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TheRock/rocm-libraries/projects/miopen/driver/dropout_driver.hpp
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Flatten subprojects into a single base monorepo
2026-09-02 16:34:47 -07:00

511 lines
17 KiB
C++

/*******************************************************************************
*
* MIT License
*
* Copyright (c) 2019 Advanced Micro Devices, Inc.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*
*******************************************************************************/
#ifndef GUARD_MIOPEN_DROPOUT_DRIVER_HPP
#define GUARD_MIOPEN_DROPOUT_DRIVER_HPP
#include "InputFlags.hpp"
#include "driver.hpp"
#include "dropout_gpu_emulator.hpp"
#include "tensor_driver.hpp"
#include "timer.hpp"
#include "util_driver.hpp"
#include "util_file.hpp"
#include <../test/verify.hpp>
#include <miopen/dropout.hpp>
#include <miopen/miopen.h>
#include <algorithm>
#include <array>
#include <cfloat>
#include <cstring>
#include <memory>
#include <numeric>
#include <sstream>
#include <vector>
template <typename Tgpu, typename Tref = Tgpu>
class DropoutDriver : public Driver
{
public:
DropoutDriver() : Driver()
{
miopenCreateTensorDescriptor(&inputTensor);
miopenCreateTensorDescriptor(&outputTensor);
miopenCreateDropoutDescriptor(&DropoutDesc);
reservespace_dev = nullptr;
data_type = std::is_same<Tgpu, float16>{} ? miopenHalf : miopenFloat;
}
int AddCmdLineArgs() override;
int ParseCmdLineArgs(int argc, char* argv[]) override;
InputFlags& GetInputFlags() override { return inflags; }
int GetandSetData() override;
std::vector<int> GetInputTensorLengthsFromCmdLine(std::string input_str);
int AllocateBuffersAndCopy() override;
int RunForwardGPU() override;
int RunForwardCPU();
int RunBackwardGPU() override;
int RunBackwardCPU();
int VerifyForward() override;
int VerifyBackward() override;
~DropoutDriver() override
{
miopenDestroyTensorDescriptor(inputTensor);
miopenDestroyTensorDescriptor(outputTensor);
miopenDestroyDropoutDescriptor(DropoutDesc);
}
private:
InputFlags inflags;
miopenTensorDescriptor_t inputTensor;
miopenTensorDescriptor_t outputTensor;
std::unique_ptr<GPUMem> in_dev;
std::unique_ptr<GPUMem> out_dev;
std::unique_ptr<GPUMem> dout_dev;
std::unique_ptr<GPUMem> din_dev;
std::unique_ptr<GPUMem> reservespace_dev;
std::unique_ptr<GPUMem> states_dev;
tensor<Tgpu> in;
tensor<Tgpu> out;
tensor<Tgpu> dout;
tensor<Tgpu> din;
tensor<Tref> outhost;
tensor<Tref> din_host;
std::vector<rocrand_state_xorwow> states_host;
std::vector<unsigned char> reservespace;
std::vector<unsigned char> reservespace_host;
miopenDropoutDescriptor_t DropoutDesc;
float dropout;
unsigned long long seed;
bool use_mask;
bool multithread;
};
template <typename Tgpu, typename Tref>
int DropoutDriver<Tgpu, Tref>::ParseCmdLineArgs(int argc, char* argv[])
{
inflags.Parse(argc, argv);
if(inflags.GetValueInt("time") == 1)
{
miopenEnableProfiling(GetHandle(), true);
}
return miopenStatusSuccess;
}
template <typename Tgpu, typename Tref>
int DropoutDriver<Tgpu, Tref>::GetandSetData()
{
std::vector<int> in_len = GetInputTensorLengthsFromCmdLine(inflags.GetValueStr("input_dim"));
SetTensorNd(inputTensor, in_len, data_type);
SetTensorNd(outputTensor, in_len, data_type);
dropout = static_cast<float>(inflags.GetValueDouble("dropout"));
