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Commit 6af2b468 authored by Adam Osewski's avatar Adam Osewski
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CGEMM int4 example.

parent 6ceb900b
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example/22_cgemm/CMakeLists.txt
View file @ 6af2b468
...@@ -5,7 +5,13 @@ add_example_executable(example_cgemm_xdl_fp16 cgemm_xdl_fp16.cpp) ...@@ -5,7 +5,13 @@ add_example_executable(example_cgemm_xdl_fp16 cgemm_xdl_fp16.cpp)
add_example_executable(example_cgemm_xdl_fp32 cgemm_xdl_fp32.cpp) add_example_executable(example_cgemm_xdl_fp32 cgemm_xdl_fp32.cpp)
add_example_executable(example_cgemm_xdl_int8 cgemm_xdl_int8.cpp) add_example_executable(example_cgemm_xdl_int8 cgemm_xdl_int8.cpp)
add_dependencies(example_cgemm_xdl example_cgemm_xdl_bf16) add_dependencies(example_cgemm_xdl
add_dependencies(example_cgemm_xdl example_cgemm_xdl_fp16) example_cgemm_xdl_bf16
add_dependencies(example_cgemm_xdl example_cgemm_xdl_fp32) example_cgemm_xdl_fp16
add_dependencies(example_cgemm_xdl example_cgemm_xdl_int8) example_cgemm_xdl_fp32
example_cgemm_xdl_int8)
if(USE_BITINT_EXTENSION_INT4)
add_example_executable(example_cgemm_xdl_int4 cgemm_xdl_int4.cpp)
add_dependencies(example_cgemm_xdl example_cgemm_xdl_int4)
endif()
example/22_cgemm/cgemm_xdl_bf16.cpp
View file @ 6af2b468
...@@ -117,16 +117,16 @@ int main(int argc, char* argv[]) ...@@ -117,16 +117,16 @@ int main(int argc, char* argv[])
exit(0); exit(0);
} }
return run_cgemm_xdl<ADataType, return !run_cgemm_xdl<ADataType,
BDataType, BDataType,
CDataType, CDataType,
ALayout, ALayout,
BLayout, BLayout,
CLayout, CLayout,
PassThrough, PassThrough,
PassThrough, PassThrough,
PassThrough, PassThrough,
DeviceCGemmInstance, DeviceCGemmInstance,
ReferenceCGemmInstance>( ReferenceCGemmInstance>(
M, N, K, StrideA, StrideB, StrideC, do_verification, init_method, time_kernel); M, N, K, StrideA, StrideB, StrideC, do_verification, init_method, time_kernel);
} }
example/22_cgemm/cgemm_xdl_common.hpp
View file @ 6af2b468
...@@ -21,6 +21,9 @@ using F32 = float; ...@@ -21,6 +21,9 @@ using F32 = float;
using BF16 = ck::bhalf_t; using BF16 = ck::bhalf_t;
using INT8 = std::int8_t; using INT8 = std::int8_t;
using INT32 = std::int32_t; using INT32 = std::int32_t;
#ifdef CK_EXPERIMENTAL_BIT_INT_EXTENSION_INT4
using INT4 = ck::int4_t;
#endif
template <typename ADataType, template <typename ADataType,
typename BDataType, typename BDataType,
...@@ -32,17 +35,31 @@ template <typename ADataType, ...@@ -32,17 +35,31 @@ template <typename ADataType,
typename BElementwiseOperation, typename BElementwiseOperation,
typename CElementwiseOperation, typename CElementwiseOperation,
typename DeviceCGemmInstance, typename DeviceCGemmInstance,
typename ReferenceCGemmInstance> typename ReferenceCGemmInstance,
int run_cgemm_xdl(ck::index_t M, typename KernelADataType = ADataType,
ck::index_t N, typename KernelBDataType = BDataType,
ck::index_t K, typename KernelCDataType = CDataType>
ck::index_t StrideA, bool run_cgemm_xdl(ck::index_t M,
ck::index_t StrideB, ck::index_t N,
ck::index_t StrideC, ck::index_t K,
bool do_verification, ck::index_t StrideA,
int init_method, ck::index_t StrideB,
bool time_kernel) ck::index_t StrideC,
bool do_verification,
int init_method,
bool time_kernel)
{ {
#ifdef CK_EXPERIMENTAL_BIT_INT_EXTENSION_INT4
static_assert(sizeof(ck::int4_t) == sizeof(int8_t),
"sizeof ck::int4_t and int8_t is different!");
static_assert(sizeof(ADataType) == sizeof(KernelADataType),
"sizeof ADataType and KernelADataType is different!");
static_assert(sizeof(BDataType) == sizeof(KernelBDataType),
"sizeof BDataType and KernelBDataType is different!");
static_assert(sizeof(CDataType) == sizeof(KernelCDataType),
"sizeof CDataType and KernelCDataType is different!");
#endif
auto f_host_tensor_descriptor = auto f_host_tensor_descriptor =
[](std::size_t row, std::size_t col, std::size_t stride, auto layout) { [](std::size_t row, std::size_t col, std::size_t stride, auto layout) {
if(std::is_same<decltype(layout), ck::tensor_layout::gemm::RowMajor>::value) if(std::is_same<decltype(layout), ck::tensor_layout::gemm::RowMajor>::value)
...@@ -61,8 +78,10 @@ int run_cgemm_xdl(ck::index_t M, ...@@ -61,8 +78,10 @@ int run_cgemm_xdl(ck::index_t M,
Tensor<ADataType> a_m_k_imag(f_host_tensor_descriptor(M, K, StrideA, ALayout{})); Tensor<ADataType> a_m_k_imag(f_host_tensor_descriptor(M, K, StrideA, ALayout{}));
Tensor<BDataType> b_k_n_real(f_host_tensor_descriptor(K, N, StrideB, BLayout{})); Tensor<BDataType> b_k_n_real(f_host_tensor_descriptor(K, N, StrideB, BLayout{}));
Tensor<BDataType> b_k_n_imag(f_host_tensor_descriptor(K, N, StrideB, BLayout{})); Tensor<BDataType> b_k_n_imag(f_host_tensor_descriptor(K, N, StrideB, BLayout{}));
Tensor<CDataType> c_m_n_real_device_result(f_host_tensor_descriptor(M, N, StrideC, CLayout{})); Tensor<KernelCDataType> c_m_n_real_device_result(
Tensor<CDataType> c_m_n_imag_device_result(f_host_tensor_descriptor(M, N, StrideC, CLayout{})); f_host_tensor_descriptor(M, N, StrideC, CLayout{}));
Tensor<KernelCDataType> c_m_n_imag_device_result(
f_host_tensor_descriptor(M, N, StrideC, CLayout{}));
std::cout << "a_m_k_real: " << a_m_k_real.mDesc << std::endl; std::cout << "a_m_k_real: " << a_m_k_real.mDesc << std::endl;
std::cout << "a_m_k_imag: " << a_m_k_imag.mDesc << std::endl; std::cout << "a_m_k_imag: " << a_m_k_imag.mDesc << std::endl;
...@@ -89,16 +108,35 @@ int run_cgemm_xdl(ck::index_t M, ...@@ -89,16 +108,35 @@ int run_cgemm_xdl(ck::index_t M,
auto cgemm = DeviceCGemmInstance{}; auto cgemm = DeviceCGemmInstance{};
DeviceMem a_m_k_real_device_buf(sizeof(ADataType) * a_m_k_real.mDesc.GetElementSpaceSize()); DeviceMem a_m_k_real_device_buf(sizeof(KernelADataType) *
DeviceMem a_m_k_imag_device_buf(sizeof(ADataType) * a_m_k_imag.mDesc.GetElementSpaceSize()); a_m_k_real.mDesc.GetElementSpaceSize());
DeviceMem b_k_n_real_device_buf(sizeof(BDataType) * b_k_n_real.mDesc.GetElementSpaceSize()); DeviceMem a_m_k_imag_device_buf(sizeof(KernelADataType) *
DeviceMem b_k_n_imag_device_buf(sizeof(BDataType) * b_k_n_imag.mDesc.GetElementSpaceSize()); a_m_k_imag.mDesc.GetElementSpaceSize());
