(s)

(s)

(s)

(s)

(s)

(s)

(s)

(s)

(s)

(s)

(s)

(s)

(cls)

(cls)

(cls)

(cls)

(cls)

(cls)

(s, file_path, **kwargs)

(s, file_path, **kwargs)

(self, *args, **kwargs)

(self, *args, **kwargs)

(self)

(self)

(self, *args, **kwargs)

(self, *args, **kwargs)

(self, *args, **kwargs)

(self, index)

(self, *args, **kwargs)

(self, index)

(self, index)

(self, context_length: int=None, context_stride: int=None, context_overlap: int=None, context

(self)

(self, img_width: int, video_length: int)

(self, draw: ImageDraw.ImageDraw, vs: VisualizeSettings, home_x: int=0, home_y: int=0)

(self, in_channels: int, cond_embed_dim: int, act_fn: str = "silu", ops=comfy.ops.disable_weight_init)

(self, in_c, out_c, down: bool, ksize=3, sk=False, use_conv=True, ops=comfy.ops.disable_weigh

(self, channels, use_conv: bool, dims=2, out_channels=None, padding=1, ops=comfy.ops.disable_

(self)

(self, device="cpu")

(self, sd_type: str, mm_format: str, mm_version: str, mm_name: str)

(self, mm_state_dict: dict[str, Tensor], mm_info: AnimateDiffInfo, init_kwargs: dict[str]={})

( self, in_channels, block_type: str, block_idx: int, module_idx: int,

( self, in_channels, num_attention_heads, attention_head_dim, num_laye

( self, dim, num_attention_heads, attention_head_dim, attention_block_

(self, d_model, dropout=0.0, max_len=24)

( self, attention_mode=None, cross_frame_attention_mode=None, temporal_pe=Fals

(self, mm_state_dict: dict[str, Tensor], mm_info: AnimateDiffInfo)

( self, in_channels, block_type: str=BlockType.DOWN, block_idx

( self, in_channels, block_type: str, block_idx: int,

(self, beta_schedule: str, linear_start: float=None, linear_end: float=None, given_betas: Tensor=None, timeste

(self, *args, **kwargs)

(self, model_sampling: comfy.model_sampling.ModelSamplingDiscrete, model_type: ModelType)

(self, preset: str, index: int, mult_multival: Union[float, Tensor]=None, effect_multival: Union[float, Tensor

(self, query_dim, context_dim=None, heads=8, dim_head=64, dropout=0., dtype=None, device=None,

(self, num_groups: int, num_channels: int, eps: float = 1e-5, affine: bool = True, device=Non

(self, effect_multival: Union[float, Tensor]=None)

(self, multival: Union[float, Tensor], effect_multival: Union[float, Tensor]=None)

(self, block_type: str, block_idx: Union[int, None]=None, module_idx: Union[int, None]=None)

(self, id: PerBlockId, effect: Union[float, Tensor, None]=None, scales: Union[list[Union[floa

(self, start_percent: float = 0.0, scale_multival: Union[float, Tensor]=None

(self)

(self)

(self, name: str, strength: float = 1.0, hash: str="")

(self)

(self)

(self, image: Tensor, vae: VAE)

(self, block_out_channels: tuple[int] = (320, 640, 1280, 1280), num_attentio

(self)

(self, in_channels: int, index: int, num_attention_heads: i

(self, channel_in, channel_out, heads: int=8,

(self, embed_dim: int, max_seq_length: int = 32)

(self)

(self)

(self, model: ModelPatcher)

(self)

(self, init_motion_model: Union[MotionModelPatcher, list[MotionModelPatcher]]=None)

(self, unlimited_area_hack: bool=False, apply_mm_groupnorm_hack: bool=True, apply_v2_properly

(self, effect: Union[float, Tensor, None]=None, scales: Union[list[float, Tensor], None]=list

(self)

(self)

(self)

(self)

(self, holder: FunctionInjectionHolder=None)

(self, holder: FunctionInjectionHolder=None)

(self, adjust_pe: 'AdjustGroup'=None, adjust_weight: 'AdjustGroup'=None,

(self, print_adjustment=False)

(self, cap_initial_pe_length: int=0, interpolate_pe_to_length: int=0, initia

(self, all_ADD=0.0, all_MULT=1.0, pe_ADD=0.0, pe_MULT=1.0,

(self, initial: ADJUST_TYPES=None)

(self, downscale_factor=8, channels=[320, 640, 1280, 1280],

(self, in_c, out_c, down: bool, ksize=3, sk=False, use_conv=True, ops=comfy.ops.disable_weigh

(self, channels, use_conv: bool, dims=2, out_channels=None, padding=1, ops=comfy.ops.disable_

(self, batch_offset: int=0, noise_type: str=None, seed_gen: str=None, seed_offset: int=0, noise_layers: NoiseL

(self, noise_type: str, determinism: str, seed_offset: int, seed_override: int=None)

(self, noise_type: str, batch_offset: int, seed_gen_override: str, seed_offset: int, seed_override: int=None,

(self, noise_type: str, batch_offset: int, seed_gen_override: str, seed_offset: int, seed_override: int=None,

(self, noise_type: str, batch_offset: int, seed_gen_override: str, seed_offset: int, seed_override: int=None,

(self, noise_type: str, batch_offset: int, seed_gen_override: str, seed_offset: int, seed_override: int=None,

(self, noise_type: str, batch_offset: int, seed_gen_override: str, seed_offset: int, seed_override: int=None,