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 #include "tensorflow/core/common_runtime/single_threaded_cpu_device.h"
17
18 #define EIGEN_USE_THREADS
19
20 #include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
21 #include "tensorflow/core/common_runtime/device.h"
22 #include "tensorflow/core/framework/allocator.h"
23 #include "tensorflow/core/framework/tensor.pb.h"
24 #include "tensorflow/core/framework/tensor_util.h"
25 #include "tensorflow/core/lib/core/threadpool.h"
26
27 namespace tensorflow {
28
29 namespace {
30
31 static constexpr int kNumThreads = 1;
32
GraphRunnerThreadPool()33 thread::ThreadPool* GraphRunnerThreadPool() {
34 static thread::ThreadPool* thread_pool =
35 new thread::ThreadPool(Env::Default(), "graph_runner", kNumThreads);
36 return thread_pool;
37 }
38
39 // A simple single-threaded CPU device. This can be used to run inexpensive
40 // computations. In particular, using this avoids initializing the global thread
41 // pools in LocalDevice.
42 class SingleThreadedCpuDevice : public Device {
43 public:
SingleThreadedCpuDevice(Env * env)44 explicit SingleThreadedCpuDevice(Env* env)
45 : Device(env, Device::BuildDeviceAttributes("/device:CPU:0", DEVICE_CPU,
46 Bytes(256 << 20),
47 DeviceLocality())) {
48 eigen_worker_threads_.num_threads = kNumThreads;
49 eigen_worker_threads_.workers = GraphRunnerThreadPool();
50 eigen_device_.reset(new Eigen::ThreadPoolDevice(
51 eigen_worker_threads_.workers->AsEigenThreadPool(),
52 eigen_worker_threads_.num_threads));
53 set_tensorflow_cpu_worker_threads(&eigen_worker_threads_);
54 set_eigen_cpu_device(eigen_device_.get());
55 }
56
~SingleThreadedCpuDevice()57 ~SingleThreadedCpuDevice() override { eigen_device_.reset(); }
58
Sync()59 Status Sync() override { return Status::OK(); }
60
MakeTensorFromProto(const TensorProto & tensor_proto,const AllocatorAttributes alloc_attrs,Tensor * tensor)61 Status MakeTensorFromProto(const TensorProto& tensor_proto,
62 const AllocatorAttributes alloc_attrs,
63 Tensor* tensor) override {
64 Tensor parsed(tensor_proto.dtype());
65 if (!parsed.FromProto(cpu_allocator(), tensor_proto)) {
66 return errors::InvalidArgument("Cannot parse tensor from tensor_proto.");
67 }
68 *tensor = parsed;
69 return Status::OK();
70 }
71
CopyTensorInSameDevice(const Tensor * input_tensor,Tensor * output_tensor,const DeviceContext *,StatusCallback done)72 void CopyTensorInSameDevice(const Tensor* input_tensor, Tensor* output_tensor,
73 const DeviceContext*,
74 StatusCallback done) override {
75 if (input_tensor->NumElements() != output_tensor->NumElements()) {
76 done(errors::Internal(
77 "SingleThreadedCPU->SingleThreadedCPU copy shape mismatch: input=",
78 input_tensor->shape(), ", output=", output_tensor->shape()));
79 return;
80 }
81 tensor::DeepCopy(*input_tensor, output_tensor);
82 done(Status::OK());
83 }
84
GetAllocator(AllocatorAttributes attr)85 Allocator* GetAllocator(AllocatorAttributes attr) override {
86 return cpu_allocator();
87 }
88
89 private:
90 DeviceBase::CpuWorkerThreads eigen_worker_threads_;
91 std::unique_ptr<Eigen::ThreadPoolDevice> eigen_device_;
92 };
93
94 } // namespace
95
NewSingleThreadedCpuDevice(Env * env)96 Device* NewSingleThreadedCpuDevice(Env* env) {
97 return new SingleThreadedCpuDevice(env);
98 }
99
100 } // namespace tensorflow
101