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Functions431 in github.com/JaceyHuang/Gen3R

⨍ Functions 431◇ Types & classes 84
↓ 1 callersFunctionworker_init_fn
(_seed)
train_dit.py:1269
Method__call__
(self, n_samples, generator=None, device=None)
gen3r/utils/discrete_sampler.py:31
Method__call__
Generates spatial positions for a batch of patches. Args: batch_size: Number of samples in the batch. height: Height
gen3r/models/vggt/layers/rope.py:39
Method__call__
Function invoked when calling the pipeline for generation. Args: Examples: Returns:
gen3r/pipeline/pipeline_gen3r.py:555
Method__getitem__
(self, index)
train_geo_adapter_pl.py:60
Method__getitem__
(self, index: int)
gen3r/data/dataset.py:77
Method__getitem__
(self, index: int)
gen3r/data/dataset.py:301
Method__init__
( self, args, learning_rate=1e-5, recon_loss_weight=1., similarity_los
train_geo_adapter_pl.py:82
Method__init__
(self, num_idx, uniform_sampling=False)
gen3r/utils/discrete_sampler.py:6
Method__init__
( self, num_train_timesteps: int = 1000, solver_order: int = 2, prediction_typ
gen3r/utils/fm_solvers.py:129
Method__init__
( self, num_train_timesteps: int = 1000, solver_order: int = 2,
gen3r/utils/fm_solvers_unipc.py:77
Method__init__
(self, max_num_frames: int, height: int, width: int, max_interval: int=None, fix_start_frame: int=None, *args,
gen3r/data/dataset.py:170
Method__init__
( self, dataset_configs: List[Dict[str, Any]], max_num_frames: int, height: in
gen3r/data/dataset.py:230
Method__init__
Initializes the 2D RoPE module.
gen3r/models/vggt/layers/rope.py:79
Method__init__
(self, drop_prob=None)
gen3r/models/vggt/layers/drop_path.py:29
Method__init__
( self, dim: int, num_heads: int, mlp_ratio: float = 4.0, qkv_bias: bo
gen3r/models/vggt/layers/block.py:28
Method__init__
( self, dim: int, init_values: Union[float, Tensor] = 1e-5, inplace: bool = Fa
gen3r/models/vggt/layers/layer_scale.py:16
Method__init__
( self, dim: int, num_heads: int = 8, qkv_bias: bool = True, proj_bias
gen3r/models/vggt/layers/attention.py:22
Method__init__
( self, in_features: int, hidden_features: Optional[int] = None, out_features:
gen3r/models/vggt/layers/mlp.py:17
Method__init__
( self, in_features: int, hidden_features: Optional[int] = None, out_features:
gen3r/models/vggt/layers/swiglu_ffn.py:55
Method__init__
( self, img_size: Union[int, Tuple[int, int]] = 224, patch_size: Union[int, Tuple[int,
gen3r/models/vggt/layers/patch_embed.py:37
Method__init__
Args: img_size (int, tuple): input image size patch_size (int, tuple): patch size in_chans (int): number
gen3r/models/vggt/layers/vision_transformer.py:43
Method__init__
Init. Args: features (int): number of features
gen3r/models/vggt/heads/dpt_head.py:374
Method__init__
Init. Args: features (int): number of features
gen3r/models/vggt/heads/dpt_head.py:419
Method__init__
( self, dim_in: int = 2048, trunk_depth: int = 4, pose_encoding_type: str = "a
gen3r/models/vggt/heads/camera_head.py:28
Method__init__
( self, img_size=518, patch_size=14, embed_dim=1024, depth=24,
gen3r/models/vggt/models/aggregator.py:52
Method__init__
(self, img_size=518, patch_size=14, embed_dim=1024)
gen3r/models/vggt/models/vggt.py:19
Method__init__
(self, size=None)
gen3r/models/geometry_adapter/geometry_adapter.py:28
Method__init__
(self, *args, **kwargs)
gen3r/models/geometry_adapter/geometry_adapter.py:41
Method__init__
(self, dim, mode, resample_scale=4)
gen3r/models/geometry_adapter/geometry_adapter.py:86
Method__init__
(self, in_dim, out_dim, dropout=0.0)
