(self, float_val: Union[float, list[float]]=None)

(original_timesteps=50)

(self, record)

(model: ModelPatcher, context_opts: ContextOptionsGroup=None, sampler_name: str=None, scheduler: str=None,

(angle: np.ndarray, T: np.ndarray, speed: float, n=16, base=16)

(self)

(mm_state_dict: dict[str, Tensor], mm_name: str, mm_format: str)

(mm_state_dict: dict[str, Tensor])

(self, patcher: MotionModelPatcher)

(cls, alias: str)

(self, patcher: MotionModelPatcher)

(self)

(motion_model: MotionModelPatcher, lora: MotionLoraInfo)

(model_name: str, model: ModelPatcher, motion_lora: MotionLoraList = None, motion_model_settings: AnimateDiffS

(self, id: int)

(self, model: ModelPatcher)

(self)

(self, camera_features: list[Tensor])

(self, motion_model_settings: AnimateDiffSettings)

(poses: list[list[float]], pose_width, pose_height)

(path)

(motion_model: MotionModelPatcher, all_per_blocks: AllPerBlocks)

(schedule_A: SigmaSchedule, schedule_B: SigmaSchedule, name_a: str="

(module)

(self, channels=[320, 640, 1280, 1280], nums_rb=3, cin=64, ksize=3, sk=False, use_conv=True,

(seed: int, latents: Tensor, noise_type: str=NoiseLayerType.DEFAULT, batch_offset: int=0, extra_args: dict={},

(noise: Tensor, noise_type: str, seed: int, extra_args: dict, device=RandDevice.CPU)

(self, op: str, attr: str)

(pairs: list[InputPair], length: int, clip: CLIP, options: PromptOptions, val

(self, op: str, attr: str)

(self, unet_blocks: nn.ModuleList, ref_blocks: nn.ModuleList, sample_module_name: str)

(self)

(self)

(self, timesteps: list[Tensor])

(state_dict: dict[str, Tensor])

(self, keyframe: ADKeyframe)

(self, extra: CFGExtras)

(self, extra: ContextExtra)

(self, scale_multival: Union[float, Tensor], prev_extras: CFGExtrasGroup=None)

(self, lora: MotionLoraInfo)

(self)

(self)

(items,t)

(x_in: Tensor, sub_conds_out, sub_conds, ctx_idxs: list[int], window_idx: int, total_windows: int, timestep,

(self, cfg_multival: Union[float, Tensor], cfg_extras: CFGExtrasGroup=None)

()

(cls, seed: int, latents: Tensor, existing_seed_gen: str=COMFY, seed_gen: str=USE_EXISTING, noise_type: str=No

(seeds: list[int], latents: Tensor, seed_offset: int=0, extra_args: dict={}, device=RandDevice.CPU)

(self, down: Union[ADBlockHolder, None]=None, mid: Union[ADB

(window: list[int], gd: GridDisplay, y_grid_offset: int, color: tuple)

(text: str, font: ImageFont, gd: GridDisplay, x: int, y: int, color=Colors.WHITE, centered=True)

(executor, model: BaseModel, x_in: Tensor, conds, timestep: Tensor, enumerated_context_windows: list[tuple[int

(text: str, length: int, clip: CLIP, options: PromptOptions)

(text: str, length: int)

(cls, alias: str)

(self)

(first_element: str)

(mm_state_dict: dict[str, Tensor], block_name: str)

(conds: list[dict], c_concat: comfy.conds.CONDNoiseShape)

(length: int, full_length: int, idxs: list[int], ctx_opts: ContextOptions, sigma: Tensor=None)

(cls, seed_gen: str)

(mm_state_dict: dict[str, Tensor])

(self, input_tensor: Tensor)

(x: Tensor, scale: float, is_low=True)

(self, x: Tensor)

(lora_name: str)

(cls, preset: str)

(self, transformer_options: dict[str])

(model: ModelPatcher)

(self, model: ModelPatcher, step: int)

(self)

(self)

(params: InjectionParams, manual_cast=False)

(pairs: list[InputPair], length: int)

(self)

(mm_state_dict: dict[str, Tensor])

(self)

(mm_state_dict: dict[str, Tensor])

(self, index: int)

(self)

(self)

(self)

(cls)

(self)

(self, model: BaseModel, model_options: dict[str])

(self, model: BaseModel)

(model_dict: dict[str, Tensor], key: str, new_length: int)

(self, attr: str, op: str)

(self)

(self)

(self, length: int)

(self)

(tensor_from: Tensor, tensor_to: Tensor, strength_to: Tensor)

(x, x_min=0.0, x_max=1.0, new_min=0.0, new_max=1.0)

(self)