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add license in file (#303)
This commit is contained in:
Chao Liu
@@ -1,389 +1,392 @@
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#include <cmath>
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#include <cstdlib>
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#include <numeric>
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#include <type_traits>
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#include <vector>
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#include <gtest/gtest.h>
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#include "ck/ck.hpp"
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#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
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#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
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#include "ck/library/utility/check_err.hpp"
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#include "ck/library/utility/conv_util.hpp"
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#include "ck/library/utility/fill.hpp"
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#include "ck/library/host_tensor/host_tensor.hpp"
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#include "ck/library/reference_tensor_operation/cpu/reference_conv_fwd.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 <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 = ck::utils::FillMonotonicSeq<InDataType>,
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typename FillWeightsOp = ck::utils::FillConstant<WeiDataType>>
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Tensor<OutDataType>
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run_reference_convolution_forward(const ck::utils::conv::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::utils::conv::get_host_tensor_descriptor(input_dims, InLayout{}));
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Tensor<WeiDataType> weights(
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ck::utils::conv::get_host_tensor_descriptor(filter_dims, WeiLayout{}));
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Tensor<OutDataType> host_output(
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ck::utils::conv::get_host_tensor_descriptor(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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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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return host_output;
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}
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} // anonymous namespace
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TEST(ReferenceConvolutionFWD, Conv2DNHWC)
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{
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ck::utils::conv::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 = run_reference_convolution_forward<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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EXPECT_TRUE(ck::utils::check_err(
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out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
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EXPECT_TRUE(ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"));
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}
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TEST(ReferenceConvolutionFWD, Conv2DNHWCStridesDilationsPadding)
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{
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ck::utils::conv::ConvParams params;
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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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auto out_tensor = run_reference_convolution_forward<2>(params);
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std::vector<std::size_t> ref_dims = std::vector<std::size_t>{1, 2, 5, 5};
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std::vector<float> ref_data{
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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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EXPECT_TRUE(ck::utils::check_err(
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out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
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EXPECT_TRUE(ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"));
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}
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TEST(ReferenceConvolutionFWD, Conv1DNWC)
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{
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ck::utils::conv::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 =
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run_reference_convolution_forward<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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EXPECT_TRUE(ck::utils::check_err(
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out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
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EXPECT_TRUE(ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"));
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}
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TEST(ReferenceConvolutionFWD, Conv1DNWCStridesDilationsPadding)
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{
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ck::utils::conv::ConvParams params;
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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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auto out_tensor =
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run_reference_convolution_forward<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, 2, 5};
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std::vector<float> ref_data{9., 9., 19.5, 19.5, 31.5, 31.5, 43.5, 43.5, 55.5, 55.5};
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EXPECT_TRUE(ck::utils::check_err(
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out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
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EXPECT_TRUE(ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"));
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}
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TEST(ReferenceConvolutionFWD, Conv1DNWCSameOutputSize)
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{
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ck::utils::conv::ConvParams params;
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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 = run_reference_convolution_forward<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, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
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std::vector<std::size_t> ref_dims{2, 16, 16};
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std::vector<float> ref_data{
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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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EXPECT_TRUE(ck::utils::check_err(
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out_tensor2.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
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EXPECT_TRUE(ck::utils::check_err(out_tensor2.mData, ref_data, "Error: incorrect results!"));
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}
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TEST(ReferenceConvolutionFWD, Conv3DNCDHW)
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{
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ck::utils::conv::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};
|
||||
params.input_spatial_lengths_ = std::vector<ck::index_t>{6, 6, 6};
|
||||
params.conv_filter_strides_ = std::vector<ck::index_t>{1, 1, 1};
|
||||
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};
|
||||
|
||||
auto out_tensor = run_reference_convolution_forward<3,
|
||||
float,
|
||||
float,
|
||||
float,
|
||||
ck::tensor_layout::convolution::NCDHW,
|
||||
ck::tensor_layout::convolution::KCZYX,
|
||||
ck::tensor_layout::convolution::NKDHW>(
|
||||
params, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
|
||||
std::vector<std::size_t> ref_dims{1, 1, 4, 4, 4};
|
||||
std::vector<float> ref_data{
