82 lines
3.5 KiB
C++
82 lines
3.5 KiB
C++
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#ifndef TFLITE_WITH_RUY
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#include "tensorflow/lite/kernels/cpu_backend_gemm_eigen.h"
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// See b/131835803: in TFLite code, because eigen_spatial_convolutions.h does
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// #define Eigen EigenForTFLite, it is difficult to have any #include of Eigen
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// headers in a header file, as that results in name classes (compilation
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// errors) depending on the order in which these headers are #included.
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// So we have moved the #include of Eigen here, in a .cc file, where we have
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// control over the header #include sequence.
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#include "third_party/eigen3/Eigen/Core"
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#include "tensorflow/lite/kernels/cpu_backend_context.h"
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#include "tensorflow/lite/kernels/cpu_backend_gemm_params.h"
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#include "tensorflow/lite/kernels/internal/common.h"
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namespace tflite {
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namespace cpu_backend_gemm {
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namespace detail {
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// This function is out-of-line in a .cc file because of the issue
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// noted above in the comment on the #include for Eigen/Core.
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void GemmImplUsingEigen::Run(
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const MatrixParams<float>& lhs_params, const float* lhs_data,
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const MatrixParams<float>& rhs_params, const float* rhs_data,
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const MatrixParams<float>& dst_params, float* dst_data,
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const GemmParams<float, float>& params, CpuBackendContext* /* context */) {
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// This code assumes specific storage orders, encoded in these Eigen types.
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// These assumptions have been checked by TF_LITE_ASSERT's in the public
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// Gemm entry point already, before the implementation gets to this point.
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using EigenMatrixMapRowMajorConst =
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Eigen::Map<const Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic,
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Eigen::RowMajor>>;
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using EigenMatrixMapColMajorConst =
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Eigen::Map<const Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic,
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Eigen::ColMajor>>;
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using EigenMatrixMapColMajorMutable = Eigen::Map<
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Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::ColMajor>>;
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EigenMatrixMapRowMajorConst eigen_lhs(lhs_data, lhs_params.rows,
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lhs_params.cols);
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EigenMatrixMapColMajorConst eigen_rhs(rhs_data, rhs_params.rows,
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rhs_params.cols);
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EigenMatrixMapColMajorMutable eigen_dst(dst_data, dst_params.rows,
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dst_params.cols);
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if (rhs_params.cols == 1) {
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eigen_dst.col(0).noalias() = eigen_lhs * eigen_rhs.col(0);
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} else if (lhs_params.rows == 1) {
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eigen_dst.row(0).noalias() = eigen_lhs.row(0) * eigen_rhs;
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} else {
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eigen_dst.noalias() = eigen_lhs * eigen_rhs;
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}
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if (params.bias) {
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BiasAndClamp(params.clamp_min, params.clamp_max, dst_params.rows,
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params.bias, dst_params.rows * dst_params.cols, dst_data);
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} else {
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eigen_dst = eigen_dst.cwiseMin(params.clamp_max).cwiseMax(params.clamp_min);
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}
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}
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} // namespace detail
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} // namespace cpu_backend_gemm
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} // namespace tflite
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#endif // not TFLITE_WITH_RUY
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