Die Oberfläche ist lokalisiert; Skill-Beschreibungen und -Dokumente werden per KI automatisch in Ihre Sprache übersetzt. Code, Befehle, Pfade und Fachbegriffe bleiben im Original, maßgeblich ist das Dokument des Autors.
Skills entdecken
Produktivität · SKILL.md

core-components

core-components

Reusable Pyramid-Flow model APIs, Causal Video VAE, diffusion schedulers, and distributed helpers.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill-Dokumentation

GitHub

name: core-components description: "Reusable Pyramid-Flow model APIs, Causal Video VAE, diffusion schedulers, and distributed helpers." disable-model-invocation: true metadata: disco-role: operating license: MIT

Pyramid-Flow Core Components

Use this sub-skill when the task is about Pyramid-Flow's reusable runtime building blocks rather than an end-to-end workflow launcher.

Route here for

  • PyramidDiTForVideoGeneration construction, component relationships, text-to-video/image-to-video method signatures, latent decoding, VAE tiling, and CPU offload API semantics.
  • CausalVideoVAE and CausalVideoVAELossWrapper encode/decode/reconstruct APIs, latent shapes, and safe tiny round-trip checks.
  • PyramidFlowMatchEulerDiscreteScheduler and DDPMCosineScheduler initialization, timestep setup, and step() semantics.
  • trainer_misc distributed helpers shared by inference and training: rank/world-size helpers, DDP initialization, sequence-parallel groups, sync-input groups, and FSDP epoch helper entry points.

Route elsewhere

  • Generation demo launchers, Gradio apps, prompt/image recipes, checkpoint download commands, and multi-GPU generation wrappers -> generation-inference.
  • JSONL annotations, dataset fixtures, text-feature extraction, and VAE-latent precompute flows -> data-preparation.
  • Training shell launchers, CLI flag catalogs, AR/non-AR DiT fine-tuning recipes, and VAE training recipes -> training-workflows.

Bundled references

  • API reference has verified signatures, imports, scheduler/VAE smoke facts, dependency versions, and shape contracts.
  • Model overview explains how DiT, text encoders, VAE, schedulers, and distributed helpers fit together.
  • Troubleshooting covers dependency drift, CUDA visibility, scheduler stage errors, VAE shape/device misuse, and invalid model paths or variants.

Bundled script

Run the safe component smoke from any working directory once Pyramid-Flow's import roots are importable in the active Python environment:

python PATH_TO_SKILL_TREE/sub-skills/core-components/scripts/smoke_core_components.py --help
python PATH_TO_SKILL_TREE/sub-skills/core-components/scripts/smoke_core_components.py --package-root PATH_TO_PYRAMID_FLOW

The smoke checks imports, package versions, scheduler CPU math, a tiny CPU Causal Video VAE encode/decode round-trip, and optional negative cases without downloading checkpoints or launching generation/training.

Gespeicherte Skills