Upload docbank.py

docbank.py

@@ -16,9 +16,10 @@
 
 import csv
 import os
+import itertools
 import numpy as np
 from PIL import Image
-
+from transformers import AutoTokenizer
 import datasets
 
 # TODO: Add BibTeX citation
@@ -56,6 +57,7 @@ _FEATURES = datasets.Features(
     {
         "id": datasets.Value("string"),
         "tokens": datasets.Sequence(datasets.Value("string")),
+        "input_ids": datasets.Sequence(datasets.Value("int64")),
         "bboxes": datasets.Sequence(datasets.Sequence(datasets.Value("int64"))),
         "RGBs": datasets.Sequence(datasets.Sequence(datasets.Value("int64"))),
         "fonts": datasets.Sequence(datasets.Value("string")),
@@ -136,6 +138,7 @@ class Docbank(datasets.GeneratorBasedBuilder):
     ]
 
     DEFAULT_CONFIG_NAME = "small"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+    TOKENIZER = AutoTokenizer.from_pretrained("xlm-roberta-base")
 
     def _info(self):
         # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
@@ -236,10 +239,17 @@ class Docbank(datasets.GeneratorBasedBuilder):
                         labels.append(row[9])
             except:
                 continue
+            tokenized_inputs = self.TOKENIZER(
+                tokens,
+                add_special_tokens=False,
+                return_offsets_mapping=False,
+                return_attention_mask=False,
+            )
 
             yield key, {
                 "id": f_id,
                 "tokens": tokens,
+                'input_ids': list(itertools.chain.from_iterable(tokenized_inputs['input_ids'])),
                 "bboxes": bboxes,
                 "RGBs": rgbs,
                 "fonts": fonts,