Handle sequences longer than max_seq_size

core/poldeepner.py

 import codecs
 import os
 import torch
-import tqdm
 from torch.utils.data.dataloader import DataLoader
 
-from core.model.xlmr_for_token_classification import XLMRForTokenClassification
-from core.utils.data_utils import InputExample, convert_examples_to_features, create_dataset, read_params, \
-    wrap_annotations, align_tokens_with_text
-from core.utils.tokenization import TokenizerSpaces
+from poldeepner2.model.xlmr_for_token_classification import XLMRForTokenClassification
+from poldeepner2.pipeline.tokenization import TokenizerSpaces
+from poldeepner2.utils.data_utils import read_params, InputExample, create_dataset, wrap_annotations, \
+    align_tokens_with_text
+from poldeepner2.utils.sequences import convert_examples_to_features
 
 
 class PolDeepNer2: