IsLittleEndian */

CIntFromPy */

Args: in_channels (int): number of input channels. Default: 6. (p + rgb) embed_dim (int): embedding dimension

Separable depthwise convolution with aggregation . Args: channels (List[int]): [description] conv_args ([type], optio

CodeObjectCache */

Group keys based on common prefixes. A prefix is the string up to the final "." in each key. Args: keys (list[str]): list of para

Group keys based on common prefixes. A prefix is the string up to the final "." in each key. Args: keys (list[str]): list of para

Format a group of parameter name suffixes into a loggable string. Args: group (list[str]): list of parameter name suffixes. Retur

Format a group of parameter name suffixes into a loggable string. Args: group (list[str]): list of parameter name suffixes. Retur

Lazily initialize the dataset. This is necessary to init the Tensorflow dataset pipeline in the (dataloader) process that will be us

* Called during search to add an element matching the criteria. * @return true if the search should be continued, false if the result

* Called during search to add an element matching the criteria. * @return true if the search should be continued, false if the results are * suf

* Called during search to add an element matching the criteria. * @return true if the search should be continued, false if the results are * suf

* Builds the index */

* Builds the index */

Returns list of utf-8 byte and a corresponding list of unicode strings. The reversible bpe codes work on unicode strings. This means you

Get the number of samples per-class.

* Create a tree node that subdivides the list of vecs from vind[first] * to vind[last]. The routine is called recursively on each sublist. *

* Create a tree node that subdivides the list of vecs from vind[first] * to vind[last]. The routine is called recursively on each sublist. *

* Create a tree node that subdivides the list of vecs from vind[first] * to vind[last]. The routine is called recursively on each sublist. *

opperations

pc_xyz: 3D coordinates of point clouds pc_sem_ins: semantic or instance labels plot_colors: custom color list

Input: xyz: pointcloud data, [B, N, 3] npoint: number of samples Return: centroids: sampled pointcloud index, [B, npo

Get the Shape IoU shape IoU: the mean part iou for each shape Args: pred (_type_): _description_ target (_type_): _description

Initialize and get a logger by name. If the logger has not been initialized, this method will initialize the logger by adding one or two handl

Initialize and get a logger by name. If the logger has not been initialized, this method will initialize the logger by adding one or two handl

Get a logging-friendly message to report parameter names (keys) that are in the model but not found in a checkpoint. Args: keys (

Return set of symbol pairs in a word. Word is represented as tuple of symbols (symbols being variable-length strings).

Get a logging-friendly message to report parameter names (keys) that are in the checkpoint but not found in the model. Args: keys

Args: points [point]: (B, N, C) knn_idx [k-Nearest Neighbor Index]: (B, N, k) Return: knn_points [k-Nearest Neighboring

Loads a previous index from a binary file. * IMPORTANT NOTE: The set of data points is NOT stored in the file, so the index object must be const

Loads a previous index from a binary file. * IMPORTANT NOTE: The set of data points is NOT stored in the file, so the * index object must be c

Loads a previous index from a binary file. * IMPORTANT NOTE: The set of data points is NOT stored in the file, so the * index object must be c