flux ¶

FluxPipelineConfig(model_path: str = '', pipeline_config_path: str | None = None, embedded_cfg_scale: float = 3.5, flow_shift: float | None = None, flow_shift_sr: float | None = None, disable_autocast: bool = False, scheduler_step_in_fp32: bool = False, is_causal: bool = False, dit_config: FluxDiTConfig = FluxDiTConfig(), dit_precision: str = 'bf16', upsampler_config: UpsamplerConfig = UpsamplerConfig(), upsampler_precision: str = 'fp32', vae_config: AutoencoderKLVAEConfig = AutoencoderKLVAEConfig(), vae_precision: str = 'fp32', vae_decode_precision: str | None = None, vae_tiling: bool = True, vae_sp: bool = True, image_encoder_config: EncoderConfig = EncoderConfig(), image_encoder_precision: str = 'fp32', text_encoder_configs: tuple[EncoderConfig, ...] = (lambda: (CLIPTextConfig(), T5LargeConfig()))(), text_encoder_precisions: tuple[str, ...] = (lambda: ('fp32', 'bf16'))(), preprocess_text_funcs: tuple[Callable[[str], str], ...] = (lambda: (preprocess_text, preprocess_text))(), postprocess_text_funcs: tuple[Callable[[BaseEncoderOutput], Tensor], ...] = (lambda: (_flux_clip_pooled_postprocess, _flux_t5_sequence_postprocess))(), dmd_denoising_steps: list[int] | None = None, ti2v_task: bool = False, lucy_edit_task: bool = False, boundary_ratio: float | None = None, scheduler_arch: str = 'FlowMatchEulerDiscreteScheduler', transformer_arch: str = 'FluxTransformer2DModel', vae_arch: str = 'AutoencoderKL', text_encoder_archs: tuple[str, ...] = ('CLIPTextModel', 'T5EncoderModel'), tokenizer_archs: tuple[str, ...] = ('CLIPTokenizer', 'T5TokenizerFast'))