Skip to content

GitLab

Commit 451aef90 authored by Rosty Geyyer's avatar Rosty Geyyer
Browse files

Add int4 example for convnd_fwd_bias_relu_add

parent 9efd033b
Show whitespace changes
Inline Side-by-side
Showing with 647 additions and 105 deletions
example/30_grouped_convnd_fwd_bias_relu_add/CMakeLists.txt
View file @ 451aef90
......@@ -9,3 +9,8 @@ target_link_libraries(example_grouped_convnd_fwd_bias_relu_add_xdl_bf16 PRIVATE
add_example_executable(example_grouped_convnd_fwd_bias_relu_add_xdl_int8 grouped_convnd_fwd_bias_relu_add_xdl_int8.cpp)
target_link_libraries(example_grouped_convnd_fwd_bias_relu_add_xdl_int8 PRIVATE utility)
if(USE_BITINT_EXTENSION_INT4)
add_example_executable(example_grouped_convnd_fwd_bias_relu_add_xdl_int4 grouped_convnd_fwd_bias_relu_add_xdl_int4.cpp)
target_link_libraries(example_grouped_convnd_fwd_bias_relu_add_xdl_int4 PRIVATE utility)
endif() # USE_BITINT_EXTENSION_INT4
\ No newline at end of file
example/30_grouped_convnd_fwd_bias_relu_add/grouped_convnd_fwd_bias_relu_add_common.hpp
View file @ 451aef90
......@@ -26,13 +26,16 @@ void print_helper_msg()
}
template <ck::index_t NDimSpatial,
typename InDataType,
typename WeiDataType,
typename InKernelDataType,
typename WeiKernelDataType,
typename CShuffleDataType,
typename OutDataType,
typename OutKernelDataType,
typename InElementOp,
typename WeiElementOp,
typename OutElementOp,
typename InUserDataType,
typename WeiUserDataType,
typename OutUserDataType,
typename DeviceConvNDFwdInstance>
int run_grouped_conv_fwd_bias_relu_add(bool do_verification,
int init_method,
......@@ -47,12 +50,12 @@ int run_grouped_conv_fwd_bias_relu_add(bool do_verification,
const WeiElementOp& wei_element_op,
const OutElementOp& out_element_op)
{
Tensor<InDataType> in(in_g_n_c_wis_desc);
Tensor<WeiDataType> wei(wei_g_k_c_xs_desc);
Tensor<OutDataType> bias(bias_g_n_k_wos_desc);
Tensor<OutDataType> residual(residual_g_n_k_wos_desc);
Tensor<OutDataType> out_host(out_g_n_k_wos_desc);
Tensor<OutDataType> out_device(out_g_n_k_wos_desc);
Tensor<InUserDataType> in(in_g_n_c_wis_desc);
Tensor<WeiUserDataType> wei(wei_g_k_c_xs_desc);
Tensor<OutUserDataType> bias(bias_g_n_k_wos_desc);
Tensor<OutUserDataType> residual(residual_g_n_k_wos_desc);
Tensor<OutUserDataType> out_host(out_g_n_k_wos_desc);
Tensor<OutUserDataType> out_device(out_g_n_k_wos_desc);
std::cout << "in: " << in.mDesc << std::endl;
std::cout << "wei: " << wei.mDesc << std::endl;
......@@ -64,21 +67,21 @@ int run_grouped_conv_fwd_bias_relu_add(bool do_verification,
{
case 0: break;
case 1:
in.GenerateTensorValue(GeneratorTensor_2<InDataType>{-5, 5});
wei.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-5, 5});
bias.GenerateTensorValue(GeneratorTensor_2<OutDataType>{-5, 5});
in.GenerateTensorValue(GeneratorTensor_2<InUserDataType>{-5, 5});
wei.GenerateTensorValue(GeneratorTensor_2<WeiUserDataType>{-5, 5});
bias.GenerateTensorValue(GeneratorTensor_2<OutUserDataType>{-5, 5});
break;
default:
in.GenerateTensorValue(GeneratorTensor_3<InDataType>{0.0, 1.0});
wei.GenerateTensorValue(GeneratorTensor_3<WeiDataType>{-0.5, 0.5});
bias.GenerateTensorValue(GeneratorTensor_3<OutDataType>{-0.5, 0.5});
in.GenerateTensorValue(GeneratorTensor_3<InUserDataType>{0.0, 1.0});
