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https://github.com/ROCm/composable_kernel.git
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427 lines
24 KiB
C++
427 lines
24 KiB
C++
#include <algorithm>
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#include <cmath>
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#include <cstdlib>
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#include <half.hpp>
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#include <numeric>
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#include <type_traits>
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#include <vector>
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#include "config.hpp"
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#include "conv_utils.hpp"
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#include "element_wise_operation.hpp"
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#include "host_tensor.hpp"
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#include "reference_conv_fwd.hpp"
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#include "tensor_layout.hpp"
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#include "test_util.hpp"
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namespace {
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using InElementOp = ck::tensor_operation::element_wise::PassThrough;
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using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
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using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
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template <typename T>
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struct FillMonotonicSeq
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{
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T m_init_value{0};
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T m_step{1};
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template <typename ForwardIter>
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void operator()(ForwardIter first, ForwardIter last) const
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{
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std::generate(first, last, [=, n = m_init_value]() mutable {
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auto tmp = n;
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n += m_step;
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return tmp;
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});
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}
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};
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template <typename T>
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struct FillConstant
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{
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T m_value{0};
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template <typename ForwardIter>
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void operator()(ForwardIter first, ForwardIter last) const
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{
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std::fill(first, last, m_value);
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}
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};
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template <ck::index_t NDim,
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typename InDataType = float,
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typename WeiDataType = float,
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typename OutDataType = float,
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typename InLayout = ck::tensor_layout::convolution::NHWC,
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typename WeiLayout = ck::tensor_layout::convolution::KYXC,
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typename OutLayout = ck::tensor_layout::convolution::NHWK,
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typename FillInputOp = FillMonotonicSeq<InDataType>,
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typename FillWeightsOp = FillConstant<WeiDataType>>
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Tensor<OutDataType> RunReferenceConv(const ck::conv_util::ConvParams& params,
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const FillInputOp& fill_input_op = FillInputOp{},
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const FillWeightsOp& fill_weights_op = FillWeightsOp{0.5f})
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{
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std::vector<std::size_t> input_dims{static_cast<std::size_t>(params.N),
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static_cast<std::size_t>(params.C)};
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input_dims.insert(std::end(input_dims),
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std::begin(params.input_spatial_lengths),
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std::end(params.input_spatial_lengths));
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std::vector<std::size_t> filter_dims{static_cast<std::size_t>(params.K),
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static_cast<std::size_t>(params.C)};
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filter_dims.insert(std::end(filter_dims),
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std::begin(params.filter_spatial_lengths),
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std::end(params.filter_spatial_lengths));
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const std::vector<ck::index_t>& output_spatial_lengths = params.GetOutputSpatialLengths();
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std::vector<std::size_t> output_dims{static_cast<std::size_t>(params.N),
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static_cast<std::size_t>(params.K)};
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output_dims.insert(std::end(output_dims),
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std::begin(output_spatial_lengths),
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std::end(output_spatial_lengths));
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Tensor<InDataType> input(ck::conv_util::GetHostTensorDescriptor(input_dims, InLayout{}));
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Tensor<WeiDataType> weights(ck::conv_util::GetHostTensorDescriptor(filter_dims, WeiLayout{}));
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Tensor<OutDataType> host_output(
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ck::conv_util::GetHostTensorDescriptor(output_dims, OutLayout{}));
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fill_input_op(input.begin(), input.end());
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fill_weights_op(weights.begin(), weights.end());
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std::fill(host_output.begin(), host_output.end(), OutDataType(0.f));
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// std::cout <<"input: " << input.mDesc << std::endl << input.mData << std::endl;
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// std::cout <<"weight: " << weights.mDesc << std::endl << weights.mData << std::endl;
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auto ref_conv = ck::tensor_operation::host::ReferenceConvFwd<InDataType,
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WeiDataType,
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OutDataType,
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InElementOp,
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WeiElementOp,
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OutElementOp,
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NDim>();
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auto ref_invoker = ref_conv.MakeInvoker();
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auto ref_argument = ref_conv.MakeArgument(input,
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weights,
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host_output,
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params.conv_filter_strides,
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params.conv_filter_dilations,
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params.input_left_pads,
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params.input_right_pads,
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InElementOp{},
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WeiElementOp{},
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OutElementOp{});
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ref_invoker.Run(ref_argument);
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// std::cout <<"output: " << host_output.mDesc << std::endl << host_output.mData << std::endl;
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return host_output;
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}
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bool TestConv2DNHWC()
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{
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bool res{true};
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ck::conv_util::ConvParams params;
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params.N = 1;
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params.K = 1;
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params.C = 2;
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params.filter_spatial_lengths = std::vector<ck::index_t>{3, 3};
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params.input_spatial_lengths = std::vector<ck::index_t>{6, 6};
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params.conv_filter_strides = std::vector<ck::index_t>{1, 1};
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params.conv_filter_dilations = std::vector<ck::index_t>{1, 1};
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params.input_left_pads = std::vector<ck::index_t>{0, 0};
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params.input_right_pads = std::vector<ck::index_t>{0, 0};
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auto out_tensor = RunReferenceConv<2>(params);
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std::vector<std::size_t> ref_dims{1, 1, 4, 4};
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std::vector<float> ref_data{130.5,
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148.5,
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166.5,
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184.5,
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238.5,
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256.5,
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274.5,
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292.5,
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346.5,
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364.5,
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382.5,
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400.5,
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454.5,
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472.5,
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490.5,
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508.5};
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res = res && test::check_err(out_tensor.mDesc.GetLengths(),
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ref_dims,
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"Error: wrong output tensor dimensions!");
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res = res && test::check_err(out_tensor.mData, ref_data, "Error: incorrect results!");
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params.N = 1;
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params.K = 2;
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params.C = 2;
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params.filter_spatial_lengths = std::vector<ck::index_t>{3, 3};
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params.input_spatial_lengths = std::vector<ck::index_t>{12, 12};
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params.conv_filter_strides = std::vector<ck::index_t>{2, 2};
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params.conv_filter_dilations = std::vector<ck::index_t>{2, 2};
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params.input_left_pads = std::vector<ck::index_t>{1, 1};
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params.input_right_pads = std::vector<ck::index_t>{1, 1};
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out_tensor = RunReferenceConv<2>(params);
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ref_dims = std::vector<std::size_t>{1, 2, 5, 5};
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ref_data = std::vector<float>{
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210., 210., 327., 327., 351., 351., 375., 375., 399., 399.,
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459., 459., 706.5, 706.5, 742.5, 742.5, 778.5, 778.5, 814.5, 814.5,
