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d85f065b15
* chore(copyright): update copyright header for codegen directory * chore(copyright): update copyright header for example directory
202 lines
8.9 KiB
C++
202 lines
8.9 KiB
C++
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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#pragma once
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#include <iostream>
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#include "ck/ck.hpp"
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#include "ck/utility/reduction_enums.hpp"
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#include "ck/utility/reduction_functions_accumulate.hpp"
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#include "ck/tensor_operation/gpu/device/reduction_operator_mapping.hpp"
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#include "ck/tensor_operation/gpu/device/impl/device_pool2d_fwd_nhwc_nhwc.hpp"
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#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
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#include "ck/library/utility/check_err.hpp"
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#include "ck/library/utility/device_memory.hpp"
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#include "ck/library/utility/host_tensor.hpp"
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#include "ck/library/utility/host_tensor_generator.hpp"
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#include "ck/library/utility/literals.hpp"
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#include "ck/library/reference_tensor_operation/cpu/reference_pool_fwd.hpp"
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using ::ck::DeviceMem;
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using ::ck::HostTensorDescriptor;
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using ::ck::Tensor;
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template <typename InDataType,
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typename OutDataType,
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typename ComputeDataType,
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typename IndexDataType,
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typename InLayout,
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typename OutLayout,
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ck::ReduceTensorOp ReduceOpId,
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bool PropagateNan,
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bool OutputIndex>
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bool pool_test(bool do_verification,
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int init_method,
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bool time_kernel,
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ck::index_t N,
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ck::index_t C,
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ck::index_t Y,
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ck::index_t X,
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ck::index_t Hi,
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ck::index_t Wi,
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ck::index_t window_stride_h,
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ck::index_t window_stride_w,
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ck::index_t window_dilation_h,
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ck::index_t window_dilation_w,
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ck::index_t in_left_pad_h,
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ck::index_t in_left_pad_w,
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ck::index_t in_right_pad_h,
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ck::index_t in_right_pad_w)
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{
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using DevicePoolFwdInstance =
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ck::tensor_operation::device::DevicePool2dFwd_NHWC_NHWC<InDataType,
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OutDataType,
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IndexDataType,
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ComputeDataType,
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ReduceOpId,
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OutputIndex,
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64, // BlockSize
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64, // ReduceMThreadClusterSize
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1, // ReduceKThreadClusterSize
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4, // ReduceMThreadSliceSize
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1, // ReduceKThreadSliceSize
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1>; // InSrcOutDstVectorSize
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const ck::index_t Ys = (Y - 1) * window_dilation_h + 1;
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const ck::index_t Xs = (X - 1) * window_dilation_w + 1;
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const ck::index_t Ho = (Hi + in_left_pad_h + in_right_pad_h - Ys) / window_stride_h + 1;
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const ck::index_t Wo = (Wi + in_left_pad_w + in_right_pad_w - Xs) / window_stride_w + 1;
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const std::vector<ck::index_t> window_spatial_lengths{Y, X};
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const std::vector<ck::index_t> window_strides{window_stride_h, window_stride_w};
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const std::vector<ck::index_t> window_dilations{window_dilation_h, window_dilation_w};
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const std::vector<ck::index_t> input_left_pads{in_left_pad_h, in_left_pad_w};
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const std::vector<ck::index_t> input_right_pads{in_right_pad_h, in_right_pad_w};
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// tensor layout
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auto f_host_tensor_descriptor =
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[](std::size_t N_, std::size_t C_, std::size_t H, std::size_t W, auto layout) {
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using namespace ck::literals;
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if constexpr(ck::is_same<decltype(layout), ck::tensor_layout::convolution::NCHW>::value)
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{
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return HostTensorDescriptor({N_, C_, H, W}, {C_ * H * W, H * W, W, 1_uz}, layout);
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}
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else if constexpr(ck::is_same<decltype(layout),
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ck::tensor_layout::convolution::NHWC>::value)
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{
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return HostTensorDescriptor({N_, C_, H, W}, {C_ * H * W, 1_uz, W * C_, C_}, layout);
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}
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};
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Tensor<InDataType> in_n_c_hi_wi(f_host_tensor_descriptor(N, C, Hi, Wi, InLayout{}));
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Tensor<OutDataType> out_n_c_ho_wo_host(f_host_tensor_descriptor(N, C, Ho, Wo, OutLayout{}));
