Skip to content

GitLab

"docs/vscode:/vscode.git/clone" did not exist on "8ba6e3b4c7270b3f34f70ecda70d4739acb11ca0"
Unverified Commit bf98b476 authored by Bartłomiej Kocot's avatar Bartłomiej Kocot Committed by GitHub
Browse files

Add bilinear conv fwd and bwd data instances (#1164)

parent a78be3f6
Hide whitespace changes
Inline Side-by-side
Showing with 730 additions and 149 deletions
example/62_conv_fwd_activ/convnd_fwd_xdl_relu_fp16.cpp deleted 100644 → 0
View file @ a78be3f6
// SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
#include "convnd_fwd_activ_common.hpp"
using OutElementOp = ck::tensor_operation::element_wise::Relu;
using DeviceGroupedConvNDFwdActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
#include "run_convnd_fwd_activ_example.inc"
int main(int argc, char* argv[]) { return !run_convnd_fwd_example(argc, argv); }
example/62_conv_fwd_activ/convnd_fwd_xdl_sigmoid_fp16.cpp deleted 100644 → 0
View file @ a78be3f6
// SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
#include "convnd_fwd_activ_common.hpp"
using OutElementOp = ck::tensor_operation::element_wise::Sigmoid;
using DeviceGroupedConvNDFwdActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
#include "run_convnd_fwd_activ_example.inc"
int main(int argc, char* argv[]) { return !run_convnd_fwd_example(argc, argv); }
example/62_conv_fwd_activ/convnd_fwd_xdl_softrelu_fp16.cpp deleted 100644 → 0
View file @ a78be3f6
// SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
#include "convnd_fwd_activ_common.hpp"
using OutElementOp = ck::tensor_operation::element_wise::SoftRelu;
using DeviceGroupedConvNDFwdActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
#include "run_convnd_fwd_activ_example.inc"
int main(int argc, char* argv[]) { return !run_convnd_fwd_example(argc, argv); }
example/62_conv_fwd_activ/convnd_fwd_xdl_tanh_fp16.cpp deleted 100644 → 0
View file @ a78be3f6
// SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
#include "convnd_fwd_activ_common.hpp"
using OutElementOp = ck::tensor_operation::element_wise::TanH;
using DeviceGroupedConvNDFwdActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
#include "run_convnd_fwd_activ_example.inc"
int main(int argc, char* argv[]) { return !run_convnd_fwd_example(argc, argv); }
example/62_convnd_activ/CMakeLists.txt 0 → 100644
View file @ bf98b476
add_subdirectory(binary)
add_subdirectory(multi_AB)
add_subdirectory(unary)
list(APPEND gpu_list gfx908 gfx90a gfx940 gfx941 gfx942)
set(target 0)
foreach(gpu IN LISTS GPU_TARGETS)
if(gpu IN_LIST gpu_list AND target EQUAL 0)
add_custom_target(example_convnd_activ_xdl)
# ScaleAdd ScaleAdd Relu
add_example_executable(example_convnd_fwd_xdl_scaleadd_scaleadd_relu_fp16 convnd_fwd_xdl_scaleadd_scaleadd_relu_fp16.cpp)
add_example_dependencies(example_convnd_activ_xdl example_convnd_fwd_xdl_scaleadd_scaleadd_relu_fp16)
add_example_executable(example_convnd_fwd_xdl_scaleadd_scaleadd_relu_bcasted_bias_fp16 convnd_fwd_xdl_scaleadd_scaleadd_relu_bcasted_bias_fp16.cpp)
add_example_dependencies(example_convnd_activ_xdl example_convnd_fwd_xdl_scaleadd_scaleadd_relu_bcasted_bias_fp16)
set(target 1)
endif()
endforeach()
example/62_convnd_activ/binary/CMakeLists.txt 0 → 100644
View file @ bf98b476
list(APPEND gpu_list gfx908 gfx90a gfx940 gfx941 gfx942)
set(target 0)
foreach(gpu IN LISTS GPU_TARGETS)
if(gpu IN_LIST gpu_list AND target EQUAL 0)
add_custom_target(example_convnd_activ_binary_xdl)
# Bilinear residual
add_example_executable(example_convnd_fwd_xdl_bilinear_residual_fp16 convnd_fwd_xdl_bilinear_residual_fp16.cpp)
add_example_dependencies(example_convnd_activ_binary_xdl example_convnd_fwd_xdl_bilinear_residual_fp16)
add_example_executable(example_convnd_bwd_data_xdl_bilinear_residual_fp16 convnd_bwd_data_xdl_bilinear_residual_fp16.cpp)
add_example_dependencies(example_convnd_activ_binary_xdl example_convnd_bwd_data_xdl_bilinear_residual_fp16)
set(target 1)
endif()
endforeach()
example/62_convnd_activ/binary/convnd_bwd_data_xdl_bilinear_residual_fp16.cpp 0 → 100644
View file @ bf98b476
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include <iostream>
#include <numeric>
#include <type_traits>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_bwd_data_multiple_d_xdl_cshuffle_v1.hpp"
#include "ck/tensor_operation/gpu/device/convolution_backward_data_specialization.hpp"
#include "ck/library/utility/algorithm.hpp"
#include "ck/library/utility/check_err.hpp"
#include "ck/library/utility/device_memory.hpp"
#include "ck/library/utility/host_tensor.hpp"
#include "ck/library/utility/host_tensor_generator.hpp"
#include "ck/library/utility/convolution_parameter.hpp"
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
#include "ck/library/reference_tensor_operation/cpu/reference_conv_bwd_data.hpp"
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
constexpr ck::index_t NDimSpatial = 3;
using InDataType = ck::half_t;
using WeiDataType = ck::half_t;
using AccDataType = float;
using CShuffleDataType = ck::half_t;
using OutDataType = ck::half_t;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using InLayout = ck::tensor_layout::convolution::GNDHWC;
using WeiLayout = ck::tensor_layout::convolution::GKZYXC;
using OutLayout = ck::tensor_layout::convolution::GNDHWK;
using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
using InElementOp = ck::tensor_operation::element_wise::Bilinear;
static constexpr auto ConvSpec =
