fastvideo.pipelines.pipeline_registry
#
Module Contents#
Classes#
Enumeration for different pipeline types. |
Functions#
Get a pipeline registry for the specified mode, pipeline type, and workload type. |
|
Import pipeline classes based on the pipeline type and workload type. |
Data#
API#
- class fastvideo.pipelines.pipeline_registry.PipelineType[source]#
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Enumeration for different pipeline types.
Inherits from str to allow string comparison for backward compatibility.
Initialization
Initialize self. See help(type(self)) for accurate signature.
- classmethod from_string(value: str) fastvideo.pipelines.pipeline_registry.PipelineType [source]#
Convert string to PipelineType enum.
- fastvideo.pipelines.pipeline_registry.get_pipeline_registry(pipeline_type: fastvideo.pipelines.pipeline_registry.PipelineType | str | None = None) fastvideo.pipelines.pipeline_registry._PipelineRegistry [source]#
Get a pipeline registry for the specified mode, pipeline type, and workload type.
- Parameters:
pipeline_type – Pipeline type to load. If None and mode is provided, will be derived from mode.
- Returns:
A pipeline registry instance.
- fastvideo.pipelines.pipeline_registry.import_pipeline_classes(pipeline_types: list[fastvideo.pipelines.pipeline_registry.PipelineType] | fastvideo.pipelines.pipeline_registry.PipelineType | None = None) dict[str, dict[str, dict[str, type[fastvideo.pipelines.composed_pipeline_base.ComposedPipelineBase] | None]]] [source]#
Import pipeline classes based on the pipeline type and workload type.
- Parameters:
pipeline_types – The pipeline types to load (basic, preprocessing, training). If None, loads all types.
- Returns:
{pipeline_type: {architecture_name: {pipeline_name: pipeline_cls}}} e.g., {“basic”: {“wan”: {“WanPipeline”: WanPipeline}}}
- Return type:
A three-level nested dictionary