From e42a27a0e45152905d34601590ddf29ff2f38795 Mon Sep 17 00:00:00 2001 From: Vladimir Mandic Date: Mon, 11 Aug 2025 08:30:46 -0400 Subject: [PATCH] fix chroma Signed-off-by: Vladimir Mandic --- cli/test-all-models.py | 106 +++++++++++++++++++--------------- installer.py | 2 +- modules/sd_models.py | 7 ++- pipelines/generic.py | 8 ++- pipelines/model_chroma.py | 1 + pipelines/model_hunyuandit.py | 29 ++++++++++ 6 files changed, 102 insertions(+), 51 deletions(-) create mode 100644 pipelines/model_hunyuandit.py diff --git a/cli/test-all-models.py b/cli/test-all-models.py index bc8f4027a..163c193d6 100755 --- a/cli/test-all-models.py +++ b/cli/test-all-models.py @@ -1,10 +1,14 @@ #!/usr/bin/env python """ +Warning: - fal/AuraFlow-v0.3: layer_class_name=Linear layer_weight_shape=torch.Size([3072, 2, 1024]) weights_dtype=int8 unsupported +- Kwai-Kolors/Kolors-diffusers: `set_input_embeddings` not auto‑handled for ChatGLMModel +Error: - nvidia/Cosmos-Predict2-2B-Text2Image: mat1 and mat2 shapes cannot be multiplied (512x4096 and 1024x2048) - nvidia/Cosmos-Predict2-14B-Text2Image: mat1 and mat2 shapes cannot be multiplied (512x4096 and 1024x5120) +- Tencent-Hunyuan/HunyuanDiT-v1.2-Diffusers: CUDA error: device-side assert triggered +Other: - HiDream-ai/HiDream-I1-Full: 30+s/it -- Kwai-Kolors/Kolors-diffusers: `set_input_embeddings` not auto‑handled for ChatGLMModel """ import io @@ -25,49 +29,53 @@ urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning) output_folder = 'outputs/compare' -models = [ - "sdxl-base-v10-vaefix", - "tempest-by-vlad-0.1", - "icbinpXL_v6", - "briaai/BRIA-3.2", - "Freepik/F-Lite", - "Freepik/F-Lite-Texture", - "ostris/Flex.2-preview", - "stabilityai/stable-diffusion-3.5-medium", - "stabilityai/stable-diffusion-3.5-large", - "fal/AuraFlow-v0.3", - "fal/AuraFlow-v0.2", - "zai-org/CogView4-6B", - "zai-org/CogView3-Plus-3B", - # "nvidia/Cosmos-Predict2-2B-Text2Image", - # "nvidia/Cosmos-Predict2-14B-Text2Image", - "Qwen/Qwen-Image", - "vladmandic/Qwen-Lightning", - "Shitao/OmniGen-v1-diffusers", - "OmniGen2/OmniGen2", - # "HiDream-ai/HiDream-I1-Full", - "Kwai-Kolors/Kolors-diffusers", - "lodestones/Chroma1-HD", - "vladmandic/chroma-unlocked-v50-annealed", - "vladmandic/chroma-unlocked-v48", - "vladmandic/chroma-unlocked-v48-detail-calibrated", - "Alpha-VLLM/Lumina-Next-SFT-diffusers", - "Alpha-VLLM/Lumina-Image-2.0", - "MeissonFlow/Meissonic", - "Efficient-Large-Model/SANA1.5_1.6B_1024px_diffusers", - "Efficient-Large-Model/SANA1.5_4.8B_1024px_diffusers", - "PixArt-alpha/PixArt-XL-2-1024-MS", - "PixArt-alpha/PixArt-Sigma-XL-2-1024-MS", - "Wan-AI/Wan2.1-T2V-1.3B-Diffusers", - "Wan-AI/Wan2.1-T2V-14B-Diffusers", - "stabilityai/stable-cascade", -] +models = { + "sdxl-base-v10-vaefix": {}, + "tempest-by-vlad-0.1": {}, + "icbinpXL_v6": {}, + "briaai/BRIA-3.2": {}, + "Freepik/F-Lite": {}, + "Freepik/F-Lite-Texture": {}, + "ostris/Flex.2-preview": {}, + "playgroundai/playground-v2-1024px-aesthetic": {}, + "playground-v2.5-1024px-aesthetic.fp16": { "sampler_name": "DPM++ 2M EDM" }, + "stabilityai/stable-diffusion-3.5-medium": {}, + "stabilityai/stable-diffusion-3.5-large": {}, + "fal/AuraFlow-v0.3": {}, + "fal/AuraFlow-v0.2": {}, + "zai-org/CogView4-6B": {}, + "zai-org/CogView3-Plus-3B": {}, + # "Tencent-Hunyuan/HunyuanDiT-v1.2-Diffusers": {}, + # "nvidia/Cosmos-Predict2-2B-Text2Image": {}, + # "nvidia/Cosmos-Predict2-14B-Text2Image": {}, + "Qwen/Qwen-Image": {}, + "vladmandic/Qwen-Lightning": {}, + "Shitao/OmniGen-v1-diffusers": {}, + "OmniGen2/OmniGen2": {}, + # "HiDream-ai/HiDream-I1-Full": {}, + "Kwai-Kolors/Kolors-diffusers": {}, + "lodestones/Chroma1-HD": {}, + "vladmandic/chroma-unlocked-v50-annealed": {}, + "vladmandic/chroma-unlocked-v48": {}, + "vladmandic/chroma-unlocked-v48-detail-calibrated": {}, + "Alpha-VLLM/Lumina-Next-SFT-diffusers": {}, + "Alpha-VLLM/Lumina-Image-2.0": {}, + "MeissonFlow/Meissonic": {}, + "Efficient-Large-Model/SANA1.5_1.6B_1024px_diffusers": {}, + "Efficient-Large-Model/SANA1.5_4.8B_1024px_diffusers": {}, + "PixArt-alpha/PixArt-XL-2-1024-MS": {}, + "PixArt-alpha/PixArt-Sigma-XL-2-1024-MS": {}, + "Wan-AI/Wan2.1-T2V-1.3B-Diffusers": {}, + "Wan-AI/Wan2.1-T2V-14B-Diffusers": {}, + "stabilityai/stable-cascade": {}, +} models_tbd = [ "black-forest-labs/FLUX.1-dev", "black-forest-labs/FLUX.1-Kontext-dev", "black-forest-labs/FLUX.1-Krea-dev", - "Tencent-Hunyuan/HunyuanDiT-v1.2-Diffusers", # TODO "kandinsky-community/kandinsky-3", # TODO + "kandinsky-community/kandinsky-2-2-decoder", + "kandinsky-community/kandinsky-2-1", ] styles = [ 'Fixed Astronaut', @@ -103,7 +111,7 @@ def read_history(): log.info(f'history: file="{fn}" records={len(history)}') -def write_history(model:str, style:str, image:str='', size:tuple=(0,0), duration:float=0, info:str='', error:str=''): +def write_history(model:str, style:str, image:str='', size:tuple=(0,0), duration:float=0, info:str=''): fn = os.path.join(output_folder, 'history.json') history.append({ 'model': model, @@ -113,7 +121,6 @@ def write_history(model:str, style:str, image:str='', size:tuple=(0,0), duration 'size': size, 'time': duration, 'info': info, - 'error': error, }) with open(fn, "w", encoding='utf8') as file: data = json.dumps(history) # pylint: disable=no-member @@ -137,9 +144,11 @@ def request(endpoint: str, dct: dict = None, method: str = 'POST'): def generate(): # pylint: disable=redefined-outer-name - for m, model in enumerate(models): + idx = 0 + for model, args in models.items(): + idx += 1 model_name = pathvalidate.sanitize_filename(model, replacement_text='_') - log.info(f'model: name="{model}" n={m+1}/{len(models)}') + log.info(f'model: n={idx+1}/{len(models)} name="{model}"') for s, style in enumerate(styles): try: model_name = pathvalidate.sanitize_filename(model, replacement_text='_') @@ -152,9 +161,12 @@ def generate(): # pylint: disable=redefined-outer-name if not loaded or not (model in loaded.get('checkpoint') or model in loaded.get('title') or model in loaded.get('name')): log.error(f' model: error="{model}"') continue - log.info(f' style: name="{style}" n={s+1}/{len(styles)} fn="{fn}"') t0 = time.time() - data = request('/sdapi/v1/txt2img', { 'styles': [style] }) + params = { 'styles': [style] } + for k, v in args.items(): + params[k] = v + log.info(f' style: n={s+1}/{len(styles)} name="{style}" args={params} fn="{fn}"') + data = request('/sdapi/v1/txt2img', params) t1 = time.time() if 'images' in data and len(data['images']) > 0: b64 = data['images'][0].split(',',1)[0] @@ -164,13 +176,13 @@ def generate(): # pylint: disable=redefined-outer-name image.save(fn) write_history(model=model, style=style, image=fn, size=image.size, duration=round(t1-t0, 3), info=info) else: - # write_history(model=model, style=style, duration=round(t1-t0, 3), error='no image') + # write_history(model=model, style=style, duration=round(t1-t0, 3), info='no image') log.error(f' model: error="{model}" style="{style}" no image') except Exception as e: if 'Connection refused' in str(e) or 'RemoteDisconnected' in str(e): log.error('server offline') os._exit(1) - # write_history(model=model, style=style, duration=round(t1-t0, 3), error=str(e)) + # write_history(model=model, style=style, duration=round(t1-t0, 3), info=str(e)) log.error(f' model: error="{model}" style="{style}" exception="{e}"') diff --git a/installer.py b/installer.py index 800edd0a7..6de6a025e 100644 --- a/installer.py +++ b/installer.py @@ -593,7 +593,7 @@ def check_diffusers(): t_start = time.time() if args.skip_all or args.skip_git: return - sha = '7b10e4ae65cc5830c581fba58638f5afb6e587cf' # diffusers commit hash + sha = '4a9dbd56f68214f0c949b8036a58c9ac3607f54e' # diffusers commit hash pkg = pkg_resources.working_set.by_key.get('diffusers', None) minor = int(pkg.version.split('.')[1] if pkg is not None else -1) cur = opts.get('diffusers_version', '') if minor > -1 else '' diff --git a/modules/sd_models.py b/modules/sd_models.py index 553da62eb..da863a924 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -323,7 +323,8 @@ def load_diffuser_force(model_type, checkpoint_info, diffusers_load_config, op=' allow_post_quant = False elif model_type in ['Chroma']: from pipelines.model_chroma import load_chroma - sd_model, allow_post_quant = load_chroma(checkpoint_info, diffusers_load_config) + sd_model = load_chroma(checkpoint_info, diffusers_load_config) + allow_post_quant = False elif model_type in ['Lumina 2']: from pipelines.model_lumina import load_lumina2 sd_model = load_lumina2(checkpoint_info, diffusers_load_config) @@ -376,6 +377,10 @@ def load_diffuser_force(model_type, checkpoint_info, diffusers_load_config, op=' from pipelines.model_qwen import load_qwen sd_model = load_qwen(checkpoint_info, diffusers_load_config) allow_post_quant = False + elif model_type in ['HunyuanDiT']: + from pipelines.model_hunyuandit import load_hunyuandit + sd_model = load_hunyuandit(checkpoint_info, diffusers_load_config) + allow_post_quant = False except Exception as e: shared.log.error(f'Load {op}: path="{checkpoint_info.path}" {e}') if debug_load: diff --git a/pipelines/generic.py b/pipelines/generic.py index 7b9039413..3801963d5 100644 --- a/pipelines/generic.py +++ b/pipelines/generic.py @@ -8,7 +8,7 @@ from modules import shared, devices, sd_models, model_quant debug = shared.log.trace if os.environ.get('SD_LOAD_DEBUG', None) is not None else lambda *args, **kwargs: None -def load_transformer(repo_id, cls_name, load_config={}, subfolder="transformer", allow_quant=True): +def load_transformer(repo_id, cls_name, load_config={}, subfolder="transformer", allow_quant=True, variant=None): load_args, quant_args = model_quant.get_dit_args(load_config, module='Model', device_map=True, allow_quant=allow_quant) quant_type = model_quant.get_quant_type(quant_args) @@ -45,6 +45,8 @@ def load_transformer(repo_id, cls_name, load_config={}, subfolder="transformer", shared.log.debug(f'Load model: transformer="{repo_id}" cls={cls_name.__name__} quant="{quant_type}" args={load_args}') if subfolder is not None: load_args['subfolder'] = subfolder + if variant is not None: + load_args['variant'] = variant transformer = cls_name.from_pretrained( repo_id, cache_dir=shared.opts.hfcache_dir, @@ -56,7 +58,7 @@ def load_transformer(repo_id, cls_name, load_config={}, subfolder="transformer", return transformer -def load_text_encoder(repo_id, cls_name, load_config={}, subfolder="text_encoder", allow_quant=True, allow_shared=True): +def load_text_encoder(repo_id, cls_name, load_config={}, subfolder="text_encoder", allow_quant=True, allow_shared=True, variant=None): load_args, quant_args = model_quant.get_dit_args(load_config, module='TE', device_map=True, allow_quant=allow_quant) quant_type = model_quant.get_quant_type(quant_args) text_encoder = None @@ -120,6 +122,8 @@ def load_text_encoder(repo_id, cls_name, load_config={}, subfolder="text_encoder shared.log.debug(f'Load model: text_encoder="{repo_id}" cls={cls_name.__name__} quant="{quant_type}" shared={shared.opts.te_shared_t5}') if subfolder is not None: load_args['subfolder'] = subfolder + if variant is not None: + load_args['variant'] = variant text_encoder = cls_name.from_pretrained( repo_id, cache_dir=shared.opts.hfcache_dir, diff --git a/pipelines/model_chroma.py b/pipelines/model_chroma.py index 5efa9b436..b0a28fa69 100644 --- a/pipelines/model_chroma.py +++ b/pipelines/model_chroma.py @@ -30,5 +30,6 @@ def load_chroma(checkpoint_info, diffusers_load_config={}): diffusers.pipelines.auto_pipeline.AUTO_IMAGE2IMAGE_PIPELINES_MAPPING["chroma"] = diffusers.ChromaImg2ImgPipeline del text_encoder del transformer + devices.torch_gc(force=True, reason='load') return pipe diff --git a/pipelines/model_hunyuandit.py b/pipelines/model_hunyuandit.py new file mode 100644 index 000000000..39d51a560 --- /dev/null +++ b/pipelines/model_hunyuandit.py @@ -0,0 +1,29 @@ +import transformers +import diffusers +from modules import shared, sd_models, devices, model_quant, sd_hijack_te +from pipelines import generic + + +def load_hunyuandit(checkpoint_info, diffusers_load_config={}): + repo_id = sd_models.path_to_repo(checkpoint_info) + sd_models.hf_auth_check(checkpoint_info) + + load_args, _quant_args = model_quant.get_dit_args(diffusers_load_config) + shared.log.debug(f'Load model: type=HunyuanDiT repo="{repo_id}" config={diffusers_load_config} offload={shared.opts.diffusers_offload_mode} dtype={devices.dtype} args={load_args}') + + transformer = generic.load_transformer(repo_id, cls_name=diffusers.HunyuanDiT2DModel, load_config=diffusers_load_config) + text_encoder_2 = generic.load_text_encoder(repo_id, cls_name=transformers.T5EncoderModel, load_config=diffusers_load_config, subfolder="text_encoder_2") + + pipe = diffusers.HunyuanDiTPipeline.from_pretrained( + repo_id, + transformer=transformer, + text_encoder_2=text_encoder_2, + cache_dir=shared.opts.diffusers_dir, + **load_args, + ) + + del text_encoder_2 + del transformer + sd_hijack_te.init_hijack(pipe) + devices.torch_gc(force=True, reason='load') + return pipe