mirror of
https://github.com/ROCm/composable_kernel.git
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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>
[ROCm/composable_kernel commit: 690c75a7eb]
This commit is contained in:
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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@@ -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_conv2d_fwd_xdl_c_shuffle_bias_activation_nhwc_kyxc_nhwk.hpp"
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#include "element_wise_operation.hpp"
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#include "device_conv2d_fwd_xdl_c_shuffle_bias_activation_nhwc_kyxc_nhwk.hpp"
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#include "reference_conv_fwd_bias_activation.hpp"
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using InDataType = ck::half_t;
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using WeiDataType = ck::half_t;
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@@ -37,63 +38,53 @@ static constexpr auto ConvFwdDefault =
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// clang-format off
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using DeviceConvFwdInstance = ck::tensor_operation::device::
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DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_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| 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| GlobalMemory| 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| DataOperation| | | | | | | | | 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, MemorySet, 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_Bias_Activation_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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MemorySet, // OutGlobalMemoryDataOperation
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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_reference_calculation(const Tensor<TIn>& in_n_c_hi_wi,
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const Tensor<TWei>& wei_k_c_y_x,
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Tensor<TOut>& out_n_k_ho_wo,
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const Tensor<TOut>& bias_k,
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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>& /* in_right_pads */,
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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_k_c_y_x.mDesc.GetLengths()[1]; ++c)
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{
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for(int y = 0; y < wei_k_c_y_x.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_k_c_y_x.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_n_c_hi_wi.mDesc.GetLengths()[2] && wi >= 0 &&
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wi < in_n_c_hi_wi.mDesc.GetLengths()[3])
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{
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v += in_element_op(static_cast<const double>(in_n_c_hi_wi(n, c, hi, wi))) *
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wei_element_op(static_cast<const double>(wei_k_c_y_x(k, c, y, x)));
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}
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}
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}
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}
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out_n_k_ho_wo(n, k, ho, wo) = out_element_op(v, bias_k(k));
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};
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make_ParallelTensorFunctor(f_nchw,
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out_n_k_ho_wo.mDesc.GetLengths()[0],
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out_n_k_ho_wo.mDesc.GetLengths()[1],
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out_n_k_ho_wo.mDesc.GetLengths()[2],
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out_n_k_ho_wo.mDesc.GetLengths()[3])(
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std::thread::hardware_concurrency());
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}
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using ReferenceConvFwdInstance =
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ck::tensor_operation::host::ReferenceConvFwd_Bias_Activation<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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@@ -277,17 +268,21 @@ int main(int argc, char* argv[])
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if(do_verification)
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{
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host_reference_calculation(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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bias_k,
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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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bias_k,
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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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@@ -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_conv2d_fwd_xdl_c_shuffle_bias_activation_add_nhwc_kyxc_nhwk.hpp"
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#include "element_wise_operation.hpp"
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#include "device_conv2d_fwd_xdl_c_shuffle_bias_activation_add_nhwc_kyxc_nhwk.hpp"
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#include "reference_conv_fwd_bias_activation_add.hpp"
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using InDataType = ck::half_t;
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using WeiDataType = ck::half_t;
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@@ -35,70 +36,52 @@ static constexpr auto ConvFwdDefault =
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// clang-format off
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using DeviceConvFwdInstance = ck::tensor_operation::device::
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DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Add_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
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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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// | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
<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>;
|
||||
DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Add_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<
|
||||
InDataType, // InDataType
|
||||
WeiDataType, // WeiDataType
|
||||
OutDataType, // OutDataType
|
||||
AccDataType, // AccDataType
|
||||
InElementOp, // InElementwiseOperation
|
||||
WeiElementOp, // WeiElementwiseOperation
|
||||
OutElementOp, // OutElementwiseOperation
|
||||
ConvFwdDefault, // ConvForwardSpecialization
|
||||
256, // BlockSize
|
||||
128, // MPerBlock
|
||||
256, // NPerBlock
|
||||
4, // K0PerBlock
|
||||
8, // K1
|
||||
32, // MPerXdl
|
||||
32, // NPerXdl
|
||||
2, // MXdlPerWave
|
||||
4, // NXdlPerWave
|
||||
S<4, 64, 1>, // ABlockTransferThreadClusterLengths_K0_M_K1
|
||||
S<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
|
||||
S<1, 0, 2>, // ABlockTransferSrcAccessOrder
|
||||
