Merge remote-tracking branch 'upstream/develop' into gemm-layernorm-4

test/softmax/test_softmax_fp32.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "gtest/gtest.h"
+#include "test_softmax_util.hpp"
+
+template <ck::index_t N>
+using I = ck::Number<N>;
+
+template <typename Tuple>
+class TestSoftmaxFP32 : public ck::TestSoftmax<Tuple>
+{
+};
+
+// clang-format off
+using KernelTypes = ::testing::Types<
+// InDataType, AccDataType, OutDataType, Rank, NumReduceDim, BlockSize, MThreadClusterSize, KThreadClusterSize, MThreadSliceSize, KThreadSliceSize, InSrcVectorDim, InSrcVectorSize, OutDstVectorSize>
+    std::tuple<float, float, float, I<3>, I<1>, I<256>, I<8>, I<32>, I<1>, I<4>, I<1>, I<4>, I<4>>,
+    std::tuple<float, float, float, I<3>, I<1>, I<256>, I<4>, I<64>, I<1>, I<4>, I<1>, I<4>, I<4>>,
+    std::tuple<float, float, float, I<3>, I<1>, I<256>, I<2>, I<128>, I<1>, I<4>, I<1>, I<4>, I<4>>,
+    std::tuple<float, float, float, I<3>, I<1>, I<256>, I<1>, I<256>, I<1>, I<4>, I<1>, I<4>, I<4>>,
+    std::tuple<float, float, float, I<3>, I<2>, I<256>, I<8>, I<32>, I<1>, I<4>, I<1>, I<4>, I<4>>,
+    std::tuple<float, float, float, I<3>, I<2>, I<256>, I<4>, I<64>, I<1>, I<4>, I<1>, I<4>, I<4>>,
+    std::tuple<float, float, float, I<3>, I<2>, I<256>, I<2>, I<128>, I<1>, I<4>, I<1>, I<4>, I<4>>,
+    std::tuple<float, float, float, I<3>, I<2>, I<256>, I<1>, I<256>, I<1>, I<4>, I<1>, I<4>, I<4>>
+    >;
+// clang-format on
+TYPED_TEST_SUITE(TestSoftmaxFP32, KernelTypes);
+TYPED_TEST(TestSoftmaxFP32, Test_FP32) { this->Run(); }

