Merge remote-tracking branch 'origin/develop' into stream-k-initial-impl

test/convnd_fwd/CMakeLists.txt

-add_gtest_executable(test_convnd_fwd convnd_fwd.cpp)
-target_link_libraries(test_convnd_fwd PRIVATE utility device_conv2d_fwd_instance)
+if(GPU_TARGETS MATCHES "gfx908" OR GPU_TARGETS MATCHES "gfx90a" OR GPU_TARGETS MATCHES "gfx940")
+   add_gtest_executable(test_convnd_fwd convnd_fwd.cpp)
+   target_link_libraries(test_convnd_fwd PRIVATE utility device_conv2d_fwd_instance)
+endif()

test/gemm_layernorm/CMakeLists.txt

-add_custom_target(test_gemm_layernorm)
-
-add_gtest_executable(test_gemm_add_relu_add_layernorm_fp16 test_gemm_add_relu_add_layernorm_fp16.cpp)
-
-target_link_libraries(test_gemm_add_relu_add_layernorm_fp16 PRIVATE utility device_gemm_add_relu_add_layernorm_instance)
-
-add_dependencies(test_gemm_layernorm test_gemm_add_relu_add_layernorm_fp16)
+if(GPU_TARGETS MATCHES "gfx908" OR GPU_TARGETS MATCHES "gfx90a" OR GPU_TARGETS MATCHES "gfx940")
+   add_custom_target(test_gemm_layernorm)
+   add_gtest_executable(test_gemm_add_relu_add_layernorm_fp16 test_gemm_add_relu_add_layernorm_fp16.cpp)
+   target_link_libraries(test_gemm_add_relu_add_layernorm_fp16 PRIVATE utility device_gemm_add_relu_add_layernorm_instance)
+   add_dependencies(test_gemm_layernorm test_gemm_add_relu_add_layernorm_fp16)
+endif()

test/gemm_split_k/CMakeLists.txt

-add_test_executable(test_gemm_split_k gemm_split_k.cpp)
-target_link_libraries(test_gemm_split_k PRIVATE utility)
-target_link_libraries(test_gemm_split_k PRIVATE device_gemm_splitk_instance)
+if(GPU_TARGETS MATCHES "gfx908" OR GPU_TARGETS MATCHES "gfx90a" OR GPU_TARGETS MATCHES "gfx940")
+   add_test_executable(test_gemm_split_k gemm_split_k.cpp)
+   target_link_libraries(test_gemm_split_k PRIVATE utility)
+   target_link_libraries(test_gemm_split_k PRIVATE device_gemm_splitk_instance)
+endif()

test/grouped_convnd_bwd_weight/CMakeLists.txt

-add_gtest_executable(test_grouped_convnd_bwd_weight grouped_convnd_bwd_weight.cpp) 
-target_link_libraries(test_grouped_convnd_bwd_weight PRIVATE utility device_grouped_conv1d_bwd_weight_instance device_grouped_conv2d_bwd_weight_instance device_grouped_conv3d_bwd_weight_instance)
+if(GPU_TARGETS MATCHES "gfx908" OR GPU_TARGETS MATCHES "gfx90a" OR GPU_TARGETS MATCHES "gfx940")
+   add_gtest_executable(test_grouped_convnd_bwd_weight grouped_convnd_bwd_weight.cpp)
+    target_link_libraries(test_grouped_convnd_bwd_weight PRIVATE utility device_grouped_conv1d_bwd_weight_instance device_grouped_conv2d_bwd_weight_instance device_grouped_conv3d_bwd_weight_instance)
+endif()
\ No newline at end of file

test/grouped_gemm/CMakeLists.txt

-add_test_executable(test_grouped_gemm_fp16 grouped_gemm_fp16.cpp)
-target_link_libraries(test_grouped_gemm_fp16 PRIVATE utility)
-target_link_libraries(test_grouped_gemm_fp16 PRIVATE device_grouped_gemm_instance)
+if(GPU_TARGETS MATCHES "gfx908" OR GPU_TARGETS MATCHES "gfx90a" OR GPU_TARGETS MATCHES "gfx940")
+   add_test_executable(test_grouped_gemm_fp16 grouped_gemm_fp16.cpp)
+   target_link_libraries(test_grouped_gemm_fp16 PRIVATE utility)
+   target_link_libraries(test_grouped_gemm_fp16 PRIVATE device_grouped_gemm_instance)
+endif()