gen3r/models/geometry_adapter/geometry_adapter.py:207
Method__init__
(self, dim)
gen3r/models/geometry_adapter/geometry_adapter.py:248
Method__init__
(self, input_dim=8192, dim=256, z_dim=16,
gen3r/models/geometry_adapter/geometry_adapter.py:280
Method__init__
(self, output_dim=8192, dim=128, z_dim=4,
gen3r/models/geometry_adapter/geometry_adapter.py:391
Method__init__
(self, dim=256, z_dim=16, input_dim=8192,
gen3r/models/geometry_adapter/geometry_adapter.py:513
Method__init__
( self, latent_channels=16, hidden_dim=256, input_dim=8192, output_dim
gen3r/models/geometry_adapter/geometry_adapter.py:657
Method__init__
(self, dim)
gen3r/models/videoxfun_wan/wan_camera_adapter.py:44
Method__init__
(self, dim, eps=1e-5)
gen3r/models/videoxfun_wan/wan_transformer3d.py:403
Method__init__
(self, dim, eps=1e-6, elementwise_affine=False)
gen3r/models/videoxfun_wan/wan_transformer3d.py:422
Method__init__
(self, dim, num_heads, window_size=(-1, -1),
gen3r/models/videoxfun_wan/wan_transformer3d.py:435
Method__init__
(self, dim, num_heads, window_size=(-1, -1),
gen3r/models/videoxfun_wan/wan_transformer3d.py:528
Method__init__
(self, cross_attn_type, dim, ffn_dim, num_
gen3r/models/videoxfun_wan/wan_transformer3d.py:591
Method__init__
(self, in_dim, out_dim)
gen3r/models/videoxfun_wan/wan_transformer3d.py:700
Method__init__
r""" Initialize the diffusion model backbone. Args: model_type (`str`, *optional*, defaults to 't2v'): Mo
gen3r/models/videoxfun_wan/wan_transformer3d.py:726
Method__init__
(self, dim, num_heads, dropout=0.1, eps=1e-5)
gen3r/models/videoxfun_wan/wan_xlm_roberta.py:12
Method__init__
(self, dim, num_heads, post_norm, dropout=0.1, eps=1e-5)
gen3r/models/videoxfun_wan/wan_xlm_roberta.py:51
Method__init__
(self, dim, dim_attn, num_heads, dropout=0.1)
gen3r/models/videoxfun_wan/wan_text_encoder.py:63
Method__init__
(self, dim, dim_ffn, dropout=0.1)
gen3r/models/videoxfun_wan/wan_text_encoder.py:117
Method__init__
(self, dim, dim_attn, dim_ffn, num_heads,
gen3r/models/videoxfun_wan/wan_text_encoder.py:137
Method__init__
(self, dim, dim_attn, dim_ffn, num_heads,
gen3r/models/videoxfun_wan/wan_text_encoder.py:170
Method__init__
(self, num_buckets, num_heads, bidirectional, max_dist=128)
gen3r/models/videoxfun_wan/wan_text_encoder.py:212
Method__init__
( self, vocab, dim, dim_attn, dim_ffn, num_heads, num_
gen3r/models/videoxfun_wan/wan_text_encoder.py:262
Method__init__
(self, *args, **kwargs)
gen3r/models/videoxfun_wan/wan_vae.py:29
Method__init__
(self, dim, mode)
gen3r/models/videoxfun_wan/wan_vae.py:75
Method__init__
(self, in_dim, out_dim, dropout=0.0)
gen3r/models/videoxfun_wan/wan_vae.py:195
Method__init__
(self, dim)
gen3r/models/videoxfun_wan/wan_vae.py:235
Method__init__
(self, dim=128, z_dim=4, dim_mult=[1, 2, 4, 4],
gen3r/models/videoxfun_wan/wan_vae.py:274
Method__init__
(self, dim=128, z_dim=4, dim_mult=[1, 2, 4, 4],
gen3r/models/videoxfun_wan/wan_vae.py:378
Method__init__
(self, dim=128, z_dim=4, dim_mult=[1, 2, 4, 4],
gen3r/models/videoxfun_wan/wan_vae.py:492
Method__init__
( self, latent_channels=16, temporal_compression_ratio=4, spacial_compression_
gen3r/models/videoxfun_wan/wan_vae.py:627
Method__init__
(self, dim, num_heads, causal=False, attn_
gen3r/models/videoxfun_wan/wan_image_encoder.py:58
Method__init__
(self, dim, mlp_ratio, num_heads, post_nor
gen3r/models/videoxfun_wan/wan_image_encoder.py:117
Method__init__
(self, dim, mlp_ratio, num_heads, activati
gen3r/models/videoxfun_wan/wan_image_encoder.py:161
Method__init__
(self, image_size=224, patch_size=16, dim=768,
