abd00505d1
Using this we can eliminate large numbers of calls to predict intra, and is also faster than most of the variance functions it replaces. This is an equivalence transform so coding performance is unaffected. Encoder speedup is approx 7% when var_tx, super_tx and ext_tx are all enabled. Change-Id: I0d4c83afc4a97a1826f3abd864bd68e41bb504fb
134 lines
3.5 KiB
C++
134 lines
3.5 KiB
C++
/*
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* Copyright (c) 2014 The WebM project authors. All Rights Reserved.
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*
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* Use of this source code is governed by a BSD-style license
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* that can be found in the LICENSE file in the root of the source
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* tree. An additional intellectual property rights grant can be found
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* in the file PATENTS. All contributing project authors may
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* be found in the AUTHORS file in the root of the source tree.
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*/
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#include <cmath>
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#include <cstdlib>
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#include <string>
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#include "third_party/googletest/src/include/gtest/gtest.h"
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#include "./vpx_config.h"
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#include "./vpx_dsp_rtcd.h"
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#include "vpx_ports/mem.h"
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#include "test/acm_random.h"
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#include "test/clear_system_state.h"
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#include "test/register_state_check.h"
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#include "test/util.h"
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using libvpx_test::ACMRandom;
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namespace {
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const int kNumIterations = 10000;
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typedef uint64_t (*SSI16Func)(const int16_t *src,
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int stride ,
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int size);
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typedef std::tr1::tuple<SSI16Func, SSI16Func> SumSquaresParam;
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class SumSquaresTest : public ::testing::TestWithParam<SumSquaresParam> {
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public:
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virtual ~SumSquaresTest() {}
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virtual void SetUp() {
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ref_func_ = GET_PARAM(0);
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tst_func_ = GET_PARAM(1);
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}
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virtual void TearDown() { libvpx_test::ClearSystemState(); }
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protected:
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SSI16Func ref_func_;
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SSI16Func tst_func_;
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};
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TEST_P(SumSquaresTest, OperationCheck) {
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ACMRandom rnd(ACMRandom::DeterministicSeed());
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DECLARE_ALIGNED(16, int16_t, src[256*256]);
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int failed = 0;
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const int msb = 11; // Up to 12 bit input
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const int limit = 1 << (msb+1);
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for (int k = 0; k < kNumIterations; k++) {
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int size = 4 << rnd(6); // Up to 128x128
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int stride = 4 << rnd(7); // Up to 256 stride
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while (stride < size) { // Make sure it's valid
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stride = 4 << rnd(7);
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}
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for (int ii = 0 ; ii < size; ii++) {
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for (int jj = 0; jj < size; jj++) {
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src[ii*stride+jj] = rnd(2) ? rnd(limit) : -rnd(limit);
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}
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}
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uint64_t res_ref = ref_func_(src, stride, size);
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uint64_t res_tst;
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ASM_REGISTER_STATE_CHECK(res_tst = tst_func_(src, stride, size));
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if (!failed) {
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failed = res_ref != res_tst;
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EXPECT_EQ(res_ref, res_tst)
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<< "Error: Sum Squares Test"
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<< " C output does not match optimized output.";
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}
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}
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}
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TEST_P(SumSquaresTest, ExtremeValues) {
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ACMRandom rnd(ACMRandom::DeterministicSeed());
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DECLARE_ALIGNED(16, int16_t, src[256*256]);
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int failed = 0;
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const int msb = 11; // Up to 12 bit input
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const int limit = 1 << (msb+1);
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for (int k = 0; k < kNumIterations; k++) {
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int size = 4 << rnd(6); // Up to 128x128
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int stride = 4 << rnd(7); // Up to 256 stride
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while (stride < size) { // Make sure it's valid
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stride = 4 << rnd(7);
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}
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int val = rnd(2) ? limit-1 : -(limit-1);
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for (int ii = 0 ; ii < size; ii++) {
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for (int jj = 0; jj < size; jj++) {
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src[ii*stride+jj] = val;
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}
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}
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uint64_t res_ref = ref_func_(src, stride, size);
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uint64_t res_tst;
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ASM_REGISTER_STATE_CHECK(res_tst = tst_func_(src, stride, size));
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if (!failed) {
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failed = res_ref != res_tst;
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EXPECT_EQ(res_ref, res_tst)
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<< "Error: Sum Squares Test"
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<< " C output does not match optimized output.";
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}
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}
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}
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using std::tr1::make_tuple;
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#if HAVE_SSE2
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INSTANTIATE_TEST_CASE_P(
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SSE2, SumSquaresTest,
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::testing::Values(
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make_tuple(&vpx_sum_squares_2d_i16_c, &vpx_sum_squares_2d_i16_sse2)
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)
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);
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#endif // HAVE_SSE2
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} // namespace
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