提交 d13dd3b6 编写于 作者: T tensor-tang

revert profiling

上级 4d11c8e9
......@@ -156,10 +156,27 @@ void TestInference(const std::string& dirname,
auto executor = paddle::framework::Executor(place);
auto* scope = new paddle::framework::Scope();
// Profile the performance
paddle::platform::ProfilerState state;
if (paddle::platform::is_cpu_place(place)) {
state = paddle::platform::ProfilerState::kCPU;
} else {
#ifdef PADDLE_WITH_CUDA
state = paddle::platform::ProfilerState::kAll;
// The default device_id of paddle::platform::CUDAPlace is 0.
// Users can get the device_id using:
// int device_id = place.GetDeviceId();
paddle::platform::SetDeviceId(0);
#else
PADDLE_THROW("'CUDAPlace' is not supported in CPU only device.");
#endif
}
// 2. Initialize the inference_program and load parameters
std::unique_ptr<paddle::framework::ProgramDesc> inference_program;
// Enable the profiler
paddle::platform::EnableProfiler(state);
{
paddle::platform::RecordEvent record_event(
"init_program",
......@@ -172,6 +189,10 @@ void TestInference(const std::string& dirname,
EnableMKLDNN(inference_program);
}
}
// Disable the profiler and print the timing information
paddle::platform::DisableProfiler(paddle::platform::EventSortingKey::kDefault,
"load_program_profiler");
paddle::platform::ResetProfiler();
// 3. Get the feed_target_names and fetch_target_names
const std::vector<std::string>& feed_target_names =
......@@ -212,6 +233,9 @@ void TestInference(const std::string& dirname,
true, CreateVars);
}
// Enable the profiler
paddle::platform::EnableProfiler(state);
// Run repeat times to profile the performance
for (int i = 0; i < repeat; ++i) {
paddle::platform::RecordEvent record_event(
......@@ -228,6 +252,11 @@ void TestInference(const std::string& dirname,
CreateVars);
}
}
// Disable the profiler and print the timing information
paddle::platform::DisableProfiler(
paddle::platform::EventSortingKey::kDefault, "run_inference_profiler");
paddle::platform::ResetProfiler();
}
delete scope;
......
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