gen3r/models/videoxfun_wan/wan_image_encoder.py:214
Method__init__
(self, **kwargs)
gen3r/models/videoxfun_wan/wan_image_encoder.py:308
Method__init__
(self, embed_dim=1024, image_size=224, patch_size=14,
gen3r/models/videoxfun_wan/wan_image_encoder.py:333
Method__init__
(self)
gen3r/models/videoxfun_wan/wan_image_encoder.py:506
Method__init__
( self, coefficients: list[float], num_steps: int, rel_l1_thresh: float = 0.0,
gen3r/models/videoxfun_wan/cache_utils.py:27
Method__init__
( self, tokenizer: AutoTokenizer, text_encoder: WanT5EncoderModel, transformer
gen3r/pipeline/pipeline_gen3r.py:179
Method__len__
(self)
train_geo_adapter_pl.py:77
Method__len__
(self)
gen3r/utils/fm_solvers.py:856
Method__len__
(self)
gen3r/utils/fm_solvers_unipc.py:799
Method__len__
(self)
gen3r/data/dataset.py:73
Method__len__
(self)
gen3r/data/dataset.py:297
Method_load_state_dict_any
(path)
gen3r/models/geometry_adapter/geometry_adapter.py:746
Method_load_state_dict_any
(path)
gen3r/models/videoxfun_wan/wan_text_encoder.py:339
Method_load_state_dict_any
(path)
gen3r/models/videoxfun_wan/wan_vae.py:698
Method_load_state_dict_any
(path)
gen3r/models/videoxfun_wan/wan_image_encoder.py:541
Method_set_gradient_checkpointing
(self, enable, gradient_checkpointing_func=None)
gen3r/models/videoxfun_wan/wan_transformer3d.py:909
Method_sigma_to_t
(self, sigma)
gen3r/utils/fm_solvers.py:330
Method_sigma_to_t
(self, sigma)
gen3r/utils/fm_solvers_unipc.py:269
Function_worker_init_fn
(worker_id)
train_dit.py:1271
Methodadd_noise
( self, original_samples: torch.Tensor, noise: torch.Tensor, timesteps: torch.
gen3r/utils/fm_solvers.py:815
Methodadd_noise
( self, original_samples: torch.Tensor, noise: torch.Tensor, timesteps: torch.
gen3r/utils/fm_solvers_unipc.py:758
Methodattention_kwargs
(self)
gen3r/pipeline/pipeline_gen3r.py:546
Methodattn_residual_func
(x: Tensor, pos=None)
gen3r/models/vggt/layers/block.py:82
Methodattn_residual_func
(x: Tensor, attn_bias=None)
gen3r/models/vggt/layers/block.py:219
Methodbegin_index
The index for the first timestep. It should be set from pipeline with `set_begin_index` method.
gen3r/utils/fm_solvers.py:209
Methodbegin_index
The index for the first timestep. It should be set from pipeline with `set_begin_index` method.
gen3r/utils/fm_solvers_unipc.py:142
Methodconfigure_optimizers
(self)
train_geo_adapter_pl.py:157
Methodcreate_custom_forward
(module)
gen3r/models/videoxfun_wan/wan_transformer3d.py:1039
Methodcross_attn_ffn
(x, context, context_lens, e)
gen3r/models/videoxfun_wan/wan_transformer3d.py:654
Methodcustom_forward
(*inputs)
gen3r/models/videoxfun_wan/wan_transformer3d.py:1040
Methoddisable_riflex
(self)
gen3r/models/videoxfun_wan/wan_transformer3d.py:891
Methoddisable_teacache
(self)
gen3r/models/videoxfun_wan/wan_transformer3d.py:872
Methoddtype
`torch.dtype`: The dtype of the module (assuming that all the module parameters have the same dtype).
gen3r/models/vggt/heads/dpt_head.py:133
Methoddtype
`torch.dtype`: The dtype of the module (assuming that all the module parameters have the same dtype).
gen3r/models/vggt/heads/camera_head.py:86
Methoddtype
`torch.dtype`: The dtype of the module (assuming that all the module parameters have the same dtype).
gen3r/models/vggt/models/aggregator.py:149
Methoddtype
`torch.dtype`: The dtype of the module (assuming that all the module parameters have the same dtype).
gen3r/models/vggt/models/vggt.py:104
Methodenable_multi_gpus_inference
(self,)
gen3r/models/videoxfun_wan/wan_transformer3d.py:902
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