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| import torch | |
| class UNetController(): | |
| # Static variables (Hyperparameters) | |
| Is_freeu_enabled = False | |
| Freeu_parm = {'s1': 0.6, 's2': 0.4, 'b1': 1.1, 'b2': 1.2} | |
| # Ipca parameters | |
| Use_ipca = True | |
| Ipca_position = ['down0', 'down1', 'down2', 'mid', 'up0', 'up1', 'up2'] | |
| Ipca_start_step = 0 | |
| Ipca_dropout = 0.0 | |
| Use_embeds_mask = True | |
| # SVR parameters | |
| Alpha_weaken = 0.01 # 0.01~0.5 | |
| Beta_weaken = 0.05 # 0.05~1.0 | |
| Alpha_enhance = -0.01 # -0.001~-0.02 | |
| Beta_enhance = 1.0 # 1.0~2.0 | |
| # SVR settings | |
| Prompt_embeds_mode = 'svr' | |
| Remove_pool_embeds = False | |
| Prompt_embeds_start_step = 0 | |
| Store_qkv = True | |
| # other settings | |
| Use_same_latents = True | |
| Use_same_init_noise = True | |
| Save_story_image = True | |
| def __init__(self): | |
| self._variables = {} | |
| ## Variables (updated during inference) ## | |
| self.device = "cuda" | |
| self.current_unet_position = 'down' # down, mid or up | |
| self.torch_dtype = torch.float16 | |
| self.prompts = None | |
| self.negative_prompt = None | |
| self.id_prompt = None | |
| self.frame_prompt_express = None | |
| self.frame_prompt_suppress = None | |
| self.frame_prompt_express_list = None | |
| self.frame_prompt_suppress_list = None | |
| self.tokenizer = None | |
| self.result_save_dir = None | |
| self.current_time_step = None | |
| self.do_classifier_free_guidance = None | |
| self.q_store = {} | |
| self.k_store = {} | |
| self.v_store = {} | |
| self.do_classifier_free_guidance = None | |
| self.current_unet_position = None | |
| self.ipca2_index = -1 | |
| self.ipca_time_step = -1 | |
| ## Variables End ## | |
| def print_attributes(self): | |
| """ | |
| Prints all attributes and their values of the object. | |
| """ | |
| for attr, value in vars(self).items(): | |
| print(f"{attr}: {value}") | |