wei.GenerateTensorValue(GeneratorTensor_3<WeiUserDataType>{-0.5, 0.5});
bias.GenerateTensorValue(GeneratorTensor_3<OutUserDataType>{-0.5, 0.5});
}
DeviceMem in_device_buf(sizeof(InDataType) * in.mDesc.GetElementSpaceSize());
DeviceMem wei_device_buf(sizeof(WeiDataType) * wei.mDesc.GetElementSpaceSize());
DeviceMem bias_device_buf(sizeof(OutDataType) * bias.mDesc.GetElementSpaceSize());
DeviceMem residual_device_buf(sizeof(OutDataType) * residual.mDesc.GetElementSpaceSize());
DeviceMem out_device_buf(sizeof(OutDataType) * out_device.mDesc.GetElementSpaceSize());
DeviceMem in_device_buf(sizeof(InUserDataType) * in.mDesc.GetElementSpaceSize());
DeviceMem wei_device_buf(sizeof(WeiUserDataType) * wei.mDesc.GetElementSpaceSize());
DeviceMem bias_device_buf(sizeof(OutUserDataType) * bias.mDesc.GetElementSpaceSize());
DeviceMem residual_device_buf(sizeof(OutUserDataType) * residual.mDesc.GetElementSpaceSize());
DeviceMem out_device_buf(sizeof(OutUserDataType) * out_device.mDesc.GetElementSpaceSize());
in_device_buf.ToDevice(in.mData.data());
wei_device_buf.ToDevice(wei.mData.data());
......@@ -154,7 +157,7 @@ int run_grouped_conv_fwd_bias_relu_add(bool do_verification,
float avg_time = invoker.Run(argument, StreamConfig{nullptr, time_kernel});
std::size_t flop = conv_param.GetFlops();
std::size_t num_btype = conv_param.GetByte<InDataType, WeiDataType, OutDataType>();
std::size_t num_btype = conv_param.GetByte<InUserDataType, WeiUserDataType, OutUserDataType>();
float tflops = static_cast<float>(flop) / 1.E9 / avg_time;
float gb_per_sec = num_btype / 1.E6 / avg_time;
......@@ -168,8 +171,8 @@ int run_grouped_conv_fwd_bias_relu_add(bool do_verification,
Tensor<CShuffleDataType> c_host(out_g_n_k_wos_desc);
auto ref_conv = ck::tensor_operation::host::ReferenceConvFwd<NDimSpatial,
InDataType,
WeiDataType,
InUserDataType,
WeiUserDataType,
CShuffleDataType,
InElementOp,
WeiElementOp,
......
example/30_grouped_convnd_fwd_bias_relu_add/grouped_convnd_fwd_bias_relu_add_xdl_bf16.cpp
View file @ 451aef90
......@@ -7,13 +7,19 @@
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
using InDataType = ck::bhalf_t;
using WeiDataType = ck::bhalf_t;
// kernel data types
using InKernelDataType = ck::bhalf_t;
using WeiKernelDataType = ck::bhalf_t;
using AccDataType = float;
using CShuffleDataType = float;
using BiasDataType = ck::bhalf_t;
using ResidualDataType = ck::bhalf_t;
using OutDataType = ck::bhalf_t;
using BiasKernelDataType = ck::bhalf_t;
using ResidualKernelDataType = ck::bhalf_t;
using OutKernelDataType = ck::bhalf_t;
// tensor data types
using InUserDataType = InKernelDataType;
using WeiUserDataType = WeiKernelDataType;
using OutUserDataType = OutKernelDataType;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
......@@ -40,12 +46,12 @@ using DeviceGroupedConvNDFwdInstance =
WeiLayout,
ck::Tuple<BiasLayout, ResidualLayout>,
OutLayout,
InDataType,
WeiDataType,
InKernelDataType,
WeiKernelDataType,
AccDataType,
CShuffleDataType,
ck::Tuple<BiasDataType, ResidualDataType>,
OutDataType,
ck::Tuple<BiasKernelDataType, ResidualKernelDataType>,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
......@@ -181,13 +187,16 @@ int main(int argc, char* argv[])
});
return run_grouped_conv_fwd_bias_relu_add<1,
InDataType,
WeiDataType,
InKernelDataType,
