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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}")
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