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization::Default;
template <typename OutElementOp>
using DeviceGroupedConvNDBwdDataInstance =
ck::tensor_operation::device::DeviceGroupedConvBwdDataMultipleD_Xdl_CShuffle_v1<
NDimSpatial,
OutLayout,
WeiLayout,
ck::Tuple<InLayout>,
InLayout,
OutDataType,
WeiDataType,
AccDataType,
CShuffleDataType,
ck::Tuple<InDataType>,
InDataType,
OutElementOp,
WeiElementOp,
InElementOp,
ConvSpec, // ConvForwardSpecialization
true,
true,
1, //
256, // BlockSize
128, // MPerBlock
256, // NPerBlock
32, // KPerBlock
8, // AK1
2, // BK1
32, // MPerXdl
32, // NPerXdl
2, // MXdlPerWave
4, // NXdlPerWave
S<4, 64, 1>, // ABlockTransferThreadClusterLengths_AK0_M_AK1
S<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
S<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_AK1
1, // ABlockLdsExtraM
S<4, 64, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
S<0, 2, 1>, // BBlockTransferThreadClusterArrangeOrder
S<0, 2, 1>, // BBlockTransferSrcAccessOrder
1, // BBlockTransferSrcVectorDim
4, // BBlockTransferSrcScalarPerVector
2, // BBlockTransferDstScalarPerVector_BK1
0, // BBlockLdsExtraN
1,
1,
S<1, 32, 1, 8>,
8>;
using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDBwdDataInstance<OutElementOp>;
namespace {
// Use custom implementation to pass two more tensors for post op
template <ck::index_t NDimSpatial,
typename InDataType,
typename WeiDataType,
typename OutDataType,
typename InElementOp,
typename WeiElementOp,
typename OutElementOp,
typename DeviceConvNDInstance>
bool run_grouped_conv(bool do_verification,
int init_method,
bool time_kernel,
const ck::utils::conv::ConvParam& conv_param,
const HostTensorDescriptor& in_g_n_c_wis_desc,
const HostTensorDescriptor& wei_g_k_c_xs_desc,
const HostTensorDescriptor& out_g_n_k_wos_desc,
const InElementOp& in_element_op,
const WeiElementOp& wei_element_op,
const OutElementOp& out_element_op)
{
constexpr ck::index_t NumDs = 1;
Tensor<OutDataType> out(out_g_n_k_wos_desc);
Tensor<WeiDataType> wei(wei_g_k_c_xs_desc);
Tensor<InDataType> in_host(in_g_n_c_wis_desc);
std::cout << "out: " << out.mDesc << std::endl;
std::cout << "wei: " << wei.mDesc << std::endl;
std::cout << "in: " << in_host.mDesc << std::endl;
switch(init_method)
{
case 0: break;
case 1:
out.GenerateTensorValue(GeneratorTensor_2<OutDataType>{-5, 5});
wei.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-5, 5});
in_host.GenerateTensorValue(GeneratorTensor_2<InDataType>{-5, 5});
break;
default:
out.GenerateTensorValue(GeneratorTensor_3<OutDataType>{0.0, 1.0});
wei.GenerateTensorValue(GeneratorTensor_3<WeiDataType>{-0.5, 0.5});
in_host.GenerateTensorValue(GeneratorTensor_3<InDataType>{0.0, 1.0});
}
// Initialize based on out_host
Tensor<InDataType> in_device(in_host);
DeviceMem out_device_buf(sizeof(OutDataType) * out.mDesc.GetElementSpaceSize());
DeviceMem wei_device_buf(sizeof(WeiDataType) * wei.mDesc.GetElementSpaceSize());
DeviceMem in_device_buf(sizeof(InDataType) * in_device.mDesc.GetElementSpaceSize());
out_device_buf.ToDevice(out.mData.data());
wei_device_buf.ToDevice(wei.mData.data());
in_device_buf.ToDevice(in_device.mData.data());
std::array<ck::index_t, NDimSpatial + 3> a_g_n_k_wos_lengths{};
std::array<ck::index_t, NDimSpatial + 3> a_g_n_k_wos_strides{};
std::array<ck::index_t, NDimSpatial + 3> b_g_k_c_xs_lengths{};
std::array<ck::index_t, NDimSpatial + 3> b_g_k_c_xs_strides{};
std::array<ck::index_t, NDimSpatial + 3> e_g_n_c_wis_lengths{};
std::array<ck::index_t, NDimSpatial + 3> e_g_n_c_wis_strides{};
std::array<ck::index_t, NDimSpatial> conv_filter_strides{};
std::array<ck::index_t, NDimSpatial> conv_filter_dilations{};
std::array<ck::index_t, NDimSpatial> input_left_pads{};
std::array<ck::index_t, NDimSpatial> input_right_pads{};
auto copy = [](auto& x, auto& y) { ck::ranges::copy(x, y.begin()); };
copy(out_g_n_k_wos_desc.GetLengths(), a_g_n_k_wos_lengths);
copy(out_g_n_k_wos_desc.GetStrides(), a_g_n_k_wos_strides);
copy(wei_g_k_c_xs_desc.GetLengths(), b_g_k_c_xs_lengths);
copy(wei_g_k_c_xs_desc.GetStrides(), b_g_k_c_xs_strides);
copy(in_g_n_c_wis_desc.GetLengths(), e_g_n_c_wis_lengths);
copy(in_g_n_c_wis_desc.GetStrides(), e_g_n_c_wis_strides);
copy(conv_param.conv_filter_strides_, conv_filter_strides);
copy(conv_param.conv_filter_dilations_, conv_filter_dilations);
copy(conv_param.input_left_pads_, input_left_pads);
copy(conv_param.input_right_pads_, input_right_pads);
// Use output as D
const std::array<const void*, NumDs> ds = {in_device_buf.GetDeviceBuffer()};
auto conv = DeviceConvNDInstance{};
auto invoker = conv.MakeInvoker();
auto argument = conv.MakeArgument(
out_device_buf.GetDeviceBuffer(),
wei_device_buf.GetDeviceBuffer(),
ds,
in_device_buf.GetDeviceBuffer(),
a_g_n_k_wos_lengths,
a_g_n_k_wos_strides,
b_g_k_c_xs_lengths,
b_g_k_c_xs_strides,
std::array<std::array<ck::index_t, NDimSpatial + 3>, NumDs>{e_g_n_c_wis_lengths},
std::array<std::array<ck::index_t, NDimSpatial + 3>, NumDs>{e_g_n_c_wis_strides},
e_g_n_c_wis_lengths,
e_g_n_c_wis_strides,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
input_right_pads,
out_element_op,
wei_element_op,
in_element_op);
if(!conv.IsSupportedArgument(argument))
{
throw std::runtime_error("The device op with the specified compilation parameters does "
"not support this convolution problem.");
}
float avg_time = invoker.Run(argument, StreamConfig{nullptr, time_kernel});
std::size_t flop =
conv_param.GetFlops() + 3 * conv_param.GetInputByte<InDataType>() / sizeof(InDataType);
