renaming the folders

pretrain_ict.py

@@ -33,15 +33,13 @@ from megatron.utils import average_losses_across_data_parallel_group
 
 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)
+                args.biencoder_shared_query_context_model)
+
     return model
 
 def get_group_world_size_rank():

tasks/orqa/evaluate_utils.py

@@ -18,13 +18,14 @@ import torch
 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):

tasks/orqa/natural_questions/qa_utils.py → tasks/orqa/unsupervised/qa_utils.py

@@ -22,7 +22,7 @@ from multiprocessing import Pool as ProcessPool
 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__)