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denoising-diffusion-pytorch

Use denoising-diffusion-pytorch for PyTorch DDPM/DDIM image diffusion, 1D sequence diffusion, conditioning and guidance, and advanced diffusion variants.

The English summary is being prepared. Showing the original description.

VectorSpaceLab/AREX-Skill

See how to install

Files included (27)

SKILL.md2.9 KB
references/package-overview.md2.4 KB
references/repo-provenance.md1.4 KB
references/repo-routing-metadata.json540 B
references/troubleshooting.md1.8 KB
scripts/check_env.py2.8 KB
sub-skills/advanced-variants/references/api-reference.md3.7 KB
sub-skills/advanced-variants/references/compatibility.md3.5 KB
sub-skills/advanced-variants/references/troubleshooting.md2.9 KB
sub-skills/advanced-variants/references/workflows.md4.9 KB
sub-skills/advanced-variants/scripts/smoke_advanced_variants.py5.0 KB
sub-skills/advanced-variants/SKILL.md2.7 KB
sub-skills/conditioning-guidance/references/api-reference.md4.3 KB
sub-skills/conditioning-guidance/references/troubleshooting.md2.8 KB
sub-skills/conditioning-guidance/references/workflows.md3.1 KB
sub-skills/conditioning-guidance/scripts/smoke_conditioning_guidance.py4.7 KB
sub-skills/conditioning-guidance/SKILL.md2.7 KB
sub-skills/image-diffusion/references/api-reference.md5.0 KB
sub-skills/image-diffusion/references/troubleshooting.md3.0 KB
sub-skills/image-diffusion/references/workflows.md4.5 KB
sub-skills/image-diffusion/scripts/smoke_image_diffusion.py4.1 KB
sub-skills/image-diffusion/SKILL.md2.4 KB
sub-skills/sequence-diffusion/references/api-reference.md3.5 KB
sub-skills/sequence-diffusion/references/troubleshooting.md2.2 KB
sub-skills/sequence-diffusion/references/workflows.md3.5 KB
sub-skills/sequence-diffusion/scripts/smoke_sequence_diffusion.py5.6 KB
sub-skills/sequence-diffusion/SKILL.md2.5 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

denoising-diffusion-pytorch

Use this repo skill when a Researcher needs to operate the public denoising-diffusion-pytorch package (denoising_diffusion_pytorch import) from self-contained guidance. It covers the inspected public API surface at version 2.3.1.

Install and sanity check

python -m pip install denoising-diffusion-pytorch
python - <<'PYCODE'
from denoising_diffusion_pytorch import Unet, GaussianDiffusion, Unet1D, GaussianDiffusion1D
print('denoising_diffusion_pytorch imports ok')
PYCODE

For a no-training environment check, run scripts/check_env.py. It verifies package metadata, public imports, a tiny CPU tensor operation, and optional CUDA visibility.

Route by task

User task	Read
2D image DDPM/DDIM, `Unet`, `GaussianDiffusion`, image folder `Trainer`, FID, RePaint/inpainting, image tensor shape errors	sub-skills/image-diffusion/SKILL.md
1D/time-series/sequence tensors, `Unet1D`, `GaussianDiffusion1D`, `Dataset1D`, `Trainer1D`, channel-first vs channel-last layout	sub-skills/sequence-diffusion/SKILL.md
classifier-free guidance, class labels, `cond_scale`, CFG++, external classifier `cond_fn`, `XMWrapper` multi-candidate loss	sub-skills/conditioning-guidance/SKILL.md
Karras UNets, video-shaped Karras 3D, continuous-time / v-param / EDM / simple diffusion, learned variance, weighted objective, flash/SDPA compatibility	sub-skills/advanced-variants/SKILL.md

Shared references

references/package-overview.md maps public exports, dependencies, and sub-skill ownership.
references/troubleshooting.md covers cross-cutting install/import, PyTorch/CUDA, Accelerate, optional FID, and smoke-test failures.
references/repo-provenance.md records the source snapshot and refresh baseline.

Operating rules

Use the bundled scripts for smoke tests; do not run long training or FID for routine verification.
Keep data tensors normalized to [0, 1] unless auto_normalize=False is explicitly chosen.
CPU is the default verification backend; CUDA, flash attention, FID, and Accelerate multi-GPU are optional accelerators unless a user explicitly asks for them.
The package has no public CLI entry points. Workflows are Python API workflows.
If a task asks to edit this repository rather than use the package, this repo skill can explain APIs, but repository-maintenance policy is outside the selected operating graph.

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Install

Install with a command

npx skills add https://github.com/VectorSpaceLab/AREX-Skill --skill denoising-diffusion-pytorch

Paste it into your terminal and run it (requires Node.js). You can choose which agents to install it for, such as Claude Code or Codex.

Ask your agent

Please install the following Agent Skill.
https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/denoising-diffusion-pytorch

First review SKILL.md and the bundled files and confirm there is nothing suspicious (such as sending data externally or reading credentials). Then place it in ~/.claude/skills/denoising-diffusion-pytorch/ for Claude Code, or ~/.agents/skills/denoising-diffusion-pytorch/ for Codex.

Send this text to Claude Code or Codex as is. It checks the contents before installing.

View source on GitHub

Repository: VectorSpaceLab/AREX-Skill
Stars: 338
Forks: 26
Category: Media
License: Apache-2.0
Original language: English
Last updated: Sep 3, 2026

A skill is a set of instructions and scripts for an agent. cccskills does not guarantee that skills are safe. Review the contents before you install.