experiments/STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

[RunHandler] Minor optimizations to environment variable handling.

Browse Source 
1. Avoid re-evaluating the "TF_RUN_HANDLER_USE_SUB_THREAD_POOL" environment variable each time a task is enqueued, by caching the result in a static local variable.
2. A similar optimization in `ChooseRequestsWithExponentialDistribution()`.
3. Since all the arguments are string literals, we can pass `const char*` to the `ParamFromEnv*WithDefault()` methods, to avoid creating a temporary `std::string` on each call.

PiperOrigin-RevId: 308915732
Change-Id: I1642b5d924477eb006497acf95ac7cfc17956feb
This commit is contained in:
Derek Murray 2020-04-28 16:01:50 -07:00 committed by TensorFlower Gardener
parent 1a40c422ff
commit bb1e5c0d09
3 changed files with 22 additions and 24 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
tensorflow/core/framework/run_handler.cc
View File

@ -167,7 +167,7 @@ Task ThreadWorkSource::EnqueueTask(Task t, bool is_blocking) {
} }
Waiter* w = nullptr; Waiter* w = nullptr;
bool use_sub_thread_pool = static const bool use_sub_thread_pool =
ParamFromEnvBoolWithDefault("TF_RUN_HANDLER_USE_SUB_THREAD_POOL", false); ParamFromEnvBoolWithDefault("TF_RUN_HANDLER_USE_SUB_THREAD_POOL", false);
Waiter* waiter_queue; Waiter* waiter_queue;
@ -424,7 +424,8 @@ void RunHandlerThreadPool::SetThreadWorkSources(
// thread_work_sources are order as start_request_idx, 0, 2, 4 ... 1, 3, // thread_work_sources are order as start_request_idx, 0, 2, 4 ... 1, 3,
// 5... for half of the threads and start_request_idx, 1, 3, 5 ... 0, 2, // 5... for half of the threads and start_request_idx, 1, 3, 5 ... 0, 2,
// 4... for the other half of the threads. // 4... for the other half of the threads.
int num_shards = ParamFromEnvWithDefault("TF_RUN_HANDLER_QUEUE_SHARDS", 1); static const int num_shards =
ParamFromEnvWithDefault("TF_RUN_HANDLER_QUEUE_SHARDS", 1);
int token = tid % num_shards; int token = tid % num_shards;
for (int i = 0; i < num_shards; ++i) { for (int i = 0; i < num_shards; ++i) {
for (int j = token; j < thread_work_sources.size(); j += num_shards) { for (int j = token; j < thread_work_sources.size(); j += num_shards) {