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747., 747., 1138.5, 1138.5, 1174.5, 1174.5, 1210.5, 1210.5, 1246.5, 1246.5,
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1035., 1035., 1570.5, 1570.5, 1606.5, 1606.5, 1642.5, 1642.5, 1678.5, 1678.5,
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1323., 1323., 2002.5, 2002.5, 2038.5, 2038.5, 2074.5, 2074.5, 2110.5, 2110.5};
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res = res && test::check_err(out_tensor.mDesc.GetLengths(),
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ref_dims,
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"Error: wrong output tensor dimensions!");
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res = res && test::check_err(out_tensor.mData, ref_data, "Error: incorrect results!");
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return res;
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}
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bool TestConv1DNWC()
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{
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bool res{true};
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ck::conv_util::ConvParams params;
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params.num_dim_spatial = 1;
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params.N = 1;
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params.K = 1;
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params.C = 2;
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params.filter_spatial_lengths = std::vector<ck::index_t>{3};
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params.input_spatial_lengths = std::vector<ck::index_t>{6};
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params.conv_filter_strides = std::vector<ck::index_t>{1};
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params.conv_filter_dilations = std::vector<ck::index_t>{1};
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params.input_left_pads = std::vector<ck::index_t>{0};
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params.input_right_pads = std::vector<ck::index_t>{0};
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auto out_tensor = RunReferenceConv<1,
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float,
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float,
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float,
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ck::tensor_layout::convolution::NWC,
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ck::tensor_layout::convolution::KXC,
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ck::tensor_layout::convolution::NWK>(params);
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std::vector<std::size_t> ref_dims{1, 1, 4};
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std::vector<float> ref_data{7.5, 13.5, 19.5, 25.5};
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res = res && test::check_err(out_tensor.mDesc.GetLengths(),
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ref_dims,
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"Error: wrong output tensor dimensions!");
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res = res && test::check_err(out_tensor.mData, ref_data, "Error: incorrect results!");
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params.num_dim_spatial = 1;
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params.N = 1;
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params.K = 2;
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params.C = 2;
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params.filter_spatial_lengths = std::vector<ck::index_t>{3};
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params.input_spatial_lengths = std::vector<ck::index_t>{12};
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params.conv_filter_strides = std::vector<ck::index_t>{2};
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params.conv_filter_dilations = std::vector<ck::index_t>{2};
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params.input_left_pads = std::vector<ck::index_t>{1};
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params.input_right_pads = std::vector<ck::index_t>{1};
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out_tensor = RunReferenceConv<1,
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float,
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float,
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float,
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ck::tensor_layout::convolution::NWC,
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ck::tensor_layout::convolution::KXC,
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ck::tensor_layout::convolution::NWK>(params);
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ref_dims = std::vector<std::size_t>{1, 2, 5};
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ref_data = std::vector<float>{9., 9., 19.5, 19.5, 31.5, 31.5, 43.5, 43.5, 55.5, 55.5};
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res = res && test::check_err(out_tensor.mDesc.GetLengths(),
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ref_dims,
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"Error: wrong output tensor dimensions!");
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res = res && test::check_err(out_tensor.mData, ref_data, "Error: incorrect results!");
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params.num_dim_spatial = 1;
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params.N = 2;
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params.K = 16;
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params.C = 4;
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params.filter_spatial_lengths = std::vector<ck::index_t>{3};
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params.input_spatial_lengths = std::vector<ck::index_t>{16};
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params.conv_filter_strides = std::vector<ck::index_t>{1};
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params.conv_filter_dilations = std::vector<ck::index_t>{1};
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params.input_left_pads = std::vector<ck::index_t>{1};
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params.input_right_pads = std::vector<ck::index_t>{1};
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auto out_tensor2 = RunReferenceConv<1,
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float,
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float,
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float,
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ck::tensor_layout::convolution::NWC,
