56 lines
1.9 KiB
C++
56 lines
1.9 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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#include "tensorflow/compiler/tf2xla/xla_op_kernel.h"
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#include "tensorflow/compiler/tf2xla/xla_op_registry.h"
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#include "tensorflow/compiler/xla/client/lib/slicing.h"
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#include "tensorflow/compiler/xla/client/lib/tridiagonal.h"
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#include "tensorflow/core/framework/node_def_util.h"
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#include "tensorflow/core/lib/core/errors.h"
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#include "tensorflow/core/platform/errors.h"
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namespace tensorflow {
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namespace {
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class TridiagonalSolveOp : public XlaOpKernel {
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public:
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explicit TridiagonalSolveOp(OpKernelConstruction* ctx) : XlaOpKernel(ctx) {}
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void Compile(XlaOpKernelContext* ctx) override {
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auto diagonals = ctx->Input(0);
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auto rhs = ctx->Input(1);
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bool partial_pivoting = false;
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OP_REQUIRES_OK(ctx,
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GetNodeAttr(def(), "partial_pivoting", &partial_pivoting));
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if (partial_pivoting) {
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ctx->SetStatus(errors::Unimplemented(
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"Current implementation does not yet support pivoting."));
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return;
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}
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auto result = xla::tridiagonal::ThomasSolver(diagonals, rhs);
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if (!result.ok()) {
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ctx->SetStatus(result.status());
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return;
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}
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ctx->SetOutput(0, result.ValueOrDie());
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}
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};
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REGISTER_XLA_OP(Name("TridiagonalSolve").TypeConstraint("T", kFloatTypes),
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TridiagonalSolveOp);
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} // namespace
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} // namespace tensorflow
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