_no_round) { |
| conv_params = |
| get_conv_params_no_round(do_average, 0, dsta, out_w, 1, bd); |
| } else { |
| conv_params = get_conv_params(0, 0, bd); |
| } |
| if (jj >= 4) { |
| conv_params.use_dist_wtd_comp_avg = 0; |
| } else { |
| conv_params.use_dist_wtd_comp_avg = 1; |
| conv_params.fwd_offset = quant_dist_lookup_table[ii][jj][0]; |
| conv_params.bck_offset = quant_dist_lookup_table[ii][jj][1]; |
| } |
| av1_warp_affine_c(mat, input, w, h, stride, output, 32, 32, out_w, |
| out_h, out_w, sub_x, sub_y, &conv_params, alpha, |
| beta, gamma, delta); |
| if (use_no_round) { |
| conv_params = |
| get_conv_params_no_round(do_average, 0, dstb, out_w, 1, bd); |
| } |
| if (jj >= 4) { |
| conv_params.use_dist_wtd_comp_avg = 0; |
| } else { |
| conv_params.use_dist_wtd_comp_avg = 1; |
| conv_params.fwd_offset = quant_dist_lookup_table[ii][jj][0]; |
| conv_params.bck_offset = quant_dist_lookup_table[ii][jj][1]; |
| } |
| test_impl(mat, input, w, h, stride, output2, 32, 32, out_w, out_h, |
| out_w, sub_x, sub_y, &conv_params, alpha, beta, gamma, |
| delta); |
| if (use_no_round) { |
| for (j = 0; j < out_w * out_h; ++j) |
| ASSERT_EQ(dsta[j], dstb[j]) |
| << "Pixel mismatch at index " << j << " = (" |
| << (j % out_w) << ", " << (j / out_w) << ") on iteration " |
| << i; |
| 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; |
| } else { |
| 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; |
| delete[] dsta; |
| delete[] dstb; |
| } |
| } // namespace AV1WarpFilter |
| |
| namespace AV1HighbdWarpFilter { |
| ::testing::internal::ParamGenerator<HighbdWarpTestParams> BuildParams( |
| highbd_warp_affine_func filter) { |
| const HighbdWarpTestParam params[] = { |
| make_tuple(4, 4, 100, 8, filter), make_tuple(8, 8, 100, 8, filter), |
| make_tuple(64, 64, 100, 8, filter), make_tuple(4, 16, 100, 8, filter), |
| make_tuple(32, 8, 100, 8, filter), make_tuple(4, 4, 100, 10, filter), |
| make_tuple(8, 8, 100, 10, filter), make_tuple(64, 64, 100, 10, filter), |
| make_tuple(4, 16, 100, 10, filter), make_tuple(32, 8, 100, 10, filter), |
| make_tuple(4, 4, 100, 12, filter), make_tuple(8, 8, 100, 12, filter), |
| make_tuple(64, 64, 100, 12, filter), make_tuple(4, 16, 100, 12, filter), |
| make_tuple(32, 8, 100, 12, filter), |
| }; |
| return ::testing::Combine(::testing::ValuesIn(params), |
| ::testing::Values(0, 1), ::testing::Values(0, 1), |
| ::testing::Values(0, 1), ::testing::Values(0, 1)); |
| } |
| |
| AV1HighbdWarpFilterTest::~AV1HighbdWarpFilterTest() {} |
| void AV1HighbdWarpFilterTest::SetUp() { |
| rnd_.Reset(ACMRandom::DeterministicSeed()); |
| } |
| |
| void AV1HighbdWarpFilterTest::TearDown() { libaom_test::ClearSystemState(); } |
| |
| void AV1HighbdWarpFilterTest::RunSpeedTest(highbd_warp_affine_func test_impl) { |
| const int w = 128, h = 128; |
| const int border = 16; |
| const int stride = w + 2 * border; |
| HighbdWarpTestParam param = GET_PARAM(0); |
| const int is_alpha_zero = GET_PARAM(1); |
| const int is_beta_zero = GET_PARAM(2); |
| const int is_gamma_zero = GET_PARAM(3); |
| const int is_delta_zero = GET_PARAM(4); |
| const int out_w = ::testing::get<0>(param), out_h = ::testing::get<1>(param); |
| const int bd = ::testing::get<3>(param); |
| const int mask = (1 << bd) - 1; |
| int sub_x, sub_y; |
| |
| // The warp 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; |
| uint16_t *input_ = new uint16_t[h * stride]; |
| uint16_t *input = input_ + border; |
| uint16_t *output = new uint16_t[output_n]; |
| int32_t mat[8]; |
| int16_t alpha, beta, gamma, delta; |
| ConvolveParams conv_params = get_conv_params(0, 0, bd); |
| CONV_BUF_TYPE *dsta = new CONV_BUF_TYPE[output_n]; |
| |
| generate_warped_model(&rnd_, mat, &alpha, &beta, &gamma, &delta, |
| is_alpha_zero, is_beta_zero, is_gamma_zero, |
| is_delta_zero); |
| // Generate an input block and extend its borders horizontally |
| for (int r = 0; r < h; ++r) |
| for (int c = 0; c < w; ++c) input[r * stride + c] = rnd_.Rand16() & mask; |
| for (int r = 0; r < h; ++r) { |
| for (int c = 0; c < border; ++c) { |
| input[r * stride - border + c] = input[r * stride]; |
| input[r * stride + w + c] = input[r * stride + (w - 1)]; |
| } |
| } |
| |
| sub_x = 0; |
| sub_y = 0; |
| int do_average = 0; |
| conv_params.use_dist_wtd_comp_avg = 0; |
| conv_params = get_conv_params_no_round(do_average, 0, dsta, out_w, 1, bd); |