test/pool_fwd/CMakeLists.txt

+add_custom_target(test_pool_fwd)
+
+add_gtest_executable(test_avg_pool2d_fwd test_avg_pool2d_fwd.cpp)
+add_gtest_executable(test_avg_pool3d_fwd test_avg_pool3d_fwd.cpp)
+add_gtest_executable(test_max_pool2d_fwd test_max_pool2d_fwd.cpp)
+add_gtest_executable(test_max_pool3d_fwd test_max_pool3d_fwd.cpp)
+
+target_link_libraries(test_avg_pool2d_fwd PRIVATE utility device_pool_fwd_instance)
+target_link_libraries(test_avg_pool3d_fwd PRIVATE utility device_pool_fwd_instance)
+target_link_libraries(test_max_pool2d_fwd PRIVATE utility device_pool_fwd_instance)
+target_link_libraries(test_max_pool3d_fwd PRIVATE utility device_pool_fwd_instance)
+
+add_dependencies(test_pool_fwd test_avg_pool2d_fwd)
+add_dependencies(test_pool_fwd test_avg_pool3d_fwd)
+add_dependencies(test_pool_fwd test_max_pool2d_fwd)
+add_dependencies(test_pool_fwd test_max_pool3d_fwd)

test/pool_fwd/test_avg_pool2d_fwd.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "gtest/gtest.h"
+#include "profiler/profile_pool2d_fwd_impl.hpp"
+#include "test_pool_fwd_common.hpp"
+
+template <typename Tuple>
+class TestAvgPool2dFwd : public ::testing::Test
+{
+    protected:
+    using InDataType      = std::tuple_element_t<0, Tuple>;
+    using OutDataType     = std::tuple_element_t<1, Tuple>;
+    using ComputeDataType = std::tuple_element_t<2, Tuple>;
+    using IndexDataType   = std::tuple_element_t<3, Tuple>;
+
+    std::vector<PoolingParam> params;
+
+    void Run()
+    {
+        for(auto param : params)
+        {
+            bool success =
+                ck::profiler::profile_pool2d_fwd_impl<InDataType,
+                                                      OutDataType,
+                                                      ComputeDataType,
+                                                      IndexDataType,
+                                                      ck::ReduceTensorOp::AVG,
+                                                      false,
+                                                      false>(true,
+                                                             2,
+                                                             false,
+                                                             false,
+                                                             param.length_,
+                                                             param.window_spatial_lengths_,
+                                                             param.window_strides_,
+                                                             param.input_left_pads_,
+                                                             param.input_right_pads_);
+            EXPECT_TRUE(success);
+        }
+    }
+};
+
+using KernelTypes =
+    ::testing::Types<std::tuple<F16, F16, F32, I32>, std::tuple<F32, F32, F32, I32>>;
+
+TYPED_TEST_SUITE(TestAvgPool2dFwd, KernelTypes);
+TYPED_TEST(TestAvgPool2dFwd, Test_Pool)
+{
+    // length, window_length, window_stride, left_pad, right_pad
+    this->params = {{{1, 1, 1, 1}, {1, 1}, {1, 1}, {0, 0}, {0, 0}},
+                    {{2, 16, 64, 64}, {64, 64}, {1, 1}, {0, 0}, {0, 0}},
+                    {{2, 32, 30, 30}, {2, 2}, {2, 2}, {1, 1}, {1, 1}}};
+
+    this->Run();
+}