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ck::tensor_layout::convolution::KXC,
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ck::tensor_layout::convolution::NWK>(
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params, FillMonotonicSeq<float>{0.f, 0.1f});
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ref_dims = std::vector<std::size_t>{2, 16, 16};
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ref_data = std::vector<float>{
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1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4,
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1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4,
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3.3, 3.3, 3.3, 3.3, 3.3, 3.3, 3.3, 3.3,
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3.3, 3.3, 3.3, 3.3, 3.3, 3.3, 3.3, 3.3,
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5.7, 5.7, 5.7, 5.7, 5.7, 5.7, 5.7, 5.7,
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5.7, 5.7, 5.7, 5.7, 5.7, 5.7, 5.7, 5.7,
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8.1, 8.1, 8.1, 8.1, 8.1, 8.1, 8.1, 8.1,
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8.1, 8.1, 8.1, 8.1, 8.1, 8.1, 8.1, 8.1,
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10.5, 10.5, 10.5, 10.5, 10.5, 10.5, 10.5, 10.5,
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10.5, 10.5, 10.5, 10.5, 10.5, 10.5, 10.5, 10.5,
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12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001,
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12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001,
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15.3, 15.3, 15.3, 15.3, 15.3, 15.3, 15.3, 15.3,
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15.3, 15.3, 15.3, 15.3, 15.3, 15.3, 15.3, 15.3,
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17.7, 17.7, 17.7, 17.7, 17.7, 17.7, 17.7, 17.7,
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17.7, 17.7, 17.7, 17.7, 17.7, 17.7, 17.7, 17.7,
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20.1, 20.1, 20.1, 20.1, 20.1, 20.1, 20.1, 20.1,
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20.1, 20.1, 20.1, 20.1, 20.1, 20.1, 20.1, 20.1,
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22.5, 22.5, 22.5, 22.5, 22.5, 22.5, 22.5, 22.5,
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22.5, 22.5, 22.5, 22.5, 22.5, 22.5, 22.5, 22.5,
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24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002,
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24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002,
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27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001,
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27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001,
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29.7, 29.7, 29.7, 29.7, 29.7, 29.7, 29.7, 29.7,
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29.7, 29.7, 29.7, 29.7, 29.7, 29.7, 29.7, 29.7,
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32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002,
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32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002,
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34.5, 34.5, 34.5, 34.5, 34.5, 34.5, 34.5, 34.5,
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34.5, 34.5, 34.5, 34.5, 34.5, 34.5, 34.5, 34.5,
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23.8, 23.8, 23.8, 23.8, 23.8, 23.8, 23.8, 23.8,
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23.8, 23.8, 23.8, 23.8, 23.8, 23.8, 23.8, 23.8,
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27., 27., 27., 27., 27., 27., 27., 27.,
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27., 27., 27., 27., 27., 27., 27., 27.,
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41.7, 41.7, 41.7, 41.7, 41.7, 41.7, 41.7, 41.7,
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41.7, 41.7, 41.7, 41.7, 41.7, 41.7, 41.7, 41.7,
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44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002,
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44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002,
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46.5, 46.5, 46.5, 46.5, 46.5, 46.5, 46.5, 46.5,
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46.5, 46.5, 46.5, 46.5, 46.5, 46.5, 46.5, 46.5,
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48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998,
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48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998,
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51.3, 51.3, 51.3, 51.3, 51.3, 51.3, 51.3, 51.3,
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51.3, 51.3, 51.3, 51.3, 51.3, 51.3, 51.3, 51.3,
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53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7,
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53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7,
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56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002,
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56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002,
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58.5, 58.5, 58.5, 58.5, 58.5, 58.5, 58.5, 58.5,
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58.5, 58.5, 58.5, 58.5, 58.5, 58.5, 58.5, 58.5,
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60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998,
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60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998,
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63.3, 63.3, 63.3, 63.3, 63.3, 63.3, 63.3, 63.3,
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63.3, 63.3, 63.3, 63.3, 63.3, 63.3, 63.3, 63.3,
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65.7, 65.7, 65.7, 65.7, 65.7, 65.7, 65.7, 65.7,
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65.7, 65.7, 65.7, 65.7, 65.7, 65.7, 65.7, 65.7,
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68.1, 68.1, 68.1, 68.1, 68.1, 68.1, 68.1, 68.1,
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68.1, 68.1, 68.1, 68.1, 68.1, 68.1, 68.1, 68.1,
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70.5, 70.5, 70.5, 70.5, 70.5, 70.5, 70.5, 70.5,
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70.5, 70.5, 70.5, 70.5, 70.5, 70.5, 70.5, 70.5,
