43 lines
1.5 KiB
C++
43 lines
1.5 KiB
C++
/* Copyright 2018 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 TENSORFLOW_COMPILER_XLA_CLIENT_LIB_QR_H_
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#define TENSORFLOW_COMPILER_XLA_CLIENT_LIB_QR_H_
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#include "tensorflow/compiler/xla/client/xla_builder.h"
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#include "tensorflow/compiler/xla/xla_data.pb.h"
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namespace xla {
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// Computes the QR decompositions of a batch of matrices. That is,
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// given a (batched) matrix a, computes an orthonormal matrix Q and an
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// upper-triangular matrix R such that a = QR.
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// `a` must be a (batched) matrix of size [..., m, n].
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// The algorithm implements a blocked QR decomposition; `block_size` is
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// the block size to use.
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// TODO(phawkins): handle the complex case.
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struct QRDecompositionResult {
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XlaOp q;
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XlaOp r;
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};
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StatusOr<QRDecompositionResult> QRDecomposition(
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XlaOp a, bool full_matrices, int64 block_size = 128,
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PrecisionConfig::Precision precision = PrecisionConfig::HIGHEST);
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} // namespace xla
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#endif // TENSORFLOW_COMPILER_XLA_CLIENT_LIB_QR_H_
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