pyarrow<1.0 (temporary fix for nlp package)

requirements.txt

@@ -9,6 +9,7 @@ nlp
 nltk
 numpy
 pandas>=1.0.1
+pyarrow<1.0
 scikit-learn
 scipy==1.4.1
 sentence_transformers>0.2.6

tests/test_command_line/test_augment.py

@@ -19,7 +19,6 @@ def test_command_line_augmentation(name, command, outfile, sample_output_file):
     import os
 
     # desired_text = open(sample_output_file).read().strip()
-
     # Run command and validate outputs.
     result = run_command_and_get_result(command)
 

textattack/datasets/huggingface_nlp_dataset.py

@@ -14,7 +14,7 @@ def _cb(s):
 
 
 def get_nlp_dataset_columns(dataset):
-    schema = set(dataset.schema.names)
+    schema = set(dataset.column_names)
     if {"premise", "hypothesis", "label"} <= schema:
         input_columns = ("premise", "hypothesis")
         output_column = "label"

textattack/transformations/word_swap_masked_lm.py

@@ -117,7 +117,9 @@ class WordSwapMaskedLM(WordSwap):
         )
         current_inputs = self._encode_text(masked_text.text)
         current_ids = current_inputs["input_ids"].tolist()[0]
-        word_tokens = self._lm_tokenizer.encode(current_text.words[index], add_special_tokens=False)
+        word_tokens = self._lm_tokenizer.encode(
+            current_text.words[index], add_special_tokens=False
+        )
 
         try:
             # Need try-except b/c mask-token located past max_length might be truncated by tokenizer
@@ -126,7 +128,9 @@ class WordSwapMaskedLM(WordSwap):
             return []
 
         # List of indices of tokens that are part of the target word
-        target_ids_pos = list(range(masked_index, min(masked_index + len(word_tokens), self.max_length)))
+        target_ids_pos = list(
+            range(masked_index, min(masked_index + len(word_tokens), self.max_length))
+        )
 
         if not len(target_ids_pos):
             return []