renaming the folders

def pretrain_ict_model_provider():

    args = get_args()

    #args.only_context_model = False

    #args.only_query_model = False

    #model = biencoder_model_provider()

    model = biencoder_model_provider(

                only_context_model=False,

                only_query_model=False,

                biencoder_shared_query_context_model=\

                args.biencoder_shared_query_context_model)

    return model

def get_group_world_size_rank():

from megatron import get_args, print_rank_0

from megatron.checkpointing import load_biencoder_checkpoint

from megatron.data.orqa_wiki_dataset import get_open_retrieval_wiki_dataset

from tasks.orqa.natural_questions.nq import get_nq_dataset

from tasks.orqa.natural_questions.nq import get_one_epoch_nq_dataloader

from tasks.orqa.natural_questions.nq import process_nq_batch

from tasks.orqa.natural_questions.qa_utils import calculate_matches

from megatron.data.realm_index import OpenRetreivalDataStore, FaissMIPSIndex

from megatron.model.biencoder_model import get_model_provider

from megatron.training import get_model

from tasks.orqa.unsupervised.nq import get_nq_dataset

from tasks.orqa.unsupervised.nq import get_one_epoch_nq_dataloader

from tasks.orqa.unsupervised.nq import process_nq_batch

from tasks.orqa.unsupervised.qa_utils import calculate_matches

class ORQAEvaluator(object):

    def __init__(self):

from typing import Tuple, List, Dict

import regex as re

from tasks.orqa.natural_questions.tokenizers import SimpleTokenizer

from tasks.orqa.unsupervised.tokenizers import SimpleTokenizer

logger = logging.getLogger(__name__)