2, // ABlockTransferSrcVectorDim
|
||||
8, // ABlockTransferSrcScalarPerVector
|
||||
8, // ABlockTransferDstScalarPerVector_K1
|
||||
true, // ABlockLdsAddExtraM
|
||||
S<4, 64, 1>, // BBlockTransferThreadClusterLengths_K0_N_K1
|
||||
S<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder
|
||||
S<1, 0, 2>, // BBlockTransferSrcAccessOrder
|
||||
2, // BBlockTransferSrcVectorDim
|
||||
8, // BBlockTransferSrcScalarPerVector
|
||||
8, // BBlockTransferDstScalarPerVector_K1
|
||||
true, // BBlockLdsAddExtraN
|
||||
1, // CShuffleMXdlPerWavePerShuffle
|
||||
1, // CShuffleNXdlPerWavePerShuffle
|
||||
S<1, 1, 32, 1, 1, 8>, // CBlockTransferClusterLengths_MBlock_MXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl
|
||||
8>; // CBlockTransferScalarPerVector_NWaveNPerXdl
|
||||
// clang-format on
|
||||
|
||||
template <typename TIn,
|
||||
typename TWei,
|
||||
typename TOut,
|
||||
typename InElementOp,
|
||||
typename WeiElementOp,
|
||||
typename OutElementOp>
|
||||
void host_reference_calculation(const Tensor<TIn>& in_n_c_hi_wi,
|
||||
const Tensor<TWei>& wei_k_c_y_x,
|
||||
Tensor<TOut>& out_n_k_ho_wo,
|
||||
const Tensor<TOut>& bias_k,
|
||||
const Tensor<TOut>& resi_n_k_ho_wo,
|
||||
const std::vector<ck::index_t>& conv_strides,
|
||||
const std::vector<ck::index_t>& conv_dilations,
|
||||
const std::vector<ck::index_t>& in_left_pads,
|
||||
const std::vector<ck::index_t>& /* in_right_pads */,
|
||||
const InElementOp& in_element_op,
|
||||
const WeiElementOp& wei_element_op,
|
||||
const OutElementOp& out_element_op)
|
||||
{
|
||||
auto f_nchw = [&](auto n, auto k, auto ho, auto wo) {
|
||||
double v = 0;
|
||||
for(int c = 0; c < wei_k_c_y_x.mDesc.GetLengths()[1]; ++c)
|
||||
{
|
||||
for(int y = 0; y < wei_k_c_y_x.mDesc.GetLengths()[2]; ++y)
|
||||
{
|
||||
int hi = ho * conv_strides[0] + y * conv_dilations[0] - in_left_pads[0];
|
||||
for(int x = 0; x < wei_k_c_y_x.mDesc.GetLengths()[3]; ++x)
|
||||
{
|
||||
int wi = wo * conv_strides[1] + x * conv_dilations[1] - in_left_pads[1];
|
||||
if(hi >= 0 && hi < in_n_c_hi_wi.mDesc.GetLengths()[2] && wi >= 0 &&
|
||||
wi < in_n_c_hi_wi.mDesc.GetLengths()[3])
|
||||
{
|
||||
v += in_element_op(static_cast<const double>(in_n_c_hi_wi(n, c, hi, wi))) *
|
||||
wei_element_op(static_cast<const double>(wei_k_c_y_x(k, c, y, x)));
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
double v2 = out_n_k_ho_wo(n, k, ho, wo);
|
||||
|
||||
out_element_op(v2,
|
||||
v,
|
||||
static_cast<const double>(bias_k(k)),
|
||||
static_cast<const double>(resi_n_k_ho_wo(n, k, ho, wo)));
|
||||
|
||||
out_n_k_ho_wo(n, k, ho, wo) = v2;
|
||||
};
|
||||
|
||||
make_ParallelTensorFunctor(f_nchw,
|
||||
out_n_k_ho_wo.mDesc.GetLengths()[0],
|
||||
out_n_k_ho_wo.mDesc.GetLengths()[1],
|
||||
out_n_k_ho_wo.mDesc.GetLengths()[2],
|
||||
out_n_k_ho_wo.mDesc.GetLengths()[3])(
|
||||
std::thread::hardware_concurrency());
|
||||
}
|
||||
using ReferenceConvFwdInstance =
|
||||
ck::tensor_operation::host::ReferenceConvFwd_Bias_Activation_Add<InDataType,
|
||||
WeiDataType,
|
||||
OutDataType,
|
||||
AccDataType,
|
||||
InElementOp,
|
||||
WeiElementOp,
|
||||
OutElementOp>;
|
||||
|
||||
int main(int argc, char* argv[])
|
||||
{
|
||||
@@ -292,18 +275,22 @@ int main(int argc, char* argv[])
|
||||
|
||||
if(do_verification)
|
||||
{
|
||||
host_reference_calculation(in_n_c_hi_wi,
|
||||
wei_k_c_y_x,
|
||||
out_n_k_ho_wo_host_result,
|
||||
bias_k,
|
||||
resi_n_k_ho_wo,
|
||||
conv_filter_strides,
|
||||
conv_filter_dilations,
|
||||
input_left_pads,
|
||||
input_right_pads,
|
||||
InElementOp{},
|
||||
WeiElementOp{},
|
||||
OutElementOp{});
|
||||
auto refConv = ReferenceConvFwdInstance{};
|
||||
auto refInvoker = refConv.MakeInvoker();
|
||||
|
||||
