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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>
This commit is contained in:
ltqin
166
host/include/reference_conv_fwd.hpp
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166
host/include/reference_conv_fwd.hpp
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@@ -0,0 +1,166 @@
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#ifndef REFERENCE_CONV_FWD_HPP
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#define REFERENCE_CONV_FWD_HPP
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#include <iostream>
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#include <sstream>
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#include "device_base.hpp"
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#include "host_tensor.hpp"
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namespace ck {
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namespace tensor_operation {
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namespace host {
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// out[N, K, Ho, Wo] = in[N, C, Hi, Wi] * wei[K, C, Y, X]
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template <typename InDataType,
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typename WeiDataType,
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typename OutDataType,
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typename AccDataType,
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typename InElementwiseOperation,
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typename WeiElementwiseOperation,
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typename OutElementwiseOperation>
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struct ReferenceConvFwd : public device::BaseOperator
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{
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// Argument
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struct Argument : public device::BaseArgument
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{
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Argument(const Tensor<InDataType>& in_n_c_hi_wi,
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const Tensor<WeiDataType>& wei_k_c_y_x,
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Tensor<OutDataType>& out_n_k_ho_wo,
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std::vector<ck::index_t> conv_filter_strides,
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std::vector<ck::index_t> conv_filter_dilations,
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std::vector<ck::index_t> input_left_pads,
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std::vector<ck::index_t> input_right_pads,
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InElementwiseOperation in_element_op,
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WeiElementwiseOperation wei_element_op,
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OutElementwiseOperation out_element_op)
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: in_n_c_hi_wi_{in_n_c_hi_wi},
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wei_k_c_y_x_{wei_k_c_y_x},
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out_n_k_ho_wo_{out_n_k_ho_wo},
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conv_strides_{conv_filter_strides},
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conv_dilations_{conv_filter_dilations},
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in_left_pads_{input_left_pads},
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in_right_pads_{input_right_pads},
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in_element_op_{in_element_op},
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wei_element_op_{wei_element_op},
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out_element_op_{out_element_op}
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{
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}
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const Tensor<InDataType>& in_n_c_hi_wi_;
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const Tensor<WeiDataType>& wei_k_c_y_x_;
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Tensor<OutDataType>& out_n_k_ho_wo_;
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std::vector<index_t> conv_strides_;
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std::vector<index_t> conv_dilations_;
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std::vector<index_t> in_left_pads_;
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std::vector<index_t> in_right_pads_;
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InElementwiseOperation in_element_op_;
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WeiElementwiseOperation wei_element_op_;
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OutElementwiseOperation out_element_op_;
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};
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// Invoker
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struct Invoker : public device::BaseInvoker
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{
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using Argument = ReferenceConvFwd::Argument;
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float Run(const Argument& arg)
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{
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auto f_nchw = [&](auto n, auto k, auto ho, auto wo) {
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float v = 0;
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for(int c = 0; c < arg.wei_k_c_y_x_.mDesc.GetLengths()[1]; ++c)
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{
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for(int y = 0; y < arg.wei_k_c_y_x_.mDesc.GetLengths()[2]; ++y)
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{
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int hi = ho * arg.conv_strides_[0] + y * arg.conv_dilations_[0] -
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arg.in_left_pads_[0];
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for(int x = 0; x < arg.wei_k_c_y_x_.mDesc.GetLengths()[3]; ++x)
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{
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int wi = wo * arg.conv_strides_[1] + x * arg.conv_dilations_[1] -
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arg.in_left_pads_[1];
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if(hi >= 0 && hi < arg.in_n_c_hi_wi_.mDesc.GetLengths()[2] && wi >= 0 &&
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wi < arg.in_n_c_hi_wi_.mDesc.GetLengths()[3])
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{
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v += arg.in_element_op_(
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ck::type_convert<float>(arg.in_n_c_hi_wi_(n, c, hi, wi))) *
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arg.wei_element_op_(
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ck::type_convert<float>(arg.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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arg.out_n_k_ho_wo_(n, k, ho, wo) =
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ck::type_convert<OutDataType>(arg.out_element_op_(v));
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};
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make_ParallelTensorFunctor(f_nchw,
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arg.out_n_k_ho_wo_.mDesc.GetLengths()[0],
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arg.out_n_k_ho_wo_.mDesc.GetLengths()[1],
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arg.out_n_k_ho_wo_.mDesc.GetLengths()[2],
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arg.out_n_k_ho_wo_.mDesc.GetLengths()[3])(
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std::thread::hardware_concurrency());
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return 0;
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}
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float Run(const device::BaseArgument* p_arg, int) override
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{
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return Run(*dynamic_cast<const Argument*>(p_arg));
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}
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};
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static constexpr bool IsValidCompilationParameter()
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{
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// TODO: properly implement this check
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return true;
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}
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bool IsSupportedArgument(const device::BaseArgument*) override { return true; }
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static auto MakeArgument(const Tensor<InDataType>& in_n_c_hi_wi,
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const Tensor<WeiDataType>& wei_k_c_y_x,
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Tensor<OutDataType>& out_n_k_ho_wo,
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std::vector<ck::index_t> conv_filter_strides,
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std::vector<ck::index_t> conv_filter_dilations,
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std::vector<ck::index_t> input_left_pads,
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std::vector<ck::index_t> input_right_pads,
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InElementwiseOperation in_element_op,
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WeiElementwiseOperation wei_element_op,
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OutElementwiseOperation out_element_op)
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{
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return Argument{in_n_c_hi_wi,
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wei_k_c_y_x,
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out_n_k_ho_wo,
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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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in_element_op,
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wei_element_op,
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out_element_op};
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}
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static auto MakeInvoker() { return Invoker{}; }
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virtual std::unique_ptr<device::BaseInvoker> MakeInvokerPointer()
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{
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return std::make_unique<Invoker>(Invoker{});
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}
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std::string GetTypeString() const override
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{
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auto str = std::stringstream();
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// clang-format off
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str << "ReferenceConvFwd"
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<< std::endl;
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// clang-format on
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return str.str();
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}
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};
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} // namespace host
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} // namespace tensor_operation
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} // namespace ck
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#endif
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172
host/include/reference_conv_fwd_bias_activation.hpp
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172
host/include/reference_conv_fwd_bias_activation.hpp
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@@ -0,0 +1,172 @@
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#ifndef REFERENCE_CONV_FWD_BIAS_ACTIVATION_HPP
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#define REFERENCE_CONV_FWD_BIAS_ACTIVATION_HPP
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#include <iostream>
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#include <sstream>
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#include "device_base.hpp"
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#include "host_tensor.hpp"
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namespace ck {
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namespace tensor_operation {
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namespace host {
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// out[N, Ho, Wo, K] =
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// activate(in[N, Hi, Wi, C] * wei[K, Y, X, C] + bias[K])
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template <typename InDataType,
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typename WeiDataType,
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typename OutDataType,
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typename AccDataType,
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typename InElementwiseOperation,
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typename WeiElementwiseOperation,
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typename OutElementwiseOperation>
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struct ReferenceConvFwd_Bias_Activation : public device::BaseOperator
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{
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// Argument
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struct Argument : public device::BaseArgument
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{
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Argument(const Tensor<InDataType>& in_n_c_hi_wi,
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const Tensor<WeiDataType>& wei_k_c_y_x,
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Tensor<OutDataType>& out_n_k_ho_wo,
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const Tensor<OutDataType>& bias_k,
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std::vector<ck::index_t> conv_filter_strides,
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std::vector<ck::index_t> conv_filter_dilations,
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std::vector<ck::index_t> input_left_pads,
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std::vector<ck::index_t> input_right_pads,
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InElementwiseOperation in_element_op,
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WeiElementwiseOperation wei_element_op,
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OutElementwiseOperation out_element_op)
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: in_n_c_hi_wi_{in_n_c_hi_wi},
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wei_k_c_y_x_{wei_k_c_y_x},
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out_n_k_ho_wo_{out_n_k_ho_wo},
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bias_k_{bias_k},
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conv_strides_{conv_filter_strides},
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conv_dilations_{conv_filter_dilations},
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in_left_pads_{input_left_pads},
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in_right_pads_{input_right_pads},
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in_element_op_{in_element_op},
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wei_element_op_{wei_element_op},
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out_element_op_{out_element_op}
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{
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}
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const Tensor<InDataType>& in_n_c_hi_wi_;
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const Tensor<WeiDataType>& wei_k_c_y_x_;
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Tensor<OutDataType>& out_n_k_ho_wo_;
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const Tensor<OutDataType>& bias_k_;
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std::vector<index_t> conv_strides_;
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std::vector<index_t> conv_dilations_;
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std::vector<index_t> in_left_pads_;
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std::vector<index_t> in_right_pads_;
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InElementwiseOperation in_element_op_;
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WeiElementwiseOperation wei_element_op_;
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OutElementwiseOperation out_element_op_;
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};
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// Invoker
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struct Invoker : public device::BaseInvoker
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{
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using Argument = ReferenceConvFwd_Bias_Activation::Argument;
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float Run(const Argument& arg)
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{
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auto f_nchw = [&](auto n, auto k, auto ho, auto wo) {
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float v = 0;
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for(int c = 0; c < arg.wei_k_c_y_x_.mDesc.GetLengths()[1]; ++c)
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{
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for(int y = 0; y < arg.wei_k_c_y_x_.mDesc.GetLengths()[2]; ++y)
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{
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int hi = ho * arg.conv_strides_[0] + y * arg.conv_dilations_[0] -
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arg.in_left_pads_[0];
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for(int x = 0; x < arg.wei_k_c_y_x_.mDesc.GetLengths()[3]; ++x)
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{
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int wi = wo * arg.conv_strides_[1] + x * arg.conv_dilations_[1] -
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arg.in_left_pads_[1];
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if(hi >= 0 && hi < arg.in_n_c_hi_wi_.mDesc.GetLengths()[2] && wi >= 0 &&
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wi < arg.in_n_c_hi_wi_.mDesc.GetLengths()[3])
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{
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v += arg.in_element_op_(
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ck::type_convert<float>(arg.in_n_c_hi_wi_(n, c, hi, wi))) *
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arg.wei_element_op_(
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ck::type_convert<float>(arg.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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arg.out_n_k_ho_wo_(n, k, ho, wo) =
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ck::type_convert<OutDataType>(arg.out_element_op_(v, arg.bias_k_(k)));
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};
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make_ParallelTensorFunctor(f_nchw,
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arg.out_n_k_ho_wo_.mDesc.GetLengths()[0],
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arg.out_n_k_ho_wo_.mDesc.GetLengths()[1],
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arg.out_n_k_ho_wo_.mDesc.GetLengths()[2],
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arg.out_n_k_ho_wo_.mDesc.GetLengths()[3])(
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std::thread::hardware_concurrency());
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return 0;
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}
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float Run(const device::BaseArgument* p_arg, int) override
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{
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return Run(*dynamic_cast<const Argument*>(p_arg));
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}
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};
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static constexpr bool IsValidCompilationParameter()
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{
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// TODO: properly implement this check
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return true;
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}
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bool IsSupportedArgument(const device::BaseArgument*) override { return true; }
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static auto MakeArgument(const Tensor<InDataType>& in_n_c_hi_wi,
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const Tensor<WeiDataType>& wei_k_c_y_x,
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Tensor<OutDataType>& out_n_k_ho_wo,
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const Tensor<OutDataType>& bias_k,
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std::vector<ck::index_t> conv_filter_strides,
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std::vector<ck::index_t> conv_filter_dilations,
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std::vector<ck::index_t> input_left_pads,
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std::vector<ck::index_t> input_right_pads,
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InElementwiseOperation in_element_op,
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WeiElementwiseOperation wei_element_op,
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OutElementwiseOperation out_element_op)
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{
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return Argument{in_n_c_hi_wi,
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wei_k_c_y_x,
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out_n_k_ho_wo,
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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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in_element_op,
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wei_element_op,
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out_element_op};
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}
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static auto MakeInvoker() { return Invoker{}; }
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virtual std::unique_ptr<device::BaseInvoker> MakeInvokerPointer()
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{
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return std::make_unique<Invoker>(Invoker{});
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}
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std::string GetTypeString() const override
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{
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auto str = std::stringstream();
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// clang-format off
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str << "ReferenceConvFwd_Bias_Activation"
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<< std::endl;
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// clang-format on
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return str.str();
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}
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};
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} // namespace host
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} // namespace tensor_operation
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} // namespace ck
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#endif
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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 @@
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#ifndef REFERENCE_CONV2D_FWD_BIAS_ACTIVATION_ADD_HPP
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#define REFERENCE_CONV2D_FWD_BIAS_ACTIVATION_ADD_HPP
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#include <iostream>
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#include <sstream>
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#include "device_base.hpp"
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#include "host_tensor.hpp"
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namespace ck {
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namespace tensor_operation {
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namespace host {
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// out[N, Ho, Wo, K] =
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// activate(in[N, Hi, Wi, C] * wei[K, Y, X, C] + bias[K]) + residual[N, Ho, Wo, K]
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template <typename InDataType,
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typename WeiDataType,
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typename OutDataType,
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typename AccDataType,
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typename InElementwiseOperation,
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typename WeiElementwiseOperation,
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typename OutElementwiseOperation>
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struct ReferenceConvFwd_Bias_Activation_Add : public device::BaseOperator
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{
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// Argument
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struct Argument : public device::BaseArgument
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{
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Argument(const Tensor<InDataType>& in_n_c_hi_wi,
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const Tensor<WeiDataType>& wei_k_c_y_x,
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Tensor<OutDataType>& out_n_k_ho_wo,
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const Tensor<OutDataType>& bias_k,
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const Tensor<OutDataType>& resi_n_k_ho_wo,
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std::vector<ck::index_t> conv_filter_strides,
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std::vector<ck::index_t> conv_filter_dilations,
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std::vector<ck::index_t> input_left_pads,
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std::vector<ck::index_t> input_right_pads,
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InElementwiseOperation in_element_op,
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WeiElementwiseOperation wei_element_op,
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OutElementwiseOperation out_element_op)
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: in_n_c_hi_wi_{in_n_c_hi_wi},
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wei_k_c_y_x_{wei_k_c_y_x},
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out_n_k_ho_wo_{out_n_k_ho_wo},
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bias_k_{bias_k},
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resi_n_k_ho_wo_{resi_n_k_ho_wo},
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conv_strides_{conv_filter_strides},
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conv_dilations_{conv_filter_dilations},
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in_left_pads_{input_left_pads},
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in_right_pads_{input_right_pads},
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in_element_op_{in_element_op},
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wei_element_op_{wei_element_op},
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out_element_op_{out_element_op}
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{
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}
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const Tensor<InDataType>& in_n_c_hi_wi_;
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const Tensor<WeiDataType>& wei_k_c_y_x_;
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Tensor<OutDataType>& out_n_k_ho_wo_;
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const Tensor<OutDataType>& bias_k_;
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const Tensor<OutDataType>& resi_n_k_ho_wo_;
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std::vector<index_t> conv_strides_;
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std::vector<index_t> conv_dilations_;
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std::vector<index_t> in_left_pads_;
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std::vector<index_t> in_right_pads_;
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InElementwiseOperation in_element_op_;
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WeiElementwiseOperation wei_element_op_;
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OutElementwiseOperation out_element_op_;
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};
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// Invoker
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struct Invoker : public device::BaseInvoker
|
||||
{
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using Argument = ReferenceConvFwd_Bias_Activation_Add::Argument;
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||||
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float Run(const Argument& arg)
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||||
{
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||||
auto f_nchw = [&](auto n, auto k, auto ho, auto wo) {
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||||
float v = 0;
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||||
for(int c = 0; c < arg.wei_k_c_y_x_.mDesc.GetLengths()[1]; ++c)
|
||||
{
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||||
for(int y = 0; y < arg.wei_k_c_y_x_.mDesc.GetLengths()[2]; ++y)
|
||||
{
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||||
int hi = ho * arg.conv_strides_[0] + y * arg.conv_dilations_[0] -
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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