1 /* Copyright 2019 The TensorFlow Authors. All Rights Reserved. 2 3 Licensed under the Apache License, Version 2.0 (the "License"); 4 you may not use this file except in compliance with the License. 5 You may obtain a copy of the License at 6 7 http://www.apache.org/licenses/LICENSE-2.0 8 9 Unless required by applicable law or agreed to in writing, software 10 distributed under the License is distributed on an "AS IS" BASIS, 11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 See the License for the specific language governing permissions and 13 limitations under the License. 14 ==============================================================================*/ 15 16 #ifndef TENSORFLOW_COMPILER_XLA_CLIENT_LIB_SELF_ADJOINT_EIG_H_ 17 #define TENSORFLOW_COMPILER_XLA_CLIENT_LIB_SELF_ADJOINT_EIG_H_ 18 19 #include "tensorflow/compiler/xla/client/xla_builder.h" 20 #include "tensorflow/compiler/xla/xla_data.pb.h" 21 22 namespace xla { 23 24 // The eigenvalue decomposition of a symmetric matrix, the original matrix is 25 // recovered by v * w * v_t. 26 struct SelfAdjointEigResult { 27 // The i-th column is the normalized eigenvector corresponding to the 28 // eigenvalue w[i]. Will return a matrix object if a is a matrix object. 29 XlaOp v; 30 // The eigenvalues in ascending order, each repeated according to its 31 // multiplicity. 32 XlaOp w; 33 }; 34 35 SelfAdjointEigResult SelfAdjointEig(XlaOp a, bool lower = true, 36 int64 max_iter = 100, float epsilon = 1e-6); 37 38 } // namespace xla 39 40 #endif // TENSORFLOW_COMPILER_XLA_CLIENT_LIB_SELF_ADJOINT_EIG_H_ 41
