experiments/STT-tensorflow
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Change existing call sites of the old deprecated gemmlowp WorkersPool::Execute method, which is a footgun because it destroys the Task object that it takes, to the new more explicit name LegacyExecuteAndDestroyTasks for the same behavior.

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PiperOrigin-RevId: 245999142
This commit is contained in:
Benoit Jacob 2019-04-30 12:30:39 -07:00 committed by TensorFlower Gardener
parent 7b57c5a02c
commit 6e28fe7894
3 changed files with 17 additions and 10 deletions
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7
tensorflow/lite/experimental/ruy/impl.h
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@ -285,8 +285,6 @@ void TrMul(TrMulParams* params, Context* context) {
allocator->Allocate(1, &atomic_n);
TrMulTask* tasks;
allocator->Allocate(thread_count, &tasks);
Task** tasks_ptrs;
allocator->Allocate(thread_count, &tasks_ptrs);
// Initialize allocated data.
for (int i = 0; i < num_blocks_of_rows; i++) {
@ -298,8 +296,7 @@ void TrMul(TrMulParams* params, Context* context) {
atomic_n->store(thread_count);
for (int i = 0; i < thread_count; i++) {
tasks_ptrs[i] = static_cast<Task*>(tasks + i);
new (tasks_ptrs[i])
new (tasks + i)
TrMulTask(params, block_map, atomic_n, i, lhs_packed, rhs_packed,
&context->per_thread_states[i]->tuning_resolver,
&context->per_thread_states[i]->allocator, trace);
@ -309,7 +306,7 @@ void TrMul(TrMulParams* params, Context* context) {
TraceRecordExecute(trace);
TraceStartRecordingBlockAndThreadFields(block_map, thread_count, trace);
context->workers_pool.Execute(thread_count, tasks_ptrs);
context->workers_pool.Execute(thread_count, tasks);
// Finish up.
for (int i = 0; i < thread_count; i++) {

8
tensorflow/lite/experimental/ruy/thread_pool.cc
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@ -225,17 +225,17 @@ class Thread {
BlockingCounter* const counter_to_decrement_when_ready_;
};
void ThreadPool::Execute(int task_count, Task** tasks_ptrs) {
void ThreadPool::ExecuteImpl(int task_count, int stride, Task* tasks) {
RUY_DCHECK_GE(task_count, 1);
// Task #0 will be run on the current thread.
CreateThreads(task_count - 1);
counter_to_decrement_when_ready_.Reset(task_count - 1);
for (int i = 1; i < task_count; i++) {
threads_[i - 1]->StartWork(tasks_ptrs[i]);
auto task_address = reinterpret_cast<std::uintptr_t>(tasks) + i * stride;
threads_[i - 1]->StartWork(reinterpret_cast<Task*>(task_address));
}
// Execute task #0 workload immediately on the current thread.
Task* last_task = tasks_ptrs[0];
last_task->Run();
(tasks + 0)->Run();
// Wait for the threads submitted above to finish.
counter_to_decrement_when_ready_.Wait();
}

12
tensorflow/lite/experimental/ruy/thread_pool.h
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@ -68,7 +68,13 @@ class ThreadPool {
// want to run an unbounded number of tasks on a bounded number of threads,
// then you need something higher-level than this ThreadPool, that can
// be layered on top of it by appropriately subclassing Tasks.
void Execute(int task_count, Task** tasks_ptrs);
//
// TaskType must be a subclass of ruy::Task. That is implicitly guarded by
// the static_cast in this inline implementation.
template <typename TaskType>
void Execute(int task_count, TaskType* tasks) {
ExecuteImpl(task_count, sizeof(TaskType), static_cast<Task*>(tasks));
}
private:
// Ensures that the pool has at least the given count of threads.
@ -76,6 +82,10 @@ class ThreadPool {
// be ready.
void CreateThreads(int threads_count);
// Non-templatized implementation of the public Execute method.
// See the inline implementation of Execute for how this is used.
void ExecuteImpl(int task_count, int stride, Task* tasks);
// copy construction disallowed
ThreadPool(const ThreadPool&) = delete;