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References for conv2d fwd bias relu and add (#75)
* add reference * clean up * add reference for conv * rename Co-authored-by: ltqin <letaoqin@amd.com> Co-authored-by: Chao Liu <chao.liu2@amd.com>
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ltqin
@@ -11,8 +11,9 @@
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#include "host_tensor_generator.hpp"
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#include "device_tensor.hpp"
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#include "tensor_layout.hpp"
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#include "device_operation/include/device_conv2d_fwd_xdl_c_shuffle_nhwc_kyxc_nhwk.hpp"
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#include "element_wise_operation.hpp"
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#include "device_conv2d_fwd_xdl_c_shuffle_nhwc_kyxc_nhwk.hpp"
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#include "reference_conv_fwd.hpp"
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using InDataType = ck::half_t;
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using WeiDataType = ck::half_t;
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@@ -33,65 +34,53 @@ using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
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static constexpr auto ConvFwdDefault =
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ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Default;
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// clang-format off
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using DeviceConvFwdInstance = ck::tensor_operation::device::
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DeviceConv2dFwdXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
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// clang-format off
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// | InData| WeiData| OutData| AccData| In| Wei| Out| ConvForward| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
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// | Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Specialization| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector|
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// | | | | | Operation| Operation| Operation| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NXdlPerWave_NWaveNPerXdl| _NWaveNPerXdl|
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// | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
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<InDataType, WeiDataType, OutDataType, AccDataType, InElementOp, WeiElementOp, OutElementOp, ConvFwdDefault, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 8>;
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DeviceConv2dFwdXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<
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InDataType, // InDataType
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WeiDataType, // WeiDataType
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OutDataType, // OutDataType
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AccDataType, // AccDataType
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InElementOp, // InElementwiseOperation
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WeiElementOp, // WeiElementwiseOperation
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OutElementOp, // OutElementwiseOperation
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ConvFwdDefault, // ConvForwardSpecialization
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256, // BlockSize
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128, // MPerBlock
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256, // NPerBlock
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4, // K0PerBlock
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8, // K1
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32, // MPerXdl
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32, // NPerXdl
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2, // MXdlPerWave
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4, // NXdlPerWave
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S<4, 64, 1>, // ABlockTransferThreadClusterLengths_K0_M_K1
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S<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
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S<1, 0, 2>, // ABlockTransferSrcAccessOrder
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2, // ABlockTransferSrcVectorDim
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8, // ABlockTransferSrcScalarPerVector
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8, // ABlockTransferDstScalarPerVector_K1
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true, // ABlockLdsAddExtraM
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S<4, 64, 1>, // BBlockTransferThreadClusterLengths_K0_N_K1
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S<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder
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S<1, 0, 2>, // BBlockTransferSrcAccessOrder
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2, // BBlockTransferSrcVectorDim
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8, // BBlockTransferSrcScalarPerVector
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8, // BBlockTransferDstScalarPerVector_K1
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true, // BBlockLdsAddExtraN
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1, // CShuffleMXdlPerWavePerShuffle
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1, // CShuffleNXdlPerWavePerShuffle
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S<1, 1, 32, 1, 1, 8>, // CBlockTransferClusterLengths_MBlock_MXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl
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8>; // CBlockTransferScalarPerVector_NWaveNPerXdl
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// clang-format on
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template <typename TIn,
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typename TWei,
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typename TOut,
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typename InElementOp,
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typename WeiElementOp,
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typename OutElementOp>
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void host_verify(const Tensor<TIn>& in,
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const Tensor<TWei>& wei,
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Tensor<TOut>& out,
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const std::vector<ck::index_t>& conv_strides,
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const std::vector<ck::index_t>& conv_dilations,
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const std::vector<ck::index_t>& in_left_pads,
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const std::vector<ck::index_t>&,
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const InElementOp& in_element_op,
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const WeiElementOp& wei_element_op,
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const OutElementOp& out_element_op)
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{
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auto f_nchw = [&](auto n, auto k, auto ho, auto wo) {
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double v = 0;
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for(int c = 0; c < wei.mDesc.GetLengths()[1]; ++c)
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{
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for(int y = 0; y < wei.mDesc.GetLengths()[2]; ++y)
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{
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int hi = ho * conv_strides[0] + y * conv_dilations[0] - in_left_pads[0];
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for(int x = 0; x < wei.mDesc.GetLengths()[3]; ++x)
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{
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int wi = wo * conv_strides[1] + x * conv_dilations[1] - in_left_pads[1];
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if(hi >= 0 && hi < in.mDesc.GetLengths()[2] && wi >= 0 &&
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wi < in.mDesc.GetLengths()[3])
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{
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v += in_element_op(static_cast<const double>(in(n, c, hi, wi))) *
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wei_element_op(static_cast<const double>(wei(k, c, y, x)));
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}
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}
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}
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}
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double v2 = out(n, k, ho, wo);
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out_element_op(v2, v);
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out(n, k, ho, wo) = v2;
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};
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make_ParallelTensorFunctor(f_nchw,
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out.mDesc.GetLengths()[0],
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out.mDesc.GetLengths()[1],
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out.mDesc.GetLengths()[2],
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out.mDesc.GetLengths()[3])(std::thread::hardware_concurrency());
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}
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using ReferenceConvFwdInstance = ck::tensor_operation::host::ReferenceConvFwd<InDataType,
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WeiDataType,
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OutDataType,
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AccDataType,
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InElementOp,
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WeiElementOp,
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OutElementOp>;
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int main(int argc, char* argv[])
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{
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@@ -265,16 +254,20 @@ int main(int argc, char* argv[])
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if(do_verification)
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{
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host_verify(in_n_c_hi_wi,
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wei_k_c_y_x,
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out_n_k_ho_wo_host_result,
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conv_filter_strides,
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conv_filter_dilations,
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input_left_pads,
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input_right_pads,
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InElementOp{},
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WeiElementOp{},
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OutElementOp{});
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auto refConv = ReferenceConvFwdInstance{};
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auto refInvoker = refConv.MakeInvoker();
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auto refArgument = refConv.MakeArgument(in_n_c_hi_wi,
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wei_k_c_y_x,
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out_n_k_ho_wo_host_result,
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conv_filter_strides,
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conv_filter_dilations,
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input_left_pads,
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input_right_pads,
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InElementOp{},
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WeiElementOp{},
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OutElementOp{});
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refInvoker.Run(refArgument);
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out_device_buf.FromDevice(out_n_k_ho_wo_device_result.mData.data());
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