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Functions318 in github.com/NeuralCarver/Michelangelo

⨍ Functions 318◇ Types & classes 68
Methodencode
(self, *args, **kwargs)
michelangelo/models/conditional_encoders/encoder_factory.py:19
Methodencode
(self, text)
michelangelo/models/conditional_encoders/encoder_factory.py:102
Methodencode
(self, text)
michelangelo/models/conditional_encoders/encoder_factory.py:175
Methodencode
(self, image)
michelangelo/models/conditional_encoders/encoder_factory.py:294
Methodencode
(self, image)
michelangelo/models/conditional_encoders/encoder_factory.py:375
Methodencode
(self, image)
michelangelo/models/conditional_encoders/encoder_factory.py:560
Methodencode_image
(self, img)
michelangelo/models/asl_diffusion/asl_diffuser_pl_module.py:204
Methodencode_surface
(self, surface)
michelangelo/models/asl_diffusion/asl_diffuser_pl_module.py:209
Methodencode_text
(self, text)
michelangelo/models/asl_diffusion/asl_diffuser_pl_module.py:192
Functionextract_tar
(tar_path, tar_cache_folder)
michelangelo/utils/io.py:40
Methodforward
(self, img)
michelangelo/data/transforms.py:329
Methodforward
(self, x, timestep)
michelangelo/models/modules/diffusion_transformer.py:30
Methodforward
(self, x: torch.Tensor, t: torch.Tensor, context: Optional[torch.Tensor] = None)
michelangelo/models/modules/diffusion_transformer.py:81
Methodforward
(self, x: torch.Tensor, t: torch.Tensor, context: Optional[torch.Tensor] = None)
michelangelo/models/modules/diffusion_transformer.py:129
Methodforward
(self, x: torch.Tensor)
michelangelo/models/modules/diffusion_transformer.py:200
Methodforward
(ctx, run_function, length, *args)
michelangelo/models/modules/checkpoint.py:41
Methodforward
(self, x)
michelangelo/models/modules/transformer_blocks.py:41
Methodforward
(self, qkv)
michelangelo/models/modules/transformer_blocks.py:57
Methodforward
(self, x: torch.Tensor)
michelangelo/models/modules/transformer_blocks.py:114
Methodforward
(self, x, data)
michelangelo/models/modules/transformer_blocks.py:147
Methodforward
(self, q, kv)
michelangelo/models/modules/transformer_blocks.py:166
Methodforward
(self, x: torch.Tensor, data: torch.Tensor)
michelangelo/models/modules/transformer_blocks.py:223
Methodforward
(self, x)
michelangelo/models/modules/transformer_blocks.py:243
Methodforward
(self, x: torch.Tensor)
michelangelo/models/modules/transformer_blocks.py:283
Methodforward
Forward process. Args: x: tensor of shape [..., dim] Returns: embedding: an embedding of `x` of shape [...,
michelangelo/models/modules/embedder.py:87
Methodforward
Args: x (torch.FloatTensor): [..., c] Returns: x (torch.FloatTensor): [..., d]
michelangelo/models/modules/embedder.py:119
Methodforward
(self, x)
michelangelo/models/modules/embedder.py:145
Methodforward
(self, x)
michelangelo/models/modules/transformer_vit.py:101
Methodforward
(self, qkv)
michelangelo/models/modules/transformer_vit.py:116
Methodforward
(self, x: torch.Tensor)
michelangelo/models/modules/transformer_vit.py:161
Methodforward
(self, x, data)
michelangelo/models/modules/transformer_vit.py:189
Methodforward
(self, q, kv)
michelangelo/models/modules/transformer_vit.py:205
Methodforward
(self, x: torch.Tensor, data: torch.Tensor)
michelangelo/models/modules/transformer_vit.py:250
Methodforward
(self, x)
michelangelo/models/modules/transformer_vit.py:267
Methodforward
(self, x: torch.Tensor)
michelangelo/models/modules/transformer_vit.py:305
Methodforward
Args: posteriors (DiagonalGaussianDistribution or torch.distributions.Normal): logits (torch.FloatTensor): [B, 2*N],
