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_CORE_KERNELS_PARTITIONED_FUNCTION_OPS_H_ |
17 | #define TENSORFLOW_CORE_KERNELS_PARTITIONED_FUNCTION_OPS_H_ |
18 | |
19 | #include "tensorflow/core/common_runtime/function.h" |
20 | #include "tensorflow/core/framework/function.h" |
21 | #include "tensorflow/core/framework/op_kernel.h" |
22 | #include "tensorflow/core/framework/tensor.h" |
23 | |
24 | namespace tensorflow { |
25 | |
26 | class NameAttrList; |
27 | class ConfigProto; |
28 | |
29 | // A `PartitionedCallOp` asynchronously executes a function, potentially across |
30 | // multiple devices but within a single process. The kernel places and |
31 | // partitions a given function's underlying graph, and executes each of the |
32 | // partitioned subgraphs as a function. |
33 | // |
34 | // TODO(akshayka): Support distributed execution. |
35 | class PartitionedCallOp : public AsyncOpKernel { |
36 | public: |
37 | explicit PartitionedCallOp(OpKernelConstruction* ctx); |
38 | |
39 | ~PartitionedCallOp() override; |
40 | |
41 | void ComputeAsync(OpKernelContext* ctx, DoneCallback done) override; |
42 | |
43 | private: |
44 | Status FillOutputDevices(const FunctionLibraryRuntime& lib, |
45 | const Device& cpu_device, AttrSlice attrs, |
46 | FunctionLibraryRuntime::InstantiateOptions* opts); |
47 | |
48 | Status Instantiate(FunctionLibraryRuntime* lib, OpKernelContext* ctx, |
49 | std::vector<Tensor>* inputs, |
50 | FunctionLibraryRuntime::Handle* handle); |
51 | |
52 | void RunFunction(FunctionLibraryRuntime::Handle handle, |
53 | const std::vector<Tensor>& inputs, |
54 | FunctionLibraryRuntime* lib, OpKernelContext* ctx, |
55 | DoneCallback done); |
56 | |
57 | // Using unique pointers to avoid including proto headers in kernel headers |
58 | std::unique_ptr<NameAttrList> func_; |
59 | std::unique_ptr<ConfigProto> config_proto_; |
60 | string executor_type_; |
61 | bool shared_rendezvous_; |
62 | mutex mu_; |
63 | // Cache the handle per FLR because this kernel may be instantiated for |
64 | // a stateful op, different invocations of it may use different FLRs. |
65 | // Different device placements of PartitionedCallOp also use |
66 | // different FLRs. |
67 | gtl::FlatMap<FunctionLibraryRuntime*, FunctionLibraryRuntime::Handle> handles_ |
68 | TF_GUARDED_BY(mu_); |
69 | }; |
70 | |
71 | } // namespace tensorflow |
72 | |
73 | #endif // TENSORFLOW_CORE_KERNELS_PARTITIONED_FUNCTION_OPS_H_ |
74 | |