Upload docbank.py

docbank.py

@@ -56,7 +56,6 @@ _URLS = {
 _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"))),
@@ -117,6 +116,7 @@ def merge_bbox(bbox_list):
 class Docbank(datasets.GeneratorBasedBuilder):
     """TODO: Short description of my dataset."""
 
+    CHUNK_SIZE = 512
     VERSION = datasets.Version("1.0.0")
 
     # This is an example of a dataset with multiple configurations.
@@ -212,7 +212,8 @@ class Docbank(datasets.GeneratorBasedBuilder):
         # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
         # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
         #print(filepath)
-        for key, f in enumerate(filepath):
+        key = 0
+        for f in filepath:
             #print(f)
             f_id = f['id']
             f_fp_txt = f['filepath_txt']
@@ -231,31 +232,37 @@ class Docbank(datasets.GeneratorBasedBuilder):
                     reader = csv.reader(csvfile, delimiter='\t', quotechar=' ')
                     for row in reader:
                         #if f_id == '121.tar_1606.08710.gz_mutualEnergy_05_77':
-                        #    print(row[0])
-                        tokens.append(row[0])
+                        tokenized_input = self.TOKENIZER(
+                            row[0],
+                            add_special_tokens=False,
+                            return_offsets_mapping=False,
+                            return_attention_mask=False,
+                        )
+                        tokens.append(tokenized_input['input_ids'][0] if len(tokenized_input['input_ids']) == 1 else self.TOKENIZER.unk_token_id)
                         bboxes.append(normalize_bbox(row[1:5], size))
                         rgbs.append(row[5:8])
                         fonts.append(row[8])
                         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,
-                "image": image,
-                "original_image": original_image,
-                "labels": labels
-            }
+
+            for chunk_id, index in enumerate(range(0, len(tokens), self.CHUNK_SIZE)):
+                split_tokens = tokens[index:index + self.CHUNK_SIZE]
+                split_bboxes = bboxes[index:index + self.CHUNK_SIZE]
+                split_rgbs = rgbs[index:index + self.CHUNK_SIZE]
+                split_fonts = fonts[index:index + self.CHUNK_SIZE]
+                split_labels = labels[index:index + self.CHUNK_SIZE]
+
+                yield key, {
+                    "id": f"{f_id}_{chunk_id}",
+                    'input_ids': split_tokens,
+                    "bboxes": split_bboxes,
+                    "RGBs": split_rgbs,
+                    "fonts": split_fonts,
+                    "image": image,
+                    "original_image": original_image,
+                    "labels": split_labels
+                }
+                key += 1