From 5e7e90ce8f09d1a970fb131f01c42b1882a1c06b Mon Sep 17 00:00:00 2001 From: dangqingqing Date: Tue, 28 Nov 2017 18:28:35 +0800 Subject: [PATCH] Refine paddle/v2/fluid/profiler.py. --- paddle/platform/cuda_profiler.h | 8 +- python/paddle/v2/fluid/profiler.py | 82 ++++++------------- python/paddle/v2/fluid/tests/test_profiler.py | 4 +- 3 files changed, 33 insertions(+), 61 deletions(-) diff --git a/paddle/platform/cuda_profiler.h b/paddle/platform/cuda_profiler.h index c096ce37c5..b6311cb23d 100644 --- a/paddle/platform/cuda_profiler.h +++ b/paddle/platform/cuda_profiler.h @@ -29,10 +29,10 @@ void CudaProfilerInit(std::string output_file, std::string output_mode, memcpy(buf.data(), tmpl.data(), tmpl.size()); auto result = mktemp(buf.data()); PADDLE_ENFORCE(strlen(result) != 0); - std::string config = result; + std::string config_file = result; { - std::ofstream ofs(config, std::ios::out | std::ios::trunc); + std::ofstream ofs(config_file, std::ios::out | std::ios::trunc); PADDLE_ENFORCE(ofs.is_open(), "ofstream: ", ofs.rdstate()); for (const auto& line : config_flags) { ofs << line << std::endl; @@ -42,12 +42,12 @@ void CudaProfilerInit(std::string output_file, std::string output_mode, PADDLE_ENFORCE(output_mode == "kvp" || output_mode == "csv"); cudaOutputMode_t mode = output_mode == "csv" ? cudaCSV : cudaKeyValuePair; PADDLE_ENFORCE( - cudaProfilerInitialize(config.c_str(), output_file.c_str(), mode)); + cudaProfilerInitialize(config_file.c_str(), output_file.c_str(), mode)); } void CudaProfilerStart() { PADDLE_ENFORCE(cudaProfilerStart()); } -void CudaProfilerStop() { PADDLE_ENFORCE((cudaProfilerStop())); } +void CudaProfilerStop() { PADDLE_ENFORCE(cudaProfilerStop()); } } // namespace platform } // namespace paddle diff --git a/python/paddle/v2/fluid/profiler.py b/python/paddle/v2/fluid/profiler.py index f31d6f0a61..2069b713fa 100644 --- a/python/paddle/v2/fluid/profiler.py +++ b/python/paddle/v2/fluid/profiler.py @@ -1,9 +1,9 @@ import paddle.v2.fluid.core as core -import subprocess +from contextlib import contextmanager __all__ = ['CudaProfiler'] -NV_FLAGS = [ +NVPROF_CONFIG = [ "gpustarttimestamp", "gpuendtimestamp", "gridsize3d", @@ -14,61 +14,33 @@ NV_FLAGS = [ ] -def nvporf_init(output_file, output_mode=None, flags=None): - """ - Initialize the CUDA profiler. - This methods must be called before nvprof_start. - - :param output_file: The output file name. - :type output_file: string - :param output_mode: The output mode has Key-Value pair format and - Comma separated values format. - It should be 'kv' or 'csv'. - :type output_mode: string +@contextmanager +def cuda_profiler(output_file, output_mode=None, config=None): + """The CUDA profiler. + This fuctions is used to profile CUDA program by CUDA runtime application + programming interface. The profiling result will be written into + `output_file` with Key-Value pair format or Comma separated values format. + The user can set the output mode by `output_mode` argument and set the + counters/options for profiling by `config` argument. The default config + is ['gpustarttimestamp', 'gpustarttimestamp', 'gridsize3d', + 'threadblocksize', 'streamid', 'enableonstart 0', 'conckerneltrace']. + + Args: + output_file (string) : The output file name, the result will be + written into this file. + output_mode (string) : The output mode has Key-Value pair format and + Comma separated values format. It should be 'kvp' or 'csv'. + config (string) : The profiler options and counters can refer to + "Compute Command Line Profiler User Guide". """ if output_mode is None: output_mode = 'csv' - if output_mode not in ['kv', 'csv']: - raise ValueError("The output mode must be 'key-value' or 'csv'.") - flags = NV_FLAGS if flags is None else flags - core.nvprof_init(output_file, output_mode, flags) - - -def nvporf_start(): - """ - Enables profiler collection by the active CUDA profiling tool. - """ + if output_mode not in ['kvp', 'csv']: + raise ValueError("The output mode must be 'kvp' or 'csv'.") + config = NVPROF_CONFIG if config is None else config + core.nvprof_init(output_file, output_mode, config) + # Enables profiler collection by the active CUDA profiling tool. core.nvprof_start() - - -def nvporf_stop(): - """ - Disables profiler collection. - """ + yield + # Disables profiler collection. core.nvprof_stop() - - -class CudaProfiler(object): - def __init__(self, output_file, output_mode=None, flags=None, enabled=True): - self.enabled = enabled - if not self.enabled: - return - self.entered = False - self.out_file = output_file - nvporf_init(output_file, output_mode, flags) - - def __enter__(self): - if not self.enabled: - return - if self.entered: - raise RuntimeError("The profiler traces are not reentrant") - self.entered = True - nvporf_start() - return self - - def __exit__(self, exc_type, exc_value, tb): - if exc_value is not None: - raise exc_value - if not self.enabled: - return - nvporf_stop() diff --git a/python/paddle/v2/fluid/tests/test_profiler.py b/python/paddle/v2/fluid/tests/test_profiler.py index 1fec5c99bf..973e94b976 100644 --- a/python/paddle/v2/fluid/tests/test_profiler.py +++ b/python/paddle/v2/fluid/tests/test_profiler.py @@ -18,9 +18,9 @@ class TestProfiler(unittest.TestCase): exe = fluid.Executor(place) exe.run(fluid.default_startup_program()) - with profiler.CudaProfiler("cuda_profiler.txt", 'csv') as nvprof: + with profiler.cuda_profiler('cuda_profiler.txt', 'kvp') as nvprof: for i in range(epoc): - input = np.random.random(dshape).astype("float32") + input = np.random.random(dshape).astype('float32') exe.run(fluid.default_main_program(), feed={'data': input}) -- GitLab