Skip to content

GitLab

"notebooks/vscode:/vscode.git/clone" did not exist on "2550ac5c91dcad0919b889a36fe135856558c770"
Commit 571369aa authored by A. Unique TensorFlower's avatar A. Unique TensorFlower
Browse files

Add STS-B glue data preprocessor and regression support, and alpha-order the preprocessor classes. 

PiperOrigin-RevId: 320318976
parent 7bb5ab6d
Hide whitespace changes
Inline Side-by-side
Showing with 342 additions and 285 deletions
official/nlp/data/classifier_data_lib.py
View file @ 571369aa
......@@ -31,7 +31,7 @@ from official.nlp.bert import tokenization
class InputExample(object):
"""A single training/test example for simple sequence classification."""
"""A single training/test example for simple seq regression/classification."""
def __init__(self,
guid,
......@@ -48,8 +48,9 @@ class InputExample(object):
sequence tasks, only this sequence must be specified.
text_b: (Optional) string. The untokenized text of the second sequence.
Only must be specified for sequence pair tasks.
label: (Optional) string. The label of the example. This should be
specified for train and dev examples, but not for test examples.
label: (Optional) string for classification, float for regression. The
label of the example. This should be specified for train and dev
examples, but not for test examples.
weight: (Optional) float. The weight of the example to be used during
training.
int_iden: (Optional) int. The int identification number of example in the
......@@ -84,10 +85,12 @@ class InputFeatures(object):
class DataProcessor(object):
"""Base class for data converters for sequence classification data sets."""
"""Base class for converters for seq regression/classification datasets."""
def __init__(self, process_text_fn=tokenization.convert_to_unicode):
self.process_text_fn = process_text_fn
self.is_regression = False
self.label_type = None
def get_train_examples(self, data_dir):
"""Gets a collection of `InputExample`s for the train set."""
......@@ -121,76 +124,70 @@ class DataProcessor(object):
return lines
class XnliProcessor(DataProcessor):
"""Processor for the XNLI data set."""
supported_languages = [
"ar", "bg", "de", "el", "en", "es", "fr", "hi", "ru", "sw", "th", "tr",
"ur", "vi", "zh"
]
def __init__(self,
language="en",
process_text_fn=tokenization.convert_to_unicode):
super(XnliProcessor, self).__init__(process_text_fn)
if language == "all":
self.languages = XnliProcessor.supported_languages
elif language not in XnliProcessor.supported_languages:
raise ValueError("language %s is not supported for XNLI task." % language)
else:
self.languages = [language]
class ColaProcessor(DataProcessor):
"""Processor for the CoLA data set (GLUE version)."""
def get_train_examples(self, data_dir):
"""See base class."""
lines = []
for language in self.languages:
# Skips the header.
lines.extend(
self._read_tsv(
os.path.join(data_dir, "multinli",
"multinli.train.%s.tsv" % language))[1:])
examples = []
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])
label = self.process_text_fn(line[2])
if label == self.process_text_fn("contradictory"):
label = self.process_text_fn("contradiction")
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "train.tsv")), "train")
def get_dev_examples(self, data_dir):
"""See base class."""
lines = self._read_tsv(os.path.join(data_dir, "xnli.dev.tsv"))
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "dev.tsv")), "dev")
def get_test_examples(self, data_dir):
"""See base class."""
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "test.tsv")), "test")
def get_labels(self):
"""See base class."""
return ["0", "1"]
@staticmethod
def get_processor_name():
"""See base class."""
return "COLA"
def _create_examples(self, lines, set_type):
"""Creates examples for the training and dev sets."""
examples = []
for (i, line) in enumerate(lines):
if i == 0:
# Only the test set has a header
if set_type == "test" and i == 0:
continue
guid = "dev-%d" % i
text_a = self.process_text_fn(line[6])
text_b = self.process_text_fn(line[7])
label = self.process_text_fn(line[1])
guid = "%s-%s" % (set_type, i)
if set_type == "test":
text_a = self.process_text_fn(line[1])
label = "0"
else:
text_a = self.process_text_fn(line[3])
label = self.process_text_fn(line[1])
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
InputExample(guid=guid, text_a=text_a, text_b=None, label=label))
return examples
class MnliProcessor(DataProcessor):
"""Processor for the MultiNLI data set (GLUE version)."""
def get_train_examples(self, data_dir):
"""See base class."""
