experiments/STT-tensorflow
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[Tensor] Cache the result of LogMemory::IsEnabled() in tensor.cc.

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At present, each Tensor construction and destruction call involves a non-inlined call to `LogMemory::IsEnabled()`, which tests the logging verbosity level. This change moves the result of that check to a static method in the same compilation unit, so that the check can be inlined.

PiperOrigin-RevId: 288327926
Change-Id: I3f524a4b3bcdaa4756cc3aa2189291eea1bd8a0c
This commit is contained in:
Derek Murray 2020-01-06 10:33:46 -08:00 committed by TensorFlower Gardener
parent 24d35cca11
commit cf7a3570fd
1 changed files with 10 additions and 5 deletions
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15
tensorflow/core/framework/tensor.cc
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@ -144,6 +144,11 @@ void LogUnexpectedSize(int64 actual, int64 expected) {
LOG(ERROR) << "Input size was " << actual << " and expected " << expected;
}
bool MemoryLoggingEnabled() {
static bool memory_logging_enabled = LogMemory::IsEnabled();
return memory_logging_enabled;
}
// A set of helper functions depending on T.
template <typename T>
struct Helper {
@ -476,7 +481,7 @@ Buffer<T>::Buffer(Allocator* a, int64 n,
template <typename T>
Buffer<T>::~Buffer() {
if (data()) {
if (LogMemory::IsEnabled()) {
if (MemoryLoggingEnabled()) {
RecordDeallocation();
}
TypedAllocator::Deallocate<T>(alloc_, static_cast<T*>(data()), elem_);
@ -770,7 +775,7 @@ Tensor::Tensor(Allocator* a, DataType type, const TensorShape& shape)
if (shape_.num_elements() > 0 || a->AllocatesOpaqueHandle()) {
CASES(type, buf_ = new Buffer<T>(a, shape.num_elements()));
}
if (buf_ != nullptr && buf_->data() != nullptr && LogMemory::IsEnabled()) {
if (MemoryLoggingEnabled() && buf_ != nullptr && buf_->data() != nullptr) {
LogMemory::RecordTensorAllocation("Unknown", LogMemory::UNKNOWN_STEP_ID,
*this);
}
@ -784,8 +789,8 @@ Tensor::Tensor(Allocator* a, DataType type, const TensorShape& shape,
if (shape_.num_elements() > 0 || a->AllocatesOpaqueHandle()) {
CASES(type, buf_ = new Buffer<T>(a, shape.num_elements(), allocation_attr));
}
if (!allocation_attr.allocation_will_be_logged && buf_ != nullptr &&
buf_->data() != nullptr && LogMemory::IsEnabled()) {
if (MemoryLoggingEnabled() && !allocation_attr.allocation_will_be_logged &&
buf_ != nullptr && buf_->data() != nullptr) {
LogMemory::RecordTensorAllocation("Unknown (with attributes)",
LogMemory::UNKNOWN_STEP_ID, *this);
}
@ -936,7 +941,7 @@ bool Tensor::FromProto(Allocator* a, const TensorProto& proto) {
buf_ = p;
// TODO(misard) add tracking of which kernels and steps are calling
// FromProto.
if (buf_ != nullptr && buf_->data() != nullptr && LogMemory::IsEnabled()) {
if (MemoryLoggingEnabled() && buf_ != nullptr && buf_->data() != nullptr) {
LogMemory::RecordTensorAllocation("Unknown (from Proto)",
LogMemory::UNKNOWN_STEP_ID, *this);
}