Internal change

PiperOrigin-RevId: 322197751

official/nlp/data/classifier_data_lib.py

@@ -152,10 +152,10 @@ class ColaProcessor(DataProcessor):
     return "COLA"
 
   def _create_examples(self, lines, set_type):
-    """Creates examples for the training and dev sets."""
+    """Creates examples for the training/dev/test sets."""
     examples = []
-    for (i, line) in enumerate(lines):
-      # Only the test set has a header
+    for i, line in enumerate(lines):
+      # Only the test set has a header.
       if set_type == "test" and i == 0:
         continue
       guid = "%s-%s" % (set_type, i)
@@ -173,6 +173,14 @@ class ColaProcessor(DataProcessor):
 class MnliProcessor(DataProcessor):
   """Processor for the MultiNLI data set (GLUE version)."""
 
+  def __init__(self,
+               mnli_type="matched",
+               process_text_fn=tokenization.convert_to_unicode):
+    super(MnliProcessor, self).__init__(process_text_fn)
+    if mnli_type not in ("matched", "mismatched"):
+      raise ValueError("Invalid `mnli_type`: %s" % mnli_type)
+    self.mnli_type = mnli_type
+
   def get_train_examples(self, data_dir):
     """See base class."""
     return self._create_examples(
@@ -180,14 +188,23 @@ class MnliProcessor(DataProcessor):
 
   def get_dev_examples(self, data_dir):
     """See base class."""
-    return self._create_examples(
-        self._read_tsv(os.path.join(data_dir, "dev_matched.tsv")),
-        "dev_matched")
+    if self.mnli_type == "matched":
+      return self._create_examples(
+          self._read_tsv(os.path.join(data_dir, "dev_matched.tsv")),
+          "dev_matched")
+    else:
+      return self._create_examples(
+          self._read_tsv(os.path.join(data_dir, "dev_mismatched.tsv")),
+          "dev_mismatched")
 
   def get_test_examples(self, data_dir):
     """See base class."""
-    return self._create_examples(
-        self._read_tsv(os.path.join(data_dir, "test_matched.tsv")), "test")
+    if self.mnli_type == "matched":
+      return self._create_examples(
+          self._read_tsv(os.path.join(data_dir, "test_matched.tsv")), "test")
+    else:
+      return self._create_examples(
+          self._read_tsv(os.path.join(data_dir, "test_mismatched.tsv")), "test")
 
   def get_labels(self):
     """See base class."""
@@ -199,9 +216,9 @@ class MnliProcessor(DataProcessor):
     return "MNLI"
 
   def _create_examples(self, lines, set_type):
-    """Creates examples for the training and dev sets."""
+    """Creates examples for the training/dev/test sets."""
     examples = []
-    for (i, line) in enumerate(lines):
+    for i, line in enumerate(lines):
       if i == 0:
         continue
       guid = "%s-%s" % (set_type, self.process_text_fn(line[0]))
@@ -244,9 +261,9 @@ class MrpcProcessor(DataProcessor):
     return "MRPC"
 
   def _create_examples(self, lines, set_type):
-    """Creates examples for the training and dev sets."""
+    """Creates examples for the training/dev/test sets."""
     examples = []
-    for (i, line) in enumerate(lines):
+    for i, line in enumerate(lines):
       if i == 0:
         continue
       guid = "%s-%s" % (set_type, i)
@@ -290,7 +307,7 @@ class PawsxProcessor(DataProcessor):
           self._read_tsv(os.path.join(data_dir, language, train_tsv))[1:])
 
     examples = []
-    for (i, line) in enumerate(lines):
+    for i, line in enumerate(lines):
       guid = "train-%d" % i
       text_a = self.process_text_fn(line[1])
       text_b = self.process_text_fn(line[2])
@@ -307,7 +324,7 @@ class PawsxProcessor(DataProcessor):
           self._read_tsv(os.path.join(data_dir, lang, "dev_2k.tsv"))[1:])
 
     examples = []
-    for (i, line) in enumerate(lines):
+    for i, line in enumerate(lines):
       guid = "dev-%d" % i
       text_a = self.process_text_fn(line[1])
       text_b = self.process_text_fn(line[2])
@@ -321,7 +338,7 @@ class PawsxProcessor(DataProcessor):
     examples_by_lang = {k: [] for k in self.supported_languages}
     for lang in self.supported_languages:
       lines = self._read_tsv(os.path.join(data_dir, lang, "test_2k.tsv"))[1:]
-      for (i, line) in enumerate(lines):
+      for i, line in enumerate(lines):
         guid = "test-%d" % i
         text_a = self.process_text_fn(line[1])
         text_b = self.process_text_fn(line[2])
@@ -368,9 +385,9 @@ class QnliProcessor(DataProcessor):
     return "QNLI"
 
