Merge branch 'develop' into aosewski/test_ggemm_splitk

profiler/src/profile_avg_pool2d_fwd.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <iostream>
+#include <vector>
+#include <unordered_map>
+
+#include "profiler/data_type_enum.hpp"
+#include "profiler/profile_pool2d_fwd_impl.hpp"
+#include "profiler_operation_registry.hpp"
+
+using ck::index_t;
+
+struct avgPoolFwdArgParser
+{
+    std::unordered_map<std::string, std::vector<int>> long_opts = {
+        {"length", {}}, {"wsize", {}}, {"wstride", {}}, {"pad1", {}}, {"pad2", {}}};
+
+    bool parse_opt(int argc, char* argv[], const std::string& key, int i)
+    {
+        if(std::string("--") + key == argv[i])
+        {
+            int pos = i;
+            while(++i < argc && argv[i][0] != '-') {}
+            int end = i;
+            for(int j = pos + 1; j < end; j++)
+            {
+                long_opts[key].push_back(std::stoi(argv[j]));
+            }
+            return true;
+        }
+        return false;
+    }
+
+    void operator()(int argc, char* argv[])
+    {
+        for(auto& kv : long_opts)
+        {
+            for(int i = 1; i < argc; i++)
+            {
+                if(parse_opt(argc, argv, kv.first, i))
+                    break;
+            }
+        }
+    }
+};
+
+void print_help_avg_pool2d_fwd()
+{
+    std::cout << "arg1: data type (0: fp16; 1: fp32)\n"
+              << "arg2: verification (0: no; 1: yes)\n"
+              << "arg3: initialization (0: no init; 1: integer value; 2: decimal value)\n"
+              << "arg4: print tensor value (0: no; 1: yes)\n"
+              << "arg5: time kernel (0=no, 1=yes)\n"
+              << "--length: input tensor length for NDHW(e.g, --length 2 32 30 30) \n"
+              << "--wsize: window size for YX (e.g, --wsize 2 2) \n"
+              << "--wstride: window stride for HW (e.g, --wstride 2 2) \n"
+              << "--pad1: left side of padding in HW (e.g, --pad1 1 1) \n"
+              << "--pad2: right side of padding in HW (e.g, --pad2 1 1) \n"
+              << "eg: ckProfiler avg_pool2d_fwd 0 1 2 0 1 0 --length 2 32 30 30 --wsize 2 2 "
+                 "--wstride 2 2 --pad1 1 1 --pad2 1 1"
+              << std::endl;
+}
+
+int profile_avg_pool2d_fwd(int argc, char* argv[])
+{
+    ck::DataTypeEnum data_type = ck::DataTypeEnum::Half;
+    bool do_verification       = true;
+    int init_method            = 0;
+    bool do_log                = false;
+    bool time_kernel           = true;
+
+    std::vector<index_t> in_length = {2, 32, 30, 30};
+    std::vector<index_t> wsize     = {2, 2};
+    std::vector<index_t> wstride   = {2, 2};
+    std::vector<index_t> pad1      = {1, 1};
+    std::vector<index_t> pad2      = {1, 1};
+
+    if(argc != 2 && argc != 25)
+    {
+        print_help_avg_pool2d_fwd();
+        return 0;
+    }
+    else if(argc == 25)
+    {
+        data_type       = static_cast<ck::DataTypeEnum>(std::stoi(argv[2]));
+        do_verification = std::stoi(argv[3]);
+        init_method     = std::stoi(argv[4]);
+        do_log          = std::stoi(argv[5]);
+        time_kernel     = std::stoi(argv[6]);
+
+        // parse the long options
+        avgPoolFwdArgParser arg_parser;
+        arg_parser(argc, argv);
+        in_length = arg_parser.long_opts["length"];
+        wsize     = arg_parser.long_opts["wsize"];
+        wstride   = arg_parser.long_opts["wstride"];
+        pad1      = arg_parser.long_opts["pad1"];
+        pad2      = arg_parser.long_opts["pad2"];
+    }
+
+    using F16                 = ck::half_t;
+    using F32                 = float;
+    using I32                 = int32_t;
+    constexpr auto ReduceOpId = ck::ReduceTensorOp::AVG;
+
+    if(data_type == ck::DataTypeEnum::Half)
+    {
+        ck::profiler::profile_pool2d_fwd_impl<F16, F16, F32, I32, ReduceOpId, false, false>(
+            do_verification,
+            init_method,
+            do_log,
+            time_kernel,
+            in_length,
+            wsize,
+            wstride,
+            pad1,
+            pad2);
+    }
+    else if(data_type == ck::DataTypeEnum::Float)
+    {
+        ck::profiler::profile_pool2d_fwd_impl<F32, F32, F32, I32, ReduceOpId, false, false>(
+            do_verification,
+            init_method,
+            do_log,
+            time_kernel,
+            in_length,
+            wsize,
+            wstride,
+            pad1,
+            pad2);
+    }
+    else
+    {
+        throw std::runtime_error("not implemented yet");
+    }
+
+    return 0;
+}
+
+REGISTER_PROFILER_OPERATION("avg_pool2d_fwd", "avg_pool2d fwd", profile_avg_pool2d_fwd);

