mirror of https://github.com/vladmandic/automatic
102 lines
3.9 KiB
Python
102 lines
3.9 KiB
Python
import os
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import transformers
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import diffusers
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from modules import shared, devices, sd_models, model_quant, sd_hijack_te
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def load_transformer(repo_id, diffusers_load_config={}):
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load_args, quant_args = model_quant.get_dit_args(diffusers_load_config, module='Model', device_map=True)
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fn = None
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if shared.opts.sd_unet is not None and shared.opts.sd_unet != 'Default':
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from modules import sd_unet
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if shared.opts.sd_unet not in list(sd_unet.unet_dict):
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shared.log.error(f'Load module: type=Transformer not found: {shared.opts.sd_unet}')
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return None
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fn = sd_unet.unet_dict[shared.opts.sd_unet] if os.path.exists(sd_unet.unet_dict[shared.opts.sd_unet]) else None
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if fn is not None and 'gguf' in fn.lower():
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shared.log.error('Load model: type=Cosmos format="gguf" unsupported')
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transformer = None
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elif fn is not None and 'safetensors' in fn.lower():
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shared.log.debug(f'Load model: type=Cosmos transformer="{fn}" quant="{model_quant.get_quant(repo_id)}" args={load_args}')
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transformer = diffusers.CosmosTransformer3DModel.from_single_file(fn, cache_dir=shared.opts.hfcache_dir, **load_args)
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else:
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shared.log.debug(f'Load model: type=Cosmos transformer="{repo_id}" quant="{model_quant.get_quant_type(quant_args)}" args={load_args}')
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transformer = diffusers.CosmosTransformer3DModel.from_pretrained(
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repo_id,
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subfolder="transformer",
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cache_dir=shared.opts.hfcache_dir,
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**load_args,
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**quant_args,
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)
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if shared.opts.diffusers_offload_mode != 'none' and transformer is not None:
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sd_models.move_model(transformer, devices.cpu)
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return transformer
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def load_text_encoder(repo_id, diffusers_load_config={}):
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load_args, quant_args = model_quant.get_dit_args(diffusers_load_config, module='TE', device_map=True)
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shared.log.debug(f'Load model: type=Cosmos te="{repo_id}" quant="{model_quant.get_quant_type(quant_args)}" args={load_args}')
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text_encoder = transformers.T5EncoderModel.from_pretrained(
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repo_id,
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subfolder="text_encoder",
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cache_dir=shared.opts.hfcache_dir,
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**load_args,
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**quant_args,
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)
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if shared.opts.diffusers_offload_mode != 'none' and text_encoder is not None:
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sd_models.move_model(text_encoder, devices.cpu)
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return text_encoder
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def load_cosmos_t2i(checkpoint_info, diffusers_load_config={}):
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repo_id = sd_models.path_to_repo(checkpoint_info)
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sd_models.hf_auth_check(checkpoint_info)
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transformer = load_transformer(repo_id, diffusers_load_config)
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text_encoder = load_text_encoder(repo_id, diffusers_load_config)
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safety_checker = Fake_safety_checker()
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load_args, _quant_args = model_quant.get_dit_args(diffusers_load_config, module='Model')
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shared.log.debug(f'Load model: type=Cosmos model="{checkpoint_info.name}" repo="{repo_id}" offload={shared.opts.diffusers_offload_mode} dtype={devices.dtype} args={load_args}')
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cls = diffusers.Cosmos2TextToImagePipeline
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pipe = cls.from_pretrained(
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repo_id,
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transformer=transformer,
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text_encoder=text_encoder,
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safety_checker=safety_checker,
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cache_dir=shared.opts.diffusers_dir,
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**load_args,
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)
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del text_encoder
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del transformer
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sd_hijack_te.init_hijack(pipe)
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from modules.video_models import video_vae
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pipe.vae.orig_decode = pipe.vae.decode
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pipe.vae.decode = video_vae.hijack_vae_decode
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devices.torch_gc()
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return pipe
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class Fake_safety_checker:
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def __init__(self):
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from diffusers.utils import import_utils
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import_utils._cosmos_guardrail_available = True # pylint: disable=protected-access
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def __call__(self, *args, **kwargs): # pylint: disable=unused-argument
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return
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def to(self, _device):
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pass
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def check_text_safety(self, _prompt):
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return True
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def check_video_safety(self, vid):
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return vid
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