std::size_t num_btype = conv_param.GetByte<InDataType, WeiDataType, OutDataType>() +
conv_param.GetOutputByte<InDataType>();
float tflops = static_cast<float>(flop) / 1.E9 / avg_time;
float gb_per_sec = num_btype / 1.E6 / avg_time;
std::cout << "Perf: " << avg_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s, "
<< conv.GetTypeString() << std::endl;
if(do_verification)
{
std::array<Tensor<OutDataType>, NumDs> d_tensors = {in_host};
auto ref_conv =
ck::tensor_operation::host::ReferenceConvBwdData<NDimSpatial,
InDataType,
WeiDataType,
OutDataType,
InElementOp,
WeiElementOp,
OutElementOp,
0, /*Num A Elementwise Tensors*/
0, /*Num B Elementwise Tensors*/
NumDs>();
auto ref_invoker = ref_conv.MakeInvoker();
auto ref_argument = ref_conv.MakeArgument(in_host,
wei,
out,
conv_param.conv_filter_strides_,
conv_param.conv_filter_dilations_,
conv_param.input_left_pads_,
conv_param.input_right_pads_,
in_element_op,
wei_element_op,
out_element_op,
{},
{},
d_tensors);
ref_invoker.Run(ref_argument);
in_device_buf.FromDevice(in_device.mData.data());
return ck::utils::check_err(in_device.mData, in_host.mData);
}
return true;
}
} // namespace
#include "../run_convnd_activ_example.inc"
int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }
example/62_convnd_activ/binary/convnd_fwd_xdl_bilinear_residual_fp16.cpp 0 → 100644
View file @ bf98b476
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include <iostream>
#include <numeric>
#include <type_traits>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_fwd_multiple_abd_xdl_cshuffle.hpp"
#include "ck/library/utility/algorithm.hpp"
#include "ck/library/utility/check_err.hpp"
#include "ck/library/utility/device_memory.hpp"
#include "ck/library/utility/host_tensor.hpp"
#include "ck/library/utility/host_tensor_generator.hpp"
#include "ck/library/utility/convolution_parameter.hpp"
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
#include "ck/library/reference_tensor_operation/cpu/reference_conv_fwd.hpp"
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
constexpr ck::index_t NDimSpatial = 3;
using InDataType = ck::half_t;
using WeiDataType = ck::half_t;
using AccDataType = float;
using CShuffleDataType = ck::half_t;
using OutDataType = ck::half_t;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using InLayout = ck::tensor_layout::convolution::GNDHWC;
using WeiLayout = ck::tensor_layout::convolution::GKZYXC;
using OutLayout = ck::tensor_layout::convolution::GNDHWK;
using InElementOp = ck::tensor_operation::element_wise::PassThrough;
using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
using OutElementOp = ck::tensor_operation::element_wise::Bilinear;
static constexpr auto ConvSpec =
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
template <typename OutElementOp>
using DeviceGroupedConvNDFwdInstance =
ck::tensor_operation::device::DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<
NDimSpatial,
InLayout,
WeiLayout,
ck::Tuple<OutLayout>,
OutLayout,
InDataType,
WeiDataType,
AccDataType,
CShuffleDataType,
ck::Tuple<OutDataType>,
OutDataType,
InElementOp,
WeiElementOp,
OutElementOp,
ConvSpec, // ConvForwardSpecialization
GemmSpec, // GemmSpecialization
1, //
256, // BlockSize
128, // MPerBlock
256, // NPerBlock
32, // KPerBlock
8, // AK1
8, // BK1
32, // MPerXdl
32, // NPerXdl
2, // MXdlPerWave
4, // NXdlPerWave
S<4, 64, 1>, // ABlockTransferThreadClusterLengths_AK0_M_AK1
S<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
S<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_AK1
1, // ABlockLdsExtraM
S<4, 64, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
S<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder
S<1, 0, 2>, // BBlockTransferSrcAccessOrder
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_BK1
1, // BBlockLdsExtraN
1,
1,
S<1, 32, 1, 8>,
8>;
using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
namespace {
// Use custom implementation to pass two more tensors for post op
template <ck::index_t NDimSpatial,
typename InDataType,
typename WeiDataType,
typename OutDataType,
typename InElementOp,
typename WeiElementOp,
typename OutElementOp,
typename DeviceConvNDFwdInstance>
bool run_grouped_conv(bool do_verification,
int init_method,
bool time_kernel,
const ck::utils::conv::ConvParam& conv_param,
const HostTensorDescriptor& in_g_n_c_wis_desc,
const HostTensorDescriptor& wei_g_k_c_xs_desc,
const HostTensorDescriptor& out_g_n_k_wos_desc,
const InElementOp& in_element_op,
const WeiElementOp& wei_element_op,
const OutElementOp& out_element_op)
{
constexpr ck::index_t NumDs = 1;
Tensor<InDataType> in(in_g_n_c_wis_desc);
Tensor<WeiDataType> wei(wei_g_k_c_xs_desc);
Tensor<OutDataType> out_host(out_g_n_k_wos_desc);
std::cout << "in: " << in.mDesc << std::endl;
std::cout << "wei: " << wei.mDesc << std::endl;
std::cout << "out: " << out_host.mDesc << std::endl;
switch(init_method)
{
case 0: break;
case 1:
in.GenerateTensorValue(GeneratorTensor_2<InDataType>{-2, 2});
wei.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-2, 2});
out_host.GenerateTensorValue(GeneratorTensor_2<OutDataType>{-2, 2});
break;
default:
in.GenerateTensorValue(GeneratorTensor_3<InDataType>{-1.0, 1.0});
wei.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-2, 2});
out_host.GenerateTensorValue(GeneratorTensor_3<OutDataType>{-0.05, 0.05});
}
// Initialize based on out_host
Tensor<OutDataType> out_device(out_host);
