STT-tensorflow/tensorflow/compiler/jit/xla_kernel_creator.h
A. Unique TensorFlower 5f3a3019ba Replace NodeDef with std::shared_ptr<NodeProperties> in the kernel creation code paths and try to avoid as many copies of NodeDefs as possible. This will in most cases allow sharing the NodeDef between the OpKernel and the graph Node from which it is created.
This reduces the number of allocations in the executor benchmark by about 8%:

name                                                 old time/op             new time/op             delta
BM_executor/16/1k       [Nodes = 9824  ]              911µs ± 3%              911µs ± 1%    ~     (p=0.548 n=5+5)
BM_executor/32/8k       [Nodes = 141991]             17.1ms ± 2%             16.8ms ± 1%  -2.17%  (p=0.016 n=5+5)
BM_executor/1k/16       [Nodes = 6781  ]             1.21ms ± 1%             1.25ms ± 7%    ~     (p=0.095 n=5+5)
BM_executor/8k/32       [Nodes = 130875]              4.35s ± 0%              4.34s ± 0%    ~     (p=0.841 n=5+5)
BM_executor/1k/1k       [Nodes = 526256]              3.33s ± 1%              3.31s ± 1%    ~     (p=0.095 n=5+5)
BM_FeedInputFetchOutput                              54.0µs ± 7%             56.9µs ±13%    ~     (p=0.222 n=5+5)

name                                                 old allocs/op           new allocs/op           delta
BM_executor/16/1k       [Nodes = 9824  ]              15.4k ± 0%              14.1k ± 0%  -7.95%  (p=0.008 n=5+5)
BM_executor/32/8k       [Nodes = 141991]               226k ± 0%               208k ± 0%  -7.86%  (p=0.008 n=5+5)
BM_executor/1k/16       [Nodes = 6781  ]              10.2k ± 0%               9.3k ± 0%  -8.36%  (p=0.008 n=5+5)
BM_executor/8k/32       [Nodes = 130875]               197k ± 0%               180k ± 0%  -8.31%  (p=0.016 n=4+5)
BM_executor/1k/1k       [Nodes = 526256]               771k ± 0%               706k ± 0%  -8.53%  (p=0.008 n=5+5)
BM_FeedInputFetchOutput                                58.0 ± 0%               57.0 ± 0%  -1.72%  (p=0.008 n=5+5)

PiperOrigin-RevId: 295803318
Change-Id: I0d262c6082822023f449f9817dc943d20bd302d5
2020-02-18 13:20:06 -08:00

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/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_COMPILER_JIT_XLA_KERNEL_CREATOR_H_
#define TENSORFLOW_COMPILER_JIT_XLA_KERNEL_CREATOR_H_
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/lib/core/status.h"
namespace tensorflow {
class FunctionLibraryRuntime;
class OpKernel;
class XlaKernelCreator : public CustomKernelCreator {
public:
// Given a NodeDef 'node_def' and the function library runtime 'flr', returns
// true if 'node_def' is a call to a compilable function defined in 'flr',
// with the kXlaCompileAttr set.
bool CanCreateKernel(
const FunctionLibraryRuntime& flr,
const std::shared_ptr<const NodeProperties>& props) const override;
// Given a supported NodeDef, returns a XlaLaunchOp that computes the node.
Status CreateKernel(FunctionLibraryRuntime* flr,
const std::shared_ptr<const NodeProperties>& props,
std::unique_ptr<OpKernel>* kernel) const override;
};
} // namespace tensorflow
#endif // TENSORFLOW_COMPILER_JIT_XLA_KERNEL_CREATOR_H_