use_mask = static_cast<bool>(inflags.GetValueInt("use_mask"));
multithread = (inflags.GetValueInt("mt") != 0);
auto seed_low = static_cast<unsigned long long>(std::max(inflags.GetValueInt("seed_low"), 0));
auto seed_high = static_cast<unsigned long long>(std::max(inflags.GetValueInt("seed_high"), 0));
seed = seed_high << 32 | seed_low;
return miopenStatusSuccess;
}
template <typename Tgpu, typename Tref>
int DropoutDriver<Tgpu, Tref>::AddCmdLineArgs()
{
inflags.AddInputFlag(
"forw", 'F', "0", "Direction, Forward = 1, Backward = 2 , Both = 0 (Default=0)", "int");
inflags.AddInputFlag(
"input_dim", 'd', "4", "Input dimension (Default=4, support up to 5D)", "vector");
inflags.AddInputFlag("dropout", 'p', "0.5", "Dropout rate (Default=0.5)", "float");
inflags.AddInputFlag(
"seed_low", 'l', "0", "Least significant 32 bits of seed (Default=0)", "int");
inflags.AddInputFlag(
"seed_high", 'm', "0", "Most significant 32 bits of seed (Default=0)", "int");
inflags.AddInputFlag("use_mask",
'e',
"0",
"Use existing mask in reservespace: Use 1, Not use 0 (Default=0)",
"int");
inflags.AddInputFlag(
"gen_file",
'f',
"0",
"Generate and write/overwrite PRNG skipahead files (1), No operation (0) (Default=0)",
"int");
inflags.AddInputFlag("iter", 'i', "1", "Number of Iterations (Default=1)", "int");
inflags.AddInputFlag("verify", 'V', "1", "Verify Dropout (Default=1)", "int");
inflags.AddInputFlag("time", 't', "0", "Time Each Layer (Default=0)", "int");
inflags.AddInputFlag(
"wall", 'w', "0", "Wall-clock Time Each Layer, Requires time == 1 (Default=0)", "int");
inflags.AddInputFlag("dump_output", 'o', "0", "Dumps the output buffers (Default=0)", "int");
inflags.AddInputFlag("mt", 'u', "0", "Use multithreaded version (Default=0)", "int");
return 0;
}
template <typename Tgpu, typename Tref>
std::vector<int> DropoutDriver<Tgpu, Tref>::GetInputTensorLengthsFromCmdLine(std::string input_str)
{
std::vector<int> in_lens;
std::stringstream ss(input_str);
int cont = 0;
int element;
while(ss >> element)
{
if(cont++ >= 5)
{
std::cout << "Only support up to 5D-tensor dropout" << std::endl;
break;
}
if(ss.peek() == ',' || ss.peek() == ' ')
{
ss.ignore();
}
in_lens.push_back(element);
}
return in_lens;
}
template <typename Tgpu, typename Tref>
int DropoutDriver<Tgpu, Tref>::AllocateBuffersAndCopy()
{
size_t in_sz = GetTensorSize(inputTensor);
size_t out_sz = GetTensorSize(outputTensor);
size_t reserveSpaceSizeInBytes = 0;
miopenDropoutGetReserveSpaceSize(inputTensor, &reserveSpaceSizeInBytes);
size_t reserveSpaceSize = reserveSpaceSizeInBytes / sizeof(unsigned char);
size_t statesSizeInBytes = 0;
miopenDropoutGetStatesSize(GetHandle(), &statesSizeInBytes);
size_t states_size = statesSizeInBytes / sizeof(rocrand_state_xorwow);
DEFINE_CONTEXT(ctx);
states_dev =
std::unique_ptr<GPUMem>(new GPUMem(ctx, states_size, sizeof(rocrand_state_xorwow)));
// if(inflags.GetValueInt("gen_file"))
// generate_skipahead_file();
miopenSetDropoutDescriptor(DropoutDesc,
GetHandle(),
dropout,
states_dev->GetMem(),
states_dev->GetSize(),
seed,
use_mask,
false,
MIOPEN_RNG_PSEUDO_XORWOW);
in_dev = std::unique_ptr<GPUMem>(new GPUMem(ctx, in_sz, sizeof(Tgpu)));
din_dev = std::unique_ptr<GPUMem>(new GPUMem(ctx, in_sz, sizeof(Tgpu)));
dout_dev = std::unique_ptr<GPUMem>(new GPUMem(ctx, out_sz, sizeof(Tgpu)));
