diffusion_train_extras hosts the opt-in training extras: LoRAEMA shadows only the trainable adapter params (warmup-ramped decay, default 0.99, exported as a second adapter under output_dir/ema), PersistentConditioningCache stores latent posterior stats and caption embeddings as safetensors keyed by content hash + family + resolution, and the aspect-ratio bucketing helpers group mixed-aspect datasets into same-area divisor-snapped shapes. The DiT trainer wires the first two behind config flags that default to the current behavior: ema_decay (0 disables) and cond_cache_dir (None disables). A fully warm cache skips loading the VAE and text encoders entirely; a cache hit is bit-identical to a fresh encode, including the per-channel qwen latent normalization. Also fixes the stale _gather_sigmas call in the perf test that still passed the scheduler instead of the sigma table. |
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| .. | ||
| backend | ||
| frontend | ||
| src-tauri | ||
| __init__.py | ||
| install_llama_prebuilt.py | ||
| install_node_prebuilt.py | ||
| install_python_stack.py | ||
| install_sd_cpp_prebuilt.py | ||
| LICENSE.AGPL-3.0 | ||
| node_prebuilt_pins.json | ||
| package-lock.json | ||
| package.json | ||
| setup.bat | ||
| setup.ps1 | ||
| setup.sh | ||
| Unsloth_Studio_Colab.ipynb | ||