Given something that might be a URL (or might be a local path), determine which. If it's a URL, download the file and cache it, and retur

Predict the answers to questions in a data split. :param eval_tuple: The data tuple to be evaluated. :param dump: The path of

Evaluate all data in data_tuple.

Evaluate all data in data_tuple.

r""" Loads a configuration file from a json file. Args: path_json_file (`str`): The path to the json file

Given a task returns its corresponding adapter layer. Args: task: Input task name. Returns: Adapter layer corr

Given a task returns its corresponding adapter layer. Args: task: Input task name. Returns: Adapter layer corr

Concatenates the task embedding with the embedding for the layer id and returns the final joint embedding.

Concatenates the task embedding with the embedding for the layer id and returns the final joint embedding.

Get the index (e.g. 2) from the prediction (e.g. 'C')

Load a CLIP model Parameters ---------- name : str A model name listed by `clip.available_models()`, or the path to a model check

Load model weights from LXMERT pre-training. The answers in the fine-tuned QA task (indicated by label2ans) would also be properly in

Load object features from tsv file. :param fname: The path to the tsv file. :param topk: Only load features for top K images (lines) in the t

Predict the answers to questions in a data split. :param eval_tuple: The data tuple to be evaluated. :param dump: The path of

Given a list of sources, each is a conversation list. This transform: 1. Add signal '### ' at the beginning each sentence, with end signal '\

Prints the number of trainable parameters in the model.

tensors can be an ImageList, a torch.Tensor or an iterable of Tensors. It can't be a numpy array. When tensors is an iterable of Tensors,