changed to input ids

ref_seg_ger.py

@@ -72,6 +72,9 @@ _FEATURES = datasets.Features(
         #"original_image": datasets.features.Image(),
         "labels": datasets.Sequence(datasets.features.ClassLabel(
             names=list(chain.from_iterable([['B-' + x, 'I-' + x] for x in _LABELS])) + ['O']
+        )),
+        "labels_ref": datasets.Sequence(datasets.features.ClassLabel(
+            names=['B-ref', 'I-ref', 'O-ref']
         ))
         # These are the features of your dataset like images, labels ...
     }
@@ -212,6 +215,7 @@ class RefSeg(datasets.GeneratorBasedBuilder):
             df = pd.read_csv(f, keep_default_na=False)
             input_ids = []
             labels = []
+            refs = []
             for i, row in df.iterrows():
 
                 #tokenized_input = row['token'].split(' ')
@@ -220,6 +224,8 @@ class RefSeg(datasets.GeneratorBasedBuilder):
                     continue
                 tokenized_input, offsets = zip(*tkn)
                 tokenized_input = list(tokenized_input)
+                for t in range(len(tokenized_input)):
+                    refs.append(row['ref'] + '-ref')
                 if len(tokenized_input) > 1:
                     if row['tag'] == 'B':
                         if tokenized_input[0] == '':
@@ -254,15 +260,18 @@ class RefSeg(datasets.GeneratorBasedBuilder):
 
             clean_input_ids = []
             clean_labels = []
+            clean_refs = []
             for i, input in enumerate(input_ids):
                 if input != '':
                     clean_input_ids.append(input)
                     clean_labels.append(labels[i])
+                    clean_refs.append(refs[i])
             n_chunks = int(len(clean_input_ids)/self.CHUNK_SIZE) if len(clean_input_ids)%self.CHUNK_SIZE == 0 \
                 else int(len(clean_input_ids)/self.CHUNK_SIZE) + 1
             split_ids = np.array_split(clean_input_ids, n_chunks)
             split_labels = np.array_split(clean_labels, n_chunks)
-            for chunk_ids, chunk_labels in zip(split_ids, split_labels):
+            split_refs = np.array_split(clean_refs, n_chunks)
+            for chunk_ids, chunk_labels, chunk_refs in zip(split_ids, split_labels, split_refs):
 
             #for chunk_id, index in enumerate(range(0, len(clean_input_ids), self.CHUNK_SIZE)):
                 #split_ids = clean_input_ids[index:max(len(clean_input_ids), index + self.CHUNK_SIZE)]
@@ -294,6 +303,7 @@ class RefSeg(datasets.GeneratorBasedBuilder):
                     # "fonts": split_fonts,
                     #"image": image,
                     #"original_image": original_image,
-                    "labels": chunk_labels
+                    "labels": chunk_labels,
+                    "labels_ref": chunk_refs
                 }
                 key += 1