From 0358fd019781096b98c8dfe7aff553e6636f2c74 Mon Sep 17 00:00:00 2001 From: dangqingqing Date: Tue, 23 Jan 2018 19:23:38 +0800 Subject: [PATCH] Refine profiler code. --- paddle/framework/executor.cc | 3 +-- paddle/platform/profiler.cc | 18 ++++++++++-------- paddle/platform/profiler.h | 12 ++++++------ python/paddle/v2/fluid/profiler.py | 9 +++++---- python/paddle/v2/fluid/tests/test_profiler.py | 12 ++++++------ 5 files changed, 28 insertions(+), 26 deletions(-) diff --git a/paddle/framework/executor.cc b/paddle/framework/executor.cc index 811fe03a6..d9e8921f0 100644 --- a/paddle/framework/executor.cc +++ b/paddle/framework/executor.cc @@ -120,8 +120,7 @@ void Executor::Run(const ProgramDesc& pdesc, Scope* scope, int block_id, VLOG(3) << op->DebugStringEx(local_scope); platform::DeviceContextPool& pool = platform::DeviceContextPool::Instance(); - auto dev_ctx = const_cast(pool.Get(place_)); - platform::RecordEvent record_event(op->Type(), dev_ctx); + platform::RecordEvent record_event(op->Type(), pool.Get(place_)); op->Run(*local_scope, place_); if (FLAGS_do_memory_benchmark) { diff --git a/paddle/platform/profiler.cc b/paddle/platform/profiler.cc index 8175b827c..2a8afc940 100644 --- a/paddle/platform/profiler.cc +++ b/paddle/platform/profiler.cc @@ -47,16 +47,16 @@ inline uint64_t GetTimeInNsec() { } Event::Event(EventKind kind, std::string name, uint32_t thread_id, - DeviceContext* dev_ctx) + const DeviceContext* dev_ctx) : kind_(kind), name_(name), thread_id_(thread_id), has_cuda_(false) { #ifdef PADDLE_WITH_CUDA - auto* cuda_dev_ctx = static_cast(dev_ctx); - if (cuda_dev_ctx) { + has_cuda_ = dev_ctx ? platform::is_gpu_place(dev_ctx->GetPlace()) : false; + if (has_cuda_) { + auto* cuda_dev_ctx = static_cast(dev_ctx); PADDLE_ENFORCE(cudaGetDevice(&device_)); PADDLE_ENFORCE(cudaEventCreate(&event_)); auto stream = cuda_dev_ctx->stream(); PADDLE_ENFORCE(cudaEventRecord(event_, stream)); - has_cuda_ = true; } #endif cpu_ns_ = GetTimeInNsec(); @@ -114,19 +114,20 @@ inline EventList& GetEventList() { return *g_event_list; } -void Mark(const std::string& name, DeviceContext* dev_ctx) { +void Mark(const std::string& name, const DeviceContext* dev_ctx) { GetEventList().Record(EventKind::kMark, name, g_thread_id, dev_ctx); } -void PushEvent(const std::string& name, DeviceContext* dev_ctx) { +void PushEvent(const std::string& name, const DeviceContext* dev_ctx) { GetEventList().Record(EventKind::kPushRange, name, g_thread_id, dev_ctx); } -void PopEvent(const std::string& name, DeviceContext* dev_ctx) { +void PopEvent(const std::string& name, const DeviceContext* dev_ctx) { GetEventList().Record(EventKind::kPopRange, name, g_thread_id, dev_ctx); } -RecordEvent::RecordEvent(const std::string& name, DeviceContext* dev_ctx) { +RecordEvent::RecordEvent(const std::string& name, + const DeviceContext* dev_ctx) { if (g_state == ProfilerState::kDisabled) return; dev_ctx_ = dev_ctx; name_ = name; @@ -155,6 +156,7 @@ void EnableProfiler(ProfilerState state) { DeviceContext* dev_ctx = new CUDADeviceContext(CUDAPlace(d)); Mark("_cuda_startup_", dev_ctx); dev_ctx->Wait(); + delete dev_ctx; }); } } diff --git a/paddle/platform/profiler.h b/paddle/platform/profiler.h index 85823af1d..8de1e6ad2 100644 --- a/paddle/platform/profiler.h +++ b/paddle/platform/profiler.h @@ -29,7 +29,7 @@ class Event { // The DeviceContext is used to get the cuda stream. // If CPU profiling mode, can pass nullptr. Event(EventKind kind, std::string name, uint32_t thread_id, - DeviceContext* dev_ctx); + const DeviceContext* dev_ctx); std::string kind() const; std::string name() const { return name_; } @@ -95,19 +95,19 @@ enum ProfilerState { kCUDA, // GPU profiling state }; -void Mark(const std::string& name, DeviceContext* dev_ctx); +void Mark(const std::string& name, const DeviceContext* dev_ctx); -void PushEvent(const std::string& name, DeviceContext* dev_ctx); +void PushEvent(const std::string& name, const DeviceContext* dev_ctx); -void PopEvent(const std::string& name, DeviceContext* dev_ctx); +void PopEvent(const std::string& name, const DeviceContext* dev_ctx); struct RecordEvent { - explicit RecordEvent(const std::string& name, DeviceContext* dev_ctx); + explicit RecordEvent(const std::string& name, const DeviceContext* dev_ctx); ~RecordEvent(); // The device context is used by Event to get the current cuda stream. - DeviceContext* dev_ctx_; + const DeviceContext* dev_ctx_; // Event name std::string name_; }; diff --git a/python/paddle/v2/fluid/profiler.py b/python/paddle/v2/fluid/profiler.py index a5f0f189a..51c1c8aa7 100644 --- a/python/paddle/v2/fluid/profiler.py +++ b/python/paddle/v2/fluid/profiler.py @@ -81,10 +81,11 @@ def profiler(state, sorted_key=None): to add more records. Args: - state (string) : The profiling state, It should be 'CPU' or 'GPU'. - Although users may define CPUPlace or CUDAPlace when using Fluid, - the profiler doesn't get the state based on this Place. Since the - implementation is an independent part from the Fluid. + state (string) : The profiling state, which should be 'CPU' or 'GPU', + telling the profiler to use CPU timer or GPU timer for profiling. + Although users may have already specified the execution place + (CPUPlace/CUDAPlace) in the begining, for flexibility the profiler + would not inherit this place. sorted_key (string) : If None, the profiling results will be printed in the order of first end time of events. Otherwise, the profiling results will be sorted by the this flag. This flag should be one diff --git a/python/paddle/v2/fluid/tests/test_profiler.py b/python/paddle/v2/fluid/tests/test_profiler.py index dfee4e272..34700df37 100644 --- a/python/paddle/v2/fluid/tests/test_profiler.py +++ b/python/paddle/v2/fluid/tests/test_profiler.py @@ -41,8 +41,8 @@ class TestProfiler(unittest.TestCase): exe.run(fluid.default_main_program(), feed={'data': input}) os.remove(output_file) - def profiler(self, state): - if state == 'GPU' and core.is_compile_gpu(): + def net_profiler(self, state): + if state == 'GPU' and not core.is_compile_gpu(): return startup_program = fluid.Program() main_program = fluid.Program() @@ -79,11 +79,11 @@ class TestProfiler(unittest.TestCase): acc = np.array(outs[1]) pass_acc = accuracy.eval(exe) - def not_test_cpu_profiler(self): - self.profiler('CPU') + def test_cpu_profiler(self): + self.net_profiler('CPU') - def not_test_cuda_profiler(self): - self.profiler('GPU') + def test_cuda_profiler(self): + self.net_profiler('GPU') if __name__ == '__main__': -- GitLab