out_dev = std::unique_ptr<GPUMem>(new GPUMem(ctx, out_sz, sizeof(Tgpu)));
reservespace_dev =
std::unique_ptr<GPUMem>(new GPUMem(ctx, reserveSpaceSize, sizeof(unsigned char)));
in = tensor<Tgpu>(miopen::deref(inputTensor).GetLengths(),
miopen::deref(inputTensor).GetStrides());
din = tensor<Tgpu>(miopen::deref(inputTensor).GetLengths(),
miopen::deref(inputTensor).GetStrides());
out = tensor<Tgpu>(miopen::deref(outputTensor).GetLengths(),
miopen::deref(outputTensor).GetStrides());
dout = tensor<Tgpu>(miopen::deref(outputTensor).GetLengths(),
miopen::deref(outputTensor).GetStrides());
outhost = tensor<Tref>(miopen::deref(outputTensor).GetLengths(),
miopen::deref(outputTensor).GetStrides());
din_host = tensor<Tref>(miopen::deref(inputTensor).GetLengths(),
miopen::deref(inputTensor).GetStrides());
reservespace = std::vector<unsigned char>(reserveSpaceSize, static_cast<unsigned char>(1));
reservespace_host = std::vector<unsigned char>(reserveSpaceSize, static_cast<unsigned char>(1));
states_host = std::vector<rocrand_state_xorwow>(states_size);
Tgpu Data_scale = static_cast<Tgpu>(0.01);
for(int i = 0; i < in_sz; i++)
{
in.data[i] = prng::gen_0_to_B(Data_scale);
}
for(int i = 0; i < out_sz; i++)
{
dout.data[i] = prng::gen_0_to_B(Data_scale);
}
if(inflags.GetValueInt("dump_output"))
{
dumpBufferToFile("dump_in.bin", in.data.data(), in_sz);
dumpBufferToFile("dump_dout.bin", dout.data.data(), out_sz);
}
status_t status;
status = in_dev->ToGPU(q, in.data.data());
status |= din_dev->ToGPU(q, din.data.data());
status |= out_dev->ToGPU(q, out.data.data());
status |= dout_dev->ToGPU(q, dout.data.data());
if(inflags.GetValueInt("use_mask") == 1)
{
for(int i = 0; i < reserveSpaceSize; i++)
{
reservespace[i] = static_cast<uint8_t>(prng::gen_canonical<float>() > dropout);
reservespace_host[i] = reservespace[i];
}
status |= reservespace_dev->ToGPU(q, reservespace.data());
}
if(status != STATUS_SUCCESS)
printf("Error copying data to GPU\n");
return miopenStatusSuccess;
}
template <typename Tgpu, typename Tref>
int DropoutDriver<Tgpu, Tref>::RunForwardGPU()
{
float kernel_total_time = 0.0;
float kernel_first_time = 0.0;
Timer t;
START_TIME
for(int i = 0; i < inflags.GetValueInt("iter"); i++)
{
miopenDropoutForward(GetHandle(),
DropoutDesc,
inputTensor,
inputTensor,
in_dev->GetMem(),
outputTensor,
out_dev->GetMem(),
reservespace_dev->GetMem(),
reservespace_dev->GetSize());
float time = 0.0;
miopenGetKernelTime(GetHandle(), &time);
kernel_total_time += time;
if(i == 0)
kernel_first_time = time;
}
if(inflags.GetValueInt("time") == 1)
{
STOP_TIME
if(WALL_CLOCK)
printf("Wall-clock Time Dropout Elapsed: %f ms\n",
t.gettime_ms() / inflags.GetValueInt("iter"));
int iter = inflags.GetValueInt("iter");
float kernel_average_time =
iter > 1 ? (kernel_total_time - kernel_first_time) / (iter - 1) : kernel_first_time;
printf("GPU Kernel Time Forward Dropout. Elapsed: %f ms (average)\n", kernel_average_time);
}
out_dev->FromGPU(GetStream(), out.data.data());
reservespace_dev->FromGPU(GetStream(), reservespace.data());
return miopenStatusSuccess;
}
template <typename Tgpu, typename Tref>
int DropoutDriver<Tgpu, Tref>::RunForwardCPU()
{
InitKernelStateEmulator(states_host, DropoutDesc);
RunDropoutForwardEmulator<Tgpu, Tref>(GetHandle(),
DropoutDesc,
inputTensor,
