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name: training-and-configs description: "Configure and launch DALLE2-pytorch decoder and diffusion-prior training with validated JSON configs, bundled launch wrappers, trainer APIs, checkpoint resume, and Accelerate caveats." disable-model-invocation: true metadata: disco-role: operating license: MIT

Training and Configs

Use this sub-skill when a task involves DALLE2-pytorch training setup: TrainDecoderConfig, TrainDiffusionPriorConfig, JSON configs, bundled training launch wrappers, DecoderTrainer, DiffusionPriorTrainer, checkpoint save/load/resume, or Accelerate/DeepSpeed launch decisions.

Route by Need

• For config object structure, required keys, validators, and safe template editing, read Training Configs.
• For direct Python trainer APIs, constructor signatures, optimizer/EMA behavior, save/load, and resume semantics, read Trainer API.
• For command construction, launcher flags, bundled wrappers, and Accelerate examples, read CLI Reference.
• For common failures and fixes, read Troubleshooting.
• To validate a config without starting training, run scripts/inspect_training_config.py with --kind decoder|prior --config PATH.
• To print but not execute a safe training command, run scripts/training_command_builder.py with --kind decoder|prior --config PATH --launcher python|accelerate.
• To launch training from this skill tree, use scripts/run_decoder_training.py or scripts/run_diffusion_prior_training.py. These can run for a long time and may download model or metric weights depending on the config.

Safe Starting Templates

• Decoder CPU structural smoke template: decoder-cpu-smoke.json. It uses placeholders for WebDataset and embedding roots, console logging, local checkpoint saving, CPU device, no source test data dependency, and no torchmetrics image metrics by default.
• Prior minimal template: prior-minimal.json. It uses placeholders for EmbeddingReader image and metadata URLs, console logging, local checkpoint saving, and short diffusion timesteps for config validation.

Always copy a template to a working config path, replace placeholders, then validate it before launching training.

Boundaries

• WebDataset shard keys, sidecar embedding naming, EmbeddingReader folder layout, S3/fsspec setup, tracker credentials, and provider-specific W&B/HuggingFace token handling belong in ../data-and-tracking/.
• Model construction, generation-only APIs, DALLE2, DiffusionPrior, Decoder, CLIP adapters for sampling, dream, VQGAN, and inpainting belong in ../generation-and-api/.