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Functions318 in github.com/NeuralCarver/Michelangelo

⨍ Functions 318◇ Types & classes 68
↓ 1 callersFunctiontrunc_normal_
r"""Fills the input Tensor with values drawn from a truncated normal distribution. The values are effectively drawn from the normal distributi
michelangelo/models/modules/transformer_vit.py:47
↓ 1 callersMethodunconditional_embedding
(self, batch_size=None)
michelangelo/models/conditional_encoders/encoder_factory.py:514
Method__call__
(self, sample)
michelangelo/data/transforms.py:95
Method__call__
(self, sample)
michelangelo/data/transforms.py:144
Method__call__
(self, sample)
michelangelo/data/transforms.py:196
Method__call__
(self, sample)
michelangelo/data/transforms.py:211
Method__call__
(self, sample)
michelangelo/data/transforms.py:240
Method__call__
(self, surface, *args)
michelangelo/data/transforms.py:257
Method__call__
(self, *args)
michelangelo/data/transforms.py:371
Method__init__
(self, settings, render_mode="WEBSITE")
michelangelo/utils/visualizers/pythreejs_viewer.py:14
Method__init__
(self, num_volume_samples: int = 1024, num_near_samples: int = 1024)
michelangelo/data/transforms.py:86
Method__init__
(self, use_surface_sample: bool = False, num_surface_samples: int = 4096,
michelangelo/data/transforms.py:131
Method__init__
(self, surface_feature_type: str)
michelangelo/data/transforms.py:191
Method__init__
(self, interval=(0.75, 1.25), jitter=True, jitter_scale=0.005)
michelangelo/data/transforms.py:202
Method__init__
(self, tensor_keys=("surface", "geo_points", "tex_points"))
michelangelo/data/transforms.py:237
Method__init__
(self, interval=(0.75, 1.25), jitter=True, jitter_scale=0.005)
michelangelo/data/transforms.py:251
Method__init__
( self, size, resize_radio=(0.5, 1), allow_resize_interpolations=(Interpolatio
michelangelo/data/transforms.py:282
Method__init__
(self, mesh_v: np.ndarray, mesh_f: np.ndarray, vertex_color
michelangelo/graphics/primitives/mesh.py:69
Method__init__
(self, device: torch.device, dtype: torch.dtype, width: int
michelangelo/models/modules/diffusion_transformer.py:19
Method__init__
( self, *, device: torch.device, dtype: torch.dtype,
michelangelo/models/modules/diffusion_transformer.py:38
Method__init__
( self, *, device: Optional[torch.device], dtype: Optional[tor
michelangelo/models/modules/diffusion_transformer.py:136
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, n_ctx: int,
michelangelo/models/modules/transformer_blocks.py:19
Method__init__
(self, *, device: torch.device, dtype: torch.dtype, heads: int, n_ctx: int, flash: bool = False)
michelangelo/models/modules/transformer_blocks.py:49
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, n_ctx: int,
michelangelo/models/modules/transformer_blocks.py:78
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, width: int,
michelangelo/models/modules/transformer_blocks.py:119
Method__init__
(self, *, device: torch.device, dtype: torch.dtype, heads: int, flash: bool = False, n_data:
michelangelo/models/modules/transformer_blocks.py:156
Method__init__
( self, *, device: Optional[torch.device], dtype: Optional[torch.dtype],
michelangelo/models/modules/transformer_blocks.py:189
Method__init__
( self, *, device: Optional[torch.device], dtype: Optional[torch.dtype],
michelangelo/models/modules/transformer_blocks.py:248
Method__init__
(self, in_channels, dim)
michelangelo/models/modules/embedder.py:112
Method__init__
(self, in_channels, dim)
michelangelo/models/modules/embedder.py:136
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, n_ctx: int,
michelangelo/models/modules/transformer_vit.py:83
Method__init__
(self, *, device: torch.device, dtype: torch.dtype, heads: int, n_ctx: int)
michelangelo/models/modules/transformer_vit.py:109
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, n_ctx: int,