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72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9,
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72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9,
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49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4,
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49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4};
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res = res && test::check_err(out_tensor2.mDesc.GetLengths(),
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ref_dims,
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"Error: wrong output tensor dimensions!");
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res = res && test::check_err(out_tensor2.mData, ref_data, "Error: incorrect results!");
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return res;
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}
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bool TestConv3DNCDHW()
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{
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bool res{true};
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ck::conv_util::ConvParams params;
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params.num_dim_spatial = 3;
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params.N = 1;
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params.K = 1;
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params.C = 2;
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params.filter_spatial_lengths = std::vector<ck::index_t>{3, 3, 3};
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params.input_spatial_lengths = std::vector<ck::index_t>{6, 6, 6};
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params.conv_filter_strides = std::vector<ck::index_t>{1, 1, 1};
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params.conv_filter_dilations = std::vector<ck::index_t>{1, 1, 1};
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params.input_left_pads = std::vector<ck::index_t>{0, 0, 0};
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params.input_right_pads = std::vector<ck::index_t>{0, 0, 0};
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auto out_tensor = RunReferenceConv<3,
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float,
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float,
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float,
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ck::tensor_layout::convolution::NCDHW,
|
|
ck::tensor_layout::convolution::KCZYX,
|
|
ck::tensor_layout::convolution::NKDHW>(
|
|
params, FillMonotonicSeq<float>{0.f, 0.1f});
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|
std::vector<std::size_t> ref_dims{1, 1, 4, 4, 4};
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|
std::vector<float> ref_data{
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|
407.7, 410.40002, 413.09998, 415.80002, 423.90002, 426.6, 429.30002, 432.,
|
|
440.1, 442.80002, 445.5, 448.2, 456.30002, 459., 461.7, 464.40002,
|
|
504.90002, 507.6, 510.30002, 513., 521.1, 523.8, 526.5, 529.2001,
|
|
537.3, 540., 542.7001, 545.4, 553.5, 556.2001, 558.9, 561.6,
|
|
602.10004, 604.8, 607.5, 610.2, 618.3, 621., 623.7, 626.4,
|
|
634.5, 637.2, 639.9, 642.60004, 650.7, 653.4, 656.10004, 658.8,
|
|
699.3, 702., 704.7, 707.4, 715.5, 718.2, 720.9, 723.60004,
|
|
731.7, 734.4001, 737.10004, 739.8, 747.9001, 750.60004, 753.3, 756.};
|
|
res = res && test::check_err(out_tensor.mDesc.GetLengths(),
|
|
ref_dims,
|
|
"Error [case 1]: wrong output tensor dimensions!");
|
|
res = res && test::check_err(out_tensor.mData, ref_data, "Error [case 1]: incorrect results!");
|
|
|
|
params.N = 1;
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|
params.K = 2;
|
|
params.C = 2;
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|
params.filter_spatial_lengths = std::vector<ck::index_t>{3, 3, 3};
|
|
params.input_spatial_lengths = std::vector<ck::index_t>{12, 12, 12};
|
|
params.conv_filter_strides = std::vector<ck::index_t>{3, 3, 3};
|
|
params.conv_filter_dilations = std::vector<ck::index_t>{1, 1, 1};
|
|
params.input_left_pads = std::vector<ck::index_t>{0, 0, 0};
|
|
params.input_right_pads = std::vector<ck::index_t>{0, 0, 0};
|
|
|
|
out_tensor = RunReferenceConv<3,
|
|
float,
|
|
float,
|
|
float,
|
|
ck::tensor_layout::convolution::NCDHW,
|
|
ck::tensor_layout::convolution::KCZYX,
|
|
ck::tensor_layout::convolution::NKDHW>(
|
|
params, FillMonotonicSeq<float>{0.f, 0.1f});
|
|
ref_dims = std::vector<std::size_t>{1, 2, 4, 4, 4};
|
|
ref_data = std::vector<float>{
|
|
2756.7002, 2764.7998, 2772.9001, 2781., 2853.9001, 2862., 2870.1, 2878.2002,
|
|
2951.1, 2959.2002, 2967.2998, 2975.4001, 3048.2998, 3056.4001, 3064.5, 3072.6,
|
|
3923.1, 3931.2, 3939.2998, 3947.4, 4020.2998, 4028.4001, 4036.5002, 4044.5999,
|
|
4117.5, 4125.6, 4133.7, 4141.8, 4214.7, 4222.8, 4230.9004, 4239.,
|
|
5089.5, 5097.5996, 5105.7, 5113.8, 5186.7, 5194.8, 5202.9, 5211.,
|
|
5283.9004, 5292., 5300.0996, 5308.2, 5381.0996, 5389.2, 5397.3, 5405.4004,
|
|
6255.9004, 6264.0005, 6272.1, 6280.2, 6353.1, 6361.2, 6369.301, 6377.4,
|
|
6450.301, 6458.4, 6466.5, 6474.6, 6547.5, 6555.6, 6563.699, 6571.801,
|
|
2756.7002, 2764.7998, 2772.9001, 2781., 2853.9001, 2862., 2870.1, 2878.2002,
|
|
2951.1, 2959.2002, 2967.2998, 2975.4001, 3048.2998, 3056.4001, 3064.5, 3072.6,
|
|
3923.1, 3931.2, 3939.2998, 3947.4, 4020.2998, 4028.4001, 4036.5002, 4044.5999,
|
|
4117.5, 4125.6, 4133.7, 4141.8, 4214.7, 4222.8, 4230.9004, 4239.,
|
|
5089.5, 5097.5996, 5105.7, 5113.8, 5186.7, 5194.8, 5202.9, 5211.,
|
|
5283.9004, 5292., 5300.0996, 5308.2, 5381.0996, 5389.2, 5397.3, 5405.4004,
|
|
6255.9004, 6264.0005, 6272.1, 6280.2, 6353.1, 6361.2, 6369.301, 6377.4,
|
|
6450.301, 6458.4, 6466.5, 6474.6, 6547.5, 6555.6, 6563.699, 6571.801};
|
|
res = res && test::check_err(out_tensor.mDesc.GetLengths(),
|
|
ref_dims,
|
|
"Error [case 2]: wrong output tensor dimensions!");
|
|
res =
|
|
res && test::check_err(
|
|
out_tensor.mData, ref_data, "Error [case 2]: incorrect results!", 1e-4f, 1e-6f);
|
|
|
|
return res;
|
|
}
|
|
|
|
} // anonymous namespace
|
|
|
|
int main(void)
|
|
{
|
|
bool res{true};
|
|
res = TestConv2DNHWC();
|
|
std::cout << "TestConv2DNHWC ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
|
|
res = TestConv1DNWC();
|
|
std::cout << "TestConv1DNHWC ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
|
|
res = TestConv3DNCDHW();
|
|
std::cout << "TestConv3DNCDHW ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
|
|
return res ? 0 : 1;
|
|
}
|