|
||||
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.};
|
||||
EXPECT_TRUE(ck::utils::check_err(out_tensor.mDesc.GetLengths(),
|
||||
ref_dims,
|
||||
"Error [case 1]: wrong output tensor dimensions!"));
|
||||
EXPECT_TRUE(
|
||||
ck::utils::check_err(out_tensor.mData, ref_data, "Error [case 1]: incorrect results!"));
|
||||
}
|
||||
|
||||
TEST(ReferenceConvolutionFWD, Conv3DNCDHWStridesDilations)
|
||||
{
|
||||
ck::utils::conv::ConvParams params;
|
||||
params.num_dim_spatial_ = 3;
|
||||
params.N_ = 1;
|
||||
params.K_ = 2;
|
||||
params.C_ = 2;
|
||||
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};
|
||||
|
||||
auto out_tensor = run_reference_convolution_forward<3,
|
||||
float,
|
||||
float,
|
||||
float,
|
||||
ck::tensor_layout::convolution::NCDHW,
|
||||
ck::tensor_layout::convolution::KCZYX,
|
||||
ck::tensor_layout::convolution::NKDHW>(
|
||||
params, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
|
||||
std::vector<std::size_t> ref_dims{1, 2, 4, 4, 4};
|
||||
std::vector<float> ref_data{
|
||||
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};
|
||||
EXPECT_TRUE(ck::utils::check_err(out_tensor.mDesc.GetLengths(),
|
||||
ref_dims,
|
||||
"Error [case 2]: wrong output tensor dimensions!"));
|
||||
EXPECT_TRUE(ck::utils::check_err(
|
||||
out_tensor.mData, ref_data, "Error [case 2]: incorrect results!", 1e-4f, 1e-6f));
|
||||
}
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include <cmath>
|
||||
#include <cstdlib>
|
||||
#include <numeric>
|
||||
#include <type_traits>
|
||||
#include <vector>
|
||||
#include <gtest/gtest.h>
|
||||
|
||||
#include "ck/ck.hpp"
|
||||
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
|
||||
|
||||
#include "ck/library/utility/check_err.hpp"
|
||||
#include "ck/library/utility/conv_util.hpp"
|
||||
#include "ck/library/utility/fill.hpp"
|
||||
#include "ck/library/host_tensor/host_tensor.hpp"
|
||||
#include "ck/library/reference_tensor_operation/cpu/reference_conv_fwd.hpp"
|
||||
|
||||
namespace {
|
||||
using InElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
|
||||
template <ck::index_t NDim,
|
||||
typename InDataType = float,
|
||||
typename WeiDataType = float,
|
||||
typename OutDataType = float,
|
||||
typename InLayout = ck::tensor_layout::convolution::NHWC,
|
||||
typename WeiLayout = ck::tensor_layout::convolution::KYXC,
|
||||
typename OutLayout = ck::tensor_layout::convolution::NHWK,
|
||||
typename FillInputOp = ck::utils::FillMonotonicSeq<InDataType>,
|
||||
typename FillWeightsOp = ck::utils::FillConstant<WeiDataType>>
|
||||
Tensor<OutDataType>
|
||||
run_reference_convolution_forward(const ck::utils::conv::ConvParams& params,
|
||||
const FillInputOp& fill_input_op = FillInputOp{},
|
||||
const FillWeightsOp& fill_weights_op = FillWeightsOp{0.5f})
|
||||
{
|
||||
std::vector<std::size_t> input_dims{static_cast<std::size_t>(params.N_),
|
||||
static_cast<std::size_t>(params.C_)};
|
||||
input_dims.insert(std::end(input_dims),
|
||||
std::begin(params.input_spatial_lengths_),
|
||||
std::end(params.input_spatial_lengths_));
|
||||
|
||||
std::vector<std::size_t> filter_dims{static_cast<std::size_t>(params.K_),
|
||||
static_cast<std::size_t>(params.C_)};
|
||||
filter_dims.insert(std::end(filter_dims),
|
||||
std::begin(params.filter_spatial_lengths_),
|
||||
std::end(params.filter_spatial_lengths_));
|
||||
|
||||
const std::vector<ck::index_t>& output_spatial_lengths = params.GetOutputSpatialLengths();
|
||||
std::vector<std::size_t> output_dims{static_cast<std::size_t>(params.N_),
|
||||
static_cast<std::size_t>(params.K_)};
|
||||
output_dims.insert(std::end(output_dims),
|
||||
std::begin(output_spatial_lengths),
|
||||
std::end(output_spatial_lengths));
|
||||
|
||||
Tensor<InDataType> input(ck::utils::conv::get_host_tensor_descriptor(input_dims, InLayout{}));
|
||||
Tensor<WeiDataType> weights(
|
||||
ck::utils::conv::get_host_tensor_descriptor(filter_dims, WeiLayout{}));
|
||||
Tensor<OutDataType> host_output(
|
||||
ck::utils::conv::get_host_tensor_descriptor(output_dims, OutLayout{}));
|
||||
|
||||
fill_input_op(input.begin(), input.end());
|
||||
fill_weights_op(weights.begin(), weights.end());
|
||||
std::fill(host_output.begin(), host_output.end(), OutDataType(0.f));
|
||||
|
||||
