mirror of
https://github.com/Wan-Video/Wan2.1.git
synced 2025-11-04 06:15:17 +00:00
116 lines
4.2 KiB
Python
116 lines
4.2 KiB
Python
import torch
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class family_handler():
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@staticmethod
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def set_cache_parameters(cache_type, base_model_type, model_def, inputs, skip_steps_cache):
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if base_model_type == "sky_df_1.3B":
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coefficients= [2.39676752e+03, -1.31110545e+03, 2.01331979e+02, -8.29855975e+00, 1.37887774e-01]
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else:
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coefficients= [-5784.54975374, 5449.50911966, -1811.16591783, 256.27178429, -13.02252404]
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skip_steps_cache.coefficients = coefficients
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@staticmethod
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def query_model_def(base_model_type, model_def):
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extra_model_def = {}
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if base_model_type in ["sky_df_14B"]:
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fps = 24
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else:
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fps = 16
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extra_model_def["fps"] =fps
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extra_model_def["frames_minimum"] = 17
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extra_model_def["frames_steps"] = 20
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extra_model_def["latent_size"] = 4
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extra_model_def["sliding_window"] = True
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extra_model_def["skip_layer_guidance"] = True
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extra_model_def["tea_cache"] = True
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extra_model_def["guidance_max_phases"] = 1
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extra_model_def["model_modes"] = {
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"choices": [
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("Synchronous", 0),
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("Asynchronous (better quality but around 50% extra steps added)", 5),
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],
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"default": 0,
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"label" : "Generation Type"
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}
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extra_model_def["image_prompt_types_allowed"] = "TSV"
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return extra_model_def
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@staticmethod
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def query_supported_types():
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return ["sky_df_1.3B", "sky_df_14B"]
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@staticmethod
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def query_family_maps():
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models_eqv_map = {
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"sky_df_1.3B" : "sky_df_14B",
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}
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models_comp_map = {
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"sky_df_14B": ["sky_df_1.3B"],
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}
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return models_eqv_map, models_comp_map
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@staticmethod
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def query_model_family():
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return "wan"
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@staticmethod
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def query_family_infos():
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return {}
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@staticmethod
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def get_rgb_factors(base_model_type ):
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from shared.RGB_factors import get_rgb_factors
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latent_rgb_factors, latent_rgb_factors_bias = get_rgb_factors("wan", base_model_type)
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return latent_rgb_factors, latent_rgb_factors_bias
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@staticmethod
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def query_model_files(computeList, base_model_type, model_filename, text_encoder_quantization):
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from .wan_handler import family_handler
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return family_handler.query_model_files(computeList, base_model_type, model_filename, text_encoder_quantization)
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@staticmethod
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def load_model(model_filename, model_type, base_model_type, model_def, quantizeTransformer = False, text_encoder_quantization = None, dtype = torch.bfloat16, VAE_dtype = torch.float32, mixed_precision_transformer = False, save_quantized= False, submodel_no_list = None):
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from .configs import WAN_CONFIGS
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from .wan_handler import family_handler
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cfg = WAN_CONFIGS['t2v-14B']
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from . import DTT2V
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wan_model = DTT2V(
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config=cfg,
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checkpoint_dir="ckpts",
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model_filename=model_filename,
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model_type = model_type,
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model_def = model_def,
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base_model_type=base_model_type,
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text_encoder_filename= family_handler.get_wan_text_encoder_filename(text_encoder_quantization),
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quantizeTransformer = quantizeTransformer,
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dtype = dtype,
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VAE_dtype = VAE_dtype,
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mixed_precision_transformer = mixed_precision_transformer,
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save_quantized = save_quantized
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)
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pipe = {"transformer": wan_model.model, "text_encoder" : wan_model.text_encoder.model, "vae": wan_model.vae.model }
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return wan_model, pipe
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@staticmethod
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def update_default_settings(base_model_type, model_def, ui_defaults):
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ui_defaults.update({
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"guidance_scale": 6.0,
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"flow_shift": 8,
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"sliding_window_discard_last_frames" : 0,
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"resolution": "1280x720" if "720" in base_model_type else "960x544",
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"sliding_window_size" : 121 if "720" in base_model_type else 97,
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"RIFLEx_setting": 2,
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"guidance_scale": 6,
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"flow_shift": 8,
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}) |