Files
composable_kernel/example/42_groupnorm/run_groupnorm_example.inc
2023-05-31 18:46:57 -05:00

114 lines
4.1 KiB
C++

// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
int run_groupnorm_example(int argc, char* argv[])
{
ck::index_t N = 32;
ck::index_t H = 16;
ck::index_t W = 16;
ck::index_t G = 64;
ck::index_t C = 128;
if(argc == 1)
{
// use default case
}
else if(argc == 6)
{
N = std::stoi(argv[1]);
H = std::stoi(argv[2]);
W = std::stoi(argv[3]);
G = std::stoi(argv[4]);
C = std::stoi(argv[5]);
}
else
{
std::cerr << "arg1 to 5: N, H, W, G, C" << std::endl;
return 1;
}
Tensor<XDataType> x({N, H, W, G, C});
Tensor<YDataType> y({N, H, W, G, C});
Tensor<GammaDataType> gamma({G, C});
Tensor<BetaDataType> beta({G, C});
ck::utils::FillUniformDistribution<XDataType>{0.f, 1.f}(x);
ck::utils::FillUniformDistribution<GammaDataType>{0.f, 1.f}(gamma);
ck::utils::FillUniformDistribution<BetaDataType>{0.f, 1.f}(beta);
DeviceMem x_dev(sizeof(XDataType) * x.mDesc.GetElementSpaceSize());
DeviceMem gamma_dev(sizeof(GammaDataType) * gamma.mDesc.GetElementSpaceSize());
DeviceMem beta_dev(sizeof(BetaDataType) * beta.mDesc.GetElementSpaceSize());
DeviceMem y_dev(sizeof(YDataType) * y.mDesc.GetElementSpaceSize());
x_dev.ToDevice(x.mData.data());
gamma_dev.ToDevice(gamma.mData.data());
beta_dev.ToDevice(beta.mData.data());
const auto y_element_op = YElementOp{};
auto device_instance = DeviceInstance{};
auto argument_ptr = device_instance.MakeArgumentPointer(
{N, H, W, G, C},
std::vector<ck::index_t>{x.mDesc.GetStrides().begin(), x.mDesc.GetStrides().end()},
{0, 0, 0, C, 1},
{0, 0, 0, C, 1},
std::vector<ck::index_t>{y.mDesc.GetStrides().begin(), y.mDesc.GetStrides().end()},
{1, 2, 4}, // reduction dimension: [H, W, C]
1e-6,
x_dev.GetDeviceBuffer(),
gamma_dev.GetDeviceBuffer(),
beta_dev.GetDeviceBuffer(),
y_dev.GetDeviceBuffer(),
nullptr,
nullptr,
y_element_op);
if(!device_instance.IsSupportedArgument(argument_ptr.get()))
{
std::cout << "The runtime parameters are not supported" << std::endl;
return 1;
};
size_t workspace_sz = device_instance.GetWorkSpaceSize(argument_ptr.get());
DeviceMem workspace_dev(workspace_sz);
device_instance.SetWorkSpacePointer(argument_ptr.get(), workspace_dev.GetDeviceBuffer());
auto invoker_ptr = device_instance.MakeInvokerPointer();
float ave_time = invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, true, true});
std::size_t num_btype = sizeof(XDataType) * N * H * W * G * C +
sizeof(YDataType) * N * H * W * G * C + sizeof(GammaDataType) * G * C +
sizeof(BetaDataType) * G * C;
float gb_per_sec = num_btype / 1.E6 / ave_time;
std::cout << "Perf: " << ave_time << " ms, " << gb_per_sec << " GB/s, "
<< device_instance.GetTypeString() << std::endl;
bool pass = true;
{
Tensor<YDataType> host_y({N, H, W, G, C});
using ReferenceInstance = ck::tensor_operation::host::ReferenceGroupnorm<XDataType,
GammaDataType,
BetaDataType,
YDataType,
ComputeDataType,
YElementOp>;
ReferenceInstance ref;
auto ref_argument =
ref.MakeArgument(x, gamma, beta, host_y, y_element_op, {N, H, W, G, C}, 1e-6);
auto ref_invoker = ref.MakeInvoker();
ref_invoker.Run(ref_argument);
y_dev.FromDevice(y.mData.data());
pass &= ck::utils::check_err(y, host_y, "Error: Incorrect results", 1e-3, 1e-3);
}
return (pass ? 0 : 1);
}