auto ref_conv = ck::tensor_operation::host::ReferenceConvFwd<InDataType,
|
||||
WeiDataType,
|
||||
OutDataType,
|
||||
InElementOp,
|
||||
WeiElementOp,
|
||||
OutElementOp,
|
||||
NDim>();
|
||||
auto ref_invoker = ref_conv.MakeInvoker();
|
||||
auto ref_argument = ref_conv.MakeArgument(input,
|
||||
weights,
|
||||
host_output,
|
||||
params.conv_filter_strides_,
|
||||
params.conv_filter_dilations_,
|
||||
params.input_left_pads_,
|
||||
params.input_right_pads_,
|
||||
InElementOp{},
|
||||
WeiElementOp{},
|
||||
OutElementOp{});
|
||||
|
||||
ref_invoker.Run(ref_argument);
|
||||
return host_output;
|
||||
}
|
||||
|
||||
} // anonymous namespace
|
||||
|
||||
TEST(ReferenceConvolutionFWD, Conv2DNHWC)
|
||||
{
|
||||
ck::utils::conv::ConvParams params;
|
||||
params.N_ = 1;
|
||||
params.K_ = 1;
|
||||
params.C_ = 2;
|
||||
params.filter_spatial_lengths_ = std::vector<ck::index_t>{3, 3};
|
||||
params.input_spatial_lengths_ = std::vector<ck::index_t>{6, 6};
|
||||
params.conv_filter_strides_ = std::vector<ck::index_t>{1, 1};
|
||||
params.conv_filter_dilations_ = std::vector<ck::index_t>{1, 1};
|
||||
params.input_left_pads_ = std::vector<ck::index_t>{0, 0};
|
||||
params.input_right_pads_ = std::vector<ck::index_t>{0, 0};
|
||||
|
||||
auto out_tensor = run_reference_convolution_forward<2>(params);
|
||||
std::vector<std::size_t> ref_dims{1, 1, 4, 4};
|
||||
std::vector<float> ref_data{130.5,
|
||||
148.5,
|
||||
166.5,
|
||||
184.5,
|
||||
238.5,
|
||||
256.5,
|
||||
274.5,
|
||||
292.5,
|
||||
346.5,
|
||||
364.5,
|
||||
382.5,
|
||||
400.5,
|
||||
454.5,
|
||||
472.5,
|
||||
490.5,
|
||||
508.5};
|
||||
EXPECT_TRUE(ck::utils::check_err(
|
||||
out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
|
||||
EXPECT_TRUE(ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"));
|
||||
}
|
||||
|
||||
TEST(ReferenceConvolutionFWD, Conv2DNHWCStridesDilationsPadding)
|
||||
{
|
||||
ck::utils::conv::ConvParams params;
|
||||
params.N_ = 1;
|
||||
params.K_ = 2;
|
||||
params.C_ = 2;
|
||||
params.filter_spatial_lengths_ = std::vector<ck::index_t>{3, 3};
|
||||
params.input_spatial_lengths_ = std::vector<ck::index_t>{12, 12};
|
||||
params.conv_filter_strides_ = std::vector<ck::index_t>{2, 2};
|
||||
params.conv_filter_dilations_ = std::vector<ck::index_t>{2, 2};
|
||||
params.input_left_pads_ = std::vector<ck::index_t>{1, 1};
|
||||
params.input_right_pads_ = std::vector<ck::index_t>{1, 1};
|
||||
|
||||
auto out_tensor = run_reference_convolution_forward<2>(params);
|
||||
std::vector<std::size_t> ref_dims = std::vector<std::size_t>{1, 2, 5, 5};
|
||||
std::vector<float> ref_data{
|
||||
210., 210., 327., 327., 351., 351., 375., 375., 399., 399.,
|
||||
459., 459., 706.5, 706.5, 742.5, 742.5, 778.5, 778.5, 814.5, 814.5,
|
||||
747., 747., 1138.5, 1138.5, 1174.5, 1174.5, 1210.5, 1210.5, 1246.5, 1246.5,
|
||||
1035., 1035., 1570.5, 1570.5, 1606.5, 1606.5, 1642.5, 1642.5, 1678.5, 1678.5,
|
||||
1323., 1323., 2002.5, 2002.5, 2038.5, 2038.5, 2074.5, 2074.5, 2110.5, 2110.5};
|
||||
EXPECT_TRUE(ck::utils::check_err(
|
||||
out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
|
||||
EXPECT_TRUE(ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"));
|
||||
}
|
||||
|
||||
TEST(ReferenceConvolutionFWD, Conv1DNWC)
|
||||
{
|
||||
ck::utils::conv::ConvParams params;
|
||||
params.num_dim_spatial_ = 1;
|
||||
params.N_ = 1;
|
||||
params.K_ = 1;
|
||||
params.C_ = 2;
|
||||
params.filter_spatial_lengths_ = std::vector<ck::index_t>{3};
|
||||
params.input_spatial_lengths_ = std::vector<ck::index_t>{6};
|
||||
params.conv_filter_strides_ = std::vector<ck::index_t>{1};
|
||||
params.conv_filter_dilations_ = std::vector<ck::index_t>{1};
|
||||
params.input_left_pads_ = std::vector<ck::index_t>{0};
|
||||
params.input_right_pads_ = std::vector<ck::index_t>{0};
|
||||
|
||||
auto out_tensor =
|
||||
run_reference_convolution_forward<1,
|
||||
float,
|
||||
float,
|
||||
float,
|
||||
ck::tensor_layout::convolution::NWC,
|
||||
ck::tensor_layout::convolution::KXC,
|
||||
ck::tensor_layout::convolution::NWK>(params);
|
||||
std::vector<std::size_t> ref_dims{1, 1, 4};
|
||||
std::vector<float> ref_data{7.5, 13.5, 19.5, 25.5};
|
||||
EXPECT_TRUE(ck::utils::check_err(
|
||||
out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
|
||||
