Python module

registry

Model registry, for tracking various model variants.

`PipelineRegistry`

class max.pipelines.lib.registry.PipelineRegistry(architectures)

Parameters:: architectures (list [ SupportedArchitecture ] )

`get_active_huggingface_config()`

get_active_huggingface_config(huggingface_repo)

Retrieves or creates a cached HuggingFace AutoConfig for the given model configuration.

This method maintains a cache of HuggingFace configurations to avoid reloading them unnecessarily which incurs a huggingface hub API call. If a config for the given model hasn’t been loaded before, it will create a new one using AutoConfig.from_pretrained() with the model’s settings.

Parameters:: huggingface_repo (HuggingFaceRepo ) – The HuggingFaceRepo containing the model.
Returns:: The HuggingFace configuration object for the model.
Return type:: AutoConfig

`get_active_tokenizer()`

get_active_tokenizer(huggingface_repo)

Retrieves or creates a cached HuggingFace AutoTokenizer for the given model configuration.

This method maintains a cache of HuggingFace tokenizers to avoid reloading them unnecessarily which incurs a huggingface hub API call. If a tokenizer for the given model hasn’t been loaded before, it will create a new one using AutoTokenizer.from_pretrained() with the model’s settings.

Parameters:: huggingface_repo (HuggingFaceRepo ) – The HuggingFaceRepo containing the model.
Returns:: The HuggingFace tokenizer for the model.
Return type:: PreTrainedTokenizer | PreTrainedTokenizerFast

`register()`

register(architecture, *, allow_override=False)

Add new architecture to registry.

Parameters:

architecture (SupportedArchitecture )
allow_override (bool )

Return type:

None

`reset()`

reset()

Return type:: None

`retrieve()`

retrieve(pipeline_config, task=PipelineTask.TEXT_GENERATION, override_architecture=None)

Parameters:

pipeline_config (PipelineConfig )
task (PipelineTask )
override_architecture (str | None )

Return type:

tuple[PipelineTokenizer, PipelineTypes]

`retrieve_architecture()`

retrieve_architecture(huggingface_repo)

Parameters:: huggingface_repo (HuggingFaceRepo )
Return type:: SupportedArchitecture | None

`retrieve_factory()`

retrieve_factory(pipeline_config, task=PipelineTask.TEXT_GENERATION, override_architecture=None)

Parameters:

pipeline_config (PipelineConfig )
task (PipelineTask )
override_architecture (str | None )

Return type:

tuple[PipelineTokenizer, Callable[[], PipelineTypes]]

`SupportedArchitecture`

class max.pipelines.lib.registry.SupportedArchitecture(name, example_repo_ids, default_encoding, supported_encodings, pipeline_model, task, tokenizer, default_weights_format, multi_gpu_supported=False, rope_type=RopeType.none, weight_adapters=None)

Initializes a model architecture supported by MAX pipelines.

New architectures should be registered into the PipelineRegistry.

Parameters:

name (str ) – Architecture name.
example_repo_ids (list [ str ] ) – Hugging Face repo_id which runs this architecture.
default_encoding (SupportedEncoding ) – Default encoding for the model.
supported_encodings (dict [ SupportedEncoding , list [ KVCacheStrategy ] ] ) – Alternate encodings supported.
pipeline_model (type [ PipelineModel ] ) – PipelineModel class that defines the model graph and execution.
task (PipelineTask ) – Which pipeline task should the model run with.
tokenizer (Callable [ ... , PipelineTokenizer ] ) – Tokenizer used to preprocess model inputs.
default_weights_format (WeightsFormat ) – The weights format used in pipeline_model.
weight_converters – A dictionary of weight loaders to use if the input checkpoint has a different format than the default.
multi_gpu_supported (bool )
rope_type (RopeType )
weight_adapters (dict [ WeightsFormat , WeightsAdapter ] | None )

`tokenizer_cls`

property tokenizer_cls*: type[PipelineTokenizer]*

`get_pipeline_for_task()`

max.pipelines.lib.registry.get_pipeline_for_task(task, pipeline_config)

Parameters:

task (PipelineTask )
pipeline_config (PipelineConfig )

Return type:

type[TextGenerationPipeline] | type[EmbeddingsPipeline] | type[SpeculativeDecodingTextGenerationPipeline] | type[AudioGeneratorPipeline] | type[SpeechTokenGenerationPipeline]

PipelineRegistry​

get_active_huggingface_config()​

get_active_tokenizer()​

register()​

reset()​

retrieve()​

retrieve_architecture()​

retrieve_factory()​

SupportedArchitecture​

tokenizer_cls​

get_pipeline_for_task()​

`PipelineRegistry`

`get_active_huggingface_config()`

`get_active_tokenizer()`

`register()`

`reset()`

`retrieve()`

`retrieve_architecture()`

`retrieve_factory()`

`SupportedArchitecture`

`tokenizer_cls`

`get_pipeline_for_task()`