Kohya S. 34e7138b6a Add/modify some implementation for anima (#2261) ...

* fix: update extend-exclude list in _typos.toml to include configs

* fix: exclude anima tests from pytest

* feat: add entry for 'temperal' in extend-words section of _typos.toml for Qwen-Image VAE

* fix: update default value for --discrete_flow_shift in anima training guide

* feat: add Qwen-Image VAE

* feat: simplify encode_tokens

* feat: use unified attention module, add wrapper for state dict compatibility

* feat: loading with dynamic fp8 optimization and LoRA support

* feat: add anima minimal inference script (WIP)

* format: format

* feat: simplify target module selection by regular expression patterns

* feat: kept caption dropout rate in cache and handle in training script

* feat: update train_llm_adapter and verbose default values to string type

* fix: use strategy instead of using tokenizers directly

* feat: add dtype property and all-zero mask handling in cross-attention in LLMAdapterTransformerBlock

* feat: support 5d tensor in get_noisy_model_input_and_timesteps

* feat: update loss calculation to support 5d tensor

* fix: update argument names in anima_train_utils to align with other archtectures

* feat: simplify Anima training script and update empty caption handling

* feat: support LoRA format without `net.` prefix

* fix: update to work fp8_scaled option

* feat: add regex-based learning rates and dimensions handling in create_network

* fix: improve regex matching for module selection and learning rates in LoRANetwork

* fix: update logging message for regex match in LoRANetwork

* fix: keep latents 4D except DiT call

* feat: enhance block swap functionality for inference and training in Anima model

* feat: refactor Anima training script

* feat: optimize VAE processing by adjusting tensor dimensions and data types

* fix: wait all block trasfer before siwtching offloader mode

* feat: update Anima training guide with new argument specifications and regex-based module selection. Thank you Claude!

* feat: support LORA for Qwen3

* feat: update Anima SAI model spec metadata handling

* fix: remove unused code

* feat: split CFG processing in do_sample function to reduce memory usage

* feat: add VAE chunking and caching options to reduce memory usage

* feat: optimize RMSNorm forward method and remove unused torch_attention_op

* Update library/strategy_anima.py

Use torch.all instead of all.

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update library/safetensors_utils.py

Fix duplicated new_key for concat_hook.

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update anima_minimal_inference.py

Remove unused code.

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update anima_train.py

Remove unused import.

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update library/anima_train_utils.py

Remove unused import.

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* fix: review with Copilot

* feat: add script to convert LoRA format to ComfyUI compatible format (WIP, not tested yet)

* feat: add process_escape function to handle escape sequences in prompts

* feat: enhance LoRA weight handling in model loading and add text encoder loading function

* feat: improve ComfyUI conversion script with prefix constants and module name adjustments

* feat: update caption dropout documentation to clarify cache regeneration requirement

* feat: add clarification on learning rate adjustments

* feat: add note on PyTorch version requirement to prevent NaN loss

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Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

2026-02-13 08:15:06 +09:00

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