Merge branch 'develop' into amd-develop

test/wrapper/test_tensor.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <cstdlib>
+#include <iostream>
+#include <initializer_list>
+#include <vector>
+#include <gtest/gtest.h>
+
+#include "ck/library/utility/device_memory.hpp"
+
+#include "ck/host_utility/kernel_launch.hpp"
+
+#include "ck/utility/common_header.hpp"
+
+#include "ck/wrapper/layout.hpp"
+#include "ck/wrapper/tensor.hpp"
+
+// Compare data in tensor with offset from layout.
+// Data and offset should match if physical memory has been initialized with
+// sequentially increasing values from 0.
+template <typename TensorType>
+__host__ __device__ bool TestTensorCheck3d(TensorType& tensor)
+{
+    const auto& layout = ck::wrapper::layout(tensor);
+    for(ck::index_t d = 0; d < ck::wrapper::size<0>(ck::wrapper::get<0>(layout)); d++)
+    {
+        for(ck::index_t h = 0; h < ck::wrapper::size<1>(ck::wrapper::get<0>(layout)); h++)
+        {
+            for(ck::index_t w = 0; w < ck::wrapper::size<1>(layout); w++)
+            {
+                const auto idx = ck::make_tuple(ck::make_tuple(d, h), w);
+                if(tensor(idx) != layout(idx))
+                {
+                    return false;
+                }
+            }
+        }
+    }
+    return true;
+}
+
+template <typename TensorType>
+__host__ __device__ bool TestTensorCheck1d(TensorType& tensor, ck::index_t start_offset = 0)
+{
+    const auto& layout = ck::wrapper::layout(tensor);
+    for(ck::index_t w = 0; w < ck::wrapper::size<0>(layout); w++)
+    {
+        if(tensor(w) - start_offset != layout(ck::make_tuple(w)))
+        {
+            return false;
+        }
+    }
+    return true;
+}
+
+template <ck::index_t nelems, typename TensorType>
+__host__ __device__ bool StaticTestTensorCheck1d(TensorType& tensor)
+{
+    const auto& layout = ck::wrapper::layout(tensor);
+    bool success       = true;
+    ck::static_for<0, nelems, 1>{}([&](auto w) {
+        if(tensor(ck::Number<w.value>{}) != layout(ck::make_tuple(w.value)))
+        {
+            success = false;
+        }
+    });
+    return success;
+}
+
+template <typename TensorType>
+__host__ __device__ void InitTensor(TensorType& tensor)
+{
+    for(ck::index_t i = 0; i < ck::wrapper::size(ck::wrapper::layout(tensor)); i++)
+    {
+        tensor(i) = i;
+    }
+}
+
+template <ck::index_t nelems, typename TensorType>
+__host__ __device__ void StaticInitTensor(TensorType& tensor)
+{
+
+    ck::static_for<0, nelems, 1>{}([&](auto i) { tensor(ck::Number<i.value>{}) = i.value; });
+}
+
+// Tests
+TEST(TestTensor, ReadWriteHostMemory)
+{
+    constexpr ck::index_t nelems = 8;
+
+    std::array<ck::index_t, nelems> data;
+    const auto layout = ck::wrapper::make_layout(ck::make_tuple(ck::make_tuple(2, 2), 2));
+    auto tensor = ck::wrapper::make_tensor<ck::wrapper::MemoryTypeEnum::Generic>(&data[0], layout);
+    InitTensor(tensor);
+
+    EXPECT_TRUE(TestTensorCheck1d(tensor));
+    EXPECT_TRUE(TestTensorCheck3d(tensor));
+}
+
+__global__ void TestTensorReadWriteDevice(void* data, void* success)
+{
+    constexpr ck::index_t nelems            = 8;
+    constexpr ck::index_t scalar_per_vector = 1;
+    __shared__ ck::index_t p_shared[nelems];
+
+    ck::index_t* casted_data_ptr = static_cast<ck::index_t*>(data);
+    bool* casted_success_ptr     = static_cast<bool*>(success);
+
+    const auto layout = ck::wrapper::make_layout(ck::make_tuple(ck::make_tuple(2, 2), 2));
+    constexpr auto register_layout = ck::wrapper::make_layout(ck::make_tuple(ck::Number<8>{}));
+
+    auto tensor_global =
+        ck::wrapper::make_tensor<ck::wrapper::MemoryTypeEnum::Global>(casted_data_ptr, layout);
+    auto tensor_lds  = ck::wrapper::make_tensor<ck::wrapper::MemoryTypeEnum::Lds>(p_shared, layout);
+    auto tensor_vgpr = ck::wrapper::make_register_tensor<ck::wrapper::MemoryTypeEnum::Vgpr,