WeiKernelDataType,
CShuffleDataType,
OutDataType,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
InUserDataType,
WeiUserDataType,
OutUserDataType,
DeviceGroupedConvNDFwdInstance<1,
InLayout,
WeiLayout,
......@@ -290,13 +299,16 @@ int main(int argc, char* argv[])
});
return run_grouped_conv_fwd_bias_relu_add<2,
InDataType,
WeiDataType,
InKernelDataType,
WeiKernelDataType,
CShuffleDataType,
OutDataType,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
InUserDataType,
WeiUserDataType,
OutUserDataType,
DeviceGroupedConvNDFwdInstance<2,
InLayout,
WeiLayout,
......@@ -413,13 +425,16 @@ int main(int argc, char* argv[])
});
return run_grouped_conv_fwd_bias_relu_add<3,
InDataType,
WeiDataType,
InKernelDataType,
WeiKernelDataType,
CShuffleDataType,
OutDataType,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
InUserDataType,
WeiUserDataType,
OutUserDataType,
DeviceGroupedConvNDFwdInstance<3,
InLayout,
WeiLayout,
......
example/30_grouped_convnd_fwd_bias_relu_add/grouped_convnd_fwd_bias_relu_add_xdl_fp16.cpp
View file @ 451aef90
......@@ -7,13 +7,19 @@
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
using InDataType = ck::half_t;
using WeiDataType = ck::half_t;
// kernel data types
using InKernelDataType = ck::half_t;
using WeiKernelDataType = ck::half_t;
using AccDataType = float;
using CShuffleDataType = ck::half_t;
using BiasDataType = ck::half_t;
using ResidualDataType = ck::half_t;
using OutDataType = ck::half_t;
using BiasKernelDataType = ck::half_t;
using ResidualKernelDataType = ck::half_t;
using OutKernelDataType = ck::half_t;
// tensor data types
using InUserDataType = InKernelDataType;
using WeiUserDataType = WeiKernelDataType;
using OutUserDataType = OutKernelDataType;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
......@@ -40,12 +46,12 @@ using DeviceGroupedConvNDFwdInstance =
WeiLayout,
ck::Tuple<BiasLayout, ResidualLayout>,
OutLayout,
InDataType,
WeiDataType,
InKernelDataType,
WeiKernelDataType,
AccDataType,
CShuffleDataType,
ck::Tuple<BiasDataType, ResidualDataType>,
OutDataType,
ck::Tuple<BiasKernelDataType, ResidualKernelDataType>,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
......@@ -181,13 +187,16 @@ int main(int argc, char* argv[])
});
return run_grouped_conv_fwd_bias_relu_add<1,
InDataType,
WeiDataType,
InKernelDataType,
WeiKernelDataType,
CShuffleDataType,
OutDataType,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
InUserDataType,
WeiUserDataType,
OutUserDataType,
DeviceGroupedConvNDFwdInstance<1,
InLayout,
WeiLayout,
......@@ -290,13 +299,16 @@ int main(int argc, char* argv[])
});
return run_grouped_conv_fwd_bias_relu_add<2,
InDataType,
WeiDataType,
InKernelDataType,
WeiKernelDataType,
CShuffleDataType,
OutDataType,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
InUserDataType,
WeiUserDataType,
OutUserDataType,
DeviceGroupedConvNDFwdInstance<2,
InLayout,
WeiLayout,
......@@ -413,13 +425,16 @@ int main(int argc, char* argv[])
});
return run_grouped_conv_fwd_bias_relu_add<3,
InDataType,
WeiDataType,
InKernelDataType,
WeiKernelDataType,
CShuffleDataType,
OutDataType,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
InUserDataType,
WeiUserDataType,
OutUserDataType,
DeviceGroupedConvNDFwdInstance<3,
InLayout,
WeiLayout,
......
