mirror of https://github.com/vladmandic/automatic
64 lines
2.4 KiB
Python
64 lines
2.4 KiB
Python
import sys
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import transformers
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from modules import shared, devices, sd_models, model_quant, sd_hijack_te
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def load_dit(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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shared.log.debug(f'Load model: type=FLite dit="{repo_id}" quant="{model_quant.get_quant_type(quant_args)}" args={load_args}')
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import pipelines.f_lite
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sys.modules['f_lite'] = pipelines.f_lite
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transformer = pipelines.f_lite.DiT.from_pretrained(
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repo_id,
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subfolder="dit_model",
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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=FLite 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_flite(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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from pipelines.f_lite import FLitePipeline
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dit_model = load_dit(repo_id, diffusers_load_config)
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text_encoder = 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='Model')
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shared.log.debug(f'Load model: type=FLite model="{checkpoint_info.name}" repo="{repo_id}" offload={shared.opts.diffusers_offload_mode} dtype={devices.dtype} args={load_args}')
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pipe = FLitePipeline.from_pretrained(
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repo_id,
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revision="refs/pr/8",
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dit_model=dit_model,
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text_encoder=text_encoder,
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trust_remote_code=True,
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cache_dir=shared.opts.diffusers_dir,
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**load_args,
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)
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sd_hijack_te.init_hijack(pipe)
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del text_encoder
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del dit_model
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devices.torch_gc()
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return pipe
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