mindformers.core.ProfileMonitor

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class mindformers.core.ProfileMonitor(start_step=1, stop_step=10, output_path=None, start_profile=True, profile_rank_ids=None, profile_pipeline=False, profile_communication=False, profile_memory=False, config=None, profiler_level=0, with_stack=False, data_simplification=True, **kwargs)[source]

Profile analysis in training.

Parameters

  • start_step (int) – The step to start profiling. Default: 1.

  • stop_step (int) – The step to stop profiling. Default: 10.

  • output_path (str) – The result of profiling will be saved in this path. Default: None.

  • start_profile (str) – Whether to enable profiling. Default: True.

  • profile_rank_ids (list) – Specify rank ids to enable profiling. Default: None(All rank ids are enabled).

  • profile_pipeline (str) – Whether to enable profiling on one card of each parallel stage. Default: False.

  • profile_communication (str) – Whether to collect communication performance data during multi-device training. Default: False.

  • profile_memory (str) – Whether to collect Tensor memory data. Default: False.

  • config (dict) – Configuration items, used to profile relevant configuration information, such as parallel configuration. Default: None.

  • profiler_level (int) –

    Collection level of profiling data(0, 1, 2). Default: 0.

    • 0: The most streamlined level of performance data collection, only collecting execution time data for computational operators and basic data for large communication operators.

    • 1: In addition to level 0, extra data is collected for CANN layer AscendCL, AICORE performance data, and small communication operators.

    • 2: In addition to level 1, extra data is collected for graph compile level O2 and Runtime in the CANN layer.

  • with_stack (str) – Whether to collect Python-side stack trace data. Default: False.

  • data_simplification (str) – Whether to enable data simplification, which will delete the FRAMEWORK directory and other extraneous data after exporting profiling data. Default: True.

Examples

>>> from mindformers.core import ProfileMonitor
>>> monitor = ProfileMonitor(output_path='./profile_dir')