DeviceMem c_m_n_real_device_buf(sizeof(CDataType) * DeviceMem b_k_n_real_device_buf(sizeof(KernelBDataType) *
b_k_n_real.mDesc.GetElementSpaceSize());
DeviceMem b_k_n_imag_device_buf(sizeof(KernelBDataType) *
b_k_n_imag.mDesc.GetElementSpaceSize());
DeviceMem c_m_n_real_device_buf(sizeof(KernelCDataType) *
c_m_n_real_device_result.mDesc.GetElementSpaceSize()); c_m_n_real_device_result.mDesc.GetElementSpaceSize());
DeviceMem c_m_n_imag_device_buf(sizeof(CDataType) * DeviceMem c_m_n_imag_device_buf(sizeof(KernelCDataType) *
c_m_n_imag_device_result.mDesc.GetElementSpaceSize()); c_m_n_imag_device_result.mDesc.GetElementSpaceSize());
DeviceMem workspace_device_buf(cgemm.GetWorkspaceSize(M, N, K, StrideA, StrideB, StrideC)); DeviceMem workspace_device_buf(cgemm.GetWorkspaceSize(M, N, K, StrideA, StrideB, StrideC));
#ifdef CK_EXPERIMENTAL_BIT_INT_EXTENSION_INT4
if constexpr(std::is_same_v<ADataType, ck::int4_t>)
{
Tensor<KernelADataType> a_m_k_real_converted(a_m_k_real);
Tensor<KernelADataType> a_m_k_imag_converted(a_m_k_imag);
Tensor<KernelBDataType> b_k_n_real_converted(b_k_n_real);
Tensor<KernelBDataType> b_k_n_imag_converted(b_k_n_imag);
a_m_k_real = a_m_k_real_converted;
a_m_k_imag = a_m_k_imag_converted;
b_k_n_real = b_k_n_real_converted;
b_k_n_imag = b_k_n_imag_converted;
}
#endif // CK_EXPERIMENTAL_BIT_INT_EXTENSION_INT4
a_m_k_real_device_buf.ToDevice(a_m_k_real.mData.data()); a_m_k_real_device_buf.ToDevice(a_m_k_real.mData.data());
a_m_k_imag_device_buf.ToDevice(a_m_k_imag.mData.data()); a_m_k_imag_device_buf.ToDevice(a_m_k_imag.mData.data());
b_k_n_real_device_buf.ToDevice(b_k_n_real.mData.data()); b_k_n_real_device_buf.ToDevice(b_k_n_real.mData.data());
...@@ -111,13 +149,13 @@ int run_cgemm_xdl(ck::index_t M, ...@@ -111,13 +149,13 @@ int run_cgemm_xdl(ck::index_t M,
// do GEMM // do GEMM
auto invoker = cgemm.MakeInvoker(); auto invoker = cgemm.MakeInvoker();
auto argument = auto argument =
cgemm.MakeArgument(static_cast<ADataType*>(a_m_k_real_device_buf.GetDeviceBuffer()), cgemm.MakeArgument(static_cast<KernelADataType*>(a_m_k_real_device_buf.GetDeviceBuffer()),
static_cast<ADataType*>(a_m_k_imag_device_buf.GetDeviceBuffer()), static_cast<KernelADataType*>(a_m_k_imag_device_buf.GetDeviceBuffer()),
static_cast<BDataType*>(b_k_n_real_device_buf.GetDeviceBuffer()), static_cast<KernelBDataType*>(b_k_n_real_device_buf.GetDeviceBuffer()),
static_cast<BDataType*>(b_k_n_imag_device_buf.GetDeviceBuffer()), static_cast<KernelBDataType*>(b_k_n_imag_device_buf.GetDeviceBuffer()),
static_cast<CDataType*>(c_m_n_real_device_buf.GetDeviceBuffer()), static_cast<KernelCDataType*>(c_m_n_real_device_buf.GetDeviceBuffer()),
static_cast<CDataType*>(c_m_n_imag_device_buf.GetDeviceBuffer()), static_cast<KernelCDataType*>(c_m_n_imag_device_buf.GetDeviceBuffer()),
static_cast<CDataType*>(workspace_device_buf.GetDeviceBuffer()), static_cast<KernelCDataType*>(workspace_device_buf.GetDeviceBuffer()),
M, M,
N, N,
K, K,
...@@ -142,16 +180,12 @@ int run_cgemm_xdl(ck::index_t M, ...@@ -142,16 +180,12 @@ int run_cgemm_xdl(ck::index_t M,
std::size_t(2) * std::size_t(2) *
