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Functions571 in github.com/openai/shap-e

⨍ Functions 571◇ Types & classes 112
Method__call__
( self, batch_size: int, images: Optional[Iterable[Optional[ImageType]]] = None,
shap_e/models/generation/pretrained_clip.py:237
Method__call__
(self, x)
shap_e/models/nn/ops.py:40
Method__contains__
(self, key)
shap_e/util/collections.py:28
Method__eq__
(self, other)
shap_e/util/collections.py:113
Method__getitem__
(self, key)
shap_e/util/collections.py:50
Method__init__
(self, sigma_data: float = 0.5)
shap_e/diffusion/k_diffusion.py:32
Method__init__
(self, model, diffusion)
shap_e/diffusion/k_diffusion.py:80
Method__init__
( self, *, betas: Sequence[float], model_mean_type: str, model_var_typ
shap_e/diffusion/gaussian_diffusion.py:192
Method__init__
(self, use_timesteps: Iterable[int], **kwargs)
shap_e/diffusion/gaussian_diffusion.py:1012
Method__init__
:param bbox_min: the left/bottommost corner of the bounding box :param bbox_max: the other corner of the bounding box :param
shap_e/models/volume.py:94
Method__init__
( self, *, radius: float, center: ArrayType = (0.0, 0.0, 0.0), min_dis
shap_e/models/volume.py:227
Method__init__
( self, sdf: Model, tf: Model, volume: Volume, grid_size: int,
shap_e/models/stf/renderer.py:46
Method__init__
(self, initial_bias: float = -0.1, **kwargs)
shap_e/models/stf/mlp.py:184
Method__init__
( self, n_channels: int = 3, **kwargs, )
shap_e/models/stf/mlp.py:199
Method__init__
( self, n_samples: int, void_model: NeRFModel, foreground_model: NeRFModel,
shap_e/models/nerf/renderer.py:205
Method__init__
:param depth_mode: linear samples ts linearly in depth. harmonic ensures closer points are sampled more densely.
shap_e/models/nerf/ray.py:416
Method__init__
:param volume_range: the range in which a ray intersects the given volume. :param raw: dictionary of raw outputs from the NeRF models
shap_e/models/nerf/ray.py:465
Method__init__
( self, background: ArrayType, trainable: bool = False, channel_scale: float =
shap_e/models/nerf/model.py:47
Method__init__
( self, device: torch.device, *, input_channels: int = 3, output_chann
shap_e/models/generation/pooled_mlp.py:8
Method__init__
(self, *, device: torch.device, wrapped: nn.Module, n_ctx: int, d_latent: int)
shap_e/models/generation/latent_diffusion.py:8
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, n_ctx: int,
shap_e/models/generation/transformer.py:20
Method__init__
(self, *, device: torch.device, dtype: torch.dtype, heads: int, n_ctx: int)
shap_e/models/generation/transformer.py:62
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, n_ctx: int,
shap_e/models/generation/transformer.py:84
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, n_ctx: int,
shap_e/models/generation/transformer.py:115
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, input_channels: i
shap_e/models/generation/transformer.py:152
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, n_ctx: int = 1024
shap_e/models/generation/transformer.py:240
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, n_ctx: int = 1024
shap_e/models/generation/transformer.py:302
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, cond_input_channe
shap_e/models/generation/transformer.py:372
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, n_ctx: int = 4096
shap_e/models/generation/transformer.py:426
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, n_ctx: int,
shap_e/models/generation/perceiver.py:14
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, heads: int, n_ctx: int, n_data: int )
shap_e/models/generation/perceiver.py:51
