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sdnext/pipelines/model_cosmos.py
2025-10-30 03:11:50 +03:00

56 lines
2.0 KiB
Python

import transformers
import diffusers
from modules import shared, devices, sd_models, model_quant, sd_hijack_te, sd_hijack_vae
from pipelines import generic
def load_cosmos_t2i(checkpoint_info, diffusers_load_config=None):
if diffusers_load_config is None:
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, allow_quant=False)
shared.log.debug(f'Load model: type=Cosmos 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.CosmosTransformer3DModel, load_config=diffusers_load_config, subfolder="transformer")
repo_te = 'nvidia/Cosmos-Predict2-2B-Text2Image' if 'Cosmos-Predict2-14B-Text2Image' in repo_id else repo_id
text_encoder = generic.load_text_encoder(repo_te, cls_name=transformers.T5EncoderModel, load_config=diffusers_load_config, subfolder="text_encoder", allow_shared=False) # cosmos does use standard t5
safety_checker = Fake_safety_checker()
pipe = diffusers.Cosmos2TextToImagePipeline.from_pretrained(
repo_id,
transformer=transformer,
text_encoder=text_encoder,
safety_checker=safety_checker,
cache_dir=shared.opts.diffusers_dir,
**load_args,
)
del text_encoder
del transformer
sd_hijack_te.init_hijack(pipe)
sd_hijack_vae.init_hijack(pipe)
devices.torch_gc()
return pipe
class Fake_safety_checker:
def __init__(self):
from diffusers.utils import import_utils
import_utils._cosmos_guardrail_available = True # pylint: disable=protected-access
def __call__(self, *args, **kwargs): # pylint: disable=unused-argument
return
def to(self, _device):
pass
def check_text_safety(self, _prompt):
return True
def check_video_safety(self, vid):
return vid