DeviceMem in_device_buf(sizeof(InDataType) * in.mDesc.GetElementSpaceSize());
DeviceMem wei_device_buf(sizeof(WeiDataType) * wei.mDesc.GetElementSpaceSize());
DeviceMem out_device_buf(sizeof(OutDataType) * out_device.mDesc.GetElementSpaceSize());
in_device_buf.ToDevice(in.mData.data());
wei_device_buf.ToDevice(wei.mData.data());
out_device_buf.ToDevice(out_device.mData.data());
std::array<ck::index_t, NDimSpatial + 3> a_g_n_c_wis_lengths{};
std::array<ck::index_t, NDimSpatial + 3> a_g_n_c_wis_strides{};
std::array<ck::index_t, NDimSpatial + 3> b_g_k_c_xs_lengths{};
std::array<ck::index_t, NDimSpatial + 3> b_g_k_c_xs_strides{};
std::array<ck::index_t, NDimSpatial + 3> e_g_n_k_wos_lengths{};
std::array<ck::index_t, NDimSpatial + 3> e_g_n_k_wos_strides{};
std::array<ck::index_t, NDimSpatial> conv_filter_strides{};
std::array<ck::index_t, NDimSpatial> conv_filter_dilations{};
std::array<ck::index_t, NDimSpatial> input_left_pads{};
std::array<ck::index_t, NDimSpatial> input_right_pads{};
auto copy = [](const auto& x, auto& y) { ck::ranges::copy(x, y.begin()); };
copy(in_g_n_c_wis_desc.GetLengths(), a_g_n_c_wis_lengths);
copy(in_g_n_c_wis_desc.GetStrides(), a_g_n_c_wis_strides);
copy(wei_g_k_c_xs_desc.GetLengths(), b_g_k_c_xs_lengths);
copy(wei_g_k_c_xs_desc.GetStrides(), b_g_k_c_xs_strides);
copy(out_g_n_k_wos_desc.GetLengths(), e_g_n_k_wos_lengths);
copy(out_g_n_k_wos_desc.GetStrides(), e_g_n_k_wos_strides);
copy(conv_param.conv_filter_strides_, conv_filter_strides);
copy(conv_param.conv_filter_dilations_, conv_filter_dilations);
copy(conv_param.input_left_pads_, input_left_pads);
copy(conv_param.input_right_pads_, input_right_pads);
// Use output as D
const std::array<const void*, NumDs> ds = {out_device_buf.GetDeviceBuffer()};
auto conv = DeviceConvNDFwdInstance{};
auto invoker = conv.MakeInvoker();
auto argument = conv.MakeArgument(
in_device_buf.GetDeviceBuffer(),
wei_device_buf.GetDeviceBuffer(),
ds,
out_device_buf.GetDeviceBuffer(),
a_g_n_c_wis_lengths,
a_g_n_c_wis_strides,
b_g_k_c_xs_lengths,
b_g_k_c_xs_strides,
std::array<std::array<ck::index_t, NDimSpatial + 3>, NumDs>{e_g_n_k_wos_lengths},
std::array<std::array<ck::index_t, NDimSpatial + 3>, NumDs>{e_g_n_k_wos_strides},
e_g_n_k_wos_lengths,
e_g_n_k_wos_strides,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
input_right_pads,
in_element_op,
wei_element_op,
out_element_op);
if(!conv.IsSupportedArgument(argument))
{
throw std::runtime_error("The device op with the specified compilation parameters does "
"not support this convolution problem.");
}
float avg_time = invoker.Run(argument, StreamConfig{nullptr, time_kernel});
std::size_t flop =
conv_param.GetFlops() + 3 * conv_param.GetOutputByte<OutDataType>() / sizeof(OutDataType);
std::size_t num_btype = conv_param.GetByte<InDataType, WeiDataType, OutDataType>() +
conv_param.GetOutputByte<OutDataType>();
float tflops = static_cast<float>(flop) / 1.E9 / avg_time;
float gb_per_sec = num_btype / 1.E6 / avg_time;
std::cout << "Perf: " << avg_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s, "
<< conv.GetTypeString() << std::endl;
if(do_verification)
{
std::array<Tensor<OutDataType>, NumDs> d_tensors = {out_host};
auto ref_conv =
ck::tensor_operation::host::ReferenceConvFwd<NDimSpatial,
InDataType,
WeiDataType,
OutDataType,
InElementOp,
WeiElementOp,
OutElementOp,
0, /*Num A Elementwise Tensors*/
0, /*Num B Elementwise Tensors*/
NumDs>();
auto ref_invoker = ref_conv.MakeInvoker();
auto ref_argument = ref_conv.MakeArgument(in,
wei,
out_host,
conv_param.conv_filter_strides_,
conv_param.conv_filter_dilations_,
conv_param.input_left_pads_,
conv_param.input_right_pads_,
in_element_op,
wei_element_op,
out_element_op,
{},
{},
d_tensors);
ref_invoker.Run(ref_argument);
out_device_buf.FromDevice(out_device.mData.data());
return ck::utils::check_err(out_device, out_host, "Error: incorrect results!");
}
return true;
}
} // namespace
#include "../run_convnd_activ_example.inc"
int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }
example/62_conv_fwd_activ/convnd_fwd_xdl_scaleadd_scaleadd_relu_bcasted_bias_fp16.cpp → example/62_convnd_activ/convnd_fwd_xdl_scaleadd_scaleadd_relu_bcasted_bias_fp16.cpp
View file @ bf98b476
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
#include <algorithm> #include <algorithm>
#include <cstdlib> #include <cstdlib>
...@@ -97,7 +97,7 @@ using DeviceGroupedConvNDFwdInstance = ...@@ -97,7 +97,7 @@ using DeviceGroupedConvNDFwdInstance =
S<1, 32, 1, 8>, S<1, 32, 1, 8>,
8>; 8>;
using DeviceGroupedConvNDFwdActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>; using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
namespace { namespace {
// Use custom implementation to pass two more tensors for post op // Use custom implementation to pass two more tensors for post op
...@@ -109,16 +109,16 @@ template <ck::index_t NDimSpatial, ...@@ -109,16 +109,16 @@ template <ck::index_t NDimSpatial,
typename WeiElementOp, typename WeiElementOp,
typename OutElementOp, typename OutElementOp,
typename DeviceConvNDFwdInstance> typename DeviceConvNDFwdInstance>
bool run_grouped_conv_fwd(bool do_verification, bool run_grouped_conv(bool do_verification,
int init_method, int init_method,
bool time_kernel, bool time_kernel,
const ck::utils::conv::ConvParam& conv_param, const ck::utils::conv::ConvParam& conv_param,
const HostTensorDescriptor& in_g_n_c_wis_desc, const HostTensorDescriptor& in_g_n_c_wis_desc,