EXPECT_TRUE(ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"));
|
||||
}
|
||||
|
||||
TEST(ReferenceConvolutionFWD, Conv1DNWCStridesDilationsPadding)
|
||||
{
|
||||
ck::utils::conv::ConvParams params;
|
||||
params.num_dim_spatial_ = 1;
|
||||
params.N_ = 1;
|
||||
params.K_ = 2;
|
||||
params.C_ = 2;
|
||||
params.filter_spatial_lengths_ = std::vector<ck::index_t>{3};
|
||||
params.input_spatial_lengths_ = std::vector<ck::index_t>{12};
|
||||
params.conv_filter_strides_ = std::vector<ck::index_t>{2};
|
||||
params.conv_filter_dilations_ = std::vector<ck::index_t>{2};
|
||||
params.input_left_pads_ = std::vector<ck::index_t>{1};
|
||||
params.input_right_pads_ = std::vector<ck::index_t>{1};
|
||||
|
||||
auto out_tensor =
|
||||
run_reference_convolution_forward<1,
|
||||
float,
|
||||
float,
|
||||
float,
|
||||
ck::tensor_layout::convolution::NWC,
|
||||
ck::tensor_layout::convolution::KXC,
|
||||
ck::tensor_layout::convolution::NWK>(params);
|
||||
std::vector<std::size_t> ref_dims{1, 2, 5};
|
||||
std::vector<float> ref_data{9., 9., 19.5, 19.5, 31.5, 31.5, 43.5, 43.5, 55.5, 55.5};
|
||||
EXPECT_TRUE(ck::utils::check_err(
|
||||
out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
|
||||
EXPECT_TRUE(ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"));
|
||||
}
|
||||
|
||||
TEST(ReferenceConvolutionFWD, Conv1DNWCSameOutputSize)
|
||||
{
|
||||
ck::utils::conv::ConvParams params;
|
||||
params.num_dim_spatial_ = 1;
|
||||
params.N_ = 2;
|
||||
params.K_ = 16;
|
||||
params.C_ = 4;
|
||||
params.filter_spatial_lengths_ = std::vector<ck::index_t>{3};
|
||||
params.input_spatial_lengths_ = std::vector<ck::index_t>{16};
|
||||
params.conv_filter_strides_ = std::vector<ck::index_t>{1};
|
||||
params.conv_filter_dilations_ = std::vector<ck::index_t>{1};
|
||||
params.input_left_pads_ = std::vector<ck::index_t>{1};
|
||||
params.input_right_pads_ = std::vector<ck::index_t>{1};
|
||||
|
||||
auto out_tensor2 = run_reference_convolution_forward<1,
|
||||
float,
|
||||
float,
|
||||
float,
|
||||
ck::tensor_layout::convolution::NWC,
|
||||
ck::tensor_layout::convolution::KXC,
|
||||
ck::tensor_layout::convolution::NWK>(
|
||||
params, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
|
||||
|
||||
std::vector<std::size_t> ref_dims{2, 16, 16};
|
||||
std::vector<float> ref_data{
|
||||
1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4,
|
||||
1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4,
|
||||
3.3, 3.3, 3.3, 3.3, 3.3, 3.3, 3.3, 3.3,
|
||||
3.3, 3.3, 3.3, 3.3, 3.3, 3.3, 3.3, 3.3,
|
||||
5.7, 5.7, 5.7, 5.7, 5.7, 5.7, 5.7, 5.7,
|
||||
5.7, 5.7, 5.7, 5.7, 5.7, 5.7, 5.7, 5.7,
|
||||
8.1, 8.1, 8.1, 8.1, 8.1, 8.1, 8.1, 8.1,
|
||||
8.1, 8.1, 8.1, 8.1, 8.1, 8.1, 8.1, 8.1,
|
||||
10.5, 10.5, 10.5, 10.5, 10.5, 10.5, 10.5, 10.5,
|
||||
10.5, 10.5, 10.5, 10.5, 10.5, 10.5, 10.5, 10.5,
|
||||
12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001,
|
||||
12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001,
|
||||
15.3, 15.3, 15.3, 15.3, 15.3, 15.3, 15.3, 15.3,
|
||||
15.3, 15.3, 15.3, 15.3, 15.3, 15.3, 15.3, 15.3,
|
||||
17.7, 17.7, 17.7, 17.7, 17.7, 17.7, 17.7, 17.7,
|
||||
17.7, 17.7, 17.7, 17.7, 17.7, 17.7, 17.7, 17.7,
|
||||
20.1, 20.1, 20.1, 20.1, 20.1, 20.1, 20.1, 20.1,
|
||||
20.1, 20.1, 20.1, 20.1, 20.1, 20.1, 20.1, 20.1,
|
||||
22.5, 22.5, 22.5, 22.5, 22.5, 22.5, 22.5, 22.5,
|
||||
22.5, 22.5, 22.5, 22.5, 22.5, 22.5, 22.5, 22.5,
|
||||
24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002,
|
||||
24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002,
|
||||
27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001,
|
||||
27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001,
|
||||
29.7, 29.7, 29.7, 29.7, 29.7, 29.7, 29.7, 29.7,
|
||||
29.7, 29.7, 29.7, 29.7, 29.7, 29.7, 29.7, 29.7,
|
||||
32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002,
|
||||
32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002,
|
||||
34.5, 34.5, 34.5, 34.5, 34.5, 34.5, 34.5, 34.5,
|
||||
34.5, 34.5, 34.5, 34.5, 34.5, 34.5, 34.5, 34.5,
|
||||
23.8, 23.8, 23.8, 23.8, 23.8, 23.8, 23.8, 23.8,
|
||||
23.8, 23.8, 23.8, 23.8, 23.8, 23.8, 23.8, 23.8,
|
||||
27., 27., 27., 27., 27., 27., 27., 27.,
|
||||
27., 27., 27., 27., 27., 27., 27., 27.,
|
||||
41.7, 41.7, 41.7, 41.7, 41.7, 41.7, 41.7, 41.7,
|
||||