michelangelo/models/modules/transformer_vit.py:129
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, width: int,
michelangelo/models/modules/transformer_vit.py:166
Method__init__
(self, *, device: torch.device, dtype: torch.dtype, heads: int, n_data: Optional[int] = None)
michelangelo/models/modules/transformer_vit.py:198
Method__init__
( self, *, device: Optional[torch.device], dtype: Optional[torch.dtype],
michelangelo/models/modules/transformer_vit.py:220
Method__init__
( self, *, device: Optional[torch.device], dtype: Optional[torch.dtype],
michelangelo/models/modules/transformer_vit.py:272
Method__init__
(self, value)
michelangelo/models/modules/distributions.py:15
Method__init__
(self, parameters: Union[torch.Tensor, List[torch.Tensor]], deterministic=False, feat_dim=1)
michelangelo/models/modules/distributions.py:26
Method__init__
(self, near_weight: float = 0.1, kl_weight: float = 1.0, co
michelangelo/models/tsal/loss.py:96
Method__init__
(self, contrast_weight: float = 1.0, near_weight: float = 0.1,
michelangelo/models/tsal/loss.py:194
Method__init__
(self, *, shape_model, clip_model_version: str = "openai/clip-vit-large-patc
michelangelo/models/tsal/clip_asl_module.py:13
Method__init__
(self)
michelangelo/models/tsal/tsal_base.py:18
Method__init__
(self)
michelangelo/models/tsal/tsal_base.py:25
Method__init__
(self, *args, **kwargs)
michelangelo/models/tsal/tsal_base.py:54
Method__init__
(self, *args, **kwargs)
michelangelo/models/tsal/tsal_base.py:90
Method__init__
(self, *args, **kwargs)
michelangelo/models/tsal/tsal_base.py:108
Method__init__
(self, *, device: Optional[torch.device], dtype: Optional[torch.dtype],
michelangelo/models/tsal/sal_perceiver.py:117
Method__init__
(self, *, device: Optional[torch.device], dtype: Optional[torch.dtype],
michelangelo/models/tsal/sal_perceiver.py:163
Method__init__
(self, *, device: Optional[torch.device], dtype: Optional[torch.dtype],
michelangelo/models/tsal/sal_perceiver.py:311
Method__init__
(self, *, shape_module_cfg, aligned_module_cfg, loss_cfg,
michelangelo/models/tsal/asl_pl_module.py:26
Method__init__
(self, *, module_cfg, loss_cfg, optimizer_cfg: Optional[Dic
michelangelo/models/tsal/sal_pl_module.py:24
Method__init__
(self, *, first_stage_config, cond_stage_config, denoiser_c
michelangelo/models/asl_diffusion/clip_asl_diffuser_pl_module.py:38
Method__init__
(self)
michelangelo/models/asl_diffusion/base.py:9
Method__init__
(self, *, device: Optional[torch.device], dtype: Optional[torch.dtype],
michelangelo/models/asl_diffusion/asl_udt.py:15
Method__init__
(self, *, first_stage_config, denoiser_cfg, scheduler_cfg,
michelangelo/models/asl_diffusion/asl_diffuser_pl_module.py:41
Method__init__
(self, model_path="openai/clip-vit-base-patch32")
michelangelo/models/conditional_encoders/clip.py:25
Method__init__
(self)
michelangelo/models/conditional_encoders/encoder_factory.py:16
Method__init__
( self, version="openai/clip-vit-large-patch14", tokenizer_version=None, devic
michelangelo/models/conditional_encoders/encoder_factory.py:41
Method__init__
( self, version="openai/clip-vit-large-patch14", tokenizer_version=None, devic
michelangelo/models/conditional_encoders/encoder_factory.py:114
Method__init__
( self, version="openai/clip-vit-large-patch14", device="cuda",
michelangelo/models/conditional_encoders/encoder_factory.py:188
Method__init__
( self, version="openai/clip-vit-large-patch14", device="cuda",
michelangelo/models/conditional_encoders/encoder_factory.py:301
Method__init__
( self, versions, hidden_state_dim, num_projection_vector=8,
michelangelo/models/conditional_encoders/encoder_factory.py:380
Method__repr__
(self)
michelangelo/data/transforms.py:335
Method__repr__
(self)
michelangelo/data/transforms.py:376
Method_convert_weights_to_fp16
(l)
