For the complete documentation index, see llms.txt. Markdown versions of all pages are available by appending .md to any URL (e.g. /max/get-started.md).
Python class
ProfilingConfig
ProfilingConfig
class max.pipelines.ProfilingConfig(*, config_file=None, section_name=None, gpu_profiling='off', profiling_enabled=False, profiling_output_path=None, profiling_dynolog_enabled=True, profiling_warmup_steps=0, profiling_active_steps=10, profiling_periodic_flush_seconds=60)
Bases: ConfigFileModel
Configuration for the GPU (NVTX/Nsight) and libkineto/HTA profilers.
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Parameters:
gpu_profiling
gpu_profiling: GPUProfilingMode
Whether to enable GPU profiling of the model.
model_config
model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'strict': False}
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_post_init()
model_post_init(context, /)
This function is meant to behave like a BaseModel method to initialise private attributes.
It takes context as an argument since that’s what pydantic-core passes when calling it.
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Parameters:
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- self (BaseModel) – The BaseModel instance.
- context (Any) – The context.
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Return type:
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None
profiling_active_steps
profiling_active_steps: int
Reserved; step-windowed capture is not yet implemented.
profiling_dynolog_enabled
profiling_dynolog_enabled: bool
Whether the Dynolog IPC listener is active. On by default.
profiling_enabled
profiling_enabled: bool
Master switch for the libkineto-backed profiler.
profiling_output_path
Trace output path; file or directory.
profiling_periodic_flush_seconds
profiling_periodic_flush_seconds: int
Crash-safe flush cadence.
profiling_warmup_steps
profiling_warmup_steps: int
Reserved; step-windowed capture is not yet implemented.
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