+                                                         nelems,
+                                                         scalar_per_vector,
+                                                         ck::index_t>(register_layout);
+    auto tensor_sgpr = ck::wrapper::make_register_tensor<ck::wrapper::MemoryTypeEnum::Sgpr,
+                                                         nelems,
+                                                         scalar_per_vector,
+                                                         ck::index_t>(register_layout);
+
+    InitTensor(tensor_global);
+    InitTensor(tensor_lds);
+    StaticInitTensor<nelems>(tensor_vgpr);
+    StaticInitTensor<nelems>(tensor_sgpr);
+
+    *casted_success_ptr &= TestTensorCheck1d(tensor_global);
+    *casted_success_ptr &= TestTensorCheck3d(tensor_global);
+
+    *casted_success_ptr &= TestTensorCheck1d(tensor_lds);
+    *casted_success_ptr &= TestTensorCheck3d(tensor_lds);
+
+    *casted_success_ptr &= StaticTestTensorCheck1d<nelems>(tensor_vgpr);
+
+    *casted_success_ptr &= StaticTestTensorCheck1d<nelems>(tensor_sgpr);
+}
+
+TEST(TestTensor, ReadWriteGlobalLdsRegistersMemory)
+{
+    constexpr ck::index_t nelems = 8;
+    std::array<ck::index_t, nelems> host_data;
+
+    DeviceMem data_buf(nelems * sizeof(ck::index_t));
+    data_buf.ToDevice(&host_data[0]);
+    DeviceMem success_buf(sizeof(bool));
+
+    launch_and_time_kernel(StreamConfig{},
+                           TestTensorReadWriteDevice,
+                           dim3(1),
+                           dim3(1),
+                           nelems * sizeof(ck::index_t),
+                           data_buf.GetDeviceBuffer(),
+                           success_buf.GetDeviceBuffer());
+
+    bool success;
+    success_buf.FromDevice(&success);
+    EXPECT_TRUE(success);
+}
+
+TEST(TestTensor, Slicing)
+{
+    constexpr ck::index_t nelems = 8;
+
+    std::array<ck::index_t, nelems> data;
+    const auto shape   = ck::make_tuple(ck::make_tuple(2, 2), 2);
+    const auto strides = ck::make_tuple(ck::make_tuple(1, 2), 4);
+    const auto layout  = ck::wrapper::make_layout(shape, strides);
+    auto tensor = ck::wrapper::make_tensor<ck::wrapper::MemoryTypeEnum::Generic>(&data[0], layout);
+    InitTensor(tensor);
+
+    auto tensor2x2x2 =
+        tensor(ck::make_tuple(ck::wrapper::slice(2), ck::wrapper::slice(2)), ck::wrapper::slice(2));
+    EXPECT_EQ(ck::wrapper::rank(tensor2x2x2), 2);
+    EXPECT_EQ(ck::wrapper::depth(tensor2x2x2), 2);
+    EXPECT_EQ(ck::wrapper::size(tensor2x2x2), 8);
+    EXPECT_TRUE(TestTensorCheck1d(tensor2x2x2));
+
+    auto tensor2x2 = tensor(ck::make_tuple(1, ck::wrapper::slice(2)), ck::wrapper::slice(2));
+    EXPECT_EQ(ck::wrapper::rank(tensor2x2), 2);
+    EXPECT_EQ(ck::wrapper::depth(tensor2x2), 2);
+    EXPECT_EQ(ck::wrapper::size(tensor2x2), 4);
+    EXPECT_TRUE(TestTensorCheck1d(tensor2x2, layout(ck::make_tuple(ck::make_tuple(1, 0), 0))));
+
+    auto tensor1x1 = tensor(ck::make_tuple(1, ck::wrapper::slice(1, 2)), ck::wrapper::slice(1, 2));
+    EXPECT_EQ(rank(tensor1x1), 2);
+    EXPECT_EQ(depth(tensor1x1), 2);
+    EXPECT_EQ(size(tensor1x1), 1);
+    EXPECT_TRUE(TestTensorCheck1d(tensor1x1, layout(ck::make_tuple(ck::make_tuple(1, 1), 1))));
+
+    auto tensor2 = tensor(ck::make_tuple(1, 1), ck::wrapper::slice(0, 2));
+    EXPECT_EQ(ck::wrapper::rank(tensor2), 1);
+    EXPECT_EQ(ck::wrapper::depth(tensor2), 1);
+    EXPECT_EQ(ck::wrapper::size(tensor2), 2);
+    EXPECT_TRUE(TestTensorCheck1d(tensor2, layout(ck::make_tuple(ck::make_tuple(1, 1), 0))));
+
+    // negative indexing
+    auto tensor1x2 = tensor(ck::make_tuple(1, ck::wrapper::slice(0, -2)), ck::wrapper::slice());
+    EXPECT_EQ(rank(tensor1x2), 2);
+    EXPECT_EQ(depth(tensor1x2), 2);
+    EXPECT_EQ(size(tensor1x2), 2);
+    EXPECT_TRUE(TestTensorCheck1d(tensor1x2, layout(ck::make_tuple(ck::make_tuple(1, 0), 0))));
+}