const HostTensorDescriptor& wei_g_k_c_xs_desc, const HostTensorDescriptor& wei_g_k_c_xs_desc,
const HostTensorDescriptor& out_g_n_k_wos_desc, const HostTensorDescriptor& out_g_n_k_wos_desc,
const InElementOp& in_element_op, const InElementOp& in_element_op,
const WeiElementOp& wei_element_op, const WeiElementOp& wei_element_op,
const OutElementOp& out_element_op) const OutElementOp& out_element_op)
{ {
constexpr ck::index_t NumDs = 2; constexpr ck::index_t NumDs = 2;
const ck::index_t G = out_g_n_k_wos_desc.GetLengths()[0]; const ck::index_t G = out_g_n_k_wos_desc.GetLengths()[0];
...@@ -289,6 +289,6 @@ bool run_grouped_conv_fwd(bool do_verification, ...@@ -289,6 +289,6 @@ bool run_grouped_conv_fwd(bool do_verification,
} // namespace } // namespace
#include "run_convnd_fwd_activ_example.inc" #include "run_convnd_activ_example.inc"
int main(int argc, char* argv[]) { return !run_convnd_fwd_example(argc, argv); } int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }
example/62_conv_fwd_activ/convnd_fwd_xdl_scaleadd_scaleadd_relu_fp16.cpp → example/62_convnd_activ/convnd_fwd_xdl_scaleadd_scaleadd_relu_fp16.cpp
View file @ bf98b476
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib> #include <cstdlib>
#include <iostream> #include <iostream>
...@@ -94,7 +94,7 @@ using DeviceGroupedConvNDFwdInstance = ...@@ -94,7 +94,7 @@ using DeviceGroupedConvNDFwdInstance =
S<1, 32, 1, 8>, S<1, 32, 1, 8>,
8>; 8>;
using DeviceGroupedConvNDFwdActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>; using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
namespace { namespace {
// Use custom implementation to pass two more tensors for post op // Use custom implementation to pass two more tensors for post op
...@@ -106,16 +106,16 @@ template <ck::index_t NDimSpatial, ...@@ -106,16 +106,16 @@ template <ck::index_t NDimSpatial,
typename WeiElementOp, typename WeiElementOp,
typename OutElementOp, typename OutElementOp,
typename DeviceConvNDFwdInstance> typename DeviceConvNDFwdInstance>
bool run_grouped_conv_fwd(bool do_verification, bool run_grouped_conv(bool do_verification,
int init_method, int init_method,
bool time_kernel, bool time_kernel,
const ck::utils::conv::ConvParam& conv_param, const ck::utils::conv::ConvParam& conv_param,
const HostTensorDescriptor& in_g_n_c_wis_desc, const HostTensorDescriptor& in_g_n_c_wis_desc,
const HostTensorDescriptor& wei_g_k_c_xs_desc, const HostTensorDescriptor& wei_g_k_c_xs_desc,
const HostTensorDescriptor& out_g_n_k_wos_desc, const HostTensorDescriptor& out_g_n_k_wos_desc,
const InElementOp& in_element_op, const InElementOp& in_element_op,
const WeiElementOp& wei_element_op, const WeiElementOp& wei_element_op,
const OutElementOp& out_element_op) const OutElementOp& out_element_op)
{ {
constexpr ck::index_t NumDs = 2; constexpr ck::index_t NumDs = 2;
Tensor<InDataType> in(in_g_n_c_wis_desc); Tensor<InDataType> in(in_g_n_c_wis_desc);
...@@ -265,6 +265,6 @@ bool run_grouped_conv_fwd(bool do_verification, ...@@ -265,6 +265,6 @@ bool run_grouped_conv_fwd(bool do_verification,
} // namespace } // namespace
#include "run_convnd_fwd_activ_example.inc" #include "run_convnd_activ_example.inc"
int main(int argc, char* argv[]) { return !run_convnd_fwd_example(argc, argv); } int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }
example/62_convnd_activ/multi_AB/CMakeLists.txt 0 → 100644
View file @ bf98b476
list(APPEND gpu_list gfx908 gfx90a gfx940 gfx941 gfx942)
set(target 0)
foreach(gpu IN LISTS GPU_TARGETS)
if(gpu IN_LIST gpu_list AND target EQUAL 0)
add_custom_target(example_convnd_activ_multi_ab_xdl)
# ScaleAdd on A and B
add_example_executable(example_conv_fwd_xdl_scaleadd_ab_fp16 conv_fwd_xdl_scaleadd_ab_fp16.cpp)
add_example_dependencies(example_convnd_activ_multi_ab_xdl example_conv_fwd_xdl_scaleadd_ab_fp16)
add_example_executable(example_conv_fwd_xdl_scaleadd_ab_fp32 conv_fwd_xdl_scaleadd_ab_fp32.cpp)
add_example_dependencies(example_convnd_activ_multi_ab_xdl example_conv_fwd_xdl_scaleadd_ab_fp32)
add_example_executable(example_conv_fwd_xdl_scaleadd_ab_bf16 conv_fwd_xdl_scaleadd_ab_bf16.cpp)
add_example_dependencies(example_convnd_activ_multi_ab_xdl example_conv_fwd_xdl_scaleadd_ab_bf16)
add_example_executable(example_conv_fwd_xdl_scaleadd_ab_int8 conv_fwd_xdl_scaleadd_ab_int8.cpp)
add_example_dependencies(example_convnd_activ_multi_ab_xdl example_conv_fwd_xdl_scaleadd_ab_int8)
set(target 1)
endif()
endforeach()
example/62_conv_fwd_activ/multi_AB/conv_fwd_xdl_scaleadd_ab_bf16.cpp → example/62_convnd_activ/multi_AB/conv_fwd_xdl_scaleadd_ab_bf16.cpp
View file @ bf98b476
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "convnd_fwd_activ_multi_ab_common.hpp" #include "convnd_fwd_activ_multi_ab_common.hpp"
...@@ -14,13 +14,13 @@ using BDataTypes = ck::Tuple<DataType, DataType>; ...@@ -14,13 +14,13 @@ using BDataTypes = ck::Tuple<DataType, DataType>;
using InElementOp = ck::tensor_operation::element_wise::ScaleAdd; using InElementOp = ck::tensor_operation::element_wise::ScaleAdd;
using WeiElementOp = ck::tensor_operation::element_wise::ScaleAdd; using WeiElementOp = ck::tensor_operation::element_wise::ScaleAdd;
using DeviceGroupedConvNDFwdActivInstance = DeviceGroupedConvNDMultiABFwdInstance<DataType, using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDMultiABFwdInstance<DataType,
AccDataType, AccDataType,
ADataTypes, ADataTypes,
BDataTypes, BDataTypes,
InElementOp, InElementOp,
WeiElementOp>; WeiElementOp>;