41.7, 41.7, 41.7, 41.7, 41.7, 41.7, 41.7, 41.7,
|
||||
44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002,
|
||||
44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002,
|
||||
46.5, 46.5, 46.5, 46.5, 46.5, 46.5, 46.5, 46.5,
|
||||
46.5, 46.5, 46.5, 46.5, 46.5, 46.5, 46.5, 46.5,
|
||||
48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998,
|
||||
48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998,
|
||||
51.3, 51.3, 51.3, 51.3, 51.3, 51.3, 51.3, 51.3,
|
||||
51.3, 51.3, 51.3, 51.3, 51.3, 51.3, 51.3, 51.3,
|
||||
53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7,
|
||||
53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7,
|
||||
56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002,
|
||||
56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002,
|
||||
58.5, 58.5, 58.5, 58.5, 58.5, 58.5, 58.5, 58.5,
|
||||
58.5, 58.5, 58.5, 58.5, 58.5, 58.5, 58.5, 58.5,
|
||||
60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998,
|
||||
60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998,
|
||||
63.3, 63.3, 63.3, 63.3, 63.3, 63.3, 63.3, 63.3,
|
||||
63.3, 63.3, 63.3, 63.3, 63.3, 63.3, 63.3, 63.3,
|
||||
65.7, 65.7, 65.7, 65.7, 65.7, 65.7, 65.7, 65.7,
|
||||
65.7, 65.7, 65.7, 65.7, 65.7, 65.7, 65.7, 65.7,
|
||||
68.1, 68.1, 68.1, 68.1, 68.1, 68.1, 68.1, 68.1,
|
||||
68.1, 68.1, 68.1, 68.1, 68.1, 68.1, 68.1, 68.1,
|
||||
70.5, 70.5, 70.5, 70.5, 70.5, 70.5, 70.5, 70.5,
|
||||
70.5, 70.5, 70.5, 70.5, 70.5, 70.5, 70.5, 70.5,
|
||||
72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9,
|
||||
72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9,
|
||||
49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4,
|
||||
49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4};
|
||||
EXPECT_TRUE(ck::utils::check_err(
|
||||
out_tensor2.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
|
||||
EXPECT_TRUE(ck::utils::check_err(out_tensor2.mData, ref_data, "Error: incorrect results!"));
|
||||
}
|
||||
|
||||
TEST(ReferenceConvolutionFWD, Conv3DNCDHW)
|
||||
{
|
||||
ck::utils::conv::ConvParams params;
|
||||
params.num_dim_spatial_ = 3;
|
||||
params.N_ = 1;
|
||||
params.K_ = 1;
|
||||
params.C_ = 2;
|
||||
params.filter_spatial_lengths_ = std::vector<ck::index_t>{3, 3, 3};
|
||||
params.input_spatial_lengths_ = std::vector<ck::index_t>{6, 6, 6};
|
||||
params.conv_filter_strides_ = std::vector<ck::index_t>{1, 1, 1};
|
||||
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};
|
||||
|
||||
auto out_tensor = run_reference_convolution_forward<3,
|
||||
float,
|
||||
float,
|
||||
float,
|
||||
ck::tensor_layout::convolution::NCDHW,
|
||||
ck::tensor_layout::convolution::KCZYX,
|
||||
ck::tensor_layout::convolution::NKDHW>(
|
||||
params, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
|
||||
std::vector<std::size_t> ref_dims{1, 1, 4, 4, 4};
|
||||
std::vector<float> ref_data{
|
||||
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.};
|
||||
EXPECT_TRUE(ck::utils::check_err(out_tensor.mDesc.GetLengths(),
|
||||
ref_dims,
|
||||
"Error [case 1]: wrong output tensor dimensions!"));
|
||||
EXPECT_TRUE(
|
||||
ck::utils::check_err(out_tensor.mData, ref_data, "Error [case 1]: incorrect results!"));
|
||||
}
|
||||
|
||||
TEST(ReferenceConvolutionFWD, Conv3DNCDHWStridesDilations)
|
||||
{
|
||||
ck::utils::conv::ConvParams params;
|
||||
params.num_dim_spatial_ = 3;
|
||||
params.N_ = 1;
|
||||
params.K_ = 2;
|
||||
params.C_ = 2;
|
||||
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};
|
||||
|
||||
auto out_tensor = run_reference_convolution_forward<3,
|
||||
float,
|
||||
float,
|
||||
float,
|
||||
ck::tensor_layout::convolution::NCDHW,
|
||||
ck::tensor_layout::convolution::KCZYX,
|
||||
ck::tensor_layout::convolution::NKDHW>(
|
||||
params, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
|
||||
std::vector<std::size_t> ref_dims{1, 2, 4, 4, 4};
|
||||
std::vector<float> ref_data{
|
||||
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};
|
||||
EXPECT_TRUE(ck::utils::check_err(out_tensor.mDesc.GetLengths(),
|
||||
ref_dims,
|
||||
"Error [case 2]: wrong output tensor dimensions!"));
|
||||
EXPECT_TRUE(ck::utils::check_err(
|
||||
out_tensor.mData, ref_data, "Error [case 2]: incorrect results!", 1e-4f, 1e-6f));
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user