inputTensor,
in.data,
outputTensor,
outhost.data,
reservespace_host,
states_host);
if(inflags.GetValueInt("dump_output"))
{
dumpBufferToFile<Tref>("dump_fwd_out_cpu.bin", outhost.data.data(), outhost.data.size());
}
return miopenStatusSuccess;
}
template <typename Tgpu, typename Tref>
int DropoutDriver<Tgpu, Tref>::RunBackwardGPU()
{
float kernel_total_time = 0.0;
float kernel_first_time = 0.0;
Timer t;
START_TIME
for(int i = 0; i < inflags.GetValueInt("iter"); i++)
{
miopenDropoutBackward(GetHandle(),
DropoutDesc,
inputTensor,
outputTensor,
dout_dev->GetMem(),
inputTensor,
din_dev->GetMem(),
reservespace_dev->GetMem(),
reservespace_dev->GetSize());
float time = 0.0;
miopenGetKernelTime(GetHandle(), &time);
kernel_total_time += time;
if(i == 0)
kernel_first_time = time;
}
if(inflags.GetValueInt("time") == 1)
{
STOP_TIME
if(WALL_CLOCK)
printf("Wall-clock Time Backward Dropout Elapsed: %f ms\n",
t.gettime_ms() / inflags.GetValueInt("iter"));
int iter = inflags.GetValueInt("iter");
float kernel_average_time =
iter > 1 ? (kernel_total_time - kernel_first_time) / (iter - 1) : kernel_first_time;
printf("GPU Kernel Time Backward Dropout. Elapsed: %f ms (average)\n", kernel_average_time);
}
din_dev->FromGPU(GetStream(), din.data.data());
return miopenStatusSuccess;
}
template <typename Tgpu, typename Tref>
int DropoutDriver<Tgpu, Tref>::RunBackwardCPU()
{
const auto t1 = std::chrono::high_resolution_clock::now();
for(int i = 0, iter = inflags.GetValueInt("iter"); i < iter; ++i)
{
if(multithread)
{
RunDropoutBackwardEmulatorMT<Tgpu, Tref>(DropoutDesc,
outputTensor,
dout.data,
inputTensor,
din_host.data,
reservespace_host);
}
else
{
RunDropoutBackwardEmulator<Tgpu, Tref>(DropoutDesc,
outputTensor,
dout.data,
inputTensor,
din_host.data,
reservespace_host);
}
}
const auto t2 = std::chrono::high_resolution_clock::now();
if(inflags.GetValueInt("time") == 1)
{
using float_ms = std::chrono::duration<float, std::milli>;
int iter = inflags.GetValueInt("iter");
const auto dt = (iter > 1) ? float_ms(t2 - t1).count() / iter : float_ms(t2 - t1).count();
printf("CPU Time Backward Dropout. Elapsed: %f ms (average)\n", dt);
}
if(inflags.GetValueInt("dump_output"))
{
dumpBufferToFile<Tref>("dump_bwd_out_cpu.bin", din_host.data.data(), din_host.data.size());
}
return miopenStatusSuccess;
}
template <typename Tgpu, typename Tref>
int DropoutDriver<Tgpu, Tref>::VerifyForward()
{
RunForwardCPU();
auto error = miopen::rms_range(outhost.data, out.data);
const double tolerance = std::is_same<Tgpu, float16>{} ? 5e-4 : 1e-6;
if(!std::isfinite(error) || error > tolerance)
{
std::cout << "Forward Dropout FAILED: " << error << std::endl;
}
else
{
std::cout << "Forward Dropout Verifies on CPU and GPU (" << error << ')' << std::endl;
}
return miopenStatusSuccess;
}
template <typename Tgpu, typename Tref>
int DropoutDriver<Tgpu, Tref>::VerifyBackward()
{
RunBackwardCPU();
auto error = miopen::rms_range(din_host.data, din.data);
const double tolerance = std::is_same<Tgpu, float16>{} ? 5e-4 : 1e-6;
if(!std::isfinite(error) || error > tolerance)
{
std::cout << "Backward Dropout FAILED: " << error << std::endl;
}
else
{
std::cout << "Backward Dropout Verifies on CPU and GPU (" << error << ')' << std::endl;
}
return miopenStatusSuccess;
}
#endif // GUARD_MIOPEN_DROPOUT_DRIVER_HPP