michelangelo/models/tsal/loss.py:26
Methodforward
Args: posteriors (DiagonalGaussianDistribution or torch.distributions.Normal): logits (torch.FloatTensor): [B, 2*N],
michelangelo/models/tsal/loss.py:121
Methodforward
(self, shape_embed: torch.FloatTensor, text_embed: torch.FloatTensor,
michelangelo/models/tsal/loss.py:211
Methodforward
Args: surface (torch.FloatTensor): image (torch.FloatTensor): [bs, 3, 224, 224] text (torch.LongTensor):
michelangelo/models/tsal/clip_asl_module.py:71
Methodforward
Args: pc (torch.FloatTensor): [B, N, 3] feats (torch.FloatTensor or None): [B, N, C] Returns: d
michelangelo/models/tsal/sal_perceiver.py:101
Methodforward
(self, queries: torch.FloatTensor, latents: torch.FloatTensor)
michelangelo/models/tsal/sal_perceiver.py:158
Methodforward
Args: pc (torch.FloatTensor): [B, N, 3] feats (torch.FloatTensor or None): [B, N, C] volume_queries (tor
michelangelo/models/tsal/sal_perceiver.py:281
Methodforward
Args: pc (torch.FloatTensor): [B, N, 3] feats (torch.FloatTensor or None): [B, N, C] volume_queries (tor
michelangelo/models/tsal/sal_perceiver.py:398
Methodforward
Args: surface (torch.FloatTensor): image (torch.FloatTensor): text (torch.FloatTensor): volu
michelangelo/models/tsal/asl_pl_module.py:109
Methodforward
(self, pc: torch.FloatTensor, feats: torch.FloatTensor, volume
michelangelo/models/tsal/sal_pl_module.py:99
Methodforward
Args: batch: Returns:
michelangelo/models/asl_diffusion/clip_asl_diffuser_pl_module.py:230
Methodforward
r""" Args: model_input (torch.FloatTensor): [bs, n_data, c] timestep (torch.LongTensor): [bs,] context (to
michelangelo/models/asl_diffusion/asl_udt.py:70
Methodforward
Args: batch: Returns:
michelangelo/models/asl_diffusion/asl_diffuser_pl_module.py:303
Methodforward
(self, images: Iterable[Optional[ImageType]], texts: List[str])
michelangelo/models/conditional_encoders/clip.py:72
Methodforward
(self, batch, key=None)
michelangelo/models/conditional_encoders/encoder_factory.py:29
Methodforward
(self, image, value_range=(-1, 1), zero_embedding_radio=0)
michelangelo/models/conditional_encoders/encoder_factory.py:261
Methodforward
(self, image, value_range=(-1, 1), zero_embedding_radio=0)
michelangelo/models/conditional_encoders/encoder_factory.py:358
Methodforward
(self, image, value_range=(-1, 1), zero_embedding_radio=0)
michelangelo/models/conditional_encoders/encoder_factory.py:530
Functionget_embedder
(embed_type="fourier", num_freqs=-1, input_dim=3, degree=4, num_levels=16, level_dim=2, per_l
michelangelo/models/modules/embedder.py:195
Functionget_obj_from_config
(config)
michelangelo/utils/misc.py:38
Functionget_rank
()
michelangelo/utils/misc.py:68
Functionidentity
(*args, **kwargs)
michelangelo/data/transforms.py:385
Functionimage2mesh
(args, model, guidance_scale=7.5, box_v=1.1, octree_depth=7)
inference.py:113
Functioninit_weights
(m)
michelangelo/models/modules/transformer_vit.py:72
Functionjson_loads
(data)
michelangelo/utils/io.py:25
Methodjupyter_mode
(self)
michelangelo/utils/visualizers/pythreejs_viewer.py:30
Functionkarra_sample
()
michelangelo/models/asl_diffusion/inference_utils.py:79
Methodlatent2mesh
(self, latents, *args, **kwargs)
michelangelo/models/tsal/tsal_base.py:44
Methodlatent2mesh
(self, latents, *args, **kwargs)
michelangelo/models/tsal/tsal_base.py:79
Methodlatent_shape
(self)
michelangelo/models/tsal/asl_pl_module.py:56
Methodlatent_shape
(self)
michelangelo/models/tsal/sal_pl_module.py:45
Functionload_json
(filepath)
michelangelo/utils/io.py:29
