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github.com/MinusZoneAI/ComfyUI-CogVideoX-MZ
/ functions
Functions
283 in github.com/MinusZoneAI/ComfyUI-CogVideoX-MZ
⨍
Functions
283
◇
Types & classes
50
Method
__call__
Function invoked when calling the pipeline for generation. Args: prompt (`str` or `List[str]`, *optional*):
cogvideox_fun/pipeline_cogvideox_inpaint.py:578
Method
__call__
( self, attn: Attention, hidden_states: torch.Tensor, encoder_hidden_states: t
cogvideox_fun/fun_pab_transformer_3d.py:58
Method
__call__
( self, attn: Attention, hidden_states: torch.Tensor, encoder_hidden_states: t
cogvideox_fun/fun_pab_transformer_3d.py:150
Method
__enter__
(self)
mz_gguf_loader.py:10
Method
__exit__
(self, exc_type, exc_value, traceback)
mz_gguf_loader.py:15
Method
__init__
( self, vae: AutoencoderKLCogVideoX, transformer: Union[CogVideoXTransformer3DModel, C
pipeline_cogvideox.py:142
Method
__init__
(self)
mz_gguf_loader.py:7
Method
__init__
( self, in_features, out_features, bias, dev, qtype="Q4_0", cast_dtype=torch.float16 )
mz_gguf_loader.py:59
Method
__init__
( self, num_attention_heads: int = 30, attention_head_dim: int = 64, vae_chann
cogvideo_controlnet.py:20
Method
__init__
(self)
custom_cogvideox_transformer_3d.py:69
Method
__init__
(self)
custom_cogvideox_transformer_3d.py:143
Method
__init__
( self, num_attention_heads: int = 30, attention_head_dim: int = 64, in_channe
custom_cogvideox_transformer_3d.py:421
Method
__init__
(self)
videosys/cogvideox_transformer_3d.py:42
Method
__init__
(self)
videosys/cogvideox_transformer_3d.py:134
Method
__init__
( self, num_attention_heads: int = 30, attention_head_dim: int = 64, in_channe
videosys/cogvideox_transformer_3d.py:394
Method
__init__
( self, in_channels: int, out_channels: int, kernel_size: int = 3, str
videosys/modules/downsampling.py:26
Method
__init__
( self, in_channels: int, out_channels: int, kernel_size: int = 3, str
videosys/modules/upsampling.py:25
Method
__init__
( self, patch_size: int = 2, in_channels: int = 16, embed_dim: int = 1920,
videosys/modules/embeddings.py:12
Method
__init__
( self, patch_size=(2, 4, 4), in_chans=3, embed_dim=96, norm_layer=Non
videosys/modules/embeddings.py:61
Method
__init__
(self, hidden_size, frequency_embedding_size=256)
videosys/modules/embeddings.py:109
Method
__init__
( self, conditioning_dim: int, embedding_dim: int, elementwise_affine: bool =
videosys/modules/normalization.py:8
Method
__init__
(self)
videosys/core/pipeline.py:8
Method
__init__
( self, steps: int, cross_broadcast: bool = False, cross_threshold: list = Non
videosys/core/pab_mgr.py:6
Method
__init__
(self, config: PABConfig)
videosys/core/pab_mgr.py:44
Method
__init__
(self)
cogvideox_fun/transformer_3d.py:69
Method
__init__
(self)
cogvideox_fun/transformer_3d.py:143
Method
__init__
( self, patch_size: int = 2, in_channels: int = 16, embed_dim: int = 1920,
cogvideox_fun/transformer_3d.py:211
Method
__init__
( self, num_attention_heads: int = 30, attention_head_dim: int = 64, in_channe
cogvideox_fun/transformer_3d.py:463
Method
__init__
( self, text_encoder: Union[List[T5EncoderModel], T5EncoderModel], unet, multi
cogvideox_fun/lora_utils.py:163
Method
__init__
( self, vae: AutoencoderKLCogVideoX, transformer: CogVideoXTransformer3DModel,
cogvideox_fun/pipeline_cogvideox_control.py:186
Method
__init__
( self, vae: AutoencoderKLCogVideoX, transformer: CogVideoXTransformer3DModel,
cogvideox_fun/pipeline_cogvideox_inpaint.py:234
Method
__init__
( self, in_channels: int, out_channels: int, kernel_size: Union[int, Tuple[int
cogvideox_fun/autoencoder_magvit.py:79
Method
__init__
( self, f_channels: int, zq_channels: int, groups: int = 32, )
cogvideox_fun/autoencoder_magvit.py:164
Method
__init__
( self, in_channels: int, out_channels: Optional[int] = None, dropout: float =
cogvideox_fun/autoencoder_magvit.py:218
Method
__init__
( self, in_channels: int, out_channels: int, temb_channels: int, dropo
cogvideox_fun/autoencoder_magvit.py:343
Method
__init__
( self, in_channels: int, temb_channels: int, dropout: float = 0.0, nu
cogvideox_fun/autoencoder_magvit.py:445
Method
__init__
( self, in_channels: int = 3, out_channels: int = 16, down_block_types: Tuple[
cogvideox_fun/autoencoder_magvit.py:635
Method
__init__
( self, in_channels: int = 16, out_channels: int = 3, up_block_types: Tuple[st
cogvideox_fun/autoencoder_magvit.py:769
Method
__init__
( self, in_channels: int = 3, out_channels: int = 3, down_block_types: Tuple[s
cogvideox_fun/autoencoder_magvit.py:922
Method
__init__
(self)
cogvideox_fun/fun_pab_transformer_3d.py:54
Method
__init__
(self)
cogvideox_fun/fun_pab_transformer_3d.py:146
Method
__init__
( self, patch_size: int = 2, in_channels: int = 16, embed_dim: int = 1920,
cogvideox_fun/fun_pab_transformer_3d.py:212
Method
__init__
( self, num_attention_heads: int = 30, attention_head_dim: int = 64, in_channe
cogvideox_fun/fun_pab_transformer_3d.py:444
Function
_dyn_cpu_offload_model
(model)
mz_dyn_cpu_offload.py:78
Function
_encode
( self, x: torch.Tensor, return_dict: bool = True )
mz_enable_vae_encode_tiling.py:110
Method
_get_signature_keys
(cls, obj)
videosys/core/pipeline.py:30
Method
_set_gradient_checkpointing
(self, module, value=False)
cogvideo_controlnet.py:123
Method
_set_gradient_checkpointing
(self, module, value=False)
custom_cogvideox_transformer_3d.py:521
Method
_set_gradient_checkpointing
(self, module, value=False)
videosys/cogvideox_transformer_3d.py:514
Method
_set_gradient_checkpointing
(self, module, value=False)
cogvideox_fun/transformer_3d.py:564
Method
_set_gradient_checkpointing
(self, module, value=False)
cogvideox_fun/autoencoder_magvit.py:1017
Method
_set_gradient_checkpointing
(self, module, value=False)
cogvideox_fun/fun_pab_transformer_3d.py:536
Method
apply_to
(self, text_encoder, unet, apply_text_encoder=True, apply_unet=True)
cogvideox_fun/lora_utils.py:256
Method
attn_processors
r""" Returns: `dict` of attention processors: A dictionary containing all attention processors used in the model with
custom_cogvideox_transformer_3d.py:526
Method
attn_processors
r""" Returns: `dict` of attention processors: A dictionary containing all attention processors used in the model with
cogvideox_fun/transformer_3d.py:569
Method
create_custom_forward
(module)
cogvideo_controlnet.py:190
Method
create_custom_forward
(module)
videosys/cogvideox_transformer_3d.py:579
Method
create_custom_forward
(module)
cogvideox_fun/autoencoder_magvit.py:399
Method
create_custom_forward
(module)
cogvideox_fun/autoencoder_magvit.py:487
Method
create_custom_forward
(module)
cogvideox_fun/autoencoder_magvit.py:592
Method
create_custom_forward
(module)
cogvideox_fun/autoencoder_magvit.py:714
Method
create_custom_forward
(module)
cogvideox_fun/autoencoder_magvit.py:855
Method
create_custom_forward
(module)
cogvideox_fun/fun_pab_transformer_3d.py:633
Method
create_forward
(*inputs)
cogvideox_fun/autoencoder_magvit.py:400
Method
create_forward
(*inputs)
cogvideox_fun/autoencoder_magvit.py:488
Method
create_forward
(*inputs)
cogvideox_fun/autoencoder_magvit.py:593
Method
create_modules
( is_unet: bool, root_module: torch.nn.Module, target_replace_modules: Lis
cogvideox_fun/lora_utils.py:186
Function
create_network
( multiplier: float, network_dim: Optional[int], network_alpha: Optional[float], text_encoder:
cogvideox_fun/lora_utils.py:342
Method
custom_forward
(*inputs)
cogvideo_controlnet.py:191
Method
custom_forward
(*inputs)
videosys/cogvideox_transformer_3d.py:580
Method
custom_forward
(*inputs)
cogvideox_fun/autoencoder_magvit.py:715
Method
custom_forward
(*inputs)
cogvideox_fun/autoencoder_magvit.py:856
Method
custom_forward
(*inputs)
cogvideox_fun/fun_pab_transformer_3d.py:634
Method
decode_latents
(self, latents: torch.Tensor)
cogvideox_fun/pipeline_cogvideox_control.py:324
Method
decode_latents
(self, latents: torch.Tensor)
cogvideox_fun/pipeline_cogvideox_inpaint.py:408
Method
disable_slicing
r""" Disable sliced VAE decoding. If `enable_slicing` was previously enabled, this method will go back to computing decoding in one st
cogvideox_fun/autoencoder_magvit.py:1077
Method
disable_tiling
r""" Disable tiled VAE decoding. If `enable_tiling` was previously enabled, this method will go back to computing decoding in one step
cogvideox_fun/autoencoder_magvit.py:1063
Method
do_classifier_free_guidance
(self)
pipeline_cogvideox.py:355
Method
dtype
(self)
videosys/modules/embeddings.py:176
Function
dyn_cpu_offload_model
(model)
mz_dyn_cpu_offload.py:62
Function
dyn_cpu_offload_model_vae
(vae)
mz_dyn_cpu_offload.py:29
Function
enable_encode_tiling
r""" Enable tiled VAE decoding. When this option is enabled, the VAE will split the input tensor into tiles to compute decoding and encoding i
mz_enable_vae_encode_tiling.py:141
Method
enable_gradient_checkpointing
(self)
cogvideox_fun/lora_utils.py:310
Method
enable_slicing
r""" Enable sliced VAE decoding. When this option is enabled, the VAE will split the input tensor in slices to compute decoding in sev
cogvideox_fun/autoencoder_magvit.py:1070
Method
enable_tiling
r""" Enable tiled VAE decoding. When this option is enabled, the VAE will split the input tensor into tiles to compute decoding and en
cogvideox_fun/autoencoder_magvit.py:1027
Function
encode
Encode a batch of images into latents. Args: x (`torch.Tensor`): Input batch of images. return_dict (`bool`, *optional*, defa
mz_enable_vae_encode_tiling.py:10
Function
encode
(cls, x, return_dict: bool = True)
mz_dyn_cpu_offload.py:34
Method
enumerate_params
(loras)
cogvideox_fun/lora_utils.py:290
Method
extra_repr
(self)
mz_gguf_loader.py:109
Method
fn_recursive_add_processors
(name: str, module: torch.nn.Module, processors: Dict[str, AttentionProcessor])
custom_cogvideox_transformer_3d.py:535
Method
fn_recursive_add_processors
(name: str, module: torch.nn.Module, processors: Dict[str, AttentionProcessor])
cogvideox_fun/transformer_3d.py:578
Method
fn_recursive_attn_processor
(name: str, module: torch.nn.Module, processor)
custom_cogvideox_transformer_3d.py:571
Method
fn_recursive_attn_processor
(name: str, module: torch.nn.Module, processor)
cogvideox_fun/transformer_3d.py:614
Method
forward
(self, x)
mz_gguf_loader.py:121
Method
forward
( self, hidden_states: torch.Tensor, encoder_hidden_states: torch.Tensor, cont
cogvideo_controlnet.py:142
Method
forward
( self, hidden_states: torch.Tensor, encoder_hidden_states: torch.Tensor, temb
custom_cogvideox_transformer_3d.py:294
Method
forward
( self, hidden_states: torch.Tensor, encoder_hidden_states: torch.Tensor, time
custom_cogvideox_transformer_3d.py:624
Method
forward
( self, hidden_states: torch.Tensor, encoder_hidden_states: torch.Tensor, temb
videosys/cogvideox_transformer_3d.py:290
Method
forward
( self, hidden_states: torch.Tensor, encoder_hidden_states: torch.Tensor, time
videosys/cogvideox_transformer_3d.py:517
Method
forward
(self, x: torch.Tensor)
videosys/modules/downsampling.py:40
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