#include "../run_convnd_fwd_activ_example.inc" #include "../run_convnd_activ_example.inc"
int main(int argc, char* argv[]) { return !run_convnd_fwd_example(argc, argv); } int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }
example/62_conv_fwd_activ/multi_AB/conv_fwd_xdl_scaleadd_ab_fp16.cpp → example/62_convnd_activ/multi_AB/conv_fwd_xdl_scaleadd_ab_fp16.cpp
View file @ bf98b476
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "convnd_fwd_activ_multi_ab_common.hpp" #include "convnd_fwd_activ_multi_ab_common.hpp"
...@@ -14,13 +14,13 @@ using BDataTypes = ck::Tuple<DataType, DataType>; ...@@ -14,13 +14,13 @@ using BDataTypes = ck::Tuple<DataType, DataType>;
using InElementOp = ck::tensor_operation::element_wise::ScaleAdd; using InElementOp = ck::tensor_operation::element_wise::ScaleAdd;
using WeiElementOp = ck::tensor_operation::element_wise::ScaleAdd; using WeiElementOp = ck::tensor_operation::element_wise::ScaleAdd;
using DeviceGroupedConvNDFwdActivInstance = DeviceGroupedConvNDMultiABFwdInstance<DataType, using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDMultiABFwdInstance<DataType,
AccDataType, AccDataType,
ADataTypes, ADataTypes,
BDataTypes, BDataTypes,
InElementOp, InElementOp,
WeiElementOp>; WeiElementOp>;
#include "../run_convnd_fwd_activ_example.inc" #include "../run_convnd_activ_example.inc"
int main(int argc, char* argv[]) { return !run_convnd_fwd_example(argc, argv); } int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }
example/62_conv_fwd_activ/multi_AB/conv_fwd_xdl_scaleadd_ab_fp32.cpp → example/62_convnd_activ/multi_AB/conv_fwd_xdl_scaleadd_ab_fp32.cpp
View file @ bf98b476
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "convnd_fwd_activ_multi_ab_common.hpp" #include "convnd_fwd_activ_multi_ab_common.hpp"
...@@ -14,13 +14,13 @@ using BDataTypes = ck::Tuple<DataType, DataType>; ...@@ -14,13 +14,13 @@ using BDataTypes = ck::Tuple<DataType, DataType>;
using InElementOp = ck::tensor_operation::element_wise::ScaleAdd; using InElementOp = ck::tensor_operation::element_wise::ScaleAdd;
using WeiElementOp = ck::tensor_operation::element_wise::ScaleAdd; using WeiElementOp = ck::tensor_operation::element_wise::ScaleAdd;
using DeviceGroupedConvNDFwdActivInstance = DeviceGroupedConvNDMultiABFwdInstance<DataType, using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDMultiABFwdInstance<DataType,
AccDataType, AccDataType,
ADataTypes, ADataTypes,
BDataTypes, BDataTypes,
InElementOp, InElementOp,
WeiElementOp>; WeiElementOp>;
#include "../run_convnd_fwd_activ_example.inc" #include "../run_convnd_activ_example.inc"
int main(int argc, char* argv[]) { return !run_convnd_fwd_example(argc, argv); } int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }
example/62_conv_fwd_activ/multi_AB/conv_fwd_xdl_scaleadd_ab_int8.cpp → example/62_convnd_activ/multi_AB/conv_fwd_xdl_scaleadd_ab_int8.cpp
View file @ bf98b476
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "convnd_fwd_activ_multi_ab_common.hpp" #include "convnd_fwd_activ_multi_ab_common.hpp"
...@@ -14,13 +14,13 @@ using BDataTypes = ck::Tuple<DataType, DataType>; ...@@ -14,13 +14,13 @@ using BDataTypes = ck::Tuple<DataType, DataType>;
using InElementOp = ck::tensor_operation::element_wise::ScaleAdd; using InElementOp = ck::tensor_operation::element_wise::ScaleAdd;
using WeiElementOp = ck::tensor_operation::element_wise::ScaleAdd; using WeiElementOp = ck::tensor_operation::element_wise::ScaleAdd;
using DeviceGroupedConvNDFwdActivInstance = DeviceGroupedConvNDMultiABFwdInstance<DataType, using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDMultiABFwdInstance<DataType,
AccDataType, AccDataType,
ADataTypes, ADataTypes,
BDataTypes, BDataTypes,
InElementOp, InElementOp,
WeiElementOp>; WeiElementOp>;
#include "../run_convnd_fwd_activ_example.inc" #include "../run_convnd_activ_example.inc"
int main(int argc, char* argv[]) { return !run_convnd_fwd_example(argc, argv); } int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }
example/62_conv_fwd_activ/multi_AB/convnd_fwd_activ_multi_ab_common.hpp → example/62_convnd_activ/multi_AB/convnd_fwd_activ_multi_ab_common.hpp
View file @ bf98b476
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib> #include <cstdlib>
#include <iostream> #include <iostream>
...@@ -100,16 +100,16 @@ template <ck::index_t NDimSpatial, ...@@ -100,16 +100,16 @@ template <ck::index_t NDimSpatial,
typename WeiElementOp, typename WeiElementOp,
typename OutElementOp, typename OutElementOp,
typename DeviceConvNDFwdInstance> typename DeviceConvNDFwdInstance>
bool run_grouped_conv_fwd(bool do_verification, bool run_grouped_conv(bool do_verification,
int init_method, int init_method,
bool time_kernel, bool time_kernel,
const ck::utils::conv::ConvParam& conv_param, const ck::utils::conv::ConvParam& conv_param,
const HostTensorDescriptor& in_g_n_c_wis_desc, const HostTensorDescriptor& in_g_n_c_wis_desc,
const HostTensorDescriptor& wei_g_k_c_xs_desc, const HostTensorDescriptor& wei_g_k_c_xs_desc,
const HostTensorDescriptor& out_g_n_k_wos_desc, const HostTensorDescriptor& out_g_n_k_wos_desc,
const InElementOp& in_element_op, const InElementOp& in_element_op,
const WeiElementOp& wei_element_op, const WeiElementOp& wei_element_op,
const OutElementOp& out_element_op) const OutElementOp& out_element_op)
{ {
constexpr ck::index_t NumAs = 2; constexpr ck::index_t NumAs = 2;
constexpr ck::index_t NumBs = 2; constexpr ck::index_t NumBs = 2;
......