test/pool_fwd/test_avg_pool3d_fwd.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "gtest/gtest.h"
+#include "profiler/profile_pool3d_fwd_impl.hpp"
+#include "test_pool_fwd_common.hpp"
+
+template <typename Tuple>
+class TestAvgPool3dFwd : public ::testing::Test
+{
+    protected:
+    using InDataType      = std::tuple_element_t<0, Tuple>;
+    using OutDataType     = std::tuple_element_t<1, Tuple>;
+    using ComputeDataType = std::tuple_element_t<2, Tuple>;
+    using IndexDataType   = std::tuple_element_t<3, Tuple>;
+
+    std::vector<PoolingParam> params;
+
+    void Run()
+    {
+        for(auto param : params)
+        {
+            bool success =
+                ck::profiler::profile_pool3d_fwd_impl<InDataType,
+                                                      OutDataType,
+                                                      ComputeDataType,
+                                                      IndexDataType,
+                                                      ck::ReduceTensorOp::AVG,
+                                                      false,
+                                                      false>(true,
+                                                             2,
+                                                             false,
+                                                             false,
+                                                             param.length_,
+                                                             param.window_spatial_lengths_,
+                                                             param.window_strides_,
+                                                             param.input_left_pads_,
+                                                             param.input_right_pads_);
+            EXPECT_TRUE(success);
+        }
+    }
+};
+
+using KernelTypes =
+    ::testing::Types<std::tuple<F16, F16, F32, I32>, std::tuple<F32, F32, F32, I32>>;
+
+TYPED_TEST_SUITE(TestAvgPool3dFwd, KernelTypes);
+TYPED_TEST(TestAvgPool3dFwd, Test_Pool)
+{
+    // length, window_length, window_stride, left_pad, right_pad
+    this->params = {{{1, 1, 1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}},
+                    {{2, 16, 64, 64, 64}, {64, 64, 64}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}},
+                    {{2, 32, 30, 30, 30}, {2, 2, 2}, {2, 2, 2}, {1, 1, 1}, {1, 1, 1}}};
+
+    this->Run();
+}

test/pool_fwd/test_max_pool2d_fwd.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "gtest/gtest.h"
+#include "profiler/profile_pool2d_fwd_impl.hpp"
+#include "test_pool_fwd_common.hpp"
+
+template <typename Tuple>
+class TestMaxPool2dFwd : public ::testing::Test
+{
+    protected:
+    using InDataType      = std::tuple_element_t<0, Tuple>;
+    using OutDataType     = std::tuple_element_t<1, Tuple>;
+    using ComputeDataType = std::tuple_element_t<2, Tuple>;
+    using IndexDataType   = std::tuple_element_t<3, Tuple>;
+
+    std::vector<PoolingParam> params;
+
+    void Run()
+    {
+        for(auto param : params)
+        {
+            // max pool
+            bool success =
+                ck::profiler::profile_pool2d_fwd_impl<InDataType,
+                                                      OutDataType,
+                                                      ComputeDataType,
+                                                      IndexDataType,
+                                                      ck::ReduceTensorOp::MAX,
+                                                      false,
+                                                      false>(true,
+                                                             2,
+                                                             false,
+                                                             false,
+                                                             param.length_,
+                                                             param.window_spatial_lengths_,
+                                                             param.window_strides_,
+                                                             param.input_left_pads_,
+                                                             param.input_right_pads_);
+            EXPECT_TRUE(success);
+
+            // max pool + index
+            success = ck::profiler::profile_pool2d_fwd_impl<InDataType,
+                                                            OutDataType,
+                                                            ComputeDataType,
+                                                            IndexDataType,
+                                                            ck::ReduceTensorOp::MAX,
+                                                            false,
+                                                            true>(true,
+                                                                  2,
+                                                                  false,
+                                                                  false,
+                                                                  param.length_,
+                                                                  param.window_spatial_lengths_,
+                                                                  param.window_strides_,
+                                                                  param.input_left_pads_,
+                                                                  param.input_right_pads_);
+            EXPECT_TRUE(success);
+        }
+    }
+};
+
+using KernelTypes =
+    ::testing::Types<std::tuple<F16, F16, F16, I32>, std::tuple<F32, F32, F32, I32>>;
+
+TYPED_TEST_SUITE(TestMaxPool2dFwd, KernelTypes);
+TYPED_TEST(TestMaxPool2dFwd, Test_Pool)
+{
+    // length, window_length, window_stride, left_pad, right_pad
+    this->params = {{{1, 1, 1, 1}, {1, 1}, {1, 1}, {0, 0}, {0, 0}},
+                    {{2, 16, 64, 64}, {64, 64}, {1, 1}, {0, 0}, {0, 0}},
+                    {{2, 32, 30, 30}, {2, 2}, {2, 2}, {1, 1}, {1, 1}}};
+
+    this->Run();
+}