example/30_grouped_convnd_fwd_bias_relu_add/grouped_convnd_fwd_bias_relu_add_xdl_fp32.cpp
View file @ 451aef90
......@@ -7,13 +7,19 @@
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
using InDataType = float;
using WeiDataType = float;
// kernel data types
using InKernelDataType = float;
using WeiKernelDataType = float;
using AccDataType = float;
using CShuffleDataType = float;
using BiasDataType = float;
using ResidualDataType = float;
using OutDataType = float;
using BiasKernelDataType = float;
using ResidualKernelDataType = float;
using OutKernelDataType = float;
// tensor data types
using InUserDataType = InKernelDataType;
using WeiUserDataType = WeiKernelDataType;
using OutUserDataType = OutKernelDataType;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
......@@ -40,12 +46,12 @@ using DeviceGroupedConvNDFwdInstance =
WeiLayout,
ck::Tuple<BiasLayout, ResidualLayout>,
OutLayout,
InDataType,
WeiDataType,
InKernelDataType,
WeiKernelDataType,
AccDataType,
CShuffleDataType,
ck::Tuple<BiasDataType, ResidualDataType>,
OutDataType,
ck::Tuple<BiasKernelDataType, ResidualKernelDataType>,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
......@@ -181,13 +187,16 @@ int main(int argc, char* argv[])
});
return run_grouped_conv_fwd_bias_relu_add<1,
InDataType,
WeiDataType,
InKernelDataType,
WeiKernelDataType,
CShuffleDataType,
OutDataType,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
InUserDataType,
WeiUserDataType,
OutUserDataType,
DeviceGroupedConvNDFwdInstance<1,
InLayout,
WeiLayout,
......@@ -290,13 +299,16 @@ int main(int argc, char* argv[])
});
return run_grouped_conv_fwd_bias_relu_add<2,
InDataType,
WeiDataType,
InKernelDataType,
WeiKernelDataType,
CShuffleDataType,
OutDataType,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
InUserDataType,
WeiUserDataType,
OutUserDataType,
DeviceGroupedConvNDFwdInstance<2,
InLayout,
WeiLayout,
......@@ -413,13 +425,16 @@ int main(int argc, char* argv[])
});
return run_grouped_conv_fwd_bias_relu_add<3,
InDataType,
WeiDataType,
InKernelDataType,
WeiKernelDataType,
CShuffleDataType,
OutDataType,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
InUserDataType,
WeiUserDataType,
OutUserDataType,
DeviceGroupedConvNDFwdInstance<3,
InLayout,
WeiLayout,
......
example/30_grouped_convnd_fwd_bias_relu_add/grouped_convnd_fwd_bias_relu_add_xdl_int4.cpp 0 → 100644
View file @ 451aef90
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "grouped_convnd_fwd_bias_relu_add_common.hpp"
#include "ck/tensor_operation/gpu/device/device_grouped_conv_fwd_multiple_d_xdl_cshuffle.hpp"
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
// kernel data types
using InKernelDataType = int8_t;
using WeiKernelDataType = int8_t;
using AccDataType = int32_t;
using CShuffleDataType = int8_t;
using BiasKernelDataType = int8_t;
using ResidualKernelDataType = int8_t;
using OutKernelDataType = int8_t;
// tensor data types
using InUserDataType = ck::int4_t;
using WeiUserDataType = ck::int4_t;
using OutUserDataType = ck::int4_t;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using InElementOp = ck::tensor_operation::element_wise::PassThrough;
using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
using OutElementOp = ck::tensor_operation::element_wise::AddReluAdd;
static constexpr auto ConvSpec =
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