auto refArgument = refConv.MakeArgument(in_n_c_hi_wi,
|
||||
wei_k_c_y_x,
|
||||
out_n_k_ho_wo_host_result,
|
||||
bias_k,
|
||||
resi_n_k_ho_wo,
|
||||
conv_filter_strides,
|
||||
conv_filter_dilations,
|
||||
input_left_pads,
|
||||
input_right_pads,
|
||||
InElementOp{},
|
||||
WeiElementOp{},
|
||||
OutElementOp{});
|
||||
refInvoker.Run(refArgument);
|
||||
|
||||
out_device_buf.FromDevice(out_n_k_ho_wo_device_result.mData.data());
|
||||
|
||||
|
||||
@@ -2,6 +2,7 @@ include_directories(BEFORE
|
||||
${PROJECT_SOURCE_DIR}
|
||||
${PROJECT_SOURCE_DIR}/host/host_tensor/include
|
||||
${PROJECT_SOURCE_DIR}/host/device/include
|
||||
${PROJECT_SOURCE_DIR}/host/include
|
||||
${PROJECT_SOURCE_DIR}/device_operation/include
|
||||
${PROJECT_SOURCE_DIR}/composable_kernel/include
|
||||
${PROJECT_SOURCE_DIR}/composable_kernel/include/utility
|
||||
|
||||
166
host/include/reference_conv_fwd.hpp
Normal file
166
host/include/reference_conv_fwd.hpp
Normal file
@@ -0,0 +1,166 @@
|
||||
#ifndef REFERENCE_CONV_FWD_HPP
|
||||
#define REFERENCE_CONV_FWD_HPP
|
||||
|
||||
#include <iostream>
|
||||
#include <sstream>
|
||||
#include "device_base.hpp"
|
||||
#include "host_tensor.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace host {
|
||||
|
||||
// out[N, K, Ho, Wo] = in[N, C, Hi, Wi] * wei[K, C, Y, X]
|
||||
template <typename InDataType,
|
||||
typename WeiDataType,
|
||||
typename OutDataType,
|
||||
typename AccDataType,
|
||||
typename InElementwiseOperation,
|
||||
typename WeiElementwiseOperation,
|
||||
typename OutElementwiseOperation>
|
||||
struct ReferenceConvFwd : public device::BaseOperator
|
||||
{
|
||||
// Argument
|
||||
struct Argument : public device::BaseArgument
|
||||
{
|
||||
Argument(const Tensor<InDataType>& in_n_c_hi_wi,
|
||||
const Tensor<WeiDataType>& wei_k_c_y_x,
|
||||
Tensor<OutDataType>& out_n_k_ho_wo,
|
||||
std::vector<ck::index_t> conv_filter_strides,
|
||||
std::vector<ck::index_t> conv_filter_dilations,
|
||||
std::vector<ck::index_t> input_left_pads,
|
||||
std::vector<ck::index_t> input_right_pads,
|
||||
InElementwiseOperation in_element_op,
|
||||
WeiElementwiseOperation wei_element_op,
|
||||
OutElementwiseOperation out_element_op)
|
||||
: in_n_c_hi_wi_{in_n_c_hi_wi},
|
||||
wei_k_c_y_x_{wei_k_c_y_x},
|
||||
out_n_k_ho_wo_{out_n_k_ho_wo},
|
||||
conv_strides_{conv_filter_strides},
|
||||
conv_dilations_{conv_filter_dilations},
|
||||
in_left_pads_{input_left_pads},
|
||||
in_right_pads_{input_right_pads},
|
||||
in_element_op_{in_element_op},
|
||||
wei_element_op_{wei_element_op},
|
||||
out_element_op_{out_element_op}
|
||||
{
|
||||
}
|
||||
|
||||
const Tensor<InDataType>& in_n_c_hi_wi_;
|
||||
const Tensor<WeiDataType>& wei_k_c_y_x_;
|
||||
Tensor<OutDataType>& out_n_k_ho_wo_;
|
||||
|
||||
std::vector<index_t> conv_strides_;
|
||||
std::vector<index_t> conv_dilations_;
|
||||
std::vector<index_t> in_left_pads_;
|
||||
std::vector<index_t> in_right_pads_;
|
||||
|
||||
InElementwiseOperation in_element_op_;
|
||||
WeiElementwiseOperation wei_element_op_;
|
||||
OutElementwiseOperation out_element_op_;
|
||||
};
|
||||
|
||||
// Invoker
|
||||
struct Invoker : public device::BaseInvoker
|
||||
{
|
||||
using Argument = ReferenceConvFwd::Argument;
|
||||
|
||||
float Run(const Argument& arg)
|
||||
{
|
||||
auto f_nchw = [&](auto n, auto k, auto ho, auto wo) {
|
||||
float v = 0;
|
||||
for(int c = 0; c < arg.wei_k_c_y_x_.mDesc.GetLengths()[1]; ++c)
|
||||
{
|
||||
for(int y = 0; y < arg.wei_k_c_y_x_.mDesc.GetLengths()[2]; ++y)
|
||||
{
|
||||
int hi = ho * arg.conv_strides_[0] + y * arg.conv_dilations_[0] -
|
||||
arg.in_left_pads_[0];
|
||||
for(int x = 0; x < arg.wei_k_c_y_x_.mDesc.GetLengths()[3]; ++x)
|
||||
{
|
