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import torch |
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from shared.utils import files_locator as fl |
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def get_ltxv_text_encoder_filename(text_encoder_quantization): |
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text_encoder_filename = "T5_xxl_1.1/T5_xxl_1.1_enc_bf16.safetensors" |
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if text_encoder_quantization =="int8": |
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text_encoder_filename = text_encoder_filename.replace("bf16", "quanto_bf16_int8") |
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return fl.locate_file(text_encoder_filename, True) |
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class family_handler(): |
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@staticmethod |
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def query_model_def(base_model_type, model_def): |
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LTXV_config = model_def.get("LTXV_config", "") |
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distilled= "distilled" in LTXV_config |
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extra_model_def = {} |
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if distilled: |
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extra_model_def.update({ |
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"lock_inference_steps": True, |
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"no_negative_prompt" : True, |
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}) |
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extra_model_def["fps"] = 30 |
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extra_model_def["frames_minimum"] = 17 |
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extra_model_def["frames_steps"] = 8 |
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extra_model_def["sliding_window"] = True |
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extra_model_def["image_prompt_types_allowed"] = "TSEV" |
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extra_model_def["guide_preprocessing"] = { |
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"selection": ["", "PV", "DV", "EV", "V"], |
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"labels" : { "V": "Use LTXV raw format"} |
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} |
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extra_model_def["mask_preprocessing"] = { |
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"selection": ["", "A", "NA", "XA", "XNA"], |
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} |
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extra_model_def["extra_control_frames"] = 1 |
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extra_model_def["dont_cat_preguide"]= True |
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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 ["ltxv_13B"] |
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@staticmethod |
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def query_family_maps(): |
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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("ltxv") |
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return latent_rgb_factors, latent_rgb_factors_bias |
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@staticmethod |
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def query_model_family(): |
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return "ltxv" |
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@staticmethod |
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def query_family_infos(): |
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return {"ltxv":(10, "LTX Video")} |
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@staticmethod |
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def get_vae_block_size(base_model_type): |
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return 32 |
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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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text_encoder_filename = get_ltxv_text_encoder_filename(text_encoder_quantization) |
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return { |
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"repoId" : "DeepBeepMeep/LTX_Video", |
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"sourceFolderList" : ["T5_xxl_1.1", "" ], |
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"fileList" : [ ["added_tokens.json", "special_tokens_map.json", "spiece.model", "tokenizer_config.json"] + computeList(text_encoder_filename), ["ltxv_0.9.7_VAE.safetensors", "ltxv_0.9.7_spatial_upscaler.safetensors", "ltxv_scheduler.json"] + computeList(model_filename) ] |
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} |
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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, override_text_encoder = None): |
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from .ltxv import LTXV |
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ltxv_model = LTXV( |
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model_filepath = model_filename, |
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text_encoder_filepath = get_ltxv_text_encoder_filename(text_encoder_quantization) if override_text_encoder is None else override_text_encoder, |
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model_type = model_type, |
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base_model_type = base_model_type, |
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model_def = model_def, |
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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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) |
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pipeline = ltxv_model.pipeline |
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pipe = {"transformer" : pipeline.video_pipeline.transformer, "vae" : pipeline.vae, "text_encoder" : pipeline.video_pipeline.text_encoder, "latent_upsampler" : pipeline.latent_upsampler} |
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return ltxv_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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pass |
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