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https://github.com/ROCm/composable_kernel.git
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layernorm external api (#379)
* Add layernorm client example * [What] Add default make install dir to gitignore [Why] client example need to make install
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2
client_example/05_layernorm/CMakeLists.txt
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client_example/05_layernorm/CMakeLists.txt
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add_executable(client_layernorm2d layernorm2d.cpp)
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target_link_libraries(client_layernorm2d PRIVATE composable_kernel::device_operations)
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159
client_example/05_layernorm/layernorm2d.cpp
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client_example/05_layernorm/layernorm2d.cpp
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
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#include <iomanip>
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#include <vector>
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#include <iostream>
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#include "ck/ck.hpp"
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#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
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#include "ck/tensor_operation/gpu/device/device_normalization.hpp"
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#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
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#include "ck/library/tensor_operation_instance/gpu/layernorm.hpp"
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using XDataType = ck::half_t;
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using GammaDataType = ck::half_t;
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using BetaDataType = ck::half_t;
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using YDataType = ck::half_t;
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using AccDataType = float;
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using PassThrough = ck::tensor_operation::element_wise::PassThrough;
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constexpr int Rank = 2;
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constexpr int NumReduceDim = 1;
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struct SimpleDeviceMem
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{
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SimpleDeviceMem() = delete;
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SimpleDeviceMem(std::size_t mem_size) : p_mem_{}
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{
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(void)hipMalloc(static_cast<void**>(&p_mem_), mem_size);
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}
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void* GetDeviceBuffer() { return p_mem_; }
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~SimpleDeviceMem() { (void)hipFree(p_mem_); }
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void* p_mem_;
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};
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int main(int argc, char* argv[])
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{
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ck::index_t M = 1024;
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ck::index_t N = 1024;
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ck::index_t Stride = 1024;
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auto xy_size = (M - 1) * Stride + N;
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SimpleDeviceMem x_device_buf(sizeof(XDataType) * xy_size);
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SimpleDeviceMem gamma_device_buf(sizeof(GammaDataType) * N);
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SimpleDeviceMem beta_device_buf(sizeof(BetaDataType) * N);
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SimpleDeviceMem y_device_buf(sizeof(YDataType) * xy_size);
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using DeviceOp = ck::tensor_operation::device::DeviceLayernorm<XDataType,
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GammaDataType,
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BetaDataType,
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AccDataType,
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YDataType,
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PassThrough,
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Rank,
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NumReduceDim>;
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// get device op instances
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const auto op_ptrs = ck::tensor_operation::device::instance::DeviceOperationInstanceFactory<
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DeviceOp>::GetInstances();
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std::cout << "found " << op_ptrs.size() << " instances" << std::endl;
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std::string best_op_name;
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bool found = false;
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int best_op_id = -1;
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float best_ave_time = std::numeric_limits<float>::max();
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float best_gb_per_sec = 0;
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// profile device operation instances
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std::cout << "Run all instances and do timing" << std::endl;
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for(int i = 0; i < op_ptrs.size(); ++i)
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{
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auto& op_ptr = op_ptrs[i];
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auto argument_ptr = op_ptr->MakeArgumentPointer({M, N}, // lengths
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{Stride, 1}, // xStrides
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{1}, // gammaStrides
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{1}, // betaStrides
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{Stride, 1}, // yStrides
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{1}, // reduceDims
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1e-4,
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x_device_buf.GetDeviceBuffer(),
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gamma_device_buf.GetDeviceBuffer(),
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beta_device_buf.GetDeviceBuffer(),
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y_device_buf.GetDeviceBuffer(),
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PassThrough{});
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auto invoker_ptr = op_ptr->MakeInvokerPointer();
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std::string op_name = op_ptr->GetTypeString();
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if(op_ptr->IsSupportedArgument(argument_ptr.get()))
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{
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float ave_time = invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, true});
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std::size_t num_byte = sizeof(XDataType) * M * N + sizeof(GammaDataType) * N +
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sizeof(BetaDataType) * N + sizeof(YDataType) * M * N;
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float gb_per_sec = num_byte / 1.E6 / ave_time;
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std::cout << "Perf: " << std::setw(10) << ave_time << " ms, " << gb_per_sec << " GB/s, "
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<< op_name << std::endl;
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if(ave_time < best_ave_time)
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{
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found = true;
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best_op_id = i;
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best_op_name = op_name;
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best_ave_time = ave_time;
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best_gb_per_sec = gb_per_sec;
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}
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}
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else
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{
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std::cout << op_name << " does not support this problem" << std::endl;
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}
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}
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std::cout << "Best Perf: " << best_ave_time << " ms, " << best_gb_per_sec << " GB/s, "
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<< best_op_name << std::endl;
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// run the best intance
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{
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auto& op_ptr = op_ptrs[best_op_id];
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std::cout << "Run the best instance without timing: " << op_ptr->GetTypeString()
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<< std::endl;
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auto argument_ptr = op_ptr->MakeArgumentPointer({M, N}, // lengths
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{Stride, 1}, // xStrides
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{1}, // gammaStrides
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{1}, // betaStrides
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{Stride, 1}, // yStrides
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{1}, // reduceDims
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1e-4,
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x_device_buf.GetDeviceBuffer(),
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gamma_device_buf.GetDeviceBuffer(),
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beta_device_buf.GetDeviceBuffer(),
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y_device_buf.GetDeviceBuffer(),
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PassThrough{});
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auto invoker_ptr = op_ptr->MakeInvokerPointer();
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if(op_ptr->IsSupportedArgument(argument_ptr.get()))
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{
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invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, false});
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}
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std::cout << "Done" << std::endl;
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}
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return 0;
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}
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@@ -10,3 +10,4 @@ add_subdirectory(01_gemm)
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add_subdirectory(02_gemm_add_add_fastgelu)
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add_subdirectory(03_gemm_layernorm)
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add_subdirectory(04_contraction)
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add_subdirectory(05_layernorm)
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