||||
int wi = wo * arg.conv_strides_[1] + x * arg.conv_dilations_[1] -
|
||||
arg.in_left_pads_[1];
|
||||
if(hi >= 0 && hi < arg.in_n_c_hi_wi_.mDesc.GetLengths()[2] && wi >= 0 &&
|
||||
wi < arg.in_n_c_hi_wi_.mDesc.GetLengths()[3])
|
||||
{
|
||||
v += arg.in_element_op_(
|
||||
ck::type_convert<float>(arg.in_n_c_hi_wi_(n, c, hi, wi))) *
|
||||
arg.wei_element_op_(
|
||||
ck::type_convert<float>(arg.wei_k_c_y_x_(k, c, y, x)));
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
arg.out_n_k_ho_wo_(n, k, ho, wo) =
|
||||
ck::type_convert<OutDataType>(arg.out_element_op_(v));
|
||||
};
|
||||
|
||||
make_ParallelTensorFunctor(f_nchw,
|
||||
arg.out_n_k_ho_wo_.mDesc.GetLengths()[0],
|
||||
arg.out_n_k_ho_wo_.mDesc.GetLengths()[1],
|
||||
arg.out_n_k_ho_wo_.mDesc.GetLengths()[2],
|
||||
arg.out_n_k_ho_wo_.mDesc.GetLengths()[3])(
|
||||
std::thread::hardware_concurrency());
|
||||
return 0;
|
||||
}
|
||||
|
||||
float Run(const device::BaseArgument* p_arg, int) override
|
||||
{
|
||||
return Run(*dynamic_cast<const Argument*>(p_arg));
|
||||
}
|
||||
};
|
||||
|
||||
static constexpr bool IsValidCompilationParameter()
|
||||
{
|
||||
// TODO: properly implement this check
|
||||
return true;
|
||||
}
|
||||
|
||||
bool IsSupportedArgument(const device::BaseArgument*) override { return true; }
|
||||
|
||||
static auto MakeArgument(const Tensor<InDataType>& in_n_c_hi_wi,
|
||||
const Tensor<WeiDataType>& wei_k_c_y_x,
|
||||
Tensor<OutDataType>& out_n_k_ho_wo,
|
||||
std::vector<ck::index_t> conv_filter_strides,
|
||||
std::vector<ck::index_t> conv_filter_dilations,
|
||||
std::vector<ck::index_t> input_left_pads,
|
||||
std::vector<ck::index_t> input_right_pads,
|
||||
InElementwiseOperation in_element_op,
|
||||
WeiElementwiseOperation wei_element_op,
|
||||
OutElementwiseOperation out_element_op)
|
||||
{
|
||||
return Argument{in_n_c_hi_wi,
|
||||
wei_k_c_y_x,
|
||||
out_n_k_ho_wo,
|
||||
conv_filter_strides,
|
||||
conv_filter_dilations,
|
||||
input_left_pads,
|
||||
input_right_pads,
|
||||
in_element_op,
|
||||
wei_element_op,
|
||||
out_element_op};
|
||||
}
|
||||
|
||||
static auto MakeInvoker() { return Invoker{}; }
|
||||
|
||||
virtual std::unique_ptr<device::BaseInvoker> MakeInvokerPointer()
|
||||
{
|
||||
return std::make_unique<Invoker>(Invoker{});
|
||||
}
|
||||
|
||||
std::string GetTypeString() const override
|
||||
{
|
||||
auto str = std::stringstream();
|
||||
|
||||
// clang-format off
|
||||
str << "ReferenceConvFwd"
|
||||
<< std::endl;
|
||||
// clang-format on
|
||||
|
||||
return str.str();
|
||||
}
|
||||
};
|
||||
} // namespace host
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
#endif
|
||||
172
host/include/reference_conv_fwd_bias_activation.hpp
Normal file
172
host/include/reference_conv_fwd_bias_activation.hpp
Normal file
@@ -0,0 +1,172 @@
|
||||
#ifndef REFERENCE_CONV_FWD_BIAS_ACTIVATION_HPP
|
||||
#define REFERENCE_CONV_FWD_BIAS_ACTIVATION_HPP
|
||||
|
||||
#include <iostream>
|
||||
#include <sstream>
|
||||
#include "device_base.hpp"
|
||||
#include "host_tensor.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace host {
|
||||
|
||||
// out[N, Ho, Wo, K] =
|
||||
// activate(in[N, Hi, Wi, C] * wei[K, Y, X, C] + bias[K])
|
||||
template <typename InDataType,
|
||||
typename WeiDataType,
|
||||
typename OutDataType,
|
||||
typename AccDataType,
|
||||
typename InElementwiseOperation,
|
||||
typename WeiElementwiseOperation,
|
||||
typename OutElementwiseOperation>
|
||||
struct ReferenceConvFwd_Bias_Activation : public device::BaseOperator
|
||||
{
|
||||
// Argument
|
||||
struct Argument : public device::BaseArgument
|
||||
{
|
||||
Argument(const Tensor<InDataType>& in_n_c_hi_wi,
|
||||
const Tensor<WeiDataType>& wei_k_c_y_x,
