#include #include #include #include #include #include #include "check_err.hpp" #include "config.hpp" #include "conv_fwd_util.hpp" #include "element_wise_operation.hpp" #include "fill.hpp" #include "host_tensor.hpp" #include "reference_conv_fwd.hpp" #include "tensor_layout.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 , typename FillWeightsOp = ck::utils::FillConstant> Tensor 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 input_dims{static_cast(params.N), static_cast(params.C)}; input_dims.insert(std::end(input_dims), std::begin(params.input_spatial_lengths), std::end(params.input_spatial_lengths)); std::vector filter_dims{static_cast(params.K), static_cast(params.C)}; filter_dims.insert(std::end(filter_dims), std::begin(params.filter_spatial_lengths), std::end(params.filter_spatial_lengths)); const std::vector& output_spatial_lengths = params.GetOutputSpatialLengths(); std::vector output_dims{static_cast(params.N), static_cast(params.K)}; output_dims.insert(std::end(output_dims), std::begin(output_spatial_lengths), std::end(output_spatial_lengths)); Tensor input(ck::utils::conv::get_host_tensor_descriptor(input_dims, InLayout{})); Tensor weights( ck::utils::conv::get_host_tensor_descriptor(filter_dims, WeiLayout{})); Tensor 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(); 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); // std::cout <<"output: " << host_output.mDesc << std::endl << host_output.mData << std::endl; return host_output; } bool test_conv2d_nhwc() { bool res{true}; ck::utils::conv::ConvParams params; params.N = 1; params.K = 1; params.C = 2; params.filter_spatial_lengths = std::vector{3, 3}; params.input_spatial_lengths = std::vector{6, 6}; params.conv_filter_strides = std::vector{1, 1}; params.conv_filter_dilations = std::vector{1, 1}; params.input_left_pads = std::vector{0, 0}; params.input_right_pads = std::vector{0, 0}; auto out_tensor = run_reference_convolution_forward<2>(params); std::vector ref_dims{1, 1, 4, 4}; std::vector 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}; res = res && ck::utils::check_err(out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"); res = res && ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"); params.N = 1; params.K = 2; params.C = 2; params.filter_spatial_lengths = std::vector{3, 3}; params.input_spatial_lengths = std::vector{12, 12}; params.conv_filter_strides = std::vector{2, 2}; params.conv_filter_dilations = std::vector{2, 2}; params.input_left_pads = std::vector{1, 1}; params.input_right_pads = std::vector{1, 1}; out_tensor = run_reference_convolution_forward<2>(params); ref_dims = std::vector{1, 2, 5, 5}; ref_data = std::vector{ 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}; res = res && ck::utils::check_err(out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"); res = res && ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"); return res; } bool test_conv1d_nwc() { bool res{true}; 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{3}; params.input_spatial_lengths = std::vector{6}; params.conv_filter_strides = std::vector{1}; params.conv_filter_dilations = std::vector{1}; params.input_left_pads = std::vector{0}; params.input_right_pads = std::vector{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 ref_dims{1, 1, 4}; std::vector ref_data{7.5, 13.5, 19.5, 25.5}; res = res && ck::utils::check_err(out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"); res = res && ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"); params.num_dim_spatial = 1; params.N = 1; params.K = 2; params.C = 2; params.filter_spatial_lengths = std::vector{3}; params.input_spatial_lengths = std::vector{12}; params.conv_filter_strides = std::vector{2}; params.conv_filter_dilations = std::vector{2}; params.input_left_pads = std::vector{1}; params.input_right_pads = std::vector{1}; 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); ref_dims = std::vector{1, 2, 5}; ref_data = std::vector{9., 9., 19.5, 19.5, 31.5, 31.5, 43.5, 43.5, 55.5, 55.5}; res = res && ck::utils::check_err(out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"); res = res && ck::utils::check_err(out_tensor.mData, ref_data, "Error: incorrect results!"); params.num_dim_spatial = 1; params.N = 2; params.K = 16; params.C = 4; params.filter_spatial_lengths = std::vector{3}; params.input_spatial_lengths = std::vector{16}; params.conv_filter_strides = std::vector{1}; params.conv_filter_dilations = std::vector{1}; params.input_left_pads = std::vector{1}; params.input_right_pads = std::vector{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{0.f, 0.1f}); ref_dims = std::vector{2, 16, 16}; ref_data = std::vector{ 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}; res = res && ck::utils::check_err(out_tensor2.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"); res = res && ck::utils::check_err(out_tensor2.mData, ref_data, "Error: incorrect results!"); return res; } bool test_conv3d_ncdhw() { bool res{true}; 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{3, 3, 3}; params.input_spatial_lengths = std::vector{6, 6, 6}; params.conv_filter_strides = std::vector{1, 1, 1}; params.conv_filter_dilations = std::vector{1, 1, 1}; params.input_left_pads = std::vector{0, 0, 0}; params.input_right_pads = std::vector{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{0.f, 0.1f}); std::vector ref_dims{1, 1, 4, 4, 4}; std::vector 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.}; res = res && ck::utils::check_err(out_tensor.mDesc.GetLengths(), ref_dims, "Error [case 1]: wrong output tensor dimensions!"); res = res && ck::utils::check_err(out_tensor.mData, ref_data, "Error [case 1]: incorrect results!"); params.N = 1; params.K = 2; params.C = 2; params.filter_spatial_lengths = std::vector{3, 3, 3}; params.input_spatial_lengths = std::vector{12, 12, 12}; params.conv_filter_strides = std::vector{3, 3, 3}; params.conv_filter_dilations = std::vector{1, 1, 1}; params.input_left_pads = std::vector{0, 0, 0}; params.input_right_pads = std::vector{0, 0, 0}; 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{0.f, 0.1f}); ref_dims = std::vector{1, 2, 4, 4, 4}; ref_data = std::vector{ 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 && ck::utils::check_err(out_tensor.mDesc.GetLengths(), ref_dims, "Error [case 2]: wrong output tensor dimensions!"); res = res && ck::utils::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 = test_conv2d_nhwc(); std::cout << "test_conv2d_nhwc ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl; res = test_conv1d_nwc(); std::cout << "TestConv1DNHWC ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl; res = test_conv3d_ncdhw(); std::cout << "test_conv3d_ncdhw ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl; return res ? 0 : 1; }