Commit f76c0072 authored by Jakub Piasecki's avatar Jakub Piasecki
Browse files

Merge remote-tracking branch 'origin/develop' into jakpiase/ggemm_multid_two_stage

parents f27c50a7 9c052804
......@@ -35,4 +35,9 @@ if(DTYPES MATCHES "fp8" OR NOT DEFINED DTYPES)
xdl/device_grouped_conv3d_fwd_xdl_ndhwgc_gkzyxc_ndhwgk_fp8_instance.cpp)
endif()
if(DTYPES MATCHES "bf8" OR NOT DEFINED DTYPES)
list(APPEND GROUPED_CONV3D_FWD
xdl/device_grouped_conv3d_fwd_xdl_ndhwgc_gkzyxc_ndhwgk_bf8_instance.cpp)
endif()
add_instance_library(device_grouped_conv3d_fwd_instance ${GROUPED_CONV3D_FWD})
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/tensor_operation_instance/gpu/grouped_conv_fwd/device_grouped_conv_fwd_xdl_instance.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
void add_device_grouped_conv3d_fwd_xdl_ndhwgc_gkzyxc_ndhwgk_bf8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleABD<3,
NDHWGC,
GKZYXC,
Empty_Tuple,
NDHWGK,
BF8,
BF8,
Empty_Tuple,
F8,
PassThrough,
PassThrough,
PassThrough,
BF8>>>& instances)
{
add_device_operation_instances(instances,
device_grouped_conv_fwd_xdl_bf8_instances<3,
NDHWGC,
GKZYXC,
Empty_Tuple,
NDHWGK,
ConvFwdDefault>{});
add_device_operation_instances(instances,
device_grouped_conv_fwd_xdl_bf8_instances<3,
NDHWGC,
GKZYXC,
Empty_Tuple,
NDHWGK,
ConvFwd1x1P0>{});
add_device_operation_instances(instances,
device_grouped_conv_fwd_xdl_bf8_instances<3,
NDHWGC,
GKZYXC,
Empty_Tuple,
NDHWGK,
ConvFwd1x1S1P0>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
add_instance_library(device_permute_scale_instance
device_permute_scale_1d_instances.cpp
device_permute_scale_2d_instances.cpp
device_permute_scale_3d_instances.cpp
device_permute_scale_4d_instances.cpp
device_permute_scale_5d_instances.cpp
device_permute_scale_6d_instances.cpp)
device_permute_scale_1d_fp16_instances.cpp
device_permute_scale_2d_fp16_instances.cpp
device_permute_scale_3d_fp16_instances.cpp
device_permute_scale_4d_fp16_instances.cpp
device_permute_scale_5d_fp16_instances.cpp
device_permute_scale_6d_fp16_instances.cpp
device_permute_scale_1d_fp32_instances.cpp
device_permute_scale_2d_fp32_instances.cpp
device_permute_scale_3d_fp32_instances.cpp
device_permute_scale_4d_fp32_instances.cpp
device_permute_scale_5d_fp32_instances.cpp
device_permute_scale_6d_fp32_instances.cpp)
......@@ -9,18 +9,13 @@ namespace tensor_operation {
namespace device {
namespace instance {
void add_device_permute_scale_1d_f16_instances(
std::vector<std::unique_ptr<
DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, Pass, UnaryOp, Scale, 1>>>& instances)
{
add_device_operation_instances(instances, device_permute_scale_f16_instances<1>{});
}
using Scale = element_wise::Scale;
void add_device_permute_scale_1d_f32_instances(
std::vector<std::unique_ptr<
DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, Pass, UnaryOp, Scale, 1>>>& instances)
void add_device_permute_scale_1d_f16_instances(
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, Scale, 1>>>&
instances)
{
add_device_operation_instances(instances, device_permute_scale_f32_instances<1>{});
add_device_operation_instances(instances, device_permute_scale_f16_instances<1, Scale>{});
}
} // namespace instance
......
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/tensor_operation_instance/gpu/permute_scale/device_permute_scale_instances.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using Scale = element_wise::Scale;
void add_device_permute_scale_1d_f32_instances(
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, Scale, 1>>>&
instances)
{
add_device_operation_instances(instances, device_permute_scale_f32_instances<1, Scale>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
......@@ -9,18 +9,13 @@ namespace tensor_operation {
namespace device {
namespace instance {
void add_device_permute_scale_2d_f16_instances(
std::vector<std::unique_ptr<
DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, Pass, UnaryOp, Scale, 2>>>& instances)
{
add_device_operation_instances(instances, device_permute_scale_f16_instances<2>{});
}
using Scale = element_wise::Scale;
void add_device_permute_scale_2d_f32_instances(
std::vector<std::unique_ptr<
DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, Pass, UnaryOp, Scale, 2>>>& instances)
void add_device_permute_scale_2d_f16_instances(
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, Scale, 2>>>&
instances)
{
add_device_operation_instances(instances, device_permute_scale_f32_instances<2>{});
add_device_operation_instances(instances, device_permute_scale_f16_instances<2, Scale>{});
}
} // namespace instance
......
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/tensor_operation_instance/gpu/permute_scale/device_permute_scale_instances.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using Scale = element_wise::Scale;
void add_device_permute_scale_2d_f32_instances(
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, Scale, 2>>>&
instances)
{
add_device_operation_instances(instances, device_permute_scale_f32_instances<2, Scale>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
......@@ -9,18 +9,13 @@ namespace tensor_operation {
namespace device {
namespace instance {
void add_device_permute_scale_3d_f16_instances(
std::vector<std::unique_ptr<
DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, Pass, UnaryOp, Scale, 3>>>& instances)
{
add_device_operation_instances(instances, device_permute_scale_f16_instances<3>{});
}
using Scale = element_wise::Scale;
void add_device_permute_scale_3d_f32_instances(
std::vector<std::unique_ptr<
DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, Pass, UnaryOp, Scale, 3>>>& instances)
void add_device_permute_scale_3d_f16_instances(
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, Scale, 3>>>&
instances)
{
add_device_operation_instances(instances, device_permute_scale_f32_instances<3>{});
add_device_operation_instances(instances, device_permute_scale_f16_instances<3, Scale>{});
}
} // namespace instance
......
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/tensor_operation_instance/gpu/permute_scale/device_permute_scale_instances.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using Scale = element_wise::Scale;
void add_device_permute_scale_3d_f32_instances(
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, Scale, 3>>>&
instances)
{
add_device_operation_instances(instances, device_permute_scale_f32_instances<3, Scale>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
......@@ -9,18 +9,13 @@ namespace tensor_operation {
namespace device {
namespace instance {
void add_device_permute_scale_4d_f16_instances(
std::vector<std::unique_ptr<
DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, Pass, UnaryOp, Scale, 4>>>& instances)
{
add_device_operation_instances(instances, device_permute_scale_f16_instances<4>{});
}
using Scale = element_wise::Scale;
void add_device_permute_scale_4d_f32_instances(
std::vector<std::unique_ptr<
DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, Pass, UnaryOp, Scale, 4>>>& instances)
void add_device_permute_scale_4d_f16_instances(
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, Scale, 4>>>&
instances)
{
add_device_operation_instances(instances, device_permute_scale_f32_instances<4>{});
add_device_operation_instances(instances, device_permute_scale_f16_instances<4, Scale>{});
}
} // namespace instance
......
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/tensor_operation_instance/gpu/permute_scale/device_permute_scale_instances.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using Scale = element_wise::Scale;
void add_device_permute_scale_4d_f32_instances(
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, Scale, 4>>>&
instances)
{
add_device_operation_instances(instances, device_permute_scale_f32_instances<4, Scale>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
......@@ -9,18 +9,13 @@ namespace tensor_operation {
namespace device {
namespace instance {
void add_device_permute_scale_5d_f16_instances(
std::vector<std::unique_ptr<
DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, Pass, UnaryOp, Scale, 5>>>& instances)
{
add_device_operation_instances(instances, device_permute_scale_f16_instances<5>{});
}
using Scale = element_wise::Scale;
void add_device_permute_scale_5d_f32_instances(
std::vector<std::unique_ptr<
DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, Pass, UnaryOp, Scale, 5>>>& instances)
void add_device_permute_scale_5d_f16_instances(
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, Scale, 5>>>&
instances)
{
add_device_operation_instances(instances, device_permute_scale_f32_instances<5>{});
add_device_operation_instances(instances, device_permute_scale_f16_instances<5, Scale>{});
}
} // namespace instance
......
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/tensor_operation_instance/gpu/permute_scale/device_permute_scale_instances.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using Scale = element_wise::Scale;
void add_device_permute_scale_5d_f32_instances(
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, Scale, 5>>>&
instances)
{
add_device_operation_instances(instances, device_permute_scale_f32_instances<5, Scale>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
......@@ -9,18 +9,13 @@ namespace tensor_operation {
namespace device {
namespace instance {
void add_device_permute_scale_6d_f16_instances(
std::vector<std::unique_ptr<
DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, Pass, UnaryOp, Scale, 6>>>& instances)
{
add_device_operation_instances(instances, device_permute_scale_f16_instances<6>{});
}
using Scale = element_wise::Scale;
void add_device_permute_scale_6d_f32_instances(
std::vector<std::unique_ptr<
DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, Pass, UnaryOp, Scale, 6>>>& instances)
void add_device_permute_scale_6d_f16_instances(
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, Scale, 6>>>&
instances)
{
add_device_operation_instances(instances, device_permute_scale_f32_instances<6>{});
add_device_operation_instances(instances, device_permute_scale_f16_instances<6, Scale>{});
}
} // namespace instance
......
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/tensor_operation_instance/gpu/permute_scale/device_permute_scale_instances.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using Scale = element_wise::Scale;
void add_device_permute_scale_6d_f32_instances(
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, Scale, 6>>>&
instances)
{
add_device_operation_instances(instances, device_permute_scale_f32_instances<6, Scale>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
......@@ -8,9 +8,9 @@
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_elementwise_scale.hpp"
#include "ck/tensor_operation/gpu/device/device_elementwise.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_elementwise_scale_impl.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_elementwise_dynamic_vector_dims_impl.hpp"
#include "ck/library/tensor_operation_instance/gpu/permute_scale.hpp"
......@@ -21,23 +21,12 @@
#include "ck/library/utility/literals.hpp"
namespace ck {
template <typename HostTensorA,
typename HostTensorB,
typename AElementOp,
typename BElementOp,
typename ScaleElementOp>
template <typename HostTensorA, typename HostTensorB, typename ElementOp>
void reference_permute_scale(HostTensorB& b_tensor,
const HostTensorA& a_tensor,
AElementOp a_tensor_op,
BElementOp b_tensor_op,
ScaleElementOp scale_op)
ElementOp tensor_op)
{
b_tensor.ForEach([&](auto& self, auto idx) {
auto tmp_val = a_tensor(idx);
b_tensor_op(tmp_val, tmp_val);
scale_op(tmp_val, tmp_val);
a_tensor_op(self(idx), tmp_val);
});
b_tensor.ForEach([&](auto& self, auto idx) { tensor_op(self(idx), a_tensor(idx)); });
}
namespace profiler {
......@@ -54,9 +43,7 @@ bool profile_permute_scale_impl(int do_verification,
bool pass = true;
bool instance_found = false;
using ElementOp = ck::tensor_operation::element_wise::PassThrough;
using UnaryOp = ck::tensor_operation::element_wise::UnarySquare;
using Scale = ck::tensor_operation::element_wise::Scale;
using ElementOp = ck::tensor_operation::element_wise::Scale;
float scale = 2.f;
Tensor<ADataType> a(lengths_vector, input_strides_vector);
......@@ -80,12 +67,8 @@ bool profile_permute_scale_impl(int do_verification,
std::array<const void*, 1> input = {a_device_buf.GetDeviceBuffer()};
std::array<void*, 1> output = {b_device_buf.GetDeviceBuffer()};
using DeviceOp = ck::tensor_operation::device::DeviceElementwise<ck::Tuple<ADataType>,
ck::Tuple<BDataType>,
ElementOp,
UnaryOp,
Scale,
NumDim>;
using DeviceOp = ck::tensor_operation::device::
DeviceElementwise<ck::Tuple<ADataType>, ck::Tuple<BDataType>, ElementOp, NumDim>;
// get device op instances
const auto op_ptrs = ck::tensor_operation::device::instance::DeviceOperationInstanceFactory<
......@@ -100,7 +83,7 @@ bool profile_permute_scale_impl(int do_verification,
if(do_verification)
{
reference_permute_scale(host_b, a, ElementOp{}, UnaryOp{}, Scale{scale});
reference_permute_scale(host_b, a, ElementOp{scale});
}
auto copy = [](const auto& x, auto& y) { std::copy(x.begin(), x.end(), y.begin()); };
......@@ -113,14 +96,8 @@ bool profile_permute_scale_impl(int do_verification,
for(auto& op_ptr : op_ptrs)
{
auto argument_ptr = op_ptr->MakeArgumentPointer(lengths,
{input_strides},
{output_strides},
input,
output,
ElementOp{},
UnaryOp{},
Scale{scale});
auto argument_ptr = op_ptr->MakeArgumentPointer(
lengths, {input_strides}, {output_strides}, input, output, ElementOp{scale});
auto invoker_ptr = op_ptr->MakeInvokerPointer();
......@@ -141,6 +118,7 @@ bool profile_permute_scale_impl(int do_verification,
if(do_log)
{
LogRangeAsType<float>(std::cout << "a : ", a.mData, ",") << std::endl;
LogRangeAsType<float>(std::cout << "host_b: ", host_b.mData, ",") << std::endl;
LogRangeAsType<float>(std::cout << "b: ", b.mData, ",") << std::endl;
}
}
......
......@@ -24,6 +24,7 @@ enum struct ConvDataType
BF16_BF16_BF16, // 2
INT8_INT8_INT8, // 3
F8_F8_F8, // 4
BF8_BF8_F8, // 5
};
#define OP_NAME "grouped_conv_fwd"
......@@ -38,7 +39,8 @@ static void print_helper_msg()
<< " 1: Input fp16, Weight fp16, Output fp16\n"
<< " 2: Input bf16, Weight bf16, Output bf16\n"
<< " 3: Input int8, Weight int8, Output int8\n"
<< " 4: Input fp8, Weight fp8, Output fp8)\n"
<< " 4: Input fp8, Weight fp8, Output fp8\n"
<< " 5: Input bf8, Weight bf8, Output fp8)\n"
<< "arg3: tensor layout (0: Input[G, N, Hi, Wi, C], Weight[G, K, Y, X, C], Output[G, N, Ho, Wo, K]\n"
<< " 1: Input[N, Hi, Wi, G, C], Weight[G, K, Y, X, C], Output[N, Ho, Wo, G, K])\n"
<< "arg4: verification (0: no, 1: yes)\n"
......@@ -82,6 +84,7 @@ int profile_grouped_conv_fwd(int argc, char* argv[])
using BF16 = ck::bhalf_t;
using INT8 = int8_t;
using F8 = ck::f8_t;
using BF8 = ck::bf8_t;
//
using GNWC = ck::tensor_layout::convolution::GNWC;
......@@ -257,6 +260,10 @@ int profile_grouped_conv_fwd(int argc, char* argv[])
{
return profile(I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, F8{}, F8{}, F8{});
}
else if(data_type == ConvDataType::BF8_BF8_F8)
{
return profile(I3, NDHWGC{}, GKZYXC{}, NDHWGK{}, BF8{}, BF8{}, F8{});
}
}
std::cout << "this data_type & layout is not implemented" << std::endl;
......
......@@ -37,6 +37,20 @@ static void print_helper_msg()
// clang-format on
}
void init_strides(const std::vector<ck::index_t>& lengths,
const std::vector<ck::index_t>& dims_order,
std::vector<ck::index_t>& strides)
{
ck::index_t stride = 1;
for(ck::index_t d = lengths.size() - 1; d >= 0; d--)
{
ck::index_t dim = dims_order[d];
strides[dim] = stride;
stride *= lengths[dim];
}
}
} // namespace
int profile_permute_scale(int argc, char* argv[])
......@@ -58,16 +72,21 @@ int profile_permute_scale(int argc, char* argv[])
const int num_dims = dims_argc / 3;
std::vector<ck::index_t> lengths(num_dims);
std::vector<ck::index_t> input_strides(num_dims);
std::vector<ck::index_t> output_strides(num_dims);
std::vector<ck::index_t> input_dims_order(num_dims);
std::vector<ck::index_t> output_dims_order(num_dims);
for(int i = 0; i < num_dims; i++)
{
lengths[i] = std::stoi(argv[control_argc + i]);
input_strides[i] = std::stoi(argv[control_argc + num_dims + i]);
output_strides[i] = std::stoi(argv[control_argc + 2 * num_dims + i]);
input_dims_order[i] = std::stoi(argv[control_argc + num_dims + i]);
output_dims_order[i] = std::stoi(argv[control_argc + 2 * num_dims + i]);
}
std::vector<ck::index_t> input_strides(num_dims);
std::vector<ck::index_t> output_strides(num_dims);
init_strides(lengths, input_dims_order, input_strides);
init_strides(lengths, output_dims_order, output_strides);
using F32 = float;
using F16 = ck::half_t;
......
#!/bin/bash
## GPU visibility
export HIP_VISIBLE_DEVICES=0
DRIVER="../build/bin/ckProfiler"
echo $DRIVER
OP=$1
DATATYPE=$2
VERIFY=$3
INIT=$4
LOG=$5
TIME=$6
# 1D
######## op datatype verify init log time dims in_strides_order out_strides_order
$DRIVER $OP $DATATYPE $VERIFY $INIT $LOG $TIME 67108864 0 0
# # 2D
# ######## op datatype verify init log time dims in_strides_order out_strides_order
$DRIVER $OP $DATATYPE $VERIFY $INIT $LOG $TIME 8192 8192 0 1 1 0
$DRIVER $OP $DATATYPE $VERIFY $INIT $LOG $TIME 8192 8192 1 0 0 1
# 3D
######## op datatype verify init log time dims in_strides_order out_strides_order
$DRIVER $OP $DATATYPE $VERIFY $INIT $LOG $TIME 8 1024 8192 0 1 2 2 1 0
$DRIVER $OP $DATATYPE $VERIFY $INIT $LOG $TIME 8 1024 8192 2 1 0 0 1 2
# 4D
######## op datatype verify init log time dims in_strides_order out_strides_order
$DRIVER $OP $DATATYPE $VERIFY $INIT $LOG $TIME 8 2 512 8192 0 1 2 3 3 2 1 0
$DRIVER $OP $DATATYPE $VERIFY $INIT $LOG $TIME 8 2 512 8192 3 2 1 0 0 1 2 3
# 5D
######## op datatype verify init log time dims in_strides_order out_strides_order
$DRIVER $OP $DATATYPE $VERIFY $INIT $LOG $TIME 8 2 2 256 8192 0 1 2 3 4 4 3 2 1 0
$DRIVER $OP $DATATYPE $VERIFY $INIT $LOG $TIME 8 2 2 256 8192 4 3 2 1 0 0 1 2 3 4
# 6D
######## op datatype verify init log time dims in_strides_order out_strides_order
$DRIVER $OP $DATATYPE $VERIFY $INIT $LOG $TIME 8 2 2 2 128 8192 0 1 2 3 4 5 5 4 3 2 1 0
$DRIVER $OP $DATATYPE $VERIFY $INIT $LOG $TIME 8 2 2 2 128 8192 5 4 3 2 1 0 0 1 2 3 4 5
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