|
||||
Tensor<OutDataType>& out_n_k_ho_wo,
|
||||
const Tensor<OutDataType>& bias_k,
|
||||
std::vector<ck::index_t> conv_filter_strides,
|
||||
std::vector<ck::index_t> conv_filter_dilations,
|
||||
std::vector<ck::index_t> input_left_pads,
|
||||
std::vector<ck::index_t> input_right_pads,
|
||||
InElementwiseOperation in_element_op,
|
||||
WeiElementwiseOperation wei_element_op,
|
||||
OutElementwiseOperation out_element_op)
|
||||
: in_n_c_hi_wi_{in_n_c_hi_wi},
|
||||
wei_k_c_y_x_{wei_k_c_y_x},
|
||||
out_n_k_ho_wo_{out_n_k_ho_wo},
|
||||
bias_k_{bias_k},
|
||||
conv_strides_{conv_filter_strides},
|
||||
conv_dilations_{conv_filter_dilations},
|
||||
in_left_pads_{input_left_pads},
|
||||
in_right_pads_{input_right_pads},
|
||||
in_element_op_{in_element_op},
|
||||
wei_element_op_{wei_element_op},
|
||||
out_element_op_{out_element_op}
|
||||
{
|
||||
}
|
||||
|
||||
const Tensor<InDataType>& in_n_c_hi_wi_;
|
||||
const Tensor<WeiDataType>& wei_k_c_y_x_;
|
||||
Tensor<OutDataType>& out_n_k_ho_wo_;
|
||||
const Tensor<OutDataType>& bias_k_;
|
||||
|
||||
std::vector<index_t> conv_strides_;
|
||||
std::vector<index_t> conv_dilations_;
|
||||
std::vector<index_t> in_left_pads_;
|
||||
std::vector<index_t> in_right_pads_;
|
||||
|
||||
InElementwiseOperation in_element_op_;
|
||||
WeiElementwiseOperation wei_element_op_;
|
||||
OutElementwiseOperation out_element_op_;
|
||||
};
|
||||
|
||||
// Invoker
|
||||
struct Invoker : public device::BaseInvoker
|
||||
{
|
||||
using Argument = ReferenceConvFwd_Bias_Activation::Argument;
|
||||
|
||||
float Run(const Argument& arg)
|
||||
{
|
||||
auto f_nchw = [&](auto n, auto k, auto ho, auto wo) {
|
||||
float v = 0;
|
||||
for(int c = 0; c < arg.wei_k_c_y_x_.mDesc.GetLengths()[1]; ++c)
|
||||
{
|
||||
for(int y = 0; y < arg.wei_k_c_y_x_.mDesc.GetLengths()[2]; ++y)
|
||||
{
|
||||
int hi = ho * arg.conv_strides_[0] + y * arg.conv_dilations_[0] -
|
||||
arg.in_left_pads_[0];
|
||||
for(int x = 0; x < arg.wei_k_c_y_x_.mDesc.GetLengths()[3]; ++x)
|
||||
{
|
||||
int wi = wo * arg.conv_strides_[1] + x * arg.conv_dilations_[1] -
|
||||
arg.in_left_pads_[1];
|
||||
if(hi >= 0 && hi < arg.in_n_c_hi_wi_.mDesc.GetLengths()[2] && wi >= 0 &&
|
||||
wi < arg.in_n_c_hi_wi_.mDesc.GetLengths()[3])
|
||||
{
|
||||
v += arg.in_element_op_(
|
||||
ck::type_convert<float>(arg.in_n_c_hi_wi_(n, c, hi, wi))) *
|
||||
arg.wei_element_op_(
|
||||
ck::type_convert<float>(arg.wei_k_c_y_x_(k, c, y, x)));
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
arg.out_n_k_ho_wo_(n, k, ho, wo) =
|
||||
ck::type_convert<OutDataType>(arg.out_element_op_(v, arg.bias_k_(k)));
|
||||
};
|
||||
|
||||
make_ParallelTensorFunctor(f_nchw,
|
||||
arg.out_n_k_ho_wo_.mDesc.GetLengths()[0],
|
||||
arg.out_n_k_ho_wo_.mDesc.GetLengths()[1],
|
||||
arg.out_n_k_ho_wo_.mDesc.GetLengths()[2],
|
||||
arg.out_n_k_ho_wo_.mDesc.GetLengths()[3])(
|
||||
std::thread::hardware_concurrency());
|
||||
return 0;
|
||||
}
|
||||
|
||||
float Run(const device::BaseArgument* p_arg, int) override
|
||||
{
|
||||
return Run(*dynamic_cast<const Argument*>(p_arg));
|
||||
}
|
||||
};
|
||||
|
||||
static constexpr bool IsValidCompilationParameter()
|
||||
{
|
||||
// TODO: properly implement this check
|
||||
return true;
|
||||
}
|
||||
|
||||
bool IsSupportedArgument(const device::BaseArgument*) override { return true; }
|
||||
|
||||
static auto MakeArgument(const Tensor<InDataType>& in_n_c_hi_wi,
|
||||
const Tensor<WeiDataType>& wei_k_c_y_x,
|
||||
Tensor<OutDataType>& out_n_k_ho_wo,
|
||||
const Tensor<OutDataType>& bias_k,
|
||||
std::vector<ck::index_t> conv_filter_strides,
|
||||
std::vector<ck::index_t> conv_filter_dilations,
|
||||
std::vector<ck::index_t> input_left_pads,
