old_contents: import paddle.v2.fluid.core as core
  from contextlib import contextmanager
  import os
  
  __all__ = ['CudaProfiler']
  
  NVPROF_CONFIG = [
      "gpustarttimestamp",
      "gpuendtimestamp",
      "gridsize3d",
      "threadblocksize",
      "dynsmemperblock",
      "stasmemperblock",
      "regperthread",
      "memtransfersize",
      "memtransferdir",
      "memtransferhostmemtype",
      "streamid",
      "cacheconfigrequested",
      "cacheconfigrequested",
      "cacheconfigrequested",
      "enableonstart 0",
      "conckerneltrace",
      "active_warps",
      "active_warps",
  ]
  
  
  @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 (list of 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 ['kvp', 'csv']:
          raise ValueError("The output mode must be 'kvp' or 'csv'.")
      config = NVPROF_CONFIG if config is None else config
      config_file = 'nvprof_config_file'
      with open(config_file, 'wb') as fp:
          fp.writelines(["%s\n" % item for item in config])
      core.nvprof_init(output_file, output_mode, config_file)
      # Enables profiler collection by the active CUDA profiling tool.
      core.nvprof_start()
      yield
      # Disables profiler collection.
      core.nvprof_stop()
      os.remove(config_file)
  
new_contents: import paddle.v2.fluid.core as core
  from contextlib import contextmanager
  import os
  
  __all__ = ['CudaProfiler']
  
  NVPROF_CONFIG = [
      "gpustarttimestamp",
      "gpuendtimestamp",
      "gridsize3d",
      "threadblocksize",
      "dynsmemperblock",
      "stasmemperblock",
      "regperthread",
      "memtransfersize",
      "memtransferdir",
      "memtransferhostmemtype",
      "streamid",
      "cacheconfigrequested",
      "cacheconfigexecuted",
      "countermodeaggregate",
      "enableonstart 0",
      "active_warps",
      "active_cycles",
  ]
  
  
  @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 (list of 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 ['kvp', 'csv']:
          raise ValueError("The output mode must be 'kvp' or 'csv'.")
      config = NVPROF_CONFIG if config is None else config
      config_file = 'nvprof_config_file'
      with open(config_file, 'wb') as fp:
          fp.writelines(["%s\n" % item for item in config])
      core.nvprof_init(output_file, output_mode, config_file)
      # Enables profiler collection by the active CUDA profiling tool.
      core.nvprof_start()
      yield
      # Disables profiler collection.
      core.nvprof_stop()
      os.remove(config_file)
  
subject: Fix the config arguments.