test/pool_fwd/test_max_pool3d_fwd.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "gtest/gtest.h"
+#include "profiler/profile_pool3d_fwd_impl.hpp"
+#include "test_pool_fwd_common.hpp"
+
+template <typename Tuple>
+class TestMaxPool3dFwd : public ::testing::Test
+{
+    protected:
+    using InDataType      = std::tuple_element_t<0, Tuple>;
+    using OutDataType     = std::tuple_element_t<1, Tuple>;
+    using ComputeDataType = std::tuple_element_t<2, Tuple>;
+    using IndexDataType   = std::tuple_element_t<3, Tuple>;
+
+    std::vector<PoolingParam> params;
+
+    void Run()
+    {
+        for(auto param : params)
+        {
+            // max pool
+            bool success =
+                ck::profiler::profile_pool3d_fwd_impl<InDataType,
+                                                      OutDataType,
+                                                      ComputeDataType,
+                                                      IndexDataType,
+                                                      ck::ReduceTensorOp::MAX,
+                                                      false,
+                                                      false>(true,
+                                                             2,
+                                                             false,
+                                                             false,
+                                                             param.length_,
+                                                             param.window_spatial_lengths_,
+                                                             param.window_strides_,
+                                                             param.input_left_pads_,
+                                                             param.input_right_pads_);
+            EXPECT_TRUE(success);
+
+            // max pool + index
+            success = ck::profiler::profile_pool3d_fwd_impl<InDataType,
+                                                            OutDataType,
+                                                            ComputeDataType,
+                                                            IndexDataType,
+                                                            ck::ReduceTensorOp::MAX,
+                                                            false,
+                                                            true>(true,
+                                                                  2,
+                                                                  false,
+                                                                  false,
+                                                                  param.length_,
+                                                                  param.window_spatial_lengths_,
+                                                                  param.window_strides_,
+                                                                  param.input_left_pads_,
+                                                                  param.input_right_pads_);
+            EXPECT_TRUE(success);
+        }
+    }
+};
+
+using KernelTypes =
+    ::testing::Types<std::tuple<F16, F16, F16, I32>, std::tuple<F32, F32, F32, I32>>;
+
+TYPED_TEST_SUITE(TestMaxPool3dFwd, KernelTypes);
+TYPED_TEST(TestMaxPool3dFwd, Test_Pool)
+{
+    // length, window_length, window_stride, left_pad, right_pad
+    this->params = {{{1, 1, 1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}},
+                    {{2, 16, 64, 64, 64}, {64, 64, 64}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}},
+                    {{2, 32, 30, 30, 30}, {2, 2, 2}, {2, 2, 2}, {1, 1, 1}, {1, 1, 1}}};
+
+    this->Run();
+}

test/pool_fwd/test_pool_fwd_common.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "gtest/gtest.h"
+#include "ck/ck.hpp"
+
+using F16 = ck::half_t;
+using F32 = float;
+using I32 = int32_t;
+using ck::index_t;
+
+struct PoolingParam
+{
+    PoolingParam(const std::vector<index_t>& length,
+                 const std::vector<index_t>& window_spatial_lengths,
+                 const std::vector<index_t>& window_strides,
+                 const std::vector<index_t>& input_left_pads,
+                 const std::vector<index_t>& input_right_pads)
+        : length_(length),
+          window_spatial_lengths_(window_spatial_lengths),
+          window_strides_(window_strides),
+          input_left_pads_(input_left_pads),
+          input_right_pads_(input_right_pads)
+    {
+    }
+    std::vector<index_t> length_;
+    std::vector<index_t> window_spatial_lengths_;
+    std::vector<index_t> window_strides_;
+    std::vector<index_t> input_left_pads_;
+    std::vector<index_t> input_right_pads_;
+};