|
||||
std::vector<ck::index_t> input_right_pads,
|
||||
InElementwiseOperation in_element_op,
|
||||
WeiElementwiseOperation wei_element_op,
|
||||
OutElementwiseOperation out_element_op)
|
||||
{
|
||||
return Argument{in_n_c_hi_wi,
|
||||
wei_k_c_y_x,
|
||||
out_n_k_ho_wo,
|
||||
bias_k,
|
||||
conv_filter_strides,
|
||||
conv_filter_dilations,
|
||||
input_left_pads,
|
||||
input_right_pads,
|
||||
in_element_op,
|
||||
wei_element_op,
|
||||
out_element_op};
|
||||
}
|
||||
|
||||
static auto MakeInvoker() { return Invoker{}; }
|
||||
|
||||
virtual std::unique_ptr<device::BaseInvoker> MakeInvokerPointer()
|
||||
{
|
||||
return std::make_unique<Invoker>(Invoker{});
|
||||
}
|
||||
|
||||
std::string GetTypeString() const override
|
||||
{
|
||||
auto str = std::stringstream();
|
||||
|
||||
// clang-format off
|
||||
str << "ReferenceConvFwd_Bias_Activation"
|
||||
<< std::endl;
|
||||
// clang-format on
|
||||
|
||||
return str.str();
|
||||
}
|
||||
};
|
||||
} // namespace host
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
#endif
|
||||
183
host/include/reference_conv_fwd_bias_activation_add.hpp
Normal file
183
host/include/reference_conv_fwd_bias_activation_add.hpp
Normal file
@@ -0,0 +1,183 @@
|
||||
#ifndef REFERENCE_CONV2D_FWD_BIAS_ACTIVATION_ADD_HPP
|
||||
#define REFERENCE_CONV2D_FWD_BIAS_ACTIVATION_ADD_HPP
|
||||
|
||||
#include <iostream>
|
||||
#include <sstream>
|
||||
#include "device_base.hpp"
|
||||
#include "host_tensor.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace host {
|
||||
|
||||
// out[N, Ho, Wo, K] =
|
||||
// activate(in[N, Hi, Wi, C] * wei[K, Y, X, C] + bias[K]) + residual[N, Ho, Wo, K]
|
||||
template <typename InDataType,
|
||||
typename WeiDataType,
|
||||
typename OutDataType,
|
||||
typename AccDataType,
|
||||
typename InElementwiseOperation,
|
||||
typename WeiElementwiseOperation,
|
||||
typename OutElementwiseOperation>
|
||||
struct ReferenceConvFwd_Bias_Activation_Add : public device::BaseOperator
|
||||
{
|
||||
// Argument
|
||||
struct Argument : public device::BaseArgument
|
||||
{
|
||||
Argument(const Tensor<InDataType>& in_n_c_hi_wi,
|
||||
const Tensor<WeiDataType>& wei_k_c_y_x,
|
||||
Tensor<OutDataType>& out_n_k_ho_wo,
|
||||
const Tensor<OutDataType>& bias_k,
|
||||
const Tensor<OutDataType>& resi_n_k_ho_wo,
|
||||
std::vector<ck::index_t> conv_filter_strides,
|
||||
std::vector<ck::index_t> conv_filter_dilations,
|
||||
std::vector<ck::index_t> input_left_pads,
|
||||
std::vector<ck::index_t> input_right_pads,
|
||||
InElementwiseOperation in_element_op,
|
||||
WeiElementwiseOperation wei_element_op,
|
||||
OutElementwiseOperation out_element_op)
|
||||
: in_n_c_hi_wi_{in_n_c_hi_wi},
|
||||
wei_k_c_y_x_{wei_k_c_y_x},
|
||||
out_n_k_ho_wo_{out_n_k_ho_wo},
|
||||
bias_k_{bias_k},
|
||||
resi_n_k_ho_wo_{resi_n_k_ho_wo},
|
||||
conv_strides_{conv_filter_strides},
|
||||
conv_dilations_{conv_filter_dilations},
|
||||
in_left_pads_{input_left_pads},
|
||||
in_right_pads_{input_right_pads},
|
||||
in_element_op_{in_element_op},
|
||||
wei_element_op_{wei_element_op},
|
||||
out_element_op_{out_element_op}
|
||||
{
|
||||
}
|
||||
|
||||
const Tensor<InDataType>& in_n_c_hi_wi_;
|
||||
const Tensor<WeiDataType>& wei_k_c_y_x_;
|
||||
Tensor<OutDataType>& out_n_k_ho_wo_;
|
||||
const Tensor<OutDataType>& bias_k_;
|
||||
const Tensor<OutDataType>& resi_n_k_ho_wo_;
|
||||
|
||||
std::vector<index_t> conv_strides_;
|
||||
std::vector<index_t> conv_dilations_;
|
||||
std::vector<index_t> in_left_pads_;
|
||||
std::vector<index_t> in_right_pads_;
|
||||
|
||||
InElementwiseOperation in_element_op_;
|
||||
WeiElementwiseOperation wei_element_op_;
|
||||
OutElementwiseOperation out_element_op_;
