jbrry

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function


import csv
import errno
import os
import re

jbrry

"""Downloads HuggingFace datasets and concatenates them based on split type."""

import datasets

from datasets import concatenate_datasets, load_dataset
from datasets.dataset_dict import DatasetDict

# `config_name`s for the `universal_dependencies` dataset
TBIDS = [
    "af_afribooms",

jbrry

# replace function: https://github.com/huggingface/transformers/blob/f9c16b02e3f5d2ee0a1cadb6f50dc9e3281e2536/src/transformers/data/data_collator.py#L78

def torch_default_data_collator(features: List[InputDataClass]) -> Dict[str, Any]:
    """place this function in transformers/data/data_collator.py"""
    import torch

    if not isinstance(features[0], (dict, BatchEncoding)):
        features = [vars(f) for f in features]
    first = features[0]
    batch = {}