Merge pull request #701 from QData/oct-bug-fixes

Fix bugs with t5

Author: jxmorris12

textattack/datasets/helpers/ted_multi.py

@@ -35,12 +35,19 @@ def __init__(self, source_lang="en", target_lang="de", split="test", shuffle=Fal
         self.source_lang = source_lang
         self.target_lang = target_lang
         self.shuffled = shuffle
+        self.label_map = None
+        self.output_scale_factor = None
+        self.label_names = None
+        # self.input_columns = ("Source",)
+        # self.output_column = "Translation"
+
         if shuffle:
             self._dataset.shuffle()
 
-    def _format_raw_example(self, raw_example):
-        translations = np.array(raw_example["translation"])
-        languages = np.array(raw_example["language"])
+    def _format_as_dict(self, raw_example):
+        example = raw_example["translations"]
+        translations = np.array(example["translation"])
+        languages = np.array(example["language"])
         source = translations[languages == self.source_lang][0]
         target = translations[languages == self.target_lang][0]
         source_dict = collections.OrderedDict([("Source", source)])

textattack/goal_functions/text/text_to_text_goal_function.py

@@ -4,6 +4,7 @@
 -------------------------------------------------------
 """
 
+import numpy as np
 
 from textattack.goal_function_results import TextToTextGoalFunctionResult
 from textattack.goal_functions import GoalFunction
@@ -22,7 +23,10 @@ def _goal_function_result_type(self):
 
     def _process_model_outputs(self, _, outputs):
         """Processes and validates a list of model outputs."""
-        return outputs.flatten()
+        if isinstance(outputs, np.ndarray):
+            return outputs.flatten()
+        else:
+            return outputs
 
     def _get_displayed_output(self, raw_output):
         return raw_output

textattack/models/tokenizers/t5_tokenizer.py

@@ -38,7 +38,7 @@ def __init__(self, mode="english_to_german", max_length=64):
         self.tokenizer = transformers.AutoTokenizer.from_pretrained(
             "t5-base", use_fast=True
         )
-        self.max_length = max_length
+        self.model_max_length = max_length
 
     def __call__(self, text, *args, **kwargs):
         """
@@ -55,7 +55,7 @@ def __call__(self, text, *args, **kwargs):
         else:
             for i in range(len(text)):
                 text[i] = self.tokenization_prefix + text[i]
-        return self.tokenizer(text, *args, max_length=self.max_length, **kwargs)
+        return self.tokenizer(text, *args, **kwargs)
 
     def decode(self, ids):
         """Converts IDs (typically generated by the model) back to a string."""