test/softmax/test_softmax_util.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <vector>
+#include <iostream>
+#include <gtest/gtest.h>
+
+#include "ck/ck.hpp"
+#include "ck/utility/number.hpp"
+#include "ck/tensor_operation/gpu/device/device_softmax.hpp"
+
+#include "ck/library/utility/check_err.hpp"
+#include "ck/library/host_tensor/host_tensor.hpp"
+#include "ck/library/host_tensor/device_memory.hpp"
+#include "ck/library/reference_tensor_operation/cpu/reference_softmax.hpp"
+
+namespace ck {
+
+template <typename Tuple>
+class TestSoftmax : public ::testing::Test
+{
+    protected:
+    using InDataType                            = std::tuple_element_t<0, Tuple>;
+    using AccDataType                           = std::tuple_element_t<1, Tuple>;
+    using OutDataType                           = std::tuple_element_t<2, Tuple>;
+    static constexpr index_t Rank               = std::tuple_element_t<3, Tuple>{}.value;
+    static constexpr index_t NumReduceDim       = std::tuple_element_t<4, Tuple>{}.value;
+    static constexpr index_t BlockSize          = std::tuple_element_t<5, Tuple>{}.value;
+    static constexpr index_t MThreadClusterSize = std::tuple_element_t<6, Tuple>{}.value;
+    static constexpr index_t KThreadClusterSize = std::tuple_element_t<7, Tuple>{}.value;
+    static constexpr index_t MThreadSliceSize   = std::tuple_element_t<8, Tuple>{}.value;
+    static constexpr index_t KThreadSliceSize   = std::tuple_element_t<9, Tuple>{}.value;
+    static constexpr index_t InSrcVectorDim     = std::tuple_element_t<10, Tuple>{}.value;
+    static constexpr index_t InSrcVectorSize    = std::tuple_element_t<11, Tuple>{}.value;
+    static constexpr index_t OutDstVectorSize   = std::tuple_element_t<12, Tuple>{}.value;
+
+    using ReferenceInstance =
+        tensor_operation::host::ReferenceSoftmax<InDataType, OutDataType, AccDataType>;
+
+    using DeviceInstance = tensor_operation::device::DeviceSoftmax<InDataType,
+                                                                   AccDataType,
+                                                                   OutDataType,
+                                                                   Rank,
+                                                                   NumReduceDim,
+                                                                   BlockSize,
+                                                                   MThreadClusterSize,
+                                                                   KThreadClusterSize,
+                                                                   MThreadSliceSize,
+                                                                   KThreadSliceSize,
+                                                                   InSrcVectorDim,
+                                                                   InSrcVectorSize,
+                                                                   OutDstVectorSize>;
+
+    TestSoftmax() : ref_instance_invoker_(ReferenceInstance{}.MakeInvoker()) {}
+
+    void RunSingle(std::vector<index_t> in_length, AccDataType alpha, AccDataType beta)
+    {
+        std::vector<index_t> reduce_dims(NumReduceDim);
+        std::iota(reduce_dims.begin(), reduce_dims.end(), Rank - NumReduceDim);
+
+        Tensor<InDataType> in(in_length);
+        Tensor<OutDataType> out(in_length);
+
+        in.GenerateTensorValue(GeneratorTensor_2<InDataType>{-5, 5});
+        out.GenerateTensorValue(GeneratorTensor_2<OutDataType>{-5, 5});
+
+        Tensor<OutDataType> out_ref(out);
+
+        DeviceMem in_dev(sizeof(InDataType) * in.mDesc.GetElementSpace());
+        DeviceMem out_dev(sizeof(OutDataType) * out.mDesc.GetElementSpace());
+        in_dev.ToDevice(in.mData.data());
+        out_dev.ToDevice(out.mData.data());
+
+        std::vector<index_t> i_in_lengths(in.mDesc.GetLengths().begin(),
+                                          in.mDesc.GetLengths().end());
+        std::vector<index_t> i_in_strides(in.mDesc.GetStrides().begin(),
+                                          in.mDesc.GetStrides().end());
+
+        auto device_instance = DeviceInstance{};
+        auto argument_ptr    = device_instance.MakeArgumentPointer(i_in_lengths,
+                                                                i_in_strides,
+                                                                reduce_dims,
+                                                                alpha,
+                                                                beta,
+                                                                in_dev.GetDeviceBuffer(),
+                                                                out_dev.GetDeviceBuffer());
+
+        if(!device_instance.IsSupportedArgument(argument_ptr.get()))
+        {
+            FAIL() << "Unsupported argument";
+        }
+
+        auto invoker_ptr = device_instance.MakeInvokerPointer();
+        invoker_ptr->Run(argument_ptr.get());
+
+        ref_instance_invoker_.Run({in, out_ref, alpha, beta, Rank, reduce_dims});
+
+        out_dev.FromDevice(out.mData.data());
+        EXPECT_TRUE(ck::utils::check_err(out.mData, out_ref.mData));
+    }
+
+    void Run()
+    {
+        for(auto in_length : this->in_lengths_)
+        {
+            for(auto scale : this->scales_)
+            {
+                this->RunSingle(in_length, std::get<0>(scale), std::get<1>(scale));
+            }
+        }
+    }
+
+    std::vector<std::vector<index_t>> in_lengths_ = {{1, 8, 128}, {2, 128, 1024}, {3, 9, 1032}};
+    std::vector<std::tuple<AccDataType, AccDataType>> scales_ = {{1, 0}, {2, 2}, {0, 1}};
+
+    typename ReferenceInstance::Invoker ref_instance_invoker_;
+};
+} // namespace ck

test/space_filling_curve/space_filling_curve.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
 #include <vector>
 #include <iostream>
 #include <numeric>
 #include <cassert>
 
-#include "tensor_space_filling_curve.hpp"
+#include "ck/ck.hpp"
+#include "ck/utility/common_header.hpp"
+#include "ck/tensor_description/tensor_space_filling_curve.hpp"
 
 using namespace ck;