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import torch | |
from . import model_base | |
from . import utils | |
from . import latent_formats | |
class ClipTarget: | |
def __init__(self, tokenizer, clip): | |
self.clip = clip | |
self.tokenizer = tokenizer | |
self.params = {} | |
class BASE: | |
unet_config = {} | |
unet_extra_config = { | |
"num_heads": -1, | |
"num_head_channels": 64, | |
} | |
clip_prefix = [] | |
clip_vision_prefix = None | |
noise_aug_config = None | |
sampling_settings = {} | |
latent_format = latent_formats.LatentFormat | |
def matches(s, unet_config): | |
for k in s.unet_config: | |
if s.unet_config[k] != unet_config[k]: | |
return False | |
return True | |
def model_type(self, state_dict, prefix=""): | |
return model_base.ModelType.EPS | |
def inpaint_model(self): | |
return self.unet_config["in_channels"] > 4 | |
def __init__(self, unet_config): | |
self.unet_config = unet_config | |
self.latent_format = self.latent_format() | |
for x in self.unet_extra_config: | |
self.unet_config[x] = self.unet_extra_config[x] | |
def get_model(self, state_dict, prefix="", device=None): | |
if self.noise_aug_config is not None: | |
out = model_base.SD21UNCLIP(self, self.noise_aug_config, model_type=self.model_type(state_dict, prefix), device=device) | |
else: | |
out = model_base.BaseModel(self, model_type=self.model_type(state_dict, prefix), device=device) | |
if self.inpaint_model(): | |
out.set_inpaint() | |
return out | |
def process_clip_state_dict(self, state_dict): | |
return state_dict | |
def process_unet_state_dict(self, state_dict): | |
return state_dict | |
def process_vae_state_dict(self, state_dict): | |
return state_dict | |
def process_clip_state_dict_for_saving(self, state_dict): | |
replace_prefix = {"": "cond_stage_model."} | |
return utils.state_dict_prefix_replace(state_dict, replace_prefix) | |
def process_unet_state_dict_for_saving(self, state_dict): | |
replace_prefix = {"": "model.diffusion_model."} | |
return utils.state_dict_prefix_replace(state_dict, replace_prefix) | |
def process_vae_state_dict_for_saving(self, state_dict): | |
replace_prefix = {"": "first_stage_model."} | |
return utils.state_dict_prefix_replace(state_dict, replace_prefix) | |