31
tensorflow/core/framework/run_handler_util.cc
View File

@ -23,16 +23,15 @@ limitations under the License.
namespace tensorflow { namespace tensorflow {
double ParamFromEnvWithDefault(const std::string& var_name, double ParamFromEnvWithDefault(const char* var_name, double default_value) {
double default_value) { const char* val = std::getenv(var_name);
const char* val = std::getenv(var_name.c_str());
double num; double num;
return (val && strings::safe_strtod(val, &num)) ? num : default_value; return (val && strings::safe_strtod(val, &num)) ? num : default_value;
} }
std::vector<double> ParamFromEnvWithDefault(const std::string& var_name, std::vector<double> ParamFromEnvWithDefault(const char* var_name,
std::vector<double> default_value) { std::vector<double> default_value) {
const char* val = std::getenv(var_name.c_str()); const char* val = std::getenv(var_name);
if (!val) { if (!val) {
return default_value; return default_value;
} }
@ -51,9 +50,9 @@ std::vector<double> ParamFromEnvWithDefault(const std::string& var_name,
return result; return result;
} }
std::vector<int> ParamFromEnvWithDefault(const std::string& var_name, std::vector<int> ParamFromEnvWithDefault(const char* var_name,
std::vector<int> default_value) { std::vector<int> default_value) {
const char* val = std::getenv(var_name.c_str()); const char* val = std::getenv(var_name);
if (!val) { if (!val) {
return default_value; return default_value;
} }
@ -72,9 +71,8 @@ std::vector<int> ParamFromEnvWithDefault(const std::string& var_name,
return result; return result;
} }
bool ParamFromEnvBoolWithDefault(const std::string& var_name, bool ParamFromEnvBoolWithDefault(const char* var_name, bool default_value) {
bool default_value) { const char* val = std::getenv(var_name);
const char* val = std::getenv(var_name.c_str());
return (val) ? str_util::Lowercase(val) == "true" : default_value; return (val) ? str_util::Lowercase(val) == "true" : default_value;
} }
@ -148,19 +146,20 @@ std::vector<int> ChooseRequestsWithExponentialDistribution(
static const double kPowerBase = static const double kPowerBase =
ParamFromEnvWithDefault("TF_RUN_HANDLER_EXP_DIST_POWER_BASE", 2.0); ParamFromEnvWithDefault("TF_RUN_HANDLER_EXP_DIST_POWER_BASE", 2.0);
static const int kMinEvenThreadsFromEnv = static_cast<int>(
ParamFromEnvWithDefault("TF_RUN_HANDLER_EXP_DIST_MIN_EVEN_THREADS", 1));
static const int kMaxEvenThreadsFromEnv = static_cast<int>(
ParamFromEnvWithDefault("TF_RUN_HANDLER_EXP_DIST_MAX_EVEN_THREADS", 3));
std::vector<int> request_idx_list; std::vector<int> request_idx_list;
request_idx_list.resize(num_threads); request_idx_list.resize(num_threads);
// Each request gets at least this number of threads that steal from it first. // Each request gets at least this number of threads that steal from it first.
int min_threads_per_request = int min_threads_per_request =
num_threads * kCapacityFractionForEvenDistribution / num_active_requests; num_threads * kCapacityFractionForEvenDistribution / num_active_requests;
min_threads_per_request = min_threads_per_request =
std::max(static_cast<int>(ParamFromEnvWithDefault( std::max(kMinEvenThreadsFromEnv, min_threads_per_request);
"TF_RUN_HANDLER_EXP_DIST_MIN_EVEN_THREADS", 1)),
min_threads_per_request);
min_threads_per_request = min_threads_per_request =
std::min(static_cast<int>(ParamFromEnvWithDefault( std::min(kMaxEvenThreadsFromEnv, min_threads_per_request);
"TF_RUN_HANDLER_EXP_DIST_MAX_EVEN_THREADS", 3)),
min_threads_per_request);
int num_remaining_threads = int num_remaining_threads =
std::max(0, num_threads - num_active_requests * min_threads_per_request); std::max(0, num_threads - num_active_requests * min_threads_per_request);

10
tensorflow/core/framework/run_handler_util.h
View File

@ -56,25 +56,23 @@ std::vector<int> ChooseRequestsWithExponentialDistribution(
// Look up environment variable named 'var_name' and return the value if it // Look up environment variable named 'var_name' and return the value if it
// exist and can be parsed. Return 'default_value' otherwise. // exist and can be parsed. Return 'default_value' otherwise.
double ParamFromEnvWithDefault(const std::string& var_name, double ParamFromEnvWithDefault(const char* var_name, double default_value);
double default_value);
// Look up environment variable named 'var_name' and return the value if it // Look up environment variable named 'var_name' and return the value if it
// exist and can be parsed. The value must be in format val1,val2... Return // exist and can be parsed. The value must be in format val1,val2... Return
// 'default_value' otherwise. // 'default_value' otherwise.
std::vector<double> ParamFromEnvWithDefault(const std::string& var_name, std::vector<double> ParamFromEnvWithDefault(const char* var_name,
std::vector<double> default_value); std::vector<double> default_value);
// Look up environment variable named 'var_name' and return the value if it // Look up environment variable named 'var_name' and return the value if it
// exist and can be parsed. The value must be in format val1,val2... Return // exist and can be parsed. The value must be in format val1,val2... Return
// 'default_value' otherwise. // 'default_value' otherwise.
std::vector<int> ParamFromEnvWithDefault(const std::string& var_name, std::vector<int> ParamFromEnvWithDefault(const char* var_name,
std::vector<int> default_value); std::vector<int> default_value);
// Look up environment variable named 'var_name' and return the value if it // Look up environment variable named 'var_name' and return the value if it
// exist and can be parsed. Return 'default_value' otherwise. // exist and can be parsed. Return 'default_value' otherwise.
bool ParamFromEnvBoolWithDefault(const std::string& var_name, bool ParamFromEnvBoolWithDefault(const char* var_name, bool default_value);
bool default_value);
} // end namespace tensorflow } // end namespace tensorflow
#endif // TENSORFLOW_CORE_FRAMEWORK_RUN_HANDLER_UTIL_H_ #endif // TENSORFLOW_CORE_FRAMEWORK_RUN_HANDLER_UTIL_H_