|
||||
};
|
||||
|
||||
// Invoker
|
||||
struct Invoker : public device::BaseInvoker
|
||||
{
|
||||
using Argument = ReferenceConvFwd_Bias_Activation_Add::Argument;
|
||||
|
||||
float Run(const Argument& arg)
|
||||
{
|
||||
auto f_nchw = [&](auto n, auto k, auto ho, auto wo) {
|
||||
float v = 0;
|
||||
for(int c = 0; c < arg.wei_k_c_y_x_.mDesc.GetLengths()[1]; ++c)
|
||||
{
|
||||
for(int y = 0; y < arg.wei_k_c_y_x_.mDesc.GetLengths()[2]; ++y)
|
||||
{
|
||||
int hi = ho * arg.conv_strides_[0] + y * arg.conv_dilations_[0] -
|
||||
arg.in_left_pads_[0];
|
||||
for(int x = 0; x < arg.wei_k_c_y_x_.mDesc.GetLengths()[3]; ++x)
|
||||
{
|
||||
int wi = wo * arg.conv_strides_[1] + x * arg.conv_dilations_[1] -
|
||||
arg.in_left_pads_[1];
|
||||
if(hi >= 0 && hi < arg.in_n_c_hi_wi_.mDesc.GetLengths()[2] && wi >= 0 &&
|
||||
wi < arg.in_n_c_hi_wi_.mDesc.GetLengths()[3])
|
||||
{
|
||||
v += arg.in_element_op_(
|
||||
ck::type_convert<float>(arg.in_n_c_hi_wi_(n, c, hi, wi))) *
|
||||
arg.wei_element_op_(
|
||||
ck::type_convert<float>(arg.wei_k_c_y_x_(k, c, y, x)));
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
float v2 = ck::type_convert<float>(arg.out_n_k_ho_wo_(n, k, ho, wo));
|
||||
|
||||
arg.out_element_op_(v2,
|
||||
v,
|
||||
ck::type_convert<float>(arg.bias_k_(k)),
|
||||
ck::type_convert<float>(arg.resi_n_k_ho_wo_(n, k, ho, wo)));
|
||||
|
||||
arg.out_n_k_ho_wo_(n, k, ho, wo) = ck::type_convert<OutDataType>(v2);
|
||||
};
|
||||
|
||||
make_ParallelTensorFunctor(f_nchw,
|
||||
arg.out_n_k_ho_wo_.mDesc.GetLengths()[0],
|
||||
arg.out_n_k_ho_wo_.mDesc.GetLengths()[1],
|
||||
arg.out_n_k_ho_wo_.mDesc.GetLengths()[2],
|
||||
arg.out_n_k_ho_wo_.mDesc.GetLengths()[3])(
|
||||
std::thread::hardware_concurrency());
|
||||
return 0;
|
||||
}
|
||||
|
||||
float Run(const device::BaseArgument* p_arg, int) override
|
||||
{
|
||||
return Run(*dynamic_cast<const Argument*>(p_arg));
|
||||
}
|
||||
};
|
||||
|
||||
static constexpr bool IsValidCompilationParameter()
|
||||
{
|
||||
// TODO: properly implement this check
|
||||
return true;
|
||||
}
|
||||
|
||||
bool IsSupportedArgument(const device::BaseArgument*) override { return true; }
|
||||
|
||||
static auto MakeArgument(const Tensor<InDataType>& in_n_c_hi_wi,
|
||||
const Tensor<WeiDataType>& wei_k_c_y_x,
|
||||
Tensor<OutDataType>& out_n_k_ho_wo,
|
||||
const Tensor<OutDataType>& bias_k,
|
||||
const Tensor<OutDataType>& resi_n_k_ho_wo,
|
||||
std::vector<ck::index_t> conv_filter_strides,
|
||||
std::vector<ck::index_t> conv_filter_dilations,
|
||||
std::vector<ck::index_t> input_left_pads,
|
||||
std::vector<ck::index_t> input_right_pads,
|
||||
InElementwiseOperation in_element_op,
|
||||
WeiElementwiseOperation wei_element_op,
|
||||
OutElementwiseOperation out_element_op)
|
||||
{
|
||||
return Argument{in_n_c_hi_wi,
|
||||
wei_k_c_y_x,
|
||||
out_n_k_ho_wo,
|
||||
bias_k,
|
||||
resi_n_k_ho_wo,
|
||||
conv_filter_strides,
|
||||
conv_filter_dilations,
|
||||
input_left_pads,
|
||||
input_right_pads,
|
||||
in_element_op,
|
||||
wei_element_op,
|
||||
out_element_op};
|
||||
}
|
||||
|
||||
static auto MakeInvoker() { return Invoker{}; }
|
||||
|
||||
virtual std::unique_ptr<device::BaseInvoker> MakeInvokerPointer()
|
||||
{
|
||||
return std::make_unique<Invoker>(Invoker{});
|
||||
}
|
||||
|
||||
std::string GetTypeString() const override
|
||||
{
|
||||
auto str = std::stringstream();
|
||||
|
||||
// clang-format off
|
||||
str << "ReferenceConvFwd_Bias_Activation_Add"
|
||||
<< std::endl;
|
||||
// clang-format on
|
||||
|
||||
return str.str();
|
||||
}
|
||||
};
|
||||
} // namespace host
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
#endif
|
||||
Reference in New Issue
Block a user