template <ck::index_t NDimSpatial,
typename InLayout,
typename WeiLayout,
typename BiasLayout,
typename ResidualLayout,
typename OutLayout>
using DeviceGroupedConvNDFwdInstance =
ck::tensor_operation::device::DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<
NDimSpatial,
InLayout,
WeiLayout,
ck::Tuple<BiasLayout, ResidualLayout>,
OutLayout,
InKernelDataType,
WeiKernelDataType,
AccDataType,
CShuffleDataType,
ck::Tuple<BiasKernelDataType, ResidualKernelDataType>,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
ConvSpec, // ConvForwardSpecialization
GemmSpec, // GemmSpecialization
1, //
256, // BlockSize
128, // MPerBlock
256, // NPerBlock
64, // KPerBlock
16, // AK1
16, // 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
16, // ABlockTransferSrcScalarPerVector
16, // ABlockTransferDstScalarPerVector_AK1
1, // ABlockLdsExtraM
S<4, 64, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
S<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder
S<1, 0, 2>, // BBlockTransferSrcAccessOrder
2, // BBlockTransferSrcVectorDim
16, // BBlockTransferSrcScalarPerVector
16, // BBlockTransferDstScalarPerVector_BK1
1, // BBlockLdsExtraN
1,
1,
S<1, 64, 1, 4>,
16>;
int main(int argc, char* argv[])
{
namespace ctc = ck::tensor_layout::convolution;
print_helper_msg();
bool do_verification = true;
int init_method = 1;
bool time_kernel = false;
// conventional group conv definition
// G = 2
// [N, C, Hi, Wi] = [128, 384, 71, 71]
// [K, C, Y, X] = [512, 192, 3, 3]
// [N, K, Ho, Wo] = [128, 512, 36, 36]
// CK group conv definition
// [G, N, C, Hi, Wi] = [2, 128, 192, 71, 71]
// [G, K, C, Y, X] = [2, 256, 192, 3, 3]
// [G, N, K, Ho, Wo] = [2, 128, 256, 36, 36]
ck::utils::conv::ConvParam conv_param{
2, 2, 128, 256, 192, {3, 3}, {71, 71}, {2, 2}, {1, 1}, {1, 1}, {1, 1}};
if(argc == 1)
{
// use default
}
else if(argc == 4)
{
do_verification = std::stoi(argv[1]);
init_method = std::stoi(argv[2]);
time_kernel = std::stoi(argv[3]);
}
else
{
do_verification = std::stoi(argv[1]);
init_method = std::stoi(argv[2]);
time_kernel = std::stoi(argv[3]);
const ck::index_t num_dim_spatial = std::stoi(argv[4]);
conv_param = ck::utils::conv::parse_conv_param(num_dim_spatial, 5, argv);
}
const auto in_element_op = InElementOp{};
const auto wei_element_op = WeiElementOp{};
const auto out_element_op = OutElementOp{};
if(conv_param.num_dim_spatial_ == 1)
{
using InLayout = ctc::G_NW_C;
using WeiLayout = ctc::G_K_X_C;
using BiasLayout = ctc::G_NW_K;
using ResidualLayout = ctc::G_NW_K;
using OutLayout = ctc::G_NW_K;
const auto in_g_n_c_wis_desc = HostTensorDescriptor(
{conv_param.G_, conv_param.N_, conv_param.C_, conv_param.input_spatial_lengths_[0]},
{
conv_param.C_, // g
conv_param.input_spatial_lengths_[0] * conv_param.G_ * conv_param.C_, // n
1, // c
conv_param.G_ * conv_param.C_ // wi
});
const auto wei_g_k_c_xs_desc = HostTensorDescriptor(
{conv_param.G_, conv_param.K_, conv_param.C_, conv_param.filter_spatial_lengths_[0]},
{
conv_param.K_ * conv_param.filter_spatial_lengths_[0] * conv_param.C_, // g
conv_param.filter_spatial_lengths_[0] * conv_param.C_, // k
1, // c
conv_param.C_ // x
});
const auto bias_g_n_k_wos_desc = HostTensorDescriptor(
{conv_param.G_, conv_param.N_, conv_param.K_, conv_param.output_spatial_lengths_[0]},
{
conv_param.K_, // g
0, // k
1, // c
0 // x
});
const auto residual_g_n_k_wos_desc = HostTensorDescriptor(
