fixed style issues

official/nlp/finetuning/binary_helper.py

@@ -309,16 +309,16 @@ def write_glue_classification(task,
         # Classification.
         writer.write('%d\t%s\n' % (index, class_names[prediction]))
 def write_superglue_classification(task,
-                              model,
-                              input_file,
-                              output_file,
-                              predict_batch_size,
-                              seq_length,
-                              class_names,
-                              label_type='int',
-                              min_float_value=None,
-                              max_float_value=None):
-  """Makes classification predictions for glue and writes to output file.
+                                   model,
+                                   input_file,
+                                   output_file,
+                                   predict_batch_size,
+                                   seq_length,
+                                   class_names,
+                                   label_type='int',
+                                   min_float_value=None,
+                                   max_float_value=None):
+  """Makes classification predictions for superglue and writes to output file.
 
   Args:
     task: `Task` instance.
@@ -350,7 +350,6 @@ def write_superglue_classification(task,
       include_example_id=True)
   predictions = sentence_prediction.predict(task, data_config, model)
 
-
   with tf.io.gfile.GFile(output_file, 'w') as writer:
     for index, prediction in enumerate(predictions):
       if label_type == 'int':

official/nlp/finetuning/superglue/flags.py

@@ -36,8 +36,8 @@ def define_flags():
       'run prediction using the model in `model_dir`.')
 
   flags.DEFINE_enum('task_name', None, [
-    'AX-b', 'CB', 'COPA', 'MULTIRC', 'RTE', 'WiC', 'WSC',
-    'BoolQ', 'ReCoRD', 'AX-g',
+      'AX-b', 'CB', 'COPA