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "train.tsv")), "train")
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")
def get_test_examples(self, data_dir):
"""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):
if i == 0:
continue
guid = "test-%d" % i
language = self.process_text_fn(line[0])
text_a = self.process_text_fn(line[6])
text_b = self.process_text_fn(line[7])
label = self.process_text_fn(line[1])
examples_by_lang[language].append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples_by_lang
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "test_matched.tsv")), "test")
def get_labels(self):
"""See base class."""
......@@ -199,65 +196,69 @@ class XnliProcessor(DataProcessor):
@staticmethod
def get_processor_name():
"""See base class."""
return "XNLI"
class XtremeXnliProcessor(DataProcessor):
"""Processor for the XTREME XNLI data set."""
supported_languages = [
"ar", "bg", "de", "el", "en", "es", "fr", "hi", "ru", "sw", "th", "tr",
"ur", "vi", "zh"
]
def get_train_examples(self, data_dir):
"""See base class."""
lines = self._read_tsv(os.path.join(data_dir, "train-en.tsv"))
return "MNLI"
def _create_examples(self, lines, set_type):
"""Creates examples for the training and dev sets."""
examples = []
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])
label = self.process_text_fn(line[2])
if i == 0:
continue
guid = "%s-%s" % (set_type, self.process_text_fn(line[0]))
text_a = self.process_text_fn(line[8])
text_b = self.process_text_fn(line[9])
if set_type == "test":
label = "contradiction"
else:
label = self.process_text_fn(line[-1])
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
class MrpcProcessor(DataProcessor):
"""Processor for the MRPC data set (GLUE version)."""
def get_train_examples(self, data_dir):
"""See base class."""
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "train.tsv")), "train")
def get_dev_examples(self, data_dir):
"""See base class."""
lines = self._read_tsv(os.path.join(data_dir, "dev-en.tsv"))
examples = []
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])
label = self.process_text_fn(line[2])
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "dev.tsv")), "dev")
def get_test_examples(self, data_dir):
"""See base class."""
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):
guid = f"test-{i}"
text_a = self.process_text_fn(line[0])
text_b = self.process_text_fn(line[1])
label = "contradiction"
examples_by_lang[lang].append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples_by_lang
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "test.tsv")), "test")
def get_labels(self):
"""See base class."""
return ["contradiction", "entailment", "neutral"]
return ["0", "1"]
@staticmethod
def get_processor_name():
"""See base class."""
return "XTREME-XNLI"
return "MRPC"
def _create_examples(self, lines, set_type):
"""Creates examples for the training and dev sets."""
examples = []
for (i, line) in enumerate(lines):
if i == 0:
continue
guid = "%s-%s" % (set_type, i)
text_a = self.process_text_fn(line[3])
text_b = self.process_text_fn(line[4])
if set_type == "test":
label = "0"
else:
label = self.process_text_fn(line[0])
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
class PawsxProcessor(DataProcessor):
......@@ -339,154 +340,8 @@ class PawsxProcessor(DataProcessor):
return "XTREME-PAWS-X"
class XtremePawsxProcessor(DataProcessor):
"""Processor for the XTREME PAWS-X data set."""
supported_languages = ["de", "en", "es", "fr", "ja", "ko", "zh"]
def get_train_examples(self, data_dir):
"""See base class."""
lines = self._read_tsv(os.path.join(data_dir, "train-en.tsv"))
examples = []
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])
label = self.process_text_fn(line[2])
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
def get_dev_examples(self, data_dir):
"""See base class."""
lines = self._read_tsv(os.path.join(data_dir, "dev-en.tsv"))
examples = []
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])
label = self.process_text_fn(line[2])
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
def get_test_examples(self, data_dir):
"""See base class."""
