Performs a single optimization step. Arguments: closure (callable, optional): A closure that reevaluates the model

removes reparameterization and backward hook (does not remove forward hook)

Writes to a json file.

RaiseArgTupleInvalid */

Checks if required files exist before going deeper. Args: required_files (str or list): string file name(s).

CIntToPy */

PyObjectCall2Args */

Downloads and extracts dataset. Args: dataset_dir (str): dataset directory. dataset_url (str): url to download datase

Reads json file from a path.

ObjectToMemviewSlice */

Performs a single optimization step. Arguments: closure (callable, optional): A closure that reevaluates the model

Applies reparametrization to module's `name` parameter and modifies instance attributes as appropriate. `hook_child` adds reparameter

return current time in format of 2000-01-01 12:01:01

Returns the number of training person identities. Each tuple in data contains (img_path(s), pid, camid, dsetid).

normalize a 2d matrix along axis 1

Creates dirname if it is missing.

ObjectToMemviewSlice */

None */

GetBuiltinName */

Returns the number of training cameras. Each tuple in data contains (img_path(s), pid, camid, dsetid).

:param folder_dir: :return: [(path, identiti_id, camera_id)]

CIntToPy */

ExtTypeTest */

MemviewSliceIsContig */

compute similarity matrix of label1 and label2 :param label1: torch.Tensor, [m] :param label2: torch.Tensor, [n] :return: torch.Tensor, [m, n

Loads the schedulers state. Arguments: state_dict (dict): scheduler state. Should be an object returned from a ca