Functionmkdir
(path)
michelangelo/utils/io.py:11
Methodmode
(self)
michelangelo/models/modules/distributions.py:10
Methodmode
(self)
michelangelo/models/modules/distributions.py:21
Methodnll
(self, sample, dims=(1, 2, 3))
michelangelo/models/modules/distributions.py:61
Functionnormal_kl
source: https://github.com/openai/guided-diffusion/blob/27c20a8fab9cb472df5d6bdd6c8d11c8f430b924/guided_diffusion/losses.py#L12 Compute the K
michelangelo/models/modules/distributions.py:73
Functionnpy_loads
(data)
michelangelo/utils/io.py:16
Functionnpz_loads
(data)
michelangelo/utils/io.py:21
Methodoffline
(self)
michelangelo/utils/visualizers/pythreejs_viewer.py:33
Methodon_train_batch_start
(self, batch, batch_idx)
michelangelo/models/asl_diffusion/clip_asl_diffuser_pl_module.py:172
Methodon_train_batch_start
(self, batch, batch_idx)
michelangelo/models/asl_diffusion/asl_diffuser_pl_module.py:245
Methodpoint2mesh
(self, *args, **kwargs)
michelangelo/models/tsal/tsal_base.py:47
Methodpoint2mesh
(self, *args, **kwargs)
michelangelo/models/tsal/tsal_base.py:82
Methodpoint2mesh
Args: pc: feats: bounds: octree_depth: num_chunks: Returns:
michelangelo/models/tsal/sal_pl_module.py:182
Methodquery_color
(self, *args, **kwargs)
michelangelo/models/tsal/tsal_base.py:120
Methodquery_geometry
(self, *args, **kwargs)
michelangelo/models/tsal/tsal_base.py:117
Functionreconstruction
(args, model, bounds=(-1.25, -1.25, -1.25, 1.25, 1.25, 1.25), octree_depth=7, num_chunks=10000)
inference.py:80
Methodremove_object
(self, obj_id)
michelangelo/utils/visualizers/pythreejs_viewer.py:387
Methodreset
(self)
michelangelo/utils/visualizers/pythreejs_viewer.py:395
Methodsample
(self)
michelangelo/models/modules/distributions.py:7
Methodsample
(self, batch: Dict[str, Union[torch.FloatTensor, List[str]]], sample_times: int
michelangelo/models/asl_diffusion/clip_asl_diffuser_pl_module.py:324
Methodsample
(self, batch: Dict[str, Union[torch.FloatTensor, List[str]]], sample_times: int
michelangelo/models/asl_diffusion/asl_diffuser_pl_module.py:406
Functionsequential_pos_embed
(num_len, embed_dim)
michelangelo/models/modules/embedder.py:156
Methodset_shape_model_only
(self)
michelangelo/models/tsal/clip_asl_module.py:27
Methodset_shape_model_only
(self)
michelangelo/models/tsal/tsal_base.py:70
Methodset_shape_model_only
(self)
michelangelo/models/tsal/asl_pl_module.py:52
Functiontext2mesh
(args, model, num_samples=2, guidance_scale=7.5, box_v=1.1, octree_depth=7)
inference.py:132
Functiontimestep_embedding
Create sinusoidal timestep embeddings. :param timesteps: a 1-D Tensor of N indices, one per batch element. These may be
michelangelo/models/modules/embedder.py:175
Functionto_html_frame
(content)
michelangelo/utils/visualizers/html_util.py:8
Functionto_image_embed_tag
(image: np.ndarray)
michelangelo/utils/visualizers/html_util.py:35
Functionto_single_row_table
(caption: str, content: str)
michelangelo/utils/visualizers/html_util.py:21
Methodtraining_step
Args: batch (dict): the batch sample, and it contains: - surface (torch.FloatTensor): [bs, n_surface, (3 + input
michelangelo/models/tsal/asl_pl_module.py:157
Methodtraining_step
Args: batch (dict): the batch sample, and it contains: - surface (torch.FloatTensor): [bs, n_surface, (3 + input
michelangelo/models/tsal/sal_pl_module.py:130
Methodtraining_step
Args: batch (dict): the batch sample, and it contains: - surface (torch.FloatTensor): - image (t
michelangelo/models/asl_diffusion/clip_asl_diffuser_pl_module.py:269
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