(sizeof(ADataType) * M * K + sizeof(BDataType) * K * N + sizeof(CDataType) * M * N); (sizeof(ADataType) * M * K + sizeof(BDataType) * K * N + sizeof(CDataType) * M * N);
float tflops = static_cast<float>(flop) / 1.E9 / ave_time; float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
float gb_per_sec = num_btype / 1.E6 / ave_time; float gb_per_sec = num_btype / 1.E6 / ave_time;
std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s, " std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s, "
<< cgemm.GetTypeString() << std::endl; << cgemm.GetTypeString() << std::endl;
c_m_n_real_device_buf.FromDevice(c_m_n_real_device_result.mData.data());
c_m_n_imag_device_buf.FromDevice(c_m_n_imag_device_result.mData.data());
if(do_verification) if(do_verification)
{ {
Tensor<CDataType> c_m_n_real_host_result( Tensor<CDataType> c_m_n_real_host_result(
...@@ -159,9 +193,8 @@ int run_cgemm_xdl(ck::index_t M, ...@@ -159,9 +193,8 @@ int run_cgemm_xdl(ck::index_t M,
Tensor<CDataType> c_m_n_imag_host_result( Tensor<CDataType> c_m_n_imag_host_result(
f_host_tensor_descriptor(M, N, StrideC, CLayout{})); f_host_tensor_descriptor(M, N, StrideC, CLayout{}));
auto ref_cgemm = ReferenceCGemmInstance{}; auto ref_cgemm = ReferenceCGemmInstance{};
auto ref_invoker = ref_cgemm.MakeInvoker(); auto ref_invoker = ref_cgemm.MakeInvoker();
auto ref_argument = ref_cgemm.MakeArgument(a_m_k_real, auto ref_argument = ref_cgemm.MakeArgument(a_m_k_real,
a_m_k_imag, a_m_k_imag,
b_k_n_real, b_k_n_real,
...@@ -174,19 +207,33 @@ int run_cgemm_xdl(ck::index_t M, ...@@ -174,19 +207,33 @@ int run_cgemm_xdl(ck::index_t M,
ref_invoker.Run(ref_argument); ref_invoker.Run(ref_argument);
c_m_n_real_device_buf.FromDevice(c_m_n_real_device_result.mData.data());
c_m_n_imag_device_buf.FromDevice(c_m_n_imag_device_result.mData.data());
bool result = true; bool result = true;
result = ck::utils::check_err(c_m_n_real_device_result.mData, #ifdef CK_EXPERIMENTAL_BIT_INT_EXTENSION_INT4
if constexpr(std::is_same_v<ADataType, ck::int4_t>)
{
const Tensor<CDataType> c_m_n_real_device_result_converted(c_m_n_real_device_result);
const Tensor<CDataType> c_m_n_imag_device_result_converted(c_m_n_imag_device_result);
c_m_n_real_device_result = c_m_n_real_device_result_converted;
c_m_n_imag_device_result = c_m_n_imag_device_result_converted;
}
#endif // CK_EXPERIMENTAL_BIT_INT_EXTENSION_INT4
result = ck::utils::check_err(c_m_n_real_device_result.mData,
c_m_n_real_host_result.mData, c_m_n_real_host_result.mData,
"Verification error: incorrect results in real part!", "Verification error: incorrect results in real part!",
1e-2f, 1e-2f,
1e-1f); 1e-1f);
result = result && result = result &&
ck::utils::check_err(c_m_n_imag_device_result.mData, ck::utils::check_err(c_m_n_imag_device_result.mData,
c_m_n_imag_host_result.mData, c_m_n_imag_host_result.mData,
"Verification error: incorrect results in imaginary part!", "Verification error: incorrect results in imaginary part!",
1e-2f, 1e-2f,
1e-1f); 1e-1f);
return result ? 0 : 1;
return result;
} }
return 0; return true;
} }
example/22_cgemm/cgemm_xdl_fp16.cpp
View file @ 6af2b468
...@@ -116,16 +116,16 @@ int main(int argc, char* argv[]) ...@@ -116,16 +116,16 @@ int main(int argc, char* argv[])
exit(0); exit(0);
} }
return run_cgemm_xdl<ADataType, return !run_cgemm_xdl<ADataType,
BDataType, BDataType,
CDataType, CDataType,
ALayout, ALayout,
BLayout, BLayout,
CLayout, CLayout,
PassThrough, PassThrough,
PassThrough, PassThrough,
PassThrough, PassThrough,
DeviceCGemmInstance, DeviceCGemmInstance,
ReferenceCGemmInstance>( ReferenceCGemmInstance>(
M, N, K, StrideA, StrideB, StrideC, do_verification, init_method, time_kernel); M, N, K, StrideA, StrideB, StrideC, do_verification, init_method, time_kernel);
} }
example/22_cgemm/cgemm_xdl_fp32.cpp
View file @ 6af2b468
...@@ -117,16 +117,16 @@ int main(int argc, char* argv[]) ...@@ -117,16 +117,16 @@ int main(int argc, char* argv[])
exit(0); exit(0);
} }
return run_cgemm_xdl<ADataType, return !run_cgemm_xdl<ADataType,
BDataType, BDataType,
CDataType, CDataType,
ALayout, ALayout,
BLayout, BLayout,
CLayout, CLayout,
PassThrough, PassThrough,
PassThrough, PassThrough,
PassThrough, PassThrough,
DeviceCGemmInstance, DeviceCGemmInstance,
ReferenceCGemmInstance>( ReferenceCGemmInstance>(
M, N, K, StrideA, StrideB, StrideC, do_verification, init_method, time_kernel); M, N, K, StrideA, StrideB, StrideC, do_verification, init_method, time_kernel);
} }
example/22_cgemm/cgemm_xdl_int4.cpp 0 → 100644
View file @ 6af2b468
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <iostream>
#include "cgemm_xdl_common.hpp"
#include "ck/library/reference_tensor_operation/cpu/reference_cgemm.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/tensor_operation/gpu/device/device_cgemm_4gemm_xdl_cshuffle.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
using ADataType = INT4;
using BDataType = INT4;
using CDataType = INT4;
using AccDataType = INT32;
using CShuffleDataType = INT32;
using KernelADataType = INT8;
using KernelBDataType = INT8;
using KernelCDataType = INT8;
using ALayout = ck::tensor_layout::gemm::RowMajor;
using BLayout = ck::tensor_layout::gemm::ColumnMajor;
using CLayout = ck::tensor_layout::gemm::RowMajor;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
using ReferenceCGemmInstance = ck::tensor_operation::host::
ReferenceCGemm<ADataType, BDataType, CDataType, PassThrough, PassThrough, PassThrough>;
// clang-format off
using DeviceCGemmInstance = ck::tensor_operation::device::DeviceCGemm_4Gemm_Xdl_CShuffle
<ALayout, // typename ALayout
BLayout, // typename BLayout
CLayout, // typename CLayout
KernelADataType, // typename ADataType
KernelBDataType, // typename BDataType
KernelCDataType, // typename CDataType
AccDataType, // typename GemmAccDataType
CShuffleDataType, // typename CShuffleDataType
PassThrough, // typename AElementwiseOperation
PassThrough, // typename BElementwiseOperation
PassThrough, // typename CElementwiseOperation
GemmDefault, // GemmSpecialization GemmSpec
1, // index_t NumGemmKPrefetchStage
256, // index_t BlockSize
256, // index_t MPerBlock
128, // index_t NPerBlock
64, // index_t KPerBlock
16, // index_t AK1
16, // index_t BK1
32, // index_t MPerXDL
32, // index_t NPerXDL
4, // index_t MXdlPerWave
2, // index_t NXdlPerWave
S<4, 64, 1>, // typename ABlockTransferThreadClusterLengths_AK0_M_AK1
S<1, 0, 2>, // typename ABlockTransferThreadClusterArrangeOrder
S<1, 0, 2>, // typename ABlockTransferSrcAccessOrder
2, // index_t ABlockTransferSrcVectorDim
16, // index_t ABlockTransferSrcScalarPerVector
16, // index_t ABlockTransferDstScalarPerVector_AK1
1, // index_t ABlockLdsExtraM
S<4, 64, 1>, // typename BBlockTransferThreadClusterLengths_BK0_N_BK1
S<1, 0, 2>, // typename BBlockTransferThreadClusterArrangeOrder
S<1, 0, 2>, // typename BBlockTransferSrcAccessOrder
2, // index_t BBlockTransferSrcVectorDim
8, // index_t BBlockTransferSrcScalarPerVector
8, // index_t BBlockTransferDstScalarPerVector_BK1
1, // index_t BBlockLdsExtraN
1, // index_t CShuffleMXdlPerWavePerShuffle
1, // index_t CShuffleNXdlPerWavePerShuffle
S<1, 64, 1, 4>, // typename CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock
16>; // index_t CShuffleBlockTransferScalarPerVector_NPerBlock
// clang-format on
int main(int argc, char* argv[])
{
bool do_verification = true;
int init_method = 1;
bool time_kernel = true;
// CGEMM shape
ck::index_t M = 1024;
ck::index_t N = 1152;
ck::index_t K = 512;
ck::index_t StrideA = K;
ck::index_t StrideB = K;
ck::index_t StrideC = N;
if(argc == 4)
{
do_verification = std::stoi(argv[1]);
init_method = std::stoi(argv[2]);
time_kernel = std::stoi(argv[3]);
}
else if(argc == 10)
{
do_verification = std::stoi(argv[1]);
init_method = std::stoi(argv[2]);
time_kernel = std::stoi(argv[3]);
M = std::stoi(argv[4]);
N = std::stoi(argv[5]);
K = std::stoi(argv[6]);
StrideA = std::stoi(argv[7]);
StrideB = std::stoi(argv[8]);
StrideC = std::stoi(argv[9]);
}
else
{
std::cout << "arg1: verification (0=no, 1=yes)\n"
<< "arg2: initialization (0=no init, 1=integer value, 2=decimal value)\n"
<< "arg3: time kernel (0=no, 1=yes)\n"
<< "arg4 to 9: M (256x), N(128x), K(32x), StrideA, StrideB, StrideC\n"
<< std::endl;
exit(EXIT_SUCCESS);
}
return !run_cgemm_xdl<ADataType,
BDataType,
CDataType,
ALayout,
BLayout,
CLayout,
PassThrough,
PassThrough,
PassThrough,
DeviceCGemmInstance,
ReferenceCGemmInstance,
KernelADataType,
KernelBDataType,
KernelCDataType>(
M, N, K, StrideA, StrideB, StrideC, do_verification, init_method, time_kernel);
}
example/22_cgemm/cgemm_xdl_int8.cpp
View file @ 6af2b468
...@@ -117,16 +117,16 @@ int main(int argc, char* argv[]) ...@@ -117,16 +117,16 @@ int main(int argc, char* argv[])
exit(0); exit(0);
} }
return run_cgemm_xdl<ADataType, return !run_cgemm_xdl<ADataType,
BDataType, BDataType,
CDataType, CDataType,
ALayout, ALayout,
BLayout, BLayout,
CLayout, CLayout,
PassThrough, PassThrough,
PassThrough, PassThrough,
PassThrough, PassThrough,
DeviceCGemmInstance, DeviceCGemmInstance,
ReferenceCGemmInstance>( ReferenceCGemmInstance>(
M, N, K, StrideA, StrideB, StrideC, do_verification, init_method, time_kernel); M, N, K, StrideA, StrideB, StrideC, do_verification, init_method, time_kernel);
} }
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