profiler/src/profile_groupnorm.cpp

@@ -64,7 +64,7 @@ int profile_groupnorm(int argc, char* argv[])
     ck::DataTypeEnum data_type  = ck::DataTypeEnum::Half;
     bool do_verification        = false;
     int init_method             = 0;
-    bool do_log                 = 0;
+    bool do_log                 = false;
     bool time_kernel            = 1;
     std::vector<index_t> length = {64, 16, 16, 32, 40};
 

profiler/src/profile_max_pool3d_fwd.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <iostream>
+#include <vector>
+#include <unordered_map>
+
+#include "profiler/data_type_enum.hpp"
+#include "profiler/profile_pool3d_fwd_impl.hpp"
+#include "profiler_operation_registry.hpp"
+
+using ck::index_t;
+
+struct maxPoolFwdArgParser
+{
+    std::unordered_map<std::string, std::vector<int>> long_opts = {
+        {"length", {}}, {"wsize", {}}, {"wstride", {}}, {"pad1", {}}, {"pad2", {}}};
+
+    bool parse_opt(int argc, char* argv[], const std::string& key, int i)
+    {
+        if(std::string("--") + key == argv[i])
+        {
+            int pos = i;
+            while(++i < argc && argv[i][0] != '-') {}
+            int end = i;
+            for(int j = pos + 1; j < end; j++)
+            {
+                long_opts[key].push_back(std::stoi(argv[j]));
+            }
+            return true;
+        }
+        return false;
+    }
+
+    void operator()(int argc, char* argv[])
+    {
+        for(auto& kv : long_opts)
+        {
+            for(int i = 1; i < argc; i++)
+            {
+                if(parse_opt(argc, argv, kv.first, i))
+                    break;
+            }
+        }
+    }
+};
+
+void print_help_max_pool3d_fwd()
+{
+    std::cout << "arg1: data type (0: fp16; 1: fp32)\n"
+              << "arg2: verification (0: no; 1: yes)\n"
+              << "arg3: initialization (0: no init; 1: integer value; 2: decimal value)\n"
+              << "arg4: print tensor value (0: no; 1: yes)\n"
+              << "arg5: time kernel (0=no, 1=yes)\n"
+              << "arg6: return index (0=no, 1=yes)\n"
+              << "--length: input tensor length for NCDHW(e.g, --length 2 32 30 30 30) \n"
+              << "--wsize: window size for ZYX (e.g, --wsize 2 2 2) \n"
+              << "--wstride: window stride for DHW (e.g, --wstride 2 2 2) \n"
+              << "--pad1: left side of padding in DHW (e.g, --pad1 1 1 1) \n"
+              << "--pad2: right side of padding in DHW (e.g, --pad2 1 1 1) \n"
+              << "eg: ckProfiler max_pool3d_fwd 0 1 2 0 1 0 --length 2 32 30 30 30 --wsize 2 2 2 "
+                 "--wstride 2 2 2 --pad1 1 1 1 --pad2 1 1 1"
+              << std::endl;
+}
+
+int profile_max_pool3d_fwd(int argc, char* argv[])
+{
+    ck::DataTypeEnum data_type = ck::DataTypeEnum::Half;
+    bool do_verification       = true;
+    int init_method            = 0;
+    bool do_log                = false;
+    bool time_kernel           = true;
+    bool return_index          = false;
+
+    std::vector<index_t> in_length = {2, 32, 30, 30, 30};
+    std::vector<index_t> wsize     = {2, 2, 2};
+    std::vector<index_t> wstride   = {2, 2, 2};
+    std::vector<index_t> pad1      = {1, 1, 1};
