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CUTLASS 3.2 (#1024)

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* CUTLASS 3.2
This commit is contained in:
ANIKET SHIVAM
2023-08-07 14:50:32 -10:00
committed by GitHub
parent a0d787b746
commit 4575443d44
392 changed files with 47559 additions and 7940 deletions
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129
test/unit/cute/core/array_subbyte.cpp
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@ -36,10 +36,27 @@
#include <utility>
#include <cute/container/array_subbyte.hpp>
#include <cute/tensor.hpp>
TEST(CuTe_core, ArraySubbyte)
{
using namespace cute;
{
array_subbyte<int4_t, 10> array0;
array_subbyte<int4_t, 5> array1;
fill(array0, int4_t(0));
fill(array1, int4_t(1));
for (int i = 0; i < array1.size(); ++i) {
array0[i+5] = array1[i];
}
EXPECT_EQ(int4_t(array0.back()), int4_t(1));
for (int i = 0; i < array1.size(); ++i) {
EXPECT_EQ(int4_t(array0[i]), int4_t(i / 5));
}
}
{
array_subbyte<uint8_t, 14> a;
@ -112,3 +129,115 @@ TEST(CuTe_core, ArraySubbyte)
//std::cout << std::endl;
}
}
TEST(CuTe_core, Subbyte_iterator)
{
using namespace cute;
{
array_subbyte<uint8_t, 15> a;
auto tensor = make_tensor(subbyte_iterator<uint8_t>(a.raw_data()), make_shape(15));
fill(a, uint8_t(13));
for (int i = 0; i < int(a.size()); ++i) {
EXPECT_EQ(uint8_t(tensor(i)), 13);
tensor(i) = uint8_t(i);
EXPECT_EQ(a[i], uint8_t(tensor(i)));
}
}
{
array_subbyte<int4_t, 15> a;
auto tensor = make_tensor(subbyte_iterator<int4_t>(a.raw_data()), make_shape(15));
fill(a, int4_t(-5));
for (int i = 0; i < int(a.size()); ++i) {
EXPECT_EQ(int4_t(tensor(i)), int4_t(-5));
tensor(i) = int4_t(i);
EXPECT_EQ(int4_t(a[i]), int4_t(tensor(i)));
}
}
{
array_subbyte<uint2_t, 15> a;
auto tensor = make_tensor(subbyte_iterator<uint2_t>(a.raw_data()), make_shape(15));
fill(a, uint2_t(-5));
for (int i = 0; i < int(a.size()); ++i) {
EXPECT_EQ(uint2_t(tensor(i)), uint2_t(-5));
tensor(i) = uint2_t(i);
EXPECT_EQ(uint2_t(a[i]), uint2_t(tensor(i)));
}
}
{
array_subbyte<bool, 15> a;
auto tensor = make_tensor(subbyte_iterator<bool>(a.raw_data()), make_shape(15));
fill(a, bool(1));
for (int i = 0; i < int(a.size()); ++i) {
EXPECT_EQ(bool(tensor(i)), bool(1));
tensor(i) = bool(i % 2);
EXPECT_EQ(a[i], bool(tensor(i)));
}
}
}
TEST(CuTe_core, Const_subbyte_iterator)
{
using namespace cute;
{
array_subbyte<uint8_t, 15> a;
auto tensor = make_tensor(subbyte_iterator<uint8_t const>(a.raw_data()), make_shape(15));
fill(a, uint8_t(13));
for (int i = 0; i < int(a.size()); ++i) {
EXPECT_EQ(uint8_t(tensor(i)), 13);
a[i] = uint8_t(i);
EXPECT_EQ(a[i], uint8_t(tensor(i)));
}
}
{
array_subbyte<int4_t, 15> a;
auto tensor = make_tensor(subbyte_iterator<int4_t const>(a.raw_data()), make_shape(15));
fill(a, int4_t(-5));
for (int i = 0; i < int(a.size()); ++i) {
EXPECT_EQ(int4_t(tensor(i)), int4_t(-5));
a[i] = int4_t(i);
EXPECT_EQ(int4_t(a[i]), int4_t(tensor(i)));
}
}
{
array_subbyte<uint2_t, 15> a;
auto tensor = make_tensor(subbyte_iterator<uint2_t const>(a.raw_data()), make_shape(15));
fill(a, uint2_t(-5));
for (int i = 0; i < int(a.size()); ++i) {
EXPECT_EQ(uint2_t(tensor(i)), uint2_t(-5));
a[i] = uint2_t(i);
EXPECT_EQ(uint2_t(a[i]), uint2_t(tensor(i)));
}
}
{
array_subbyte<bool, 15> a;
auto tensor = make_tensor(subbyte_iterator<bool const>(a.raw_data()), make_shape(15));
fill(a, bool(1));
for (int i = 0; i < int(a.size()); ++i) {
EXPECT_EQ(bool(tensor(i)), bool(1));
a[i] = bool(i % 2);
EXPECT_EQ(a[i], bool(tensor(i)));
}
}
}