example/62_conv_fwd_activ/run_convnd_fwd_activ_example.inc → example/62_convnd_activ/run_convnd_activ_example.inc
View file @ bf98b476
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once #pragma once
...@@ -11,7 +11,7 @@ void print_helper_msg() ...@@ -11,7 +11,7 @@ void print_helper_msg()
<< ck::utils::conv::get_conv_param_parser_helper_msg() << std::endl; << ck::utils::conv::get_conv_param_parser_helper_msg() << std::endl;
} }
bool run_convnd_fwd_example(int argc, char* argv[]) bool run_convnd_example(int argc, char* argv[])
{ {
print_helper_msg(); print_helper_msg();
...@@ -63,23 +63,23 @@ bool run_convnd_fwd_example(int argc, char* argv[]) ...@@ -63,23 +63,23 @@ bool run_convnd_fwd_example(int argc, char* argv[])
ck::utils::conv::make_output_host_tensor_descriptor_g_n_k_wos_packed<OutLayout>( ck::utils::conv::make_output_host_tensor_descriptor_g_n_k_wos_packed<OutLayout>(
conv_param); conv_param);
return run_grouped_conv_fwd<NDimSpatial, return run_grouped_conv<NDimSpatial,
InDataType, InDataType,
WeiDataType, WeiDataType,
OutDataType, OutDataType,
InElementOp, InElementOp,
WeiElementOp, WeiElementOp,
OutElementOp, OutElementOp,
DeviceGroupedConvNDFwdActivInstance>(do_verification, DeviceGroupedConvNDActivInstance>(do_verification,
init_method, init_method,
time_kernel, time_kernel,
conv_param, conv_param,
in_g_n_c_wis_desc, in_g_n_c_wis_desc,
wei_g_k_c_xs_desc, wei_g_k_c_xs_desc,
out_g_n_k_wos_desc, out_g_n_k_wos_desc,
in_element_op, in_element_op,
wei_element_op, wei_element_op,
out_element_op); out_element_op);
}; };
if(conv_param.num_dim_spatial_ == 3) if(conv_param.num_dim_spatial_ == 3)
......
example/62_conv_fwd_activ/CMakeLists.txt → example/62_convnd_activ/unary/CMakeLists.txt
View file @ bf98b476
...@@ -2,48 +2,34 @@ list(APPEND gpu_list gfx908 gfx90a gfx940 gfx941 gfx942) ...@@ -2,48 +2,34 @@ list(APPEND gpu_list gfx908 gfx90a gfx940 gfx941 gfx942)
set(target 0) set(target 0)
foreach(gpu IN LISTS GPU_TARGETS) foreach(gpu IN LISTS GPU_TARGETS)
if(gpu IN_LIST gpu_list AND target EQUAL 0) if(gpu IN_LIST gpu_list AND target EQUAL 0)
add_custom_target(example_convnd_fwd_activ_xdl) add_custom_target(example_convnd_activ_unary_xdl)
# Sigmoid # Sigmoid
add_example_executable(example_convnd_fwd_xdl_sigmoid_fp16 convnd_fwd_xdl_sigmoid_fp16.cpp) add_example_executable(example_convnd_fwd_xdl_sigmoid_fp16 convnd_fwd_xdl_sigmoid_fp16.cpp)
add_example_dependencies(example_convnd_fwd_activ_xdl example_convnd_fwd_xdl_sigmoid_fp16) add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_sigmoid_fp16)
# Tanh # Tanh
add_example_executable(example_convnd_fwd_xdl_tanh_fp16 convnd_fwd_xdl_tanh_fp16.cpp) add_example_executable(example_convnd_fwd_xdl_tanh_fp16 convnd_fwd_xdl_tanh_fp16.cpp)
add_example_dependencies(example_convnd_fwd_activ_xdl example_convnd_fwd_xdl_tanh_fp16) add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_tanh_fp16)
# Relu # Relu
add_example_executable(example_convnd_fwd_xdl_relu_fp16 convnd_fwd_xdl_relu_fp16.cpp) add_example_executable(example_convnd_fwd_xdl_relu_fp16 convnd_fwd_xdl_relu_fp16.cpp)
add_example_dependencies(example_convnd_fwd_activ_xdl example_convnd_fwd_xdl_relu_fp16) add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_relu_fp16)
# SoftRelu # SoftRelu
add_example_executable(example_convnd_fwd_xdl_softrelu_fp16 convnd_fwd_xdl_softrelu_fp16.cpp) add_example_executable(example_convnd_fwd_xdl_softrelu_fp16 convnd_fwd_xdl_softrelu_fp16.cpp)
add_example_dependencies(example_convnd_fwd_activ_xdl example_convnd_fwd_xdl_softrelu_fp16) add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_softrelu_fp16)
# Abs # Abs
add_example_executable(example_convnd_fwd_xdl_abs_fp16 convnd_fwd_xdl_abs_fp16.cpp) add_example_executable(example_convnd_fwd_xdl_abs_fp16 convnd_fwd_xdl_abs_fp16.cpp)
add_example_dependencies(example_convnd_fwd_activ_xdl example_convnd_fwd_xdl_abs_fp16) add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_abs_fp16)
# Pow # Pow
add_example_executable(example_convnd_fwd_xdl_pow_fp16 convnd_fwd_xdl_pow_fp16.cpp) add_example_executable(example_convnd_fwd_xdl_pow_fp16 convnd_fwd_xdl_pow_fp16.cpp)
add_example_dependencies(example_convnd_fwd_activ_xdl example_convnd_fwd_xdl_pow_fp16) add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_pow_fp16)