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, n_ctx: int,
shap_e/models/generation/perceiver.py:78
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, input_channels: i
shap_e/models/generation/perceiver.py:162
Method__init__
( self, device: torch.device, dtype: Optional[torch.dtype] = torch.float32, en
shap_e/models/generation/pretrained_clip.py:19
Method__init__
(self, device: torch.device, **kwargs)
shap_e/models/generation/pretrained_clip.py:220
Method__init__
( self, sdf: Optional[Model], tf: Optional[Model], nerstf: Optional[Model],
shap_e/models/nerstf/renderer.py:20
Method__init__
( self, initial_bias: float = -0.1, sdf_activation="tanh", density_activation=
shap_e/models/nerstf/mlp.py:12
Method__init__
( self, posemb_version: Optional[str], n_channels: int, out_features: int,
shap_e/models/nn/encoding.py:61
Method__init__
( self, posemb_version: Optional[str], n_channels: int, out_features: int,
shap_e/models/nn/encoding.py:117
Method__init__
(self, *args, **kwargs)
shap_e/models/nn/meta.py:103
Method__init__
(self, w0=30.0)
shap_e/models/nn/ops.py:37
Method__init__
( self, n_in, n_out, bias: bool = True, meta_scale: bool = True,
shap_e/models/nn/ops.py:115
Method__init__
( self, d_input: int, d_hidden: List[int], d_output: int, act_name: st
shap_e/models/nn/ops.py:261
Method__init__
( self, norm_shape: Union[int, Tuple[int]], eps: float = 1e-5, elementwise_affine: bool = True )
shap_e/models/nn/ops.py:312
Method__init__
( self, *, radius: float, n_point: int, n_sample: int, d_input
shap_e/models/nn/ops.py:329
Method__init__
(self, npoint, radius_list, nsample_list, in_channel, mlp_list)
shap_e/models/nn/pointnet2_utils.py:259
Method__init__
(self, in_channel, mlp)
shap_e/models/nn/pointnet2_utils.py:319
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, param_shapes: Dic
shap_e/models/transmitter/multiview_encoder.py:22
Method__init__
( self, *, device: torch.device, param_shapes: Dict[str, Tuple[int]],
shap_e/models/transmitter/base.py:33
Method__init__
( self, *, device: torch.device, param_shapes: Dict[str, Tuple[int]],
shap_e/models/transmitter/base.py:83
Method__init__
(self, encoder: Encoder, renderer: Renderer)
shap_e/models/transmitter/base.py:132
Method__init__
( self, *, device: torch.device, param_shapes: Dict[str, Tuple[int]],
shap_e/models/transmitter/base.py:146
Method__init__
( self, *, latent_ctx: int, **kwargs, )
shap_e/models/transmitter/base.py:177
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, param_shapes: Dic
shap_e/models/transmitter/pc_encoder.py:27
Method__init__
( self, *, cross_attention_dataset: str = "pcl", fps_method: str = "fps",
shap_e/models/transmitter/pc_encoder.py:202
Method__init__
( self, *, device: torch.device, param_shapes: Dict[str, Tuple[int]],
shap_e/models/transmitter/params_proj.py:34
Method__init__
( self, *, device: torch.device, param_shapes: Dict[str, Tuple[int]],
shap_e/models/transmitter/params_proj.py:64
Method__init__
( self, *, device: torch.device, vectors: int, channels: int,
shap_e/models/transmitter/params_proj.py:93
Method__init__
( self, *, device: torch.device, param_shapes: Dict[str, Tuple[int]],
shap_e/models/transmitter/params_proj.py:139
Method__init__
(self, *, device: torch.device, d_latent: int)
shap_e/models/transmitter/bottleneck.py:13
Method__init__
(self, *, coeff1: float = 1.0, device: torch.device)
shap_e/models/transmitter/bottleneck.py:48
Method__init__
(self, *, device: torch.device, d_latent: int, noise_scale: float)
shap_e/models/transmitter/bottleneck.py:69
Method__init__
( self, *, device: torch.device, d_latent: int, diffusion: Dict[str, A