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):
guid = "test-%d" % i
text_a = self.process_text_fn(line[0])
text_b = self.process_text_fn(line[1])
label = "0"
examples_by_lang[lang].append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples_by_lang
def get_labels(self):
"""See base class."""
return ["0", "1"]
@staticmethod
def get_processor_name():
"""See base class."""
return "XTREME-PAWS-X"
class MnliProcessor(DataProcessor):
"""Processor for the MultiNLI data set (GLUE version)."""
def get_train_examples(self, data_dir):
"""See base class."""
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "train.tsv")), "train")
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")
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")
def get_labels(self):
"""See base class."""
return ["contradiction", "entailment", "neutral"]
@staticmethod
def get_processor_name():
"""See base class."""
return "MNLI"
def _create_examples(self, lines, set_type):
"""Creates examples for the training and dev sets."""
examples = []
for (i, line) in enumerate(lines):
if i == 0:
continue
guid = "%s-%s" % (set_type, self.process_text_fn(line[0]))
text_a = self.process_text_fn(line[8])
text_b = self.process_text_fn(line[9])
if set_type == "test":
label = "contradiction"
else:
label = self.process_text_fn(line[-1])
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
class MrpcProcessor(DataProcessor):
"""Processor for the MRPC data set (GLUE version)."""
def get_train_examples(self, data_dir):
"""See base class."""
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "train.tsv")), "train")
def get_dev_examples(self, data_dir):
"""See base class."""
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "dev.tsv")), "dev")
def get_test_examples(self, data_dir):
"""See base class."""
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "test.tsv")), "test")
def get_labels(self):
"""See base class."""
return ["0", "1"]
@staticmethod
def get_processor_name():
"""See base class."""
return "MRPC"
def _create_examples(self, lines, set_type):
"""Creates examples for the training and dev sets."""
examples = []
for (i, line) in enumerate(lines):
if i == 0:
continue
guid = "%s-%s" % (set_type, i)
text_a = self.process_text_fn(line[3])
text_b = self.process_text_fn(line[4])
if set_type == "test":
label = "0"
else:
label = self.process_text_fn(line[0])
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
class QqpProcessor(DataProcessor):
"""Processor for the QQP data set (GLUE version)."""
class QnliProcessor(DataProcessor):
"""Processor for the QNLI data set (GLUE version)."""
def get_train_examples(self, data_dir):
"""See base class."""
......@@ -496,7 +351,7 @@ class QqpProcessor(DataProcessor):
def get_dev_examples(self, data_dir):
"""See base class."""
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "dev.tsv")), "dev")
self._read_tsv(os.path.join(data_dir, "dev.tsv")), "dev_matched")
def get_test_examples(self, data_dir):
"""See base class."""
......@@ -505,12 +360,12 @@ class QqpProcessor(DataProcessor):
def get_labels(self):
"""See base class."""
return ["0", "1"]
return ["entailment", "not_entailment"]
@staticmethod
def get_processor_name():
"""See base class."""
return "QQP"
return "QNLI"
def _create_examples(self, lines, set_type):
"""Creates examples for the training and dev sets."""
......@@ -518,20 +373,22 @@ class QqpProcessor(DataProcessor):
for (i, line) in enumerate(lines):
if i == 0:
continue
guid = "%s-%s" % (set_type, line[0])
try:
text_a = line[3]
text_b = line[4]
label = line[5]
except IndexError:
continue
guid = "%s-%s" % (set_type, 1)
if set_type == "test":
text_a = tokenization.convert_to_unicode(line[1])
text_b = tokenization.convert_to_unicode(line[2])
label = "entailment"
else:
text_a = tokenization.convert_to_unicode(line[1])
text_b = tokenization.convert_to_unicode(line[2])
label = tokenization.convert_to_unicode(line[-1])
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
class ColaProcessor(DataProcessor):
"""Processor for the CoLA data set (GLUE version)."""
class QqpProcessor(DataProcessor):
"""Processor for the QQP data set (GLUE version)."""
def get_train_examples(self, data_dir):
"""See base class."""
