[CFL] Unit Test Clean Up
Use more Templates and Classes to reduce code duplication in CfL Unit
tests.
Change-Id: If95ad57f270da7836471ba8207d21211852ac016
diff --git a/test/cfl_test.cc b/test/cfl_test.cc
index 658d50a..0274117 100644
--- a/test/cfl_test.cc
+++ b/test/cfl_test.cc
@@ -15,7 +15,7 @@
#include "test/util.h"
#include "test/acm_random.h"
-using std::tr1::make_tuple;
+using ::testing::make_tuple;
using libaom_test::ACMRandom;
@@ -40,13 +40,22 @@
typedef cfl_subtract_average_fn (*sub_avg_fn)(TX_SIZE tx_size);
-typedef std::tr1::tuple<TX_SIZE, get_subsample_fn> subsample_param;
+typedef ::testing::tuple<TX_SIZE, get_subsample_fn> subsample_param;
-typedef std::tr1::tuple<TX_SIZE, get_predict_fn> predict_param;
+typedef ::testing::tuple<TX_SIZE, get_predict_fn> predict_param;
-typedef std::tr1::tuple<TX_SIZE, get_predict_fn_hbd> predict_param_hbd;
+typedef ::testing::tuple<TX_SIZE, get_predict_fn_hbd> predict_param_hbd;
-typedef std::tr1::tuple<TX_SIZE, sub_avg_fn> sub_avg_param;
+typedef ::testing::tuple<TX_SIZE, sub_avg_fn> sub_avg_param;
+
+template <typename A>
+static void assert_eq(const A *a, const A *b, int width, int height) {
+ for (int j = 0; j < height; j++) {
+ for (int i = 0; i < width; i++) {
+ ASSERT_EQ(a[j * CFL_BUF_LINE + i], b[j * CFL_BUF_LINE + i]);
+ }
+ }
+}
static void assertFaster(int ref_elapsed_time, int elapsed_time) {
EXPECT_GT(ref_elapsed_time, elapsed_time)
@@ -65,25 +74,40 @@
<< std::endl;
}
-class CFLSubAvgTest : public ::testing::TestWithParam<sub_avg_param> {
+template <typename F>
+class CFLTest
+ : public ::testing::TestWithParam< ::testing::tuple<TX_SIZE, F> > {
public:
- virtual ~CFLSubAvgTest() {}
- virtual void SetUp() { sub_avg = GET_PARAM(1); }
+ virtual ~CFLTest() {}
+ virtual void SetUp() {
+ tx_size = ::testing::get<0>(this->GetParam());
+ width = tx_size_wide[tx_size];
+ height = tx_size_high[tx_size];
+ fun_under_test = ::testing::get<1>(this->GetParam());
+ rnd(ACMRandom::DeterministicSeed());
+ }
protected:
- int Width() const { return tx_size_wide[GET_PARAM(0)]; }
- int Height() const { return tx_size_high[GET_PARAM(0)]; }
- TX_SIZE Tx_size() const { return GET_PARAM(0); }
- sub_avg_fn sub_avg;
- int16_t data[CFL_BUF_SQUARE];
- int16_t data_ref[CFL_BUF_SQUARE];
- void init() {
- const int width = Width();
- const int height = Height();
- ACMRandom rnd(ACMRandom::DeterministicSeed());
- for (int j = 0; j < height; j++) {
- for (int i = 0; i < width; i++) {
- const int16_t d = rnd.Rand15Signed();
+ ACMRandom rnd;
+ F fun_under_test;
+ TX_SIZE tx_size;
+ int width;
+ int height;
+};
+
+template <typename F, typename I>
+class CFLTestWithData : public CFLTest<F> {
+ public:
+ virtual ~CFLTestWithData() {}
+
+ protected:
+ I data[CFL_BUF_SQUARE];
+ I data_ref[CFL_BUF_SQUARE];
+
+ void init(I (ACMRandom::*random)()) {
+ for (int j = 0; j < this->height; j++) {
+ for (int i = 0; i < this->width; i++) {
+ const I d = (this->rnd.*random)();
data[j * CFL_BUF_LINE + i] = d;
data_ref[j * CFL_BUF_LINE + i] = d;
}
@@ -91,96 +115,23 @@
}
};
-class CFLSubsampleTest : public ::testing::TestWithParam<subsample_param> {
+template <typename F, typename I>
+class CFLTestWithAlignedData : public CFLTest<F> {
public:
- virtual ~CFLSubsampleTest() {}
- virtual void SetUp() { subsample = GET_PARAM(1); }
-
- protected:
- int Width() const { return tx_size_wide[GET_PARAM(0)]; }
- int Height() const { return tx_size_high[GET_PARAM(0)]; }
- TX_SIZE Tx_size() const { return GET_PARAM(0); }
- get_subsample_fn subsample;
- uint8_t luma_pels[CFL_BUF_SQUARE];
- uint8_t luma_pels_ref[CFL_BUF_SQUARE];
- int16_t sub_luma_pels[CFL_BUF_SQUARE];
- int16_t sub_luma_pels_ref[CFL_BUF_SQUARE];
- void init(int width, int height) {
- ACMRandom rnd(ACMRandom::DeterministicSeed());
- for (int j = 0; j < height; j++) {
- for (int i = 0; i < width; i++) {
- const int val = rnd.Rand8();
- luma_pels[j * CFL_BUF_LINE + i] = val;
- luma_pels_ref[j * CFL_BUF_LINE + i] = val;
- }
- }
- }
-};
-
-class CFLPredictTest : public ::testing::TestWithParam<predict_param> {
- public:
- virtual ~CFLPredictTest() {}
+ virtual ~CFLTestWithAlignedData() {}
virtual void SetUp() {
- predict = GET_PARAM(1);
- chroma_pels_ref = reinterpret_cast<uint8_t *>(
- aom_memalign(32, sizeof(uint8_t) * CFL_BUF_SQUARE));
+ CFLTest<F>::SetUp();
+ chroma_pels_ref =
+ reinterpret_cast<I *>(aom_memalign(32, sizeof(I) * CFL_BUF_SQUARE));
+ chroma_pels =
+ reinterpret_cast<I *>(aom_memalign(32, sizeof(I) * CFL_BUF_SQUARE));
sub_luma_pels_ref = reinterpret_cast<int16_t *>(
aom_memalign(32, sizeof(int16_t) * CFL_BUF_SQUARE));
- chroma_pels = reinterpret_cast<uint8_t *>(
- aom_memalign(32, sizeof(uint8_t) * CFL_BUF_SQUARE));
sub_luma_pels = reinterpret_cast<int16_t *>(
aom_memalign(32, sizeof(int16_t) * CFL_BUF_SQUARE));
- }
-
- virtual void TearDown() {
- aom_free(chroma_pels_ref);
- aom_free(sub_luma_pels_ref);
- aom_free(chroma_pels);
- aom_free(sub_luma_pels);
- }
-
- protected:
- int Width() const { return tx_size_wide[GET_PARAM(0)]; }
- int Height() const { return tx_size_high[GET_PARAM(0)]; }
- TX_SIZE Tx_size() const { return GET_PARAM(0); }
- uint8_t *chroma_pels_ref;
- int16_t *sub_luma_pels_ref;
- uint8_t *chroma_pels;
- int16_t *sub_luma_pels;
- get_predict_fn predict;
- int alpha_q3;
- uint8_t dc;
- void init(int width, int height) {
- ACMRandom rnd(ACMRandom::DeterministicSeed());
- alpha_q3 = rnd(33) - 16;
- dc = rnd.Rand8();
- for (int j = 0; j < height; j++) {
- for (int i = 0; i < width; i++) {
- chroma_pels[j * CFL_BUF_LINE + i] = dc;
- chroma_pels_ref[j * CFL_BUF_LINE + i] = dc;
- sub_luma_pels_ref[j * CFL_BUF_LINE + i] =
- sub_luma_pels[j * CFL_BUF_LINE + i] = rnd.Rand8() - 128;
- }
- }
- }
-};
-
-class CFLPredictHBDTest : public ::testing::TestWithParam<predict_param_hbd> {
- public:
- virtual ~CFLPredictHBDTest() {}