{conv_param.G_, conv_param.N_, conv_param.K_, conv_param.output_spatial_lengths_[0]},
{
conv_param.K_, // g
0, // k
1, // c
0 // x
});
const auto out_g_n_k_wos_desc = HostTensorDescriptor(
{conv_param.G_, conv_param.N_, conv_param.K_, conv_param.output_spatial_lengths_[0]},
{
conv_param.K_, // g
conv_param.output_spatial_lengths_[0] * conv_param.G_ * conv_param.K_, // n
1, // k
conv_param.G_ * conv_param.K_ // wo
});
return run_grouped_conv_fwd_bias_relu_add<1,
InKernelDataType,
WeiKernelDataType,
CShuffleDataType,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
InUserDataType,
WeiUserDataType,
OutUserDataType,
DeviceGroupedConvNDFwdInstance<1,
InLayout,
WeiLayout,
BiasLayout,
ResidualLayout,
OutLayout>>(
do_verification,
init_method,
time_kernel,
conv_param,
in_g_n_c_wis_desc,
wei_g_k_c_xs_desc,
bias_g_n_k_wos_desc,
residual_g_n_k_wos_desc,
out_g_n_k_wos_desc,
in_element_op,
wei_element_op,
out_element_op);
}
else if(conv_param.num_dim_spatial_ == 2)
{
using InLayout = ctc::G_NHW_C;
using WeiLayout = ctc::G_K_YX_C;
using BiasLayout = ctc::G_NHW_K;
using ResidualLayout = ctc::G_NHW_K;
using OutLayout = ctc::G_NHW_K;
const auto in_g_n_c_wis_desc = HostTensorDescriptor(
{conv_param.G_,
conv_param.N_,
conv_param.C_,
conv_param.input_spatial_lengths_[0],
conv_param.input_spatial_lengths_[1]},
{
conv_param.C_, // g
conv_param.input_spatial_lengths_[0] * conv_param.input_spatial_lengths_[1] *
conv_param.G_ * conv_param.C_, // n
1, // c
conv_param.input_spatial_lengths_[1] * conv_param.G_ * conv_param.C_, // hi
conv_param.G_ * conv_param.C_ // wi
});
const auto wei_g_k_c_xs_desc =
HostTensorDescriptor({conv_param.G_,
conv_param.K_,
conv_param.C_,
conv_param.filter_spatial_lengths_[0],
conv_param.filter_spatial_lengths_[1]},
{
conv_param.K_ * conv_param.filter_spatial_lengths_[0] *
conv_param.filter_spatial_lengths_[1] * conv_param.C_, // g
conv_param.filter_spatial_lengths_[0] *
conv_param.filter_spatial_lengths_[1] * conv_param.C_, // k
1, // c
conv_param.filter_spatial_lengths_[1] * conv_param.C_, // y
conv_param.C_ // x
});
const auto bias_g_n_k_wos_desc =
HostTensorDescriptor({conv_param.G_,
conv_param.N_,
conv_param.K_,
conv_param.output_spatial_lengths_[0],
conv_param.output_spatial_lengths_[1]},
{
conv_param.K_, // g
0, // n
1, // k
0, // ho
0 // wo
});
const auto residual_g_n_k_wos_desc =
HostTensorDescriptor({conv_param.G_,
conv_param.N_,
conv_param.K_,
conv_param.output_spatial_lengths_[0],
conv_param.output_spatial_lengths_[1]},
{
conv_param.K_, // g
0, // n
1, // k
0, // ho
0 // wo
});
const auto out_g_n_k_wos_desc = HostTensorDescriptor(
{conv_param.G_,
conv_param.N_,
conv_param.K_,
conv_param.output_spatial_lengths_[0],
conv_param.output_spatial_lengths_[1]},
{
conv_param.K_, // g
conv_param.output_spatial_lengths_[0] * conv_param.output_spatial_lengths_[1] *
conv_param.G_ * conv_param.K_, // n
1, // k
conv_param.output_spatial_lengths_[1] * conv_param.G_ * conv_param.K_, // ho
conv_param.G_ * conv_param.K_ // wo
});
return run_grouped_conv_fwd_bias_relu_add<2,
InKernelDataType,
WeiKernelDataType,
CShuffleDataType,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
InUserDataType,
WeiUserDataType,
OutUserDataType,
DeviceGroupedConvNDFwdInstance<2,
InLayout,
WeiLayout,
BiasLayout,
ResidualLayout,
OutLayout>>(
do_verification,
init_method,
time_kernel,
conv_param,
in_g_n_c_wis_desc,