+    std::vector<index_t> pad2      = {1, 1, 1};
+
+    if(argc != 2 && argc != 30)
+    {
+        print_help_max_pool3d_fwd();
+        return 0;
+    }
+    else if(argc == 30)
+    {
+        data_type       = static_cast<ck::DataTypeEnum>(std::stoi(argv[2]));
+        do_verification = std::stoi(argv[3]);
+        init_method     = std::stoi(argv[4]);
+        do_log          = std::stoi(argv[5]);
+        time_kernel     = std::stoi(argv[6]);
+        return_index    = std::stoi(argv[7]);
+
+        // parse the long options
+        maxPoolFwdArgParser arg_parser;
+        arg_parser(argc, argv);
+        in_length = arg_parser.long_opts["length"];
+        wsize     = arg_parser.long_opts["wsize"];
+        wstride   = arg_parser.long_opts["wstride"];
+        pad1      = arg_parser.long_opts["pad1"];
+        pad2      = arg_parser.long_opts["pad2"];
+    }
+
+    using F16                 = ck::half_t;
+    using F32                 = float;
+    using I32                 = int32_t;
+    constexpr auto ReduceOpId = ck::ReduceTensorOp::MAX;
+
+    if(data_type == ck::DataTypeEnum::Half)
+    {
+        if(return_index)
+            ck::profiler::profile_pool3d_fwd_impl<F16, F16, F16, I32, ReduceOpId, false, true>(
+                do_verification,
+                init_method,
+                do_log,
+                time_kernel,
+                in_length,
+                wsize,
+                wstride,
+                pad1,
+                pad2);
+        else
+            ck::profiler::profile_pool3d_fwd_impl<F16, F16, F16, I32, ReduceOpId, false, false>(
+                do_verification,
+                init_method,
+                do_log,
+                time_kernel,
+                in_length,
+                wsize,
+                wstride,
+                pad1,
+                pad2);
+    }
+    else if(data_type == ck::DataTypeEnum::Float)
+    {
+        if(return_index)
+            ck::profiler::profile_pool3d_fwd_impl<F32, F32, F32, I32, ReduceOpId, false, true>(
+                do_verification,
+                init_method,
+                do_log,
+                time_kernel,
+                in_length,
+                wsize,
+                wstride,
+                pad1,
+                pad2);
+        else
+            ck::profiler::profile_pool3d_fwd_impl<F32, F32, F32, I32, ReduceOpId, false, false>(
+                do_verification,
+                init_method,
+                do_log,
+                time_kernel,
+                in_length,
+                wsize,
+                wstride,
+                pad1,
+                pad2);
+    }
+    else
+    {
+        throw std::runtime_error("not implemented yet");
+    }
+
+    return 0;
+}
+
+REGISTER_PROFILER_OPERATION("max_pool3d_fwd", "max_pool3d fwd", profile_max_pool3d_fwd);

test/CMakeLists.txt

@@ -57,6 +57,7 @@ add_subdirectory(data_type)
 add_subdirectory(elementwise_normalization)
 add_subdirectory(batchnorm)
 add_subdirectory(contraction)
+add_subdirectory(pool_fwd)
 if(GPU_TARGETS MATCHES "gfx1100")
     add_subdirectory(wmma_op)
 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_;
+};