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Tensor<IndexDataType> out_indices_n_c_ho_wo_host(
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f_host_tensor_descriptor(N, C, Ho, Wo, OutLayout{}));
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Tensor<OutDataType> out_n_c_ho_wo_device(f_host_tensor_descriptor(N, C, Ho, Wo, OutLayout{}));
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Tensor<IndexDataType> out_indices_n_c_ho_wo_device(
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f_host_tensor_descriptor(N, C, Ho, Wo, OutLayout{}));
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std::cout << "in_n_c_hi_wi: " << in_n_c_hi_wi.mDesc << std::endl;
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std::cout << "out_n_c_ho_wo: " << out_n_c_ho_wo_host.mDesc << std::endl;
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switch(init_method)
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{
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case 0: break;
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case 1: in_n_c_hi_wi.GenerateTensorValue(GeneratorTensor_1<InDataType>{1}); break;
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case 2: in_n_c_hi_wi.GenerateTensorValue(GeneratorTensor_2<InDataType>{-5, 5}); break;
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default: in_n_c_hi_wi.GenerateTensorValue(GeneratorTensor_3<InDataType>{-5.0, 5.0});
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}
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DeviceMem in_device_buf(sizeof(InDataType) * in_n_c_hi_wi.mDesc.GetElementSpaceSize());
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DeviceMem out_device_buf(sizeof(OutDataType) *
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out_n_c_ho_wo_device.mDesc.GetElementSpaceSize());
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DeviceMem out_indices_device_buf(sizeof(IndexDataType) *
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out_indices_n_c_ho_wo_device.mDesc.GetElementSpaceSize());
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in_device_buf.ToDevice(in_n_c_hi_wi.mData.data());
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auto pool = DevicePoolFwdInstance{};
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auto invoker_ptr = pool.MakeInvokerPointer();
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auto argument_ptr = pool.MakeArgumentPointer(
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static_cast<InDataType*>(in_device_buf.GetDeviceBuffer()),
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static_cast<OutDataType*>(out_device_buf.GetDeviceBuffer()),
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static_cast<IndexDataType*>(out_indices_device_buf.GetDeviceBuffer()),
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{N, C, Hi, Wi},
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{Y, X},
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{N, C, Ho, Wo},
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{C * Hi * Wi, 1, Wi * C, C},
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{C * Ho * Wo, 1, Wo * C, C},
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{C * Ho * Wo, 1, Wo * C, C},
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window_strides,
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window_dilations,
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input_left_pads,
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input_right_pads,
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{2, 3});
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if(!pool.IsSupportedArgument(argument_ptr.get()))
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{
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throw std::runtime_error("wrong! device_op with the specified compilation parameters does "
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"not support this problem");
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}
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float ave_time = invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, time_kernel});
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std::size_t flop = std::size_t(2) * N * C * Ho * Wo * Y * X;
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std::size_t num_btype =
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sizeof(InDataType) * (N * C * Hi * Wi) + sizeof(OutDataType) * (N * C * Ho * Wo);
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float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
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float gb_per_sec = num_btype / 1.E6 / ave_time;
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std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec
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<< " GB / s " << std::endl;
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bool pass = true;
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if(do_verification)
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{
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using ReferencePoolingFwdInstance =
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ck::tensor_operation::host::ReferencePoolingFwd<4,
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2,
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InDataType,
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OutDataType,
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ComputeDataType,
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IndexDataType,
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ReduceOpId,
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PropagateNan,
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OutputIndex>;
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auto ref_pooling = ReferencePoolingFwdInstance{};
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auto ref_pooling_invoker = ref_pooling.MakeInvoker();
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auto ref_pooling_argument = ref_pooling.MakeArgument(in_n_c_hi_wi,
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out_n_c_ho_wo_host,
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out_indices_n_c_ho_wo_host,
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window_spatial_lengths,
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window_strides,
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window_dilations,
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input_left_pads,
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input_right_pads);
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ref_pooling_invoker.Run(ref_pooling_argument);
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out_device_buf.FromDevice(out_n_c_ho_wo_device.mData.data());
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pass = pass && ck::utils::check_err(out_n_c_ho_wo_device, out_n_c_ho_wo_host);
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if constexpr(OutputIndex)
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{
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out_indices_device_buf.FromDevice(out_indices_n_c_ho_wo_device.mData.data());
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pass = pass &&
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ck::utils::check_err(out_indices_n_c_ho_wo_device, out_indices_n_c_ho_wo_host);
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};
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}
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return (pass);
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};
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