init

experiments/model_finetuning_ner.py

@@ -102,30 +102,30 @@ def main(
 
     def tokenize_and_align_labels(examples):
         tokens = [[preprocess(model, w) for w in t] for t in examples["text_tokenized"]]
-        if tokenizer.is_fast:
-            tokenized_inputs = tokenizer(
-                tokens,
-                truncation=True,
-                is_split_into_words=True,
-                padding="max_length",
-                max_length=128)
-            all_labels = examples["gold_label_sequence"]
-            new_labels = []
-            for ind, labels in enumerate(all_labels):
-                word_ids = tokenized_inputs.word_ids(ind)
-                new_labels.append(align_labels_with_tokens(labels, word_ids))
-            tokenized_inputs["labels"] = new_labels
-            return tokenized_inputs
-        else:
-            tokenized_inputs = tokenizer(
-                tokens, )
-            all_labels = examples["gold_label_sequence"]
-            new_labels = []
-            for ind, labels in enumerate(all_labels):
-                word_ids = tokenized_inputs.word_ids(ind)
-                new_labels.append(align_labels_with_tokens(labels, word_ids))
-            tokenized_inputs["labels"] = new_labels
-            return tokenized_inputs
+        # if tokenizer.is_fast:
+        tokenized_inputs = tokenizer(
+            tokens,
+            truncation=True,
+            is_split_into_words=True,
+            padding="max_length",
+            max_length=128)
+        all_labels = examples["gold_label_sequence"]
+        new_labels = []
+        for ind, labels in enumerate(all_labels):
+            word_ids = tokenized_inputs.word_ids(ind)
+            new_labels.append(align_labels_with_tokens(labels, word_ids))
+        tokenized_inputs["labels"] = new_labels
+        return tokenized_inputs
+        # else:
+        #     tokenized_inputs = tokenizer(
+        #         tokens)
+        #     all_labels = examples["gold_label_sequence"]
+        #     new_labels = []
+        #     for ind, labels in enumerate(all_labels):
+        #         word_ids = tokenized_inputs.word_ids(ind)
+        #         new_labels.append(align_labels_with_tokens(labels, word_ids))
+        #     tokenized_inputs["labels"] = new_labels
+        #     return tokenized_inputs