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Performance-related tweaks: Don't copy loop variables; remove ineffective std::move casts.

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PiperOrigin-RevId: 158017670
This commit is contained in:
A. Unique TensorFlower 2017-06-05 08:37:14 -07:00 committed by TensorFlower Gardener
parent 009789f742
commit a51a9846cf
7 changed files with 8 additions and 8 deletions
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2
tensorflow/core/common_runtime/gpu/process_state.cc
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@ -127,7 +127,7 @@ Allocator* ProcessState::GetGPUAllocator(const GPUOptions& options, int gpu_id,
gpu_platform->ExecutorForDevice(gpu_id).ValueOrDie(); gpu_platform->ExecutorForDevice(gpu_id).ValueOrDie();
int bus_id = se->GetDeviceDescription().numa_node(); int bus_id = se->GetDeviceDescription().numa_node();
if (bus_id >= 0 && bus_id < static_cast<int64>(gpu_visitors_.size())) { if (bus_id >= 0 && bus_id < static_cast<int64>(gpu_visitors_.size())) {
for (auto v : gpu_visitors_[bus_id]) { for (const auto& v : gpu_visitors_[bus_id]) {
gpu_allocators_[gpu_id]->AddAllocVisitor(v); gpu_allocators_[gpu_id]->AddAllocVisitor(v);
} }
} }

2
tensorflow/core/common_runtime/shape_refiner_test.cc
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@ -557,7 +557,7 @@ TEST(ShapeRefinerTest, ConstantValueAsShape_PackInt32) {
.Finalize(root.graph(), &result)); .Finalize(root.graph(), &result));
ShapeRefiner m(TF_GRAPH_DEF_VERSION, OpRegistry::Global()); ShapeRefiner m(TF_GRAPH_DEF_VERSION, OpRegistry::Global());
for (auto input : inputs) { for (const auto& input : inputs) {
TF_ASSERT_OK(m.AddNode(input.node())); TF_ASSERT_OK(m.AddNode(input.node()));
} }
TF_ASSERT_OK(m.AddNode(pack.node())); TF_ASSERT_OK(m.AddNode(pack.node()));

2
tensorflow/core/distributed_runtime/rpc/grpc_remote_worker.cc
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@ -173,7 +173,7 @@ class GrpcRemoteWorker : public WorkerInterface {
} }
IssueRequest(req_copy ? req_copy : request, response, recvtensor_, IssueRequest(req_copy ? req_copy : request, response, recvtensor_,
std::move(*cb_to_use), call_opts); *cb_to_use, call_opts);
} }
void LoggingAsync(const LoggingRequest* request, LoggingResponse* response, void LoggingAsync(const LoggingRequest* request, LoggingResponse* response,

2
tensorflow/core/distributed_runtime/worker.cc
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@ -258,7 +258,7 @@ void Worker::DoPartialRunGraph(CallOptions* opts,
} }
} }
if (request->is_last_partial_run()) { if (request->is_last_partial_run()) {
partial_run_mgr_.PartialRunDone(step_id, std::move(finish), s); partial_run_mgr_.PartialRunDone(step_id, finish, s);
} else { } else {
finish(s); finish(s);
} }

4
tensorflow/core/kernels/cuda_solvers.cc
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@ -153,7 +153,7 @@ Status CudaSolver::CopyLapackInfoToHostAsync(
info_checker_callback) const { info_checker_callback) const {
std::vector<HostLapackInfo> host_lapack_infos; std::vector<HostLapackInfo> host_lapack_infos;
if (dev_lapack_infos.empty()) { if (dev_lapack_infos.empty()) {
info_checker_callback(Status::OK(), std::move(host_lapack_infos)); info_checker_callback(Status::OK(), host_lapack_infos);
return Status::OK(); return Status::OK();
} }
@ -174,7 +174,7 @@ Status CudaSolver::CopyLapackInfoToHostAsync(
auto wrapped_info_checker_callback = auto wrapped_info_checker_callback =
[info_checker_callback](std::vector<HostLapackInfo> host_lapack_infos) { [info_checker_callback](std::vector<HostLapackInfo> host_lapack_infos) {
Status status; Status status;
for (auto host_lapack_info : host_lapack_infos) { for (const auto& host_lapack_info : host_lapack_infos) {
for (int i = 0; i < host_lapack_info.size() && status.ok(); ++i) { for (int i = 0; i < host_lapack_info.size() && status.ok(); ++i) {
const int info_value = (host_lapack_info.data())[i]; const int info_value = (host_lapack_info.data())[i];
if (info_value != 0) { if (info_value != 0) {

2
tensorflow/core/kernels/iterator_ops.cc
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@ -246,7 +246,7 @@ class OneShotIteratorOp : public OpKernel {
n.Notify(); n.Notify();
}); });
n.WaitForNotification(); n.WaitForNotification();
OP_REQUIRES_OK(ctx, std::move(factory_status)); OP_REQUIRES_OK(ctx, factory_status);
OP_REQUIRES( OP_REQUIRES(
ctx, ctx,
return_values.size() == 1 && return_values.size() == 1 &&

2
tensorflow/stream_executor/cuda/cuda_diagnostics.cc
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@ -170,7 +170,7 @@ void Diagnostician::LogDiagnosticInformation() {
VLOG(1) << "LD_LIBRARY_PATH is: \"" << library_path << "\""; VLOG(1) << "LD_LIBRARY_PATH is: \"" << library_path << "\"";
std::vector<string> pieces = port::Split(library_path, ':'); std::vector<string> pieces = port::Split(library_path, ':');
for (auto piece : pieces) { for (const auto &piece : pieces) {
if (piece.empty()) { if (piece.empty()) {
continue; continue;
} }