......@@ -555,24 +412,23 @@ class ColaProcessor(DataProcessor):
@staticmethod
def get_processor_name():
"""See base class."""
return "COLA"
return "QQP"
def _create_examples(self, lines, set_type):
"""Creates examples for the training and dev sets."""
examples = []
for (i, line) in enumerate(lines):
# Only the test set has a header
if set_type == "test" and i == 0:
if i == 0:
continue
guid = "%s-%s" % (set_type, line[0])
try:
text_a = line[3]
text_b = line[4]
label = line[5]
except IndexError:
continue
guid = "%s-%s" % (set_type, i)
if set_type == "test":
text_a = self.process_text_fn(line[1])
label = "0"
else:
text_a = self.process_text_fn(line[3])
label = self.process_text_fn(line[1])
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=None, label=label))
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
......@@ -668,8 +524,14 @@ class SstProcessor(DataProcessor):
return examples
class QnliProcessor(DataProcessor):
"""Processor for the QNLI data set (GLUE version)."""
class StsBProcessor(DataProcessor):
"""Processor for the STS-B data set (GLUE version)."""
def __init__(self, process_text_fn=tokenization.convert_to_unicode):
super(StsBProcessor, self).__init__(process_text_fn=process_text_fn)
self.is_regression = True
self.label_type = float
self._labels = None
def get_train_examples(self, data_dir):
"""See base class."""
......@@ -679,7 +541,7 @@ class QnliProcessor(DataProcessor):
def get_dev_examples(self, data_dir):
"""See base class."""
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "dev.tsv")), "dev_matched")
self._read_tsv(os.path.join(data_dir, "dev.tsv")), "dev")
def get_test_examples(self, data_dir):
"""See base class."""
......@@ -688,28 +550,26 @@ class QnliProcessor(DataProcessor):
def get_labels(self):
"""See base class."""
return ["entailment", "not_entailment"]
return self._labels
@staticmethod
def get_processor_name():
"""See base class."""
return "QNLI"
return "STS-B"
def _create_examples(self, lines, set_type):
"""Creates examples for the training and dev sets."""
examples = []
for (i, line) in enumerate(lines):
for i, line in enumerate(lines):
if i == 0:
continue
guid = "%s-%s" % (set_type, 1)
guid = "%s-%s" % (set_type, i)
text_a = tokenization.convert_to_unicode(line[7])
text_b = tokenization.convert_to_unicode(line[8])
if set_type == "test":
text_a = tokenization.convert_to_unicode(line[1])
text_b = tokenization.convert_to_unicode(line[2])
label = "entailment"
label = 0.0
else:
text_a = tokenization.convert_to_unicode(line[1])
text_b = tokenization.convert_to_unicode(line[2])
label = tokenization.convert_to_unicode(line[-1])
label = self.label_type(tokenization.convert_to_unicode(line[9]))
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
......@@ -888,6 +748,200 @@ class WnliProcessor(DataProcessor):
return examples
class XnliProcessor(DataProcessor):
"""Processor for the XNLI data set."""
supported_languages = [
"ar", "bg", "de", "el", "en", "es", "fr", "hi", "ru", "sw", "th", "tr",
"ur", "vi", "zh"
]
def __init__(self,
language="en",
process_text_fn=tokenization.convert_to_unicode):
super(XnliProcessor, self).__init__(process_text_fn)
if language == "all":
self.languages = XnliProcessor.supported_languages
elif language not in XnliProcessor.supported_languages:
raise ValueError("language %s is not supported for XNLI task." % language)
else:
self.languages = [language]
def get_train_examples(self, data_dir):
"""See base class."""
lines = []
for language in self.languages:
# Skips the header.
lines.extend(
self._read_tsv(
os.path.join(data_dir, "multinli",
"multinli.train.%s.tsv" % language))[1:])
examples = []
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])
label = self.process_text_fn(line[2])
if label == self.process_text_fn("contradictory"):
label = self.process_text_fn("contradiction")
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
def get_dev_examples(self, data_dir):
"""See base class."""
