+
    &j                     ^    ^ RI t ^RIHtHt . ROt. ROtR tR t] P                  R 4       t	R# )    N)check_errorcudartc                 H    \        \        4       P                  4       4       R# )zxStarts cuda profiler data collection.

.. warning::
    Raises CudaError in case of it is unable to start the profiler.
N)r   r   cudaProfilerStart     k/Users/jameslopez/projects/CWCArchive/cwc-podcast/.venv/lib/python3.14/site-packages/torch/cuda/profiler.pystartr
      s     **,-r   c                 H    \        \        4       P                  4       4       R# )zvStops cuda profiler data collection.

.. warning::
    Raises CudaError in case of it is unable to stop the profiler.
N)r   r   cudaProfilerStopr   r   r	   stopr      s     ))+,r   c               #  ^   "    \        4        Rx  \        4        R#   \        4        i ; i5i)aq  
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)r
   r   r   r   r	   profiler   &   s     s   - -*-)r
   r   r   )gpustarttimestampgpuendtimestamp
gridsize3dthreadblocksizestreamidzenableonstart 0conckerneltrace)

contextlib r   r   __all__DEFAULT_FLAGSr
   r   contextmanagerr   r   r   r	   <module>r      s=     ! '.-  r   