o ha @sdddlZddlZddlZddlmZmZgdZgdZdddZd d Z d d Z ej d dZ dS)N) check_errorcudart)initstartstopprofile)gpustarttimestampgpuendtimestamp gridsize3dthreadblocksizestreamidzenableonstart 0conckerneltrace key_valuecCst}t|ds tdttjdr)tjjdur)ttjjdddkr)td|dur/tn|}|dkr:|j j }n |d krC|j j }nt d t jd d $}|d dd|D|t||j||WddS1stwYdS)NcudaOutputModez-HIP does not support profiler initialization!cuda.r z.CUDA12+ does not need profiler initialization!rcsvz;supported CUDA profiler output modes are: key_value and csvT)delete css|]}|dVqdS)asciiN)encode).0frg/var/www/html/construction_image-detection-poc/venv/lib/python3.10/site-packages/torch/cuda/profiler.py -szinit..)rhasattrAssertionErrortorchversionrintsplit DEFAULT_FLAGSr KeyValuePairCSV RuntimeErrortempfileNamedTemporaryFilewritejoinflushrcudaProfilerInitializename) output_fileflags output_modertoutput_mode_enumrrrrrs*     "rcCttdS)zStarts cuda profiler data collection. .. warning:: Raises CudaError in case of it is unable to start the profiler. N)rrcudaProfilerStartrrrrr2rcCr4)zStops cuda profiler data collection. .. warning:: Raises CudaError in case of it is unable to stop the profiler. N)rrcudaProfilerStoprrrrr;r6rccs$z tdVWtdStw)a Enable profiling. Context Manager to enabling profile collection by the active profiling tool from CUDA backend. Example: >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) >>> import torch >>> model = torch.nn.Linear(20, 30).cuda() >>> inputs = torch.randn(128, 20).cuda() >>> with torch.cuda.profiler.profile() as prof: ... model(inputs) N)rrrrrrrDs r)Nr) contextlibr(r rr__all__r$rrrcontextmanagerrrrrrs