lines = self._read_tsv(os.path.join(data_dir, "xnli.dev.tsv"))
examples = []
for (i, line) in enumerate(lines):
if i == 0:
continue
guid = "dev-%d" % i
text_a = self.process_text_fn(line[6])
text_b = self.process_text_fn(line[7])
label = self.process_text_fn(line[1])
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
def get_test_examples(self, data_dir):
"""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):
if i == 0:
continue
guid = "test-%d" % i
language = self.process_text_fn(line[0])
text_a = self.process_text_fn(line[6])
text_b = self.process_text_fn(line[7])
label = self.process_text_fn(line[1])
examples_by_lang[language].append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples_by_lang
def get_labels(self):
"""See base class."""
return ["contradiction", "entailment", "neutral"]
@staticmethod
def get_processor_name():
"""See base class."""
return "XNLI"
class XtremePawsxProcessor(DataProcessor):
"""Processor for the XTREME PAWS-X data set."""
supported_languages = ["de", "en", "es", "fr", "ja", "ko", "zh"]
def get_train_examples(self, data_dir):
"""See base class."""
lines = self._read_tsv(os.path.join(data_dir, "train-en.tsv"))
examples = []
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])
label = self.process_text_fn(line[2])
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
def get_dev_examples(self, data_dir):
"""See base class."""
lines = self._read_tsv(os.path.join(data_dir, "dev-en.tsv"))
examples = []
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])
label = self.process_text_fn(line[2])
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
def get_test_examples(self, data_dir):
"""See base class."""
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):
guid = "test-%d" % i
text_a = self.process_text_fn(line[0])
text_b = self.process_text_fn(line[1])
label = "0"
examples_by_lang[lang].append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples_by_lang
def get_labels(self):
"""See base class."""
return ["0", "1"]
@staticmethod
def get_processor_name():
"""See base class."""
return "XTREME-PAWS-X"
class XtremeXnliProcessor(DataProcessor):
"""Processor for the XTREME XNLI data set."""
supported_languages = [
"ar", "bg", "de", "el", "en", "es", "fr", "hi", "ru", "sw", "th", "tr",
"ur", "vi", "zh"
]
def get_train_examples(self, data_dir):
"""See base class."""
lines = self._read_tsv(os.path.join(data_dir, "train-en.tsv"))
examples = []
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])
label = self.process_text_fn(line[2])
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
def get_dev_examples(self, data_dir):
"""See base class."""
lines = self._read_tsv(os.path.join(data_dir, "dev-en.tsv"))
examples = []
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])
label = self.process_text_fn(line[2])
examples.append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples
def get_test_examples(self, data_dir):
"""See base class."""
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):
guid = f"test-{i}"
text_a = self.process_text_fn(line[0])
text_b = self.process_text_fn(line[1])
label = "contradiction"
examples_by_lang[lang].append(
InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
return examples_by_lang
def get_labels(self):
"""See base class."""
return ["contradiction", "entailment", "neutral"]
@staticmethod
def get_processor_name():
"""See base class."""
return "XTREME-XNLI"
def convert_single_example(ex_index, example, label_list, max_seq_length,
tokenizer):
"""Converts a single `InputExample` into a single `InputFeatures`."""
......
official/nlp/data/create_finetuning_data.py
View file @ 571369aa
......@@ -51,7 +51,8 @@ flags.DEFINE_string(
flags.DEFINE_enum("classification_task_name", "MNLI",
["COLA", "MNLI", "MRPC", "PAWS-X", "QNLI", "QQP", "RTE",
"SST-2", "WNLI", "XNLI", "XTREME-XNLI", "XTREME-PAWS-X"],
"SST-2", "STS-B", "WNLI", "XNLI", "XTREME-XNLI",
"XTREME-PAWS-X"],
"The name of the task to train BERT classifier. The "
"difference between XTREME-XNLI and XNLI is: 1. the format "
"of input tsv files; 2. the dev set for XTREME is english "
......@@ -187,6 +188,8 @@ def generate_classifier_dataset():
"rte": classifier_data_lib.RteProcessor,
"sst-2":
classifier_data_lib.SstProcessor,
"sts-b":
classifier_data_lib.StsBProcessor,
"xnli":
functools.partial(classifier_data_lib.XnliProcessor,
language=FLAGS.xnli_language),
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment