Merge pull request #3586 from vladmandic/dev

Release refresh

CHANGELOG.md

@@ -1,5 +1,22 @@
 # Change Log for SD.Next
 
+## Update for 2024-11-22
+
+- Model loader improvements:  
+  - detect model components on model load fail  
+  - Flux, SD35: force unload model  
+  - Flux: apply `bnb` quant when loading *unet/transformer*  
+  - Flux: all-in-one safetensors  
+    example: <https://civitai.com/models/646328?modelVersionId=1040235>  
+  - Flux: do not recast quants  
+- Sampler improvements  
+  - update DPM FlowMatch samplers  
+- Fixes:  
+  - update `diffusers`  
+  - fix README links  
+  - fix sdxl controlnet single-file loader  
+  - relax settings validator  
+
 ## Update for 2024-11-21
 
 ### Highlights for 2024-11-21

README.md

@@ -56,7 +56,7 @@ For screenshots and informations on other available themes, see [Themes Wiki](ht
 ## Model support
 
 Additional models will be added as they become available and there is public interest in them  
-See [models overview](wiki/Models) for details on each model, including their architecture, complexity and other info  
+See [models overview](https://github.com/vladmandic/automatic/wiki/Models) for details on each model, including their architecture, complexity and other info  
 
 - [RunwayML Stable Diffusion](https://github.com/Stability-AI/stablediffusion/) 1.x and 2.x *(all variants)*
 - [StabilityAI Stable Diffusion XL](https://github.com/Stability-AI/generative-models), [StabilityAI Stable Diffusion 3.0](https://stability.ai/news/stable-diffusion-3-medium) Medium, [StabilityAI Stable Diffusion 3.5](https://huggingface.co/stabilityai/stable-diffusion-3.5-large) Medium, Large, Large Turbo
@@ -101,17 +101,17 @@ See [models overview](wiki/Models) for details on each model, including their ar
 
 ## Getting started
 
-- Get started with **SD.Next** by following the [installation instructions](wiki/Installation)  
-- For more details, check out [advanced installation](wiki/Advanced-Install) guide  
-- List and explanation of [command line arguments](wiki/CLI-Arguments)
+- Get started with **SD.Next** by following the [installation instructions](https://github.com/vladmandic/automatic/wiki/Installation)  
+- For more details, check out [advanced installation](https://github.com/vladmandic/automatic/wiki/Advanced-Install) guide  
+- List and explanation of [command line arguments](https://github.com/vladmandic/automatic/wiki/CLI-Arguments)
 - Install walkthrough [video](https://www.youtube.com/watch?v=nWTnTyFTuAs)
 
 > [!TIP]
 > And for platform specific information, check out  
-> [WSL](wiki/WSL) | [Intel Arc](wiki/Intel-ARC) | [DirectML](wiki/DirectML) | [OpenVINO](wiki/OpenVINO) | [ONNX & Olive](wiki/ONNX-Runtime) | [ZLUDA](wiki/ZLUDA) | [AMD ROCm](wiki/AMD-ROCm) | [MacOS](wiki/MacOS-Python.md) | [nVidia](wiki/nVidia)
+> [WSL](https://github.com/vladmandic/automatic/wiki/WSL) | [Intel Arc](https://github.com/vladmandic/automatic/wiki/Intel-ARC) | [DirectML](https://github.com/vladmandic/automatic/wiki/DirectML) | [OpenVINO](https://github.com/vladmandic/automatic/wiki/OpenVINO) | [ONNX & Olive](https://github.com/vladmandic/automatic/wiki/ONNX-Runtime) | [ZLUDA](https://github.com/vladmandic/automatic/wiki/ZLUDA) | [AMD ROCm](https://github.com/vladmandic/automatic/wiki/AMD-ROCm) | [MacOS](https://github.com/vladmandic/automatic/wiki/MacOS-Python.md) | [nVidia](https://github.com/vladmandic/automatic/wiki/nVidia)
 
 > [!WARNING]
-> If you run into issues, check out [troubleshooting](wiki/Troubleshooting) and [debugging](wiki/Debug) guides  
+> If you run into issues, check out [troubleshooting](https://github.com/vladmandic/automatic/wiki/Troubleshooting) and [debugging](https://github.com/vladmandic/automatic/wiki/Debug) guides  
 
 > [!TIP]
 > All command line options can also be set via env variable

TODO.md

@@ -8,6 +8,7 @@ Main ToDo list can be found at [GitHub projects](https://github.com/users/vladma
 - SD35 LoRA: <https://github.com/huggingface/diffusers/issues/9950>
 - Flux IPAdapter: <https://github.com/huggingface/diffusers/issues/9825>
 - Flux Fill/ControlNet/Redux: <https://github.com/huggingface/diffusers/pull/9985>
+- Flux NF4: <https://github.com/huggingface/diffusers/issues/9996>
 - SANA: <https://github.com/huggingface/diffusers/pull/9982>
 
 ## Other

cli/model-keys.py

@@ -38,6 +38,16 @@ def list_to_dict(flat_list):
     return result_dict
 
 
+def list_compact(flat_list):
+    result_list = []
+    for item in flat_list:
+        keys = item.split('.')
+        keys = '.'.join(keys[:2])
+        if keys not in result_list:
+            result_list.append(keys)
+    return result_list
+
+
 def guess_dct(dct: dict):
     # if has(dct, 'model.diffusion_model.input_blocks') and has(dct, 'model.diffusion_model.label_emb'):
     #    return 'sdxl'
@@ -65,7 +75,9 @@ def read_keys(fn):
     except Exception as e:
         pprint(e)
     dct = list_to_dict(keys)
+    lst = list_compact(keys)
     pprint(f'file: {fn}')
+    pprint(lst)
     pprint(remove_entries_after_depth(dct, 3))
     pprint(remove_entries_after_depth(dct, 6))
     guess = guess_dct(dct)

installer.py

@@ -459,7 +459,7 @@ def check_python(supported_minors=[9, 10, 11, 12], reason=None):
 def check_diffusers():
     if args.skip_all or args.skip_requirements:
         return
-    sha = 'cd6ca9df2987c000b28e13b19bd4eec3ef3c914b'
+    sha = 'b5fd6f13f5434d69d919cc8cedf0b11db664cf06'
     pkg = pkg_resources.working_set.by_key.get('diffusers', None)
     minor = int(pkg.version.split('.')[1] if pkg is not None else 0)
     cur = opts.get('diffusers_version', '') if minor > 0 else ''

modules/model_flux.py

@@ -194,6 +194,7 @@ def load_transformer(file_path): # triggered by opts.sd_unet change
         if _transformer is not None:
             transformer = _transformer
     else:
+        diffusers_load_config = model_quant.create_bnb_config(diffusers_load_config)
         transformer = diffusers.FluxTransformer2DModel.from_single_file(file_path, **diffusers_load_config)
     if transformer is None:
         shared.log.error('Failed to load UNet model')
@@ -213,6 +214,11 @@ def load_flux(checkpoint_info, diffusers_load_config): # triggered by opts.sd_ch
     text_encoder_2 = None
     vae = None
 
+    # unload current model
+    sd_models.unload_model_weights()
+    shared.sd_model = None
+    devices.torch_gc(force=True)
+
     # load overrides if any
     if shared.opts.sd_unet != 'None':
         try:
@@ -305,8 +311,21 @@ def load_flux(checkpoint_info, diffusers_load_config): # triggered by opts.sd_ch
         repo_id = 'black-forest-labs/FLUX.1-dev' # workaround since sayakpaul model is missing model_index.json
     for c in kwargs:
         if kwargs[c].dtype == torch.float32 and devices.dtype != torch.float32:
-            shared.log.warning(f'Load model: type=FLUX component={c} dtype={kwargs[c].dtype} cast dtype={devices.dtype}')
+            shared.log.warning(f'Load model: type=FLUX component={c} dtype={kwargs[c].dtype} cast dtype={devices.dtype} recast')
             kwargs[c] = kwargs[c].to(dtype=devices.dtype)
-    kwargs = model_quant.create_bnb_config(kwargs)
-    pipe = diffusers.FluxPipeline.from_pretrained(repo_id, cache_dir=shared.opts.diffusers_dir, **kwargs, **diffusers_load_config)
+
+    allow_bnb = 'gguf' not in (sd_unet.loaded_unet or '')
+    kwargs = model_quant.create_bnb_config(kwargs, allow_bnb)
+    if checkpoint_info.path.endswith('.safetensors') and os.path.isfile(checkpoint_info.path):
+        pipe = diffusers.FluxPipeline.from_single_file(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **kwargs, **diffusers_load_config)
+    else:
+        pipe = diffusers.FluxPipeline.from_pretrained(repo_id, cache_dir=shared.opts.diffusers_dir, **kwargs, **diffusers_load_config)
+
+    # release memory
+    transformer = None
+    text_encoder_1 = None
+    text_encoder_2 = None
+    vae = None
+    devices.torch_gc()
+
     return pipe

modules/model_quant.py

@@ -7,10 +7,10 @@
 quanto = None
 
 
-def create_bnb_config(kwargs = None):
+def create_bnb_config(kwargs = None, allow_bnb: bool = True):
     from modules import shared, devices
-    if len(shared.opts.bnb_quantization) > 0:
-        if 'Model' in shared.opts.bnb_quantization and 'transformer' not in (kwargs or {}):
+    if len(shared.opts.bnb_quantization) > 0 and allow_bnb:
+        if 'Model' in shared.opts.bnb_quantization:
             load_bnb()
             bnb_config = diffusers.BitsAndBytesConfig(
                 load_in_8bit=shared.opts.bnb_quantization_type in ['fp8'],

modules/model_sd3.py

@@ -120,6 +120,11 @@ def load_sd3(checkpoint_info, cache_dir=None, config=None):
     repo_id = sd_models.path_to_repo(checkpoint_info.name)
     fn = checkpoint_info.path
 
+    # unload current model
+    sd_models.unload_model_weights()
+    shared.sd_model = None
+    devices.torch_gc(force=True)
+
     kwargs = {}
     kwargs = load_overrides(kwargs, cache_dir)
     if fn is None or not os.path.exists(fn):
@@ -152,5 +157,5 @@ def load_sd3(checkpoint_info, cache_dir=None, config=None):
         config=config,
         **kwargs,
     )
-    devices.torch_gc(force=True)
+    devices.torch_gc()
     return pipe

modules/model_tools.py

@@ -13,6 +13,16 @@ def remove_entries_after_depth(d, depth, current_depth=0):
     return d
 
 
+def list_compact(flat_list):
+    result_list = []
+    for item in flat_list:
+        keys = item.split('.')
+        keys = '.'.join(keys[:2])
+        if keys not in result_list:
+            result_list.append(keys)
+    return result_list
+
+
 def list_to_dict(flat_list):
     result_dict = {}
     try: