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dqm_ml_core.models.config

Root job configuration model for DQM-ML pipelines.

Defines the top-level JobConfig that composes all pipeline stage configurations including storage, compute, error handling, data loading, and processor interfaces.

JobConfig

Bases: BaseModel

Root configuration for a dqm-ml job. Each field maps to a pipeline stage.

Source code in packages/dqm-ml-core/src/dqm_ml_core/models/config.py 
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class JobConfig(BaseModel):
    """Root configuration for a dqm-ml job. Each field maps to a pipeline stage."""

    model_config = ConfigDict(extra="forbid")

    storage: StorageConfig | None = None
    compute: ComputeConfig | None = None
    errors: ErrorsConfig | None = None
    dataloaders: DataLoadersConfig
    features: FeaturesInterfaceConfig | None = None
    metrics: MetricsInterfaceConfig | None = None
    gap: GapInterfaceConfig | None = None

compute: ComputeConfig | None = None class-attribute instance-attribute

dataloaders: DataLoadersConfig instance-attribute

errors: ErrorsConfig | None = None class-attribute instance-attribute

features: FeaturesInterfaceConfig | None = None class-attribute instance-attribute

gap: GapInterfaceConfig | None = None class-attribute instance-attribute

metrics: MetricsInterfaceConfig | None = None class-attribute instance-attribute

model_config = ConfigDict(extra='forbid') class-attribute instance-attribute

storage: StorageConfig | None = None class-attribute instance-attribute