---

name: modular-pipelines description: "Create, customize, debug, and test Diffusers Modular Pipeline blocks, states, component managers, sequential/loop blocks, and custom-block CLI packaging." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Modular Pipelines

Use this sub-skill for Diffusers Modular Pipeline work: ModularPipeline, ModularPipelineBlocks, SequentialPipelineBlocks, LoopSequentialPipelineBlocks, AutoPipelineBlocks, ConditionalPipelineBlocks, PipelineState, BlockState, ComponentsManager, custom block packaging, and modular pipeline tests.

Route by task

• Design or edit blocks, state keys, component specs, and workflow maps: read references/block-workflows.md.
• Build, package, load, or insert custom blocks: read references/custom-blocks.md and use scripts/modular_block_skeleton.py.
• Diagnose missing components, state mismatches, optional dependency failures, local/offline loading, dtype/device issues, and workflow selection bugs: read references/troubleshooting.md.
• Add or adapt tests for modular families: read references/testing.md.
• Check installed modular imports or diffusers-cli custom_blocks parser shape: run python sub-skills/modular-pipelines/scripts/modular_import_check.py.

Boundaries

• Stay here for modular definitions, block composition, custom blocks, component sharing/offload, and modular test patterns.
• Route classic DiffusionPipeline inference, non-modular pipeline call behavior, and end-user generation examples to pipelines-and-inference.
• Route scheduler choice, scheduler configs, and sampling algorithm comparison to schedulers unless the scheduler is only being wired as a modular component.

Quick checklist

• Every block declares all read values as InputParam and all written values as OutputParam in intermediate_outputs or final outputs.
• Leaf blocks use block_state = self.get_block_state(state), write declared fields, call self.set_block_state(state, block_state), and return (components, state).
• Loop sub-blocks receive a shared BlockState, not a PipelineState, and return (components, block_state) from each loop iteration.
• Sequential and auto blocks have clear description text, ordered block_classes/block_names, and _workflow_map entries for supported public workflows.
• Component work uses ComponentSpec, ConfigSpec, load_components, update_components, get_component_spec, and ComponentsManager rather than ad hoc attributes.
• Custom blocks ship their Python module plus modular_config.json; remote custom code loads only with explicit trust_remote_code=True.

Useful scripts

• scripts/modular_block_skeleton.py prints or writes a minimal custom block module with valid naming and state-update structure.
• scripts/modular_import_check.py verifies core modular imports and confirms custom_blocks CLI arguments are registered.