shap_e/models/transmitter/bottleneck.py:82
Method__init__
( self, *, device: torch.device, dtype: torch.dtype, param_shapes: Dic
shap_e/models/transmitter/channels_encoder.py:35
Method__init__
( self, *, input_channels: int = 6, **kwargs, )
shap_e/models/transmitter/channels_encoder.py:267
Method__init__
( self, *, cross_attention_dataset: str = "pcl", fps_method: str = "fps",
shap_e/models/transmitter/channels_encoder.py:292
Method__init__
(self, *args, **kwargs)
shap_e/util/collections.py:18
Method__init__
(self, channels: Dict[str, np.ndarray], cameras: List[Camera])
shap_e/rendering/view_data.py:191
Method__init__
(self, f_obj: BinaryIO)
shap_e/rendering/blender/view_data.py:17
Method__iter__
(self)
shap_e/models/transmitter/channels_encoder.py:226
Method__next__
(self)
shap_e/models/transmitter/channels_encoder.py:230
Method__post_init__
(self)
shap_e/models/volume.py:17
Method__post_init__
(self)
shap_e/models/nn/camera.py:51
Method_apply
(key, val)
shap_e/util/collections.py:104
Function_avg
(_key: str, loss_list: List[torch.Tensor])
shap_e/models/renderer.py:232
Function_black_bg
(h: int, w: int)
shap_e/util/image_util.py:119
Function_checker_bg
(h: int, w: int)
shap_e/util/image_util.py:127
Method_combine_fn
( prev_val: Optional[torch.Tensor], cur_val: Optional[torch.Tensor], *,
shap_e/models/nerf/ray.py:183
Method_dump
(val)
shap_e/util/collections.py:80
Function_gray_bg
(h: int, w: int)
shap_e/util/image_util.py:123
Method_integrate
(key: str, samples: torch.Tensor, weights: torch.Tensor)
shap_e/models/nerf/ray.py:341
Method_is_tensor
(_key: str, value: Any)
shap_e/models/nerf/ray.py:285
Method_iterator
(module)
shap_e/models/nn/meta.py:163
Method_mask_fn
(_key: str, tensor: torch.Tensor)
shap_e/models/nerf/ray.py:282
Method_merge_results
:param a: [..., n_a, ...]. The other dictionary containing the b's may contain extra tensors from earlier calculations, so a can
shap_e/models/nerf/ray.py:381
Function_noise_bg
(h: int, w: int)
shap_e/util/image_util.py:139
Method_query
( self, query: Query, params: AttrDict[str, torch.Tensor], options: AttrDict[s
shap_e/models/nerstf/renderer.py:63
Method_reduce_loss
(_key: str, loss: torch.Tensor)
shap_e/models/nerf/ray.py:371
Method_run_mlp
:return: the final and directionless activations at the given query
shap_e/models/stf/mlp.py:125
Methodall_keys
( self, leaves_only: bool = False, parent: Optional[str] = None, )
shap_e/util/collections.py:61
Functionappend_tensor
(val_list: Optional[List[torch.Tensor]], output: Optional[torch.Tensor])
shap_e/models/renderer.py:166
Methodbackward
(ctx, *output_grads)
shap_e/models/nn/checkpoint.py:44
Methodbackward
(ctx, *all_output_grads)
shap_e/models/nn/checkpoint.py:87
Methodbackward
( ctx, _collides_grad, ray_dists_grad, _tri_indices_grad, barycentric_grad, normals_grad )
shap_e/rendering/raycast/cast.py:111
Functionbatch_meta_parameters
(net, batch_size)
shap_e/models/nn/meta.py:221
Methodbottleneck_to_params
( self, vector: torch.Tensor, options: Optional[AttrDict] = None )
shap_e/models/transmitter/base.py:122
Methodbottleneck_to_params
( self, vector: torch.Tensor, options: Optional[AttrDict] = None )
shap_e/models/transmitter/base.py:169
Methodbottleneck_to_params
( self, vector: torch.Tensor, options: Optional[AttrDict] = None )
shap_e/models/transmitter/base.py:192
Methodcached_model_kwargs
(self, batch_size: int, model_kwargs: Dict[str, Any])
shap_e/models/generation/transformer.py:330
Methodcached_model_kwargs
(self, batch_size: int, model_kwargs: Dict[str, Any])
shap_e/models/generation/transformer.py:449
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