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