wei_g_k_c_xs_desc,
bias_g_n_k_wos_desc,
residual_g_n_k_wos_desc,
out_g_n_k_wos_desc,
in_element_op,
wei_element_op,
out_element_op);
}
else if(conv_param.num_dim_spatial_ == 3)
{
using InLayout = ctc::G_NDHW_C;
using WeiLayout = ctc::G_K_ZYX_C;
using BiasLayout = ctc::G_NDHW_K;
using ResidualLayout = ctc::G_NDHW_K;
using OutLayout = ctc::G_NDHW_K;
const auto in_g_n_c_wis_desc = HostTensorDescriptor(
{conv_param.G_,
conv_param.N_,
conv_param.C_,
conv_param.input_spatial_lengths_[0],
conv_param.input_spatial_lengths_[1],
conv_param.input_spatial_lengths_[2]},
{
conv_param.C_, // g
conv_param.input_spatial_lengths_[0] * conv_param.input_spatial_lengths_[1] *
conv_param.input_spatial_lengths_[2] * conv_param.G_ * conv_param.C_, // n
1, // c
conv_param.input_spatial_lengths_[1] * conv_param.input_spatial_lengths_[2] *
conv_param.G_ * conv_param.C_, // di
conv_param.input_spatial_lengths_[2] * conv_param.G_ * conv_param.C_, // hi
conv_param.G_ * conv_param.C_ // wi
});
const auto wei_g_k_c_xs_desc = HostTensorDescriptor(
{conv_param.G_,
conv_param.K_,
conv_param.C_,
conv_param.filter_spatial_lengths_[0],
conv_param.filter_spatial_lengths_[1],
conv_param.filter_spatial_lengths_[2]},
{
conv_param.K_ * conv_param.filter_spatial_lengths_[0] *
conv_param.filter_spatial_lengths_[1] * conv_param.filter_spatial_lengths_[2] *
conv_param.C_, // g
conv_param.filter_spatial_lengths_[0] * conv_param.filter_spatial_lengths_[1] *
conv_param.filter_spatial_lengths_[2] * conv_param.C_, // k
1, // c
conv_param.filter_spatial_lengths_[1] * conv_param.filter_spatial_lengths_[2] *
conv_param.C_, // z
conv_param.filter_spatial_lengths_[2] * conv_param.C_, // y
conv_param.C_ // x
});
const auto bias_g_n_k_wos_desc =
HostTensorDescriptor({conv_param.G_,
conv_param.N_,
conv_param.K_,
conv_param.output_spatial_lengths_[0],
conv_param.output_spatial_lengths_[1],
conv_param.output_spatial_lengths_[2]},
{
conv_param.K_, // g
0, // n
1, // k
0, // z
0, // y
0 // x
});
const auto residual_g_n_k_wos_desc =
HostTensorDescriptor({conv_param.G_,
conv_param.N_,
conv_param.K_,
conv_param.output_spatial_lengths_[0],
conv_param.output_spatial_lengths_[1],
conv_param.output_spatial_lengths_[2]},
{
conv_param.K_, // g
0, // n
1, // k
0, // z
0, // y
0 // x
});
const auto out_g_n_k_wos_desc = HostTensorDescriptor(
{conv_param.G_,
conv_param.N_,
conv_param.K_,
conv_param.output_spatial_lengths_[0],
conv_param.output_spatial_lengths_[1],
conv_param.output_spatial_lengths_[2]},
{
conv_param.K_, // g
conv_param.output_spatial_lengths_[0] * conv_param.output_spatial_lengths_[1] *
conv_param.output_spatial_lengths_[2] * conv_param.G_ * conv_param.K_, // n
1, // k
conv_param.output_spatial_lengths_[1] * conv_param.output_spatial_lengths_[2] *
conv_param.G_ * conv_param.K_, // do
conv_param.output_spatial_lengths_[2] * conv_param.G_ * conv_param.K_, // ho
conv_param.G_ * conv_param.K_ // wo
});
return run_grouped_conv_fwd_bias_relu_add<3,
InKernelDataType,
WeiKernelDataType,
CShuffleDataType,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
InUserDataType,
WeiUserDataType,
OutUserDataType,
DeviceGroupedConvNDFwdInstance<3,
InLayout,
WeiLayout,
BiasLayout,
ResidualLayout,
OutLayout>>(
do_verification,
init_method,
time_kernel,
conv_param,
in_g_n_c_wis_desc,
wei_g_k_c_xs_desc,
bias_g_n_k_wos_desc,
residual_g_n_k_wos_desc,
out_g_n_k_wos_desc,
in_element_op,
wei_element_op,
out_element_op);
}
return 0;
}
example/30_grouped_convnd_fwd_bias_relu_add/grouped_convnd_fwd_bias_relu_add_xdl_int8.cpp
View file @ 451aef90
......@@ -7,13 +7,19 @@
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
using InDataType = int8_t;
using WeiDataType = int8_t;
// kernel data types
using InKernelDataType = int8_t;
using WeiKernelDataType = int8_t;
using AccDataType = int32_t;
using CShuffleDataType = int8_t;
using BiasDataType = int8_t;
using ResidualDataType = int8_t;
using OutDataType = int8_t;
using BiasKernelDataType = int8_t;
using ResidualKernelDataType = int8_t;
using OutKernelDataType = int8_t;
// tensor data types
using InUserDataType = InKernelDataType;
using WeiUserDataType = WeiKernelDataType;
using OutUserDataType = OutKernelDataType;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
......@@ -40,12 +46,12 @@ using DeviceGroupedConvNDFwdInstance =
WeiLayout,
ck::Tuple<BiasLayout, ResidualLayout>,
OutLayout,
InDataType,
WeiDataType,
InKernelDataType,
WeiKernelDataType,
AccDataType,
CShuffleDataType,
ck::Tuple<BiasDataType, ResidualDataType>,
OutDataType,
ck::Tuple<BiasKernelDataType, ResidualKernelDataType>,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
......@@ -181,13 +187,16 @@ int main(int argc, char* argv[])
});
return run_grouped_conv_fwd_bias_relu_add<1,
InDataType,
WeiDataType,
InKernelDataType,
WeiKernelDataType,
CShuffleDataType,
OutDataType,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
InUserDataType,
WeiUserDataType,
OutUserDataType,
DeviceGroupedConvNDFwdInstance<1,
InLayout,
WeiLayout,
......@@ -290,13 +299,16 @@ int main(int argc, char* argv[])
});
return run_grouped_conv_fwd_bias_relu_add<2,
InDataType,
WeiDataType,
InKernelDataType,
WeiKernelDataType,
CShuffleDataType,
OutDataType,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
InUserDataType,
WeiUserDataType,
OutUserDataType,
DeviceGroupedConvNDFwdInstance<2,
InLayout,
WeiLayout,
......@@ -413,13 +425,16 @@ int main(int argc, char* argv[])
});
return run_grouped_conv_fwd_bias_relu_add<3,
InDataType,
WeiDataType,
InKernelDataType,
WeiKernelDataType,
CShuffleDataType,
OutDataType,
OutKernelDataType,
InElementOp,
WeiElementOp,
OutElementOp,
InUserDataType,
WeiUserDataType,
OutUserDataType,
DeviceGroupedConvNDFwdInstance<3,
InLayout,
WeiLayout,
......
include/ck/tensor_operation/gpu/element/element_wise_operation.hpp
View file @ 451aef90
......@@ -98,6 +98,16 @@ struct AddReluAdd
int32_t c = b + x2;
y = c;
}
template <>
__host__ __device__ constexpr void operator()<int4_t, int8_t, int4_t, int4_t>(
int4_t& y, const int8_t& x0, const int4_t& x1, const int4_t& x2) const
{
int32_t a = x0 + x1;
int32_t b = a > 0 ? a : 0;
int32_t c = b + x2;
y = c;
}
};
struct AddHardswishAdd
......
library/include/ck/library/utility/check_err.hpp
View file @ 451aef90
......@@ -150,7 +150,12 @@ check_err(const std::vector<T>& out,
}
template <typename T>
typename std::enable_if<std::is_integral<T>::value && !std::is_same<T, bhalf_t>::value, bool>::type
std::enable_if_t<(std::is_integral_v<T> && !std::is_same_v<T, bhalf_t>)
#ifdef CK_EXPERIMENTAL_BIT_INT_EXTENSION_INT4
|| std::is_same_v<T, int4_t>
#endif
,
bool>
check_err(const std::vector<T>& out,
const std::vector<T>& ref,
const std::string& msg = "Error: Incorrect results!",
......
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