# Clipped Relu # Clipped Relu
add_example_executable(example_convnd_fwd_xdl_clippedrelu_fp16 convnd_fwd_xdl_clippedrelu_fp16.cpp) add_example_executable(example_convnd_fwd_xdl_clippedrelu_fp16 convnd_fwd_xdl_clippedrelu_fp16.cpp)
add_example_dependencies(example_convnd_fwd_activ_xdl example_convnd_fwd_xdl_clippedrelu_fp16) add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_clippedrelu_fp16)
# Leaky Relu # Leaky Relu
add_example_executable(example_convnd_fwd_xdl_leakyrelu_fp16 convnd_fwd_xdl_leakyrelu_fp16.cpp) add_example_executable(example_convnd_fwd_xdl_leakyrelu_fp16 convnd_fwd_xdl_leakyrelu_fp16.cpp)
add_example_dependencies(example_convnd_fwd_activ_xdl example_convnd_fwd_xdl_leakyrelu_fp16) add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_leakyrelu_fp16)
# Elu # Elu
add_example_executable(example_convnd_fwd_xdl_elu_fp16 convnd_fwd_xdl_elu_fp16.cpp) add_example_executable(example_convnd_fwd_xdl_elu_fp16 convnd_fwd_xdl_elu_fp16.cpp)
add_example_dependencies(example_convnd_fwd_activ_xdl example_convnd_fwd_xdl_elu_fp16) add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_elu_fp16)
# ScaleAdd on A and B
add_example_executable(example_conv_fwd_xdl_scaleadd_ab_fp16 multi_AB/conv_fwd_xdl_scaleadd_ab_fp16.cpp)
add_example_dependencies(example_convnd_fwd_activ_xdl example_conv_fwd_xdl_scaleadd_ab_fp16)
add_example_executable(example_conv_fwd_xdl_scaleadd_ab_fp32 multi_AB/conv_fwd_xdl_scaleadd_ab_fp32.cpp)
add_example_dependencies(example_convnd_fwd_activ_xdl example_conv_fwd_xdl_scaleadd_ab_fp32)
add_example_executable(example_conv_fwd_xdl_scaleadd_ab_bf16 multi_AB/conv_fwd_xdl_scaleadd_ab_bf16.cpp)
add_example_dependencies(example_convnd_fwd_activ_xdl example_conv_fwd_xdl_scaleadd_ab_bf16)
add_example_executable(example_conv_fwd_xdl_scaleadd_ab_int8 multi_AB/conv_fwd_xdl_scaleadd_ab_int8.cpp)
add_example_dependencies(example_convnd_fwd_activ_xdl example_conv_fwd_xdl_scaleadd_ab_int8)
# ScaleAdd ScaleAdd Relu
add_example_executable(example_convnd_fwd_xdl_scaleadd_scaleadd_relu_fp16 convnd_fwd_xdl_scaleadd_scaleadd_relu_fp16.cpp)
add_example_dependencies(example_convnd_fwd_activ_xdl example_convnd_fwd_xdl_scaleadd_scaleadd_relu_fp16)
add_example_executable(example_convnd_fwd_xdl_scaleadd_scaleadd_relu_bcasted_bias_fp16 convnd_fwd_xdl_scaleadd_scaleadd_relu_bcasted_bias_fp16.cpp)
add_example_dependencies(example_convnd_fwd_activ_xdl example_convnd_fwd_xdl_scaleadd_scaleadd_relu_bcasted_bias_fp16)
set(target 1) set(target 1)
endif() endif()
endforeach() endforeach()
example/62_conv_fwd_activ/convnd_fwd_activ_common.hpp → example/62_convnd_activ/unary/convnd_fwd_activ_unary_common.hpp
View file @ bf98b476
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once #pragma once
...@@ -102,16 +102,16 @@ template <ck::index_t NDimSpatial, ...@@ -102,16 +102,16 @@ template <ck::index_t NDimSpatial,
typename WeiElementOp, typename WeiElementOp,
typename OutElementOp, typename OutElementOp,
typename DeviceConvNDFwdInstance> typename DeviceConvNDFwdInstance>
bool run_grouped_conv_fwd(bool do_verification, bool run_grouped_conv(bool do_verification,
int init_method, int init_method,
bool time_kernel, bool time_kernel,
const ck::utils::conv::ConvParam& conv_param, const ck::utils::conv::ConvParam& conv_param,
const HostTensorDescriptor& in_g_n_c_wis_desc, const HostTensorDescriptor& in_g_n_c_wis_desc,
const HostTensorDescriptor& wei_g_k_c_xs_desc, const HostTensorDescriptor& wei_g_k_c_xs_desc,
const HostTensorDescriptor& out_g_n_k_wos_desc, const HostTensorDescriptor& out_g_n_k_wos_desc,
const InElementOp& in_element_op, const InElementOp& in_element_op,
const WeiElementOp& wei_element_op, const WeiElementOp& wei_element_op,
const OutElementOp& out_element_op) const OutElementOp& out_element_op)
{ {
Tensor<InDataType> in(in_g_n_c_wis_desc); Tensor<InDataType> in(in_g_n_c_wis_desc);
Tensor<WeiDataType> wei(wei_g_k_c_xs_desc); Tensor<WeiDataType> wei(wei_g_k_c_xs_desc);
......
example/62_convnd_activ/unary/convnd_fwd_xdl_abs_fp16.cpp 0 → 100644
View file @ bf98b476
// SPDX-License-Identifier: MIT
// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "convnd_fwd_activ_unary_common.hpp"
using OutElementOp = ck::tensor_operation::element_wise::UnaryAbs;
using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
#include "../run_convnd_activ_example.inc"
int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment