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github.com/aim-uofa/Framer
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Functions
206 in github.com/aim-uofa/Framer
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Functions
206
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Types & classes
53
Method
__init__
( self, in_channels: int, temb_channels: int, dropout: float = 0.0, nu
models_diffusers/unet_3d_blocks.py:309
Method
__init__
( self, in_channels: int, out_channels: int, temb_channels: int, dropo
models_diffusers/unet_3d_blocks.py:443
Method
__init__
( self, in_channels: int, out_channels: int, temb_channels: int, dropo
models_diffusers/unet_3d_blocks.py:585
Method
__init__
( self, in_channels: int, out_channels: int, prev_output_channel: int,
models_diffusers/unet_3d_blocks.py:674
Method
__init__
( self, in_channels: int, out_channels: int, temb_channels: int, dropo
models_diffusers/unet_3d_blocks.py:934
Method
__init__
( self, in_channels: int, out_channels: int, temb_channels: int, dropo
models_diffusers/unet_3d_blocks.py:1060
Method
__init__
( self, in_channels: int, out_channels: int, prev_output_channel: int,
models_diffusers/unet_3d_blocks.py:1248
Method
__init__
( self, in_channels: int, prev_output_channel: int, out_channels: int,
models_diffusers/unet_3d_blocks.py:1444
Method
__init__
( self, in_channels: int, temb_channels: int, dropout: float = 0.0, nu
models_diffusers/unet_3d_blocks.py:1587
Method
__init__
( self, in_channels: int, out_channels: int, attention_head_dim: int = 512,
models_diffusers/unet_3d_blocks.py:1760
Method
__init__
( self, in_channels: int, out_channels: int, num_layers: int = 1, add_
models_diffusers/unet_3d_blocks.py:1823
Method
__init__
( self, in_channels: int, temb_channels: int, num_layers: int = 1, tra
models_diffusers/unet_3d_blocks.py:1873
Method
__init__
( self, in_channels: int, out_channels: int, temb_channels: int, num_l
models_diffusers/unet_3d_blocks.py:1983
Method
__init__
( self, in_channels: int, out_channels: int, temb_channels: int, num_l
models_diffusers/unet_3d_blocks.py:2073
Method
__init__
( self, in_channels: int, prev_output_channel: int, out_channels: int,
models_diffusers/unet_3d_blocks.py:2202
Method
__init__
( self, in_channels: int, out_channels: int, prev_output_channel: int,
models_diffusers/unet_3d_blocks.py:2291
Method
__init__
( self, sample_size: Optional[int] = None, in_channels: int = 8, out_channels:
models_diffusers/unet_spatio_temporal_condition.py:112
Method
__init__
( self, conditioning_embedding_channels: int, conditioning_channels: int = 3,
models_diffusers/controlnet_svd.py:73
Method
_set_gradient_checkpointing
(self, module, value=False)
models_diffusers/unet_spatio_temporal_condition.py:366
Method
_set_gradient_checkpointing
(self, module, value=False)
models_diffusers/controlnet_svd.py:402
Function
adaptively_load_state_dict
(target, state_dict)
gradio_demo/utils_drag.py:202
Function
add_drag
(tracking_points)
app.py:571
Function
add_tracking_points
(tracking_points, first_frame_path, last_frame_path, evt: gr.SelectData)
app.py:634
Function
arr2pil
(arr)
gradio_demo/utils_drag.py:259
Method
attn_processors
r""" Returns: `dict` of attention processors: A dictionary containing all attention processors used in the model with
models_diffusers/unet_spatio_temporal_condition.py:292
Method
attn_processors
r""" Returns: `dict` of attention processors: A dictionary containing all attention processors used in the model with
models_diffusers/controlnet_svd.py:328
Method
create_custom_forward
(module)
models_diffusers/unet_3d_blocks.py:1020
Method
create_custom_forward
(module, return_dict=None)
models_diffusers/unet_3d_blocks.py:1193
Method
create_custom_forward
(module, return_dict=None)
models_diffusers/unet_3d_blocks.py:1397
Method
create_custom_forward
(module)
models_diffusers/unet_3d_blocks.py:1552
Method
create_custom_forward
(module, return_dict=None)
models_diffusers/unet_3d_blocks.py:1711
Method
create_custom_forward
(module, return_dict=None)
models_diffusers/unet_3d_blocks.py:1943
Method
create_custom_forward
(module)
models_diffusers/unet_3d_blocks.py:2033
Method
create_custom_forward
(module, return_dict=None)
models_diffusers/unet_3d_blocks.py:2147
Method
create_custom_forward
(module)
models_diffusers/unet_3d_blocks.py:2255
Method
create_custom_forward
(module, return_dict=None)
models_diffusers/unet_3d_blocks.py:2365
Method
custom_forward
(*inputs)
models_diffusers/unet_3d_blocks.py:1021
Method
custom_forward
(*inputs)
models_diffusers/unet_3d_blocks.py:1194
Method
custom_forward
(*inputs)
models_diffusers/unet_3d_blocks.py:1398
Method
custom_forward
(*inputs)
models_diffusers/unet_3d_blocks.py:1553
Method
custom_forward
(*inputs)
models_diffusers/unet_3d_blocks.py:1712
Method
custom_forward
(*inputs)
models_diffusers/unet_3d_blocks.py:1944
Method
custom_forward
(*inputs)
models_diffusers/unet_3d_blocks.py:2034
Method
custom_forward
(*inputs)
models_diffusers/unet_3d_blocks.py:2148
Method
custom_forward
(*inputs)
models_diffusers/unet_3d_blocks.py:2256
Method
custom_forward
(*inputs)
models_diffusers/unet_3d_blocks.py:2366
Function
data2file
(data, filename, type=None, override=False, printable=False, **kwargs)
gradio_demo/utils_drag.py:120
Function
delete_last_drag
(tracking_points, first_frame_path, last_frame_path)
app.py:576
Function
delete_last_step
(tracking_points, first_frame_path, last_frame_path)
app.py:605
Method
do_classifier_free_guidance
(self)
pipelines/pipeline_stable_video_diffusion_interp_control.py:306
Method
enable_forward_chunking
Sets the attention processor to use [feed forward chunking](https://huggingface.co/blog/reformer#2-chunked-feed-forward-layers).
models_diffusers/unet_spatio_temporal_condition.py:371
Method
enable_forward_chunking
Sets the attention processor to use [feed forward chunking](https://huggingface.co/blog/reformer#2-chunked-feed-forward-layers).
models_diffusers/controlnet_svd.py:407
Function
file2data
(filename, type=None, printable=True, **kwargs)
gradio_demo/utils_drag.py:155
Method
fn_recursive_add_processors
( name: str, module: torch.nn.Module, processors: Dict[str, AttentionProce
models_diffusers/unet_spatio_temporal_condition.py:301
Method
fn_recursive_add_processors
( name: str, module: torch.nn.Module, processors: Dict[str, AttentionProce
models_diffusers/controlnet_svd.py:337
Method
fn_recursive_attn_processor
(name: str, module: torch.nn.Module, processor)
models_diffusers/unet_spatio_temporal_condition.py:340
Method
fn_recursive_attn_processor
(name: str, module: torch.nn.Module, processor)
models_diffusers/controlnet_svd.py:376
Method
fn_recursive_feed_forward
(module: torch.nn.Module, chunk_size: int, dim: int)
models_diffusers/unet_spatio_temporal_condition.py:390
Method
fn_recursive_feed_forward
(module: torch.nn.Module, chunk_size: int, dim: int)
models_diffusers/controlnet_svd.py:426
Method
fn_recursive_retrieve_sliceable_dims
(module: torch.nn.Module)
models_diffusers/controlnet_svd.py:731
Method
fn_recursive_set_attention_slice
(module: torch.nn.Module, slice_size: List[int])
models_diffusers/controlnet_svd.py:769
Method
forward
r""" The forward method of the `Attention` class. Args: hidden_states (`torch.Tensor`): The hidden states
models_diffusers/attention_processor.py:496
Method
forward
(self, f: torch.FloatTensor, zq: torch.FloatTensor)
models_diffusers/attention_processor.py:1696
Method
forward
The [`TransformerTemporal`] forward method. Args: hidden_states (`torch.LongTensor` of shape `(batch size, num latent pi
models_diffusers/transformer_temporal.py:124
Method
forward
Args: hidden_states (`torch.FloatTensor` of shape `(batch size, channel, height, width)`): Input hidden_states.
models_diffusers/transformer_temporal.py:280
Method
forward
(self, x: torch.Tensor, objs: torch.Tensor)
models_diffusers/attention.py:83
Method
forward
( self, hidden_states: torch.FloatTensor, attention_mask: Optional[torch.FloatTensor]
models_diffusers/attention.py:247
Method
forward
( self, hidden_states: torch.FloatTensor, num_frames: int, encoder_hidden_stat
models_diffusers/attention.py:436
Method
forward
(self, hidden_states: torch.Tensor, scale: float = 1.0)
models_diffusers/attention.py:541
Method
forward
( self, hidden_states: torch.FloatTensor, temb: Optional[torch.FloatTensor] = None,
models_diffusers/unet_3d_blocks.py:410
Method
forward
( self, hidden_states: torch.FloatTensor, temb: Optional[torch.FloatTensor] = None,
models_diffusers/unet_3d_blocks.py:543
Method
forward
( self, hidden_states: torch.FloatTensor, temb: Optional[torch.FloatTensor] = None,
models_diffusers/unet_3d_blocks.py:650
Method
forward
( self, hidden_states: torch.FloatTensor, res_hidden_states_tuple: Tuple[torch.FloatTe
models_diffusers/unet_3d_blocks.py:768
Method
forward
( self, hidden_states: torch.FloatTensor, res_hidden_states_tuple: Tuple[torch.FloatTe
models_diffusers/unet_3d_blocks.py:890
Method
forward
( self, hidden_states: torch.FloatTensor, temb: Optional[torch.FloatTensor] = None,
models_diffusers/unet_3d_blocks.py:1007
Method
forward
( self, hidden_states: torch.FloatTensor, temb: Optional[torch.FloatTensor] = None,
models_diffusers/unet_3d_blocks.py:1174
Method
forward
( self, hidden_states: torch.FloatTensor, res_hidden_states_tuple: Tuple[torch.FloatTe
models_diffusers/unet_3d_blocks.py:1355
Method
forward
( self, hidden_states: torch.FloatTensor, res_hidden_states_tuple: Tuple[torch.FloatTe
models_diffusers/unet_3d_blocks.py:1513
Method
forward
( self, hidden_states: torch.FloatTensor, temb: Optional[torch.FloatTensor] = None,
models_diffusers/unet_3d_blocks.py:1694
Method
forward
( self, hidden_states: torch.FloatTensor, image_only_indicator: torch.FloatTensor,
models_diffusers/unet_3d_blocks.py:1803
Method
forward
( self, hidden_states: torch.FloatTensor, image_only_indicator: torch.FloatTensor,
models_diffusers/unet_3d_blocks.py:1854
Method
forward
( self, hidden_states: torch.FloatTensor, temb: Optional[torch.FloatTensor] = None,
models_diffusers/unet_3d_blocks.py:1927
Method
forward
( self, hidden_states: torch.FloatTensor, temb: Optional[torch.FloatTensor] = None,
models_diffusers/unet_3d_blocks.py:2023
Method
forward
( self, hidden_states: torch.FloatTensor, temb: Optional[torch.FloatTensor] = None,
models_diffusers/unet_3d_blocks.py:2133
Method
forward
( self, hidden_states: torch.FloatTensor, res_hidden_states_tuple: Tuple[torch.FloatTe
models_diffusers/unet_3d_blocks.py:2239
Method
forward
( self, hidden_states: torch.FloatTensor, res_hidden_states_tuple: Tuple[torch.FloatTe
models_diffusers/unet_3d_blocks.py:2348
Method
forward
r""" The [`UNetSpatioTemporalConditionModel`] forward method. Args: sample (`torch.FloatTensor`): The noi
models_diffusers/unet_spatio_temporal_condition.py:400
Method
forward
(self, conditioning, point_embedding=None, point_tracks=None)
models_diffusers/controlnet_svd.py:100
Method
forward
r""" The [`UNetSpatioTemporalConditionModel`] forward method. Args: sample (`torch.FloatTensor`): The noi
models_diffusers/controlnet_svd.py:436
Method
from_unet
r""" Instantiate a [`ControlNetModel`] from [`UNet2DConditionModel`]. Parameters: unet (`UNet2DConditionModel`):
models_diffusers/controlnet_svd.py:577
Function
get_concat_v
(im1, im2)
app.py:306
Method
guidance_scale
(self)
pipelines/pipeline_stable_video_diffusion_interp_control.py:299
Function
image2arr
(filename)
gradio_demo/utils_drag.py:245
Function
import_filename
(filename)
gradio_demo/utils_drag.py:194
Function
notebook_show
(*images)
gradio_demo/utils_drag.py:268
Method
num_timesteps
(self)
pipelines/pipeline_stable_video_diffusion_interp_control.py:310
Function
preprocess_image
(image)
app.py:537
Function
preprocess_image_end
(image_end)
app.py:554
Function
reset_states
(first_frame_path, last_frame_path, tracking_points)
app.py:529
Method
run
(self, first_frame_path, last_frame_path, tracking_points, controlnet_cond_scale, motion_bucket_id)
app.py:401
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