michelangelo/models/conditional_encoders/encoder_factory.py:484
Method_forward
(self, x: torch.Tensor, t: torch.Tensor, context: Optional[torch.Tensor] = None)
michelangelo/models/modules/diffusion_transformer.py:84
Method_forward
(self, x: torch.Tensor)
michelangelo/models/modules/transformer_blocks.py:109
Method_forward
(self, x: torch.Tensor)
michelangelo/models/modules/transformer_vit.py:156
Method_forward
Args: pc (torch.FloatTensor): [B, N, 3] feats (torch.FloatTensor or None): [B, N, C] Returns:
michelangelo/models/tsal/sal_perceiver.py:74
Method_forward
(self, queries: torch.FloatTensor, latents: torch.FloatTensor)
michelangelo/models/tsal/sal_perceiver.py:151
Function_uid_shuffle
Shuffle the data in the stream. This uses a buffer of size `bufsize`. Shuffling at startup is less random; this is traded off against yie
michelangelo/data/transforms.py:44
Methodadd_lines
(self, beginning, ending, shading={}, obj=None, **kwargs)
michelangelo/utils/visualizers/pythreejs_viewer.py:307
Methodadd_mesh
(self, v, f, c=None, uv=None, n=None, shading={}, texture_data=None, **kwargs)
michelangelo/utils/visualizers/pythreejs_viewer.py:207
Methodadd_points
(self, points, c=None, shading={}, obj=None, **kwargs)
michelangelo/utils/visualizers/pythreejs_viewer.py:343
Methodadd_text
(self, text, shading={}, **kwargs)
michelangelo/utils/visualizers/pythreejs_viewer.py:447
Functionall_gather_batch
Performs all_gather operation on the provided tensors.
michelangelo/utils/misc.py:80
Methodbackward
(ctx, *output_grads)
michelangelo/models/modules/checkpoint.py:52
Functionbuild_transforms
(cfg)
michelangelo/data/transforms.py:392
Methodclip
(self)
michelangelo/models/conditional_encoders/encoder_factory.py:246
Methodclip
(self)
michelangelo/models/conditional_encoders/encoder_factory.py:338
Functioncollation_fn
Args: samples (list[dict]): combine_tensors: combine_scalars: Returns:
michelangelo/data/utils.py:21
Methodconfigure_optimizers
(self)
michelangelo/models/tsal/asl_pl_module.py:84
Methodconfigure_optimizers
(self)
michelangelo/models/tsal/sal_pl_module.py:73
Methodconfigure_optimizers
(self)
michelangelo/models/asl_diffusion/clip_asl_diffuser_pl_module.py:130
Methodconfigure_optimizers
(self)
michelangelo/models/asl_diffusion/asl_diffuser_pl_module.py:159
Methodconvert_embedding
(self, z)
michelangelo/models/conditional_encoders/encoder_factory.py:525
Methodconvert_weights
Convert applicable model parameters to fp16
michelangelo/models/conditional_encoders/encoder_factory.py:481
Methoddecode
(self, z_q, *args, **kwargs)
michelangelo/models/tsal/tsal_base.py:41
Methoddecode
(self, z_q, *args, **kwargs)
michelangelo/models/tsal/tsal_base.py:76
Methoddecode
(self, *args, **kwargs)
michelangelo/models/tsal/tsal_base.py:114
Functiondisabled_train
Overwrite model.train with this function to make sure train/eval mode does not change anymore.
michelangelo/models/asl_diffusion/clip_asl_diffuser_pl_module.py:27
Functiondisabled_train
Overwrite model.train with this function to make sure train/eval mode does not change anymore.
michelangelo/models/asl_diffusion/asl_diffuser_pl_module.py:30
Methodempty_img_cond
(self, cond)
michelangelo/models/asl_diffusion/asl_diffuser_pl_module.py:219
Methodempty_surface_cond
(self, cond)
michelangelo/models/asl_diffusion/asl_diffuser_pl_module.py:224
Methodempty_text_cond
(self, cond)
michelangelo/models/asl_diffusion/asl_diffuser_pl_module.py:214
Methodencode
(self, surface, *args, **kwargs)
michelangelo/models/tsal/tsal_base.py:38
Methodencode
(self, surface, *args, **kwargs)
michelangelo/models/tsal/tsal_base.py:73
Methodencode
(self, *args, **kwargs)
michelangelo/models/tsal/tsal_base.py:111
Methodencode
(self, surface: torch.FloatTensor, sample_posterior=True)
michelangelo/models/tsal/asl_pl_module.py:135
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