- virtual void SetUp() {
- predict = GET_PARAM(1);
- chroma_pels_ref = reinterpret_cast<uint16_t *>(
- aom_memalign(32, sizeof(uint16_t) * CFL_BUF_SQUARE));
- sub_luma_pels_ref = reinterpret_cast<int16_t *>(
- aom_memalign(32, sizeof(int16_t) * CFL_BUF_SQUARE));
- chroma_pels = reinterpret_cast<uint16_t *>(
- aom_memalign(32, sizeof(uint16_t) * CFL_BUF_SQUARE));
- sub_luma_pels = reinterpret_cast<int16_t *>(
- aom_memalign(32, sizeof(int16_t) * CFL_BUF_SQUARE));
- memset(chroma_pels_ref, 0, sizeof(int16_t) * CFL_BUF_SQUARE);
+ memset(chroma_pels_ref, 0, sizeof(I) * CFL_BUF_SQUARE);
+ memset(chroma_pels, 0, sizeof(I) * CFL_BUF_SQUARE);
memset(sub_luma_pels_ref, 0, sizeof(int16_t) * CFL_BUF_SQUARE);
- memset(chroma_pels, 0, sizeof(int16_t) * CFL_BUF_SQUARE);
memset(sub_luma_pels, 0, sizeof(int16_t) * CFL_BUF_SQUARE);
}
@@ -192,64 +143,66 @@
}
protected:
- int Width() const { return tx_size_wide[GET_PARAM(0)]; }
- int Height() const { return tx_size_high[GET_PARAM(0)]; }
- TX_SIZE Tx_size() const { return GET_PARAM(0); }
- uint16_t *chroma_pels_ref;
+ I *chroma_pels_ref;
+ I *chroma_pels;
int16_t *sub_luma_pels_ref;
- uint16_t *chroma_pels;
int16_t *sub_luma_pels;
- get_predict_fn_hbd predict;
- int bd;
int alpha_q3;
- uint8_t dc;
- void init(int width, int height) {
- ACMRandom rnd(ACMRandom::DeterministicSeed());
- bd = 12;
- alpha_q3 = rnd(33) - 16;
- dc = rnd(1 << bd);
- for (int j = 0; j < height; j++) {
- for (int i = 0; i < width; i++) {
+ I dc;
+ void init(int bd) {
+ alpha_q3 = this->rnd(33) - 16;
+ dc = this->rnd(1 << bd);
+ for (int j = 0; j < this->height; j++) {
+ for (int i = 0; i < this->width; i++) {
chroma_pels[j * CFL_BUF_LINE + i] = dc;
chroma_pels_ref[j * CFL_BUF_LINE + i] = dc;
- int rand_val = rnd(1 << bd) - (1 << (bd - 1));
- sub_luma_pels_ref[j * CFL_BUF_LINE + i] = rand_val;
- sub_luma_pels[j * CFL_BUF_LINE + i] = rand_val;
+ sub_luma_pels_ref[j * CFL_BUF_LINE + i] =
+ sub_luma_pels[j * CFL_BUF_LINE + i] = this->rnd.Rand15Signed();
}
}
}
};
+class CFLSubAvgTest : public CFLTestWithData<sub_avg_fn, int16_t> {
+ public:
+ virtual ~CFLSubAvgTest() {}
+};
+
+class CFLSubsampleTest : public CFLTestWithData<get_subsample_fn, uint8_t> {
+ public:
+ virtual ~CFLSubsampleTest() {}
+};
+
+class CFLPredictTest : public CFLTestWithAlignedData<get_predict_fn, uint8_t> {
+ public:
+ virtual ~CFLPredictTest() {}
+};
+
+class CFLPredictHBDTest
+ : public CFLTestWithAlignedData<get_predict_fn_hbd, uint16_t> {
+ public:
+ virtual ~CFLPredictHBDTest() {}
+};
+
TEST_P(CFLSubAvgTest, SubAvgTest) {
- const TX_SIZE tx_size = Tx_size();
- const int width = tx_size_wide[tx_size];
- const int height = tx_size_high[tx_size];
const cfl_subtract_average_fn ref_sub = get_subtract_average_fn_c(tx_size);
- const cfl_subtract_average_fn sub = sub_avg(tx_size);
+ const cfl_subtract_average_fn sub = fun_under_test(tx_size);
for (int it = 0; it < NUM_ITERATIONS; it++) {
- init();
+ init(&ACMRandom::Rand15Signed);
sub(data);
ref_sub(data_ref);
- for (int j = 0; j < height; j++) {
- for (int i = 0; i < width; i++) {
- ASSERT_EQ(data_ref[j * CFL_BUF_LINE + i], data[j * CFL_BUF_LINE + i]);
- }
- }
+ assert_eq<int16_t>(data, data_ref, width, height);
}
}
TEST_P(CFLSubAvgTest, DISABLED_SubAvgSpeedTest) {
- const int width = Width();
- const int height = Height();
- const TX_SIZE tx_size = Tx_size();
-
const cfl_subtract_average_fn ref_sub = get_subtract_average_fn_c(tx_size);
- const cfl_subtract_average_fn sub = sub_avg(tx_size);
+ const cfl_subtract_average_fn sub = fun_under_test(tx_size);
aom_usec_timer ref_timer;
aom_usec_timer timer;
- init();
+ init(&ACMRandom::Rand15Signed);
aom_usec_timer_start(&ref_timer);
for (int k = 0; k < NUM_ITERATIONS_SPEED; k++) {
ref_sub(data_ref);
@@ -269,46 +222,40 @@
}
TEST_P(CFLSubsampleTest, SubsampleTest) {
- const int width = Width();
- const int height = Height();
- const TX_SIZE tx_size = Tx_size();
+ int16_t sub_luma_pels[CFL_BUF_SQUARE];
+ int16_t sub_luma_pels_ref[CFL_BUF_SQUARE];
const int sub_width = width >> 1;
const int sub_height = height >> 1;
for (int it = 0; it < NUM_ITERATIONS; it++) {
- init(width, height);
- subsample(tx_size)(luma_pels, CFL_BUF_LINE, sub_luma_pels);
- cfl_get_luma_subsampling_420_lbd_c(tx_size)(luma_pels_ref, CFL_BUF_LINE,
+ init(&ACMRandom::Rand8);
+ fun_under_test(tx_size)(data, CFL_BUF_LINE, sub_luma_pels);
+ cfl_get_luma_subsampling_420_lbd_c(tx_size)(data_ref, CFL_BUF_LINE,
sub_luma_pels_ref);
- for (int j = 0; j < sub_height; j++) {
- for (int i = 0; i < sub_width; i++) {
- ASSERT_EQ(sub_luma_pels_ref[j * CFL_BUF_LINE + i],
- sub_luma_pels[j * CFL_BUF_LINE + i]);
- }
- }
+ assert_eq<int16_t>(sub_luma_pels, sub_luma_pels_ref, sub_width, sub_height);
}
}
TEST_P(CFLSubsampleTest, DISABLED_SubsampleSpeedTest) {
- const int width = Width();
- const int height = Height();
- const TX_SIZE tx_size = Tx_size();
-
+ int16_t sub_luma_pels[CFL_BUF_SQUARE];
+ int16_t sub_luma_pels_ref[CFL_BUF_SQUARE];
+ cfl_subsample_lbd_fn subsample = fun_under_test(tx_size);
+ cfl_subsample_lbd_fn subsample_ref =
+ cfl_get_luma_subsampling_420_lbd_c(tx_size);
aom_usec_timer ref_timer;
aom_usec_timer timer;
- init(width, height);
+ init(&ACMRandom::Rand8);
aom_usec_timer_start(&ref_timer);
for (int k = 0; k < NUM_ITERATIONS_SPEED; k++) {
- cfl_get_luma_subsampling_420_lbd_c(tx_size)(luma_pels, CFL_BUF_LINE,
- sub_luma_pels);
+ subsample_ref(data_ref, CFL_BUF_LINE, sub_luma_pels);
}
aom_usec_timer_mark(&ref_timer);
int ref_elapsed_time = (int)aom_usec_timer_elapsed(&ref_timer);
aom_usec_timer_start(&timer);
for (int k = 0; k < NUM_ITERATIONS_SPEED; k++) {
- subsample(tx_size)(luma_pels_ref, CFL_BUF_LINE, sub_luma_pels_ref);
+ subsample(data, CFL_BUF_LINE, sub_luma_pels_ref);
}
aom_usec_timer_mark(&timer);
int elapsed_time = (int)aom_usec_timer_elapsed(&timer);
@@ -318,34 +265,22 @@
}
TEST_P(CFLPredictTest, PredictTest) {
- const int width = Width();
- const int height = Height();
- const TX_SIZE tx_size = Tx_size();
-
for (int it = 0; it < NUM_ITERATIONS; it++) {
- init(width, height);
- predict(tx_size)(sub_luma_pels, chroma_pels, CFL_BUF_LINE, tx_size,
- alpha_q3);
+ init(8);
+ fun_under_test(tx_size)(sub_luma_pels, chroma_pels, CFL_BUF_LINE, tx_size,
+ alpha_q3);
get_predict_lbd_fn_c(tx_size)(sub_luma_pels_ref, chroma_pels_ref,
CFL_BUF_LINE, tx_size, alpha_q3);
- for (int j = 0; j < height; j++) {
- for (int i = 0; i < width; i++) {
- ASSERT_EQ(chroma_pels_ref[j * CFL_BUF_LINE + i],
- chroma_pels[j * CFL_BUF_LINE + i]);
- }
- }
+
+ assert_eq<uint8_t>(chroma_pels, chroma_pels_ref, width, height);
}
}
TEST_P(CFLPredictTest, DISABLED_PredictSpeedTest) {
- const int width = Width();
- const int height = Height();
- const TX_SIZE tx_size = Tx_size();
-
aom_usec_timer ref_timer;
aom_usec_timer timer;
- init(width, height);
+ init(8);
cfl_predict_lbd_fn predict_impl = get_predict_lbd_fn_c(tx_size);
aom_usec_timer_start(&ref_timer);
@@ -356,7 +291,7 @@
aom_usec_timer_mark(&ref_timer);
int ref_elapsed_time = (int)aom_usec_timer_elapsed(&ref_timer);
- predict_impl = predict(tx_size);
+ predict_impl = fun_under_test(tx_size);
aom_usec_timer_start(&timer);
for (int k = 0; k < NUM_ITERATIONS_SPEED; k++) {
predict_impl(sub_luma_pels, chroma_pels, CFL_BUF_LINE, tx_size, alpha_q3);
@@ -369,34 +304,23 @@
}
TEST_P(CFLPredictHBDTest, PredictHBDTest) {
- const int width = Width();
- const int height = Height();
- const TX_SIZE tx_size = Tx_size();
-
+ int bd = 12;
for (int it = 0; it < NUM_ITERATIONS; it++) {
- init(width, height);
- predict(tx_size)(sub_luma_pels, chroma_pels, CFL_BUF_LINE, tx_size,
- alpha_q3, bd);
+ init(bd);
+ fun_under_test(tx_size)(sub_luma_pels, chroma_pels, CFL_BUF_LINE, tx_size,
+ alpha_q3, bd);
get_predict_hbd_fn_c(tx_size)(sub_luma_pels_ref, chroma_pels_ref,
CFL_BUF_LINE, tx_size, alpha_q3, bd);
- for (int j = 0; j < height; j++) {
- for (int i = 0; i < width; i++) {
- ASSERT_EQ(chroma_pels_ref[j * CFL_BUF_LINE + i],
- chroma_pels[j * CFL_BUF_LINE + i]);
- }
- }
+
+ assert_eq<uint16_t>(chroma_pels, chroma_pels_ref, width, height);
}
}
TEST_P(CFLPredictHBDTest, DISABLED_PredictHBDSpeedTest) {
- const int width = Width();
- const int height = Height();
- const TX_SIZE tx_size = Tx_size();
-
aom_usec_timer ref_timer;
aom_usec_timer timer;
-
- init(width, height);
+ int bd = 12;
+ init(bd);
cfl_predict_hbd_fn predict_impl = get_predict_hbd_fn_c(tx_size);
aom_usec_timer_start(&ref_timer);
@@ -407,7 +331,7 @@
aom_usec_timer_mark(&ref_timer);
int ref_elapsed_time = (int)aom_usec_timer_elapsed(&ref_timer);
- predict_impl = predict(tx_size);
+ predict_impl = fun_under_test(tx_size);
aom_usec_timer_start(&timer);
for (int k = 0; k < NUM_ITERATIONS_SPEED; k++) {
predict_impl(sub_luma_pels, chroma_pels, CFL_BUF_LINE, tx_size, alpha_q3,