| |
| const int num_loops = 1000000000 / (out_w + out_h); |
| aom_usec_timer timer; |
| aom_usec_timer_start(&timer); |
| |
| for (int i = 0; i < num_loops; ++i) |
| test_impl(mat, input, w, h, stride, output, 32, 32, out_w, out_h, out_w, |
| sub_x, sub_y, bd, &conv_params, alpha, beta, gamma, delta); |
| |
| aom_usec_timer_mark(&timer); |
| const int elapsed_time = static_cast<int>(aom_usec_timer_elapsed(&timer)); |
| printf("highbd warp %3dx%-3d: %7.2f ns\n", out_w, out_h, |
| 1000.0 * elapsed_time / num_loops); |
| |
| delete[] input_; |
| delete[] output; |
| delete[] dsta; |
| } |
| |
| void AV1HighbdWarpFilterTest::RunCheckOutput( |
| highbd_warp_affine_func test_impl) { |
| const int w = 128, h = 128; |
| const int border = 16; |
| const int stride = w + 2 * border; |
| HighbdWarpTestParam param = GET_PARAM(0); |
| const int is_alpha_zero = GET_PARAM(1); |
| const int is_beta_zero = GET_PARAM(2); |
| const int is_gamma_zero = GET_PARAM(3); |
| const int is_delta_zero = GET_PARAM(4); |
| const int out_w = ::testing::get<0>(param), out_h = ::testing::get<1>(param); |
| const int bd = ::testing::get<3>(param); |
| const int num_iters = ::testing::get<2>(param); |
| const int mask = (1 << bd) - 1; |
| int i, j, sub_x, sub_y; |
| |
| // The warp 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; |
| uint16_t *input_ = new uint16_t[h * stride]; |
| uint16_t *input = input_ + border; |
| uint16_t *output = new uint16_t[output_n]; |
| uint16_t *output2 = new uint16_t[output_n]; |
| int32_t mat[8]; |
| int16_t alpha, beta, gamma, delta; |
| ConvolveParams conv_params = get_conv_params(0, 0, bd); |
| CONV_BUF_TYPE *dsta = new CONV_BUF_TYPE[output_n]; |
| CONV_BUF_TYPE *dstb = new CONV_BUF_TYPE[output_n]; |
| for (int i = 0; i < output_n; ++i) output[i] = output2[i] = rnd_.Rand16(); |
| |
| for (i = 0; i < num_iters; ++i) { |
| // Generate an input block and extend its borders horizontally |
| for (int r = 0; r < h; ++r) |
| for (int c = 0; c < w; ++c) input[r * stride + c] = rnd_.Rand16() & mask; |
| for (int r = 0; r < h; ++r) { |
| for (int c = 0; c < border; ++c) { |
| input[r * stride - border + c] = input[r * stride]; |
| input[r * stride + w + c] = input[r * stride + (w - 1)]; |
| } |
| } |
| const int use_no_round = rnd_.Rand8() & 1; |
| for (sub_x = 0; sub_x < 2; ++sub_x) |
| for (sub_y = 0; sub_y < 2; ++sub_y) { |
| generate_warped_model(&rnd_, mat, &alpha, &beta, &gamma, &delta, |
| is_alpha_zero, is_beta_zero, is_gamma_zero, |
| is_delta_zero); |
| for (int ii = 0; ii < 2; ++ii) { |
| for (int jj = 0; jj < 5; ++jj) { |
| for (int do_average = 0; do_average <= 1; ++do_average) { |
| if (use_no_round) { |
| conv_params = |
| get_conv_params_no_round(do_average, 0, dsta, out_w, 1, bd); |
| } else { |
| conv_params = get_conv_params(0, 0, bd); |
| } |
| if (jj >= 4) { |
| conv_params.use_dist_wtd_comp_avg = 0; |
| } else { |
| conv_params.use_dist_wtd_comp_avg = 1; |
| conv_params.fwd_offset = quant_dist_lookup_table[ii][jj][0]; |
| conv_params.bck_offset = quant_dist_lookup_table[ii][jj][1]; |
| } |
| |
| av1_highbd_warp_affine_c(mat, input, w, h, stride, output, 32, 32, |
| out_w, out_h, out_w, sub_x, sub_y, bd, |
| &conv_params, alpha, beta, gamma, delta); |
| if (use_no_round) { |
| // TODO(angiebird): Change this to test_impl once we have SIMD |
| // implementation |
| conv_params = |
| get_conv_params_no_round(do_average, 0, dstb, out_w, 1, bd); |
| } |
| if (jj >= 4) { |
| conv_params.use_dist_wtd_comp_avg = 0; |
| } else { |
| conv_params.use_dist_wtd_comp_avg = 1; |
| conv_params.fwd_offset = quant_dist_lookup_table[ii][jj][0]; |
| conv_params.bck_offset = quant_dist_lookup_table[ii][jj][1]; |
| } |
| test_impl(mat, input, w, h, stride, output2, 32, 32, out_w, out_h, |
| out_w, sub_x, sub_y, bd, &conv_params, alpha, beta, |
| gamma, delta); |
| |
| if (use_no_round) { |
| for (j = 0; j < out_w * out_h; ++j) |
| ASSERT_EQ(dsta[j], dstb[j]) |
| << "Pixel mismatch at index " << j << " = (" |
| << (j % out_w) << ", " << (j / out_w) << ") on iteration " |
| << i; |
| 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; |
| } else { |
| 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; |
| delete[] dsta; |
| delete[] dstb; |
| } |
| } // namespace AV1HighbdWarpFilter |
| } // namespace libaom_test |
