Python module
registry
Model registry, for tracking various model variants.
PipelineRegistry
class max.pipelines.registry.PipelineRegistry(architectures: list[max.pipelines.registry.SupportedArchitecture])
architecture_details()
architecture_details(pipeline_config: PipelineConfig) → SupportedArchitecture | None
Return architecture details for pipeline_config if available, None if not found.
register()
register(architecture: SupportedArchitecture)
Add new architecture to registry.
reset()
reset() → None
retrieve()
retrieve(pipeline_config: PipelineConfig) → tuple[max.pipelines.interfaces.PipelineTokenizer, max.pipelines.interfaces.TokenGenerator]
retrieve_factory()
retrieve_factory(pipeline_config: PipelineConfig) → tuple[max.pipelines.interfaces.PipelineTokenizer, Callable[[], max.pipelines.interfaces.TokenGenerator]]
validate_pipeline_config()
validate_pipeline_config(pipeline_config: PipelineConfig) → PipelineConfig
Update pipeline config with appropriate values if not provided. If invalid config is provided, error out with detailed reason.
SupportedArchitecture
class max.pipelines.registry.SupportedArchitecture(name: str, example_repo_ids: list[str], default_encoding: SupportedEncoding, supported_encodings: dict[max.pipelines.config.SupportedEncoding, list[max.pipelines.kv_cache.cache_params.KVCacheStrategy]], pipeline_model: Type[PipelineModel], tokenizer: Type[TextTokenizer | TextAndVisionTokenizer], default_weights_format: WeightsFormat, weight_converters: dict[max.pipelines.config.WeightsFormat, Type[max.graph.weights.weights.WeightsConverter]] | None = None)
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