   def _create_examples(self, lines, set_type):
-    """Creates examples for the training and dev sets."""
+    """Creates examples for the training/dev/test sets."""
     examples = []
-    for (i, line) in enumerate(lines):
+    for i, line in enumerate(lines):
       if i == 0:
         continue
       guid = "%s-%s" % (set_type, 1)
@@ -415,9 +432,9 @@ class QqpProcessor(DataProcessor):
     return "QQP"
 
   def _create_examples(self, lines, set_type):
-    """Creates examples for the training and dev sets."""
+    """Creates examples for the training/dev/test sets."""
     examples = []
-    for (i, line) in enumerate(lines):
+    for i, line in enumerate(lines):
       if i == 0:
         continue
       guid = "%s-%s" % (set_type, line[0])
@@ -462,7 +479,7 @@ class RteProcessor(DataProcessor):
     return "RTE"
 
   def _create_examples(self, lines, set_type):
-    """Creates examples for the training and dev sets."""
+    """Creates examples for the training/dev/test sets."""
     examples = []
     for i, line in enumerate(lines):
       if i == 0:
@@ -507,9 +524,9 @@ class SstProcessor(DataProcessor):
     return "SST-2"
 
   def _create_examples(self, lines, set_type):
-    """Creates examples for the training and dev sets."""
+    """Creates examples for the training/dev/test sets."""
     examples = []
-    for (i, line) in enumerate(lines):
+    for i, line in enumerate(lines):
       if i == 0:
         continue
       guid = "%s-%s" % (set_type, i)
@@ -558,7 +575,7 @@ class StsBProcessor(DataProcessor):
     return "STS-B"
 
   def _create_examples(self, lines, set_type):
-    """Creates examples for the training and dev sets."""
+    """Creates examples for the training/dev/test sets."""
     examples = []
     for i, line in enumerate(lines):
       if i == 0:
@@ -671,7 +688,7 @@ class TfdsProcessor(DataProcessor):
     return "TFDS_" + self.dataset_name
 
   def _create_examples(self, split_name, set_type):
-    """Creates examples for the training and dev sets."""
+    """Creates examples for the training/dev/test sets."""
     if split_name not in self.dataset:
       raise ValueError("Split {} not available.".format(split_name))
     dataset = self.dataset[split_name].as_numpy_iterator()
@@ -731,7 +748,7 @@ class WnliProcessor(DataProcessor):
     return "WNLI"
 
   def _create_examples(self, lines, set_type):
-    """Creates examples for the training and dev sets."""
+    """Creates examples for the training/dev/test sets."""
     examples = []
     for i, line in enumerate(lines):
       if i == 0:
@@ -777,7 +794,7 @@ class XnliProcessor(DataProcessor):
                            "multinli.train.%s.tsv" % language))[1:])
 
     examples = []
-    for (i, line) in enumerate(lines):
+    for i, line in enumerate(lines):
       guid = "train-%d" % i
       text_a = self.process_text_fn(line[0])
       text_b = self.process_text_fn(line[1])
@@ -792,7 +809,7 @@ class XnliProcessor(DataProcessor):
     """See base class."""
     lines = self._read_tsv(os.path.join(data_dir, "xnli.dev.tsv"))
     examples = []
-    for (i, line) in enumerate(lines):
+    for i, line in enumerate(lines):
       if i == 0:
         continue
       guid = "dev-%d" % i
@@ -807,7 +824,7 @@ class XnliProcessor(DataProcessor):
     """See base class."""
     lines = self._read_tsv(os.path.join(data_dir, "xnli.test.tsv"))
     examples_by_lang = {k: [] for k in XnliProcessor.supported_languages}
-    for (i, line) in enumerate(lines):
+    for i, line in enumerate(lines):
       if i == 0:
         continue
       guid = "test-%d" % i
@@ -837,7 +854,7 @@ class XtremePawsxProcessor(DataProcessor):
     """See base class."""
     lines = self._read_tsv(os.path.join(data_dir, "train-en.tsv"))
     examples = []
-    for (i, line) in enumerate(lines):
+    for i, line in enumerate(lines):
       guid = "train-%d" % i
       text_a = self.process_text_fn(line[0])
       text_b = self.process_text_fn(line[1])
@@ -851,7 +868,7 @@ class XtremePawsxProcessor(DataProcessor):
     lines = self._read_tsv(os.path.join(data_dir, "dev-en.tsv"))
 
     examples = []
-    for (i, line) in enumerate(lines):
+    for i, line in enumerate(lines):
       guid = "dev-%d" % i
       text_a = self.process_text_fn(line[0])
       text_b = self.process_text_fn(line[1])
@@ -865,7 +882,7 @@ class XtremePawsxProcessor(DataProcessor):
     examples_by_lang = {k: [] for k in self.supported_languages}
     for lang in self.supported_languages:
       lines = self._read_tsv(os.path.join(data_dir, f"test-{lang}.tsv"))
-      for (i, line) in enumerate(lines):
+      for i, line in enumerate(lines):
         guid = "test-%d" % i
         text_a = self.process_text_fn(line[0])
         text_b = self.process_text_fn(line[1])
@@ -896,7 +913,7 @@ class XtremeXnliProcessor(DataProcessor):
     lines = self._read_tsv(os.path.join(data_dir, "train-en.tsv"))
 
     examples = []
-    for (i, line) in enumerate(lines):
+    for i, line in enumerate(lines):
       guid = "train-%d" % i
       text_a = self.process_text_fn(line[0])
       text_b = self.process_text_fn(line[1])
@@ -909,7 +926,7 @@ class XtremeXnliProcessor(DataProcessor):
     """See base class."""
     lines = self._read_tsv(os.path.join(data_dir, "dev-en.tsv"))
     examples = []
-    for (i, line) in enumerate(lines):
+    for i, line in enumerate(lines):
       guid = "dev-%d" % i
       text_a = self.process_text_fn(line[0])
       text_b = self.process_text_fn(line[1])
@@ -923,7 +940,7 @@ class XtremeXnliProcessor(DataProcessor):
     examples_by_lang = {k: [] for k in self.supported_languages}
     for lang in self.supported_languages:
       lines = self._read_tsv(os.path.join(data_dir, f"test-{lang}.tsv"))
-      for (i, line) in enumerate(lines):
+      for i, line in enumerate(lines):
         guid = f"test-{i}"
         text_a = self.process_text_fn(line[0])
         text_b = self.process_text_fn(line[1])
@@ -1052,7 +1069,7 @@ def file_based_convert_examples_to_features(examples,
   tf.io.gfile.makedirs(os.path.dirname(output_file))
   writer = tf.io.TFRecordWriter(output_file)
 
-  for (ex_index, example) in enumerate(examples):
+  for ex_index, example in enumerate(examples):
     if ex_index % 10000 == 0:
       logging.info("Writing example %d of %d", ex_index, len(examples))
 

official/nlp/data/create_finetuning_data.py

@@ -59,27 +59,32 @@ flags.DEFINE_enum("classification_task_name", "MNLI",
                   "only and for XNLI is all languages combined. Same for "
                   "PAWS-X.")
 
-# XNLI task specific flag.
+# MNLI task-specific flag.
+flags.DEFINE_enum(
+    "mnli_type", "matched", ["matched", "mismatched"],
+    "The type of MNLI dataset.")
+
+# XNLI task-specific flag.
 flags.DEFINE_string(
     "xnli_language", "en",
-    "Language of training data for XNIL task. If the value is 'all', the data "
+    "Language of training data for XNLI task. If the value is 'all', the data "
     "of all languages will be used for training.")
 
-# PAWS-X task specific flag.
+# PAWS-X task-specific flag.
 flags.DEFINE_string(
     "pawsx_language", "en",
-    "Language of trainig data for PAWS-X task. If the value is 'all', the data "
+    "Language of training data for PAWS-X task. If the value is 'all', the data "
     "of all languages will be used for training.")
 
-# Retrieva task specific flags
+# Retrieval task-specific flags.
 flags.DEFINE_enum("retrieval_task_name", "bucc", ["bucc", "tatoeba"],
                   "The name of sentence retrieval task for scoring")
 
-# Tagging task specific flags
+# Tagging task-specific flags.
 flags.DEFINE_enum("tagging_task_name", "panx", ["panx", "udpos"],
                   "The name of BERT tagging (token classification) task.")
 
-# BERT Squad task specific flags.
+# BERT Squad task-specific flags.
 flags.DEFINE_string(
     "squad_data_file", None,
     "The input data file in for generating training data for BERT squad task.")
@@ -179,7 +184,8 @@ def generate_classifier_dataset():
         "cola":
             classifier_data_lib.ColaProcessor,
         "mnli":
-            classifier_data_lib.MnliProcessor,
+            functools.partial(classifier_data_lib.MnliProcessor,
+                              mnli_type=FLAGS.mnli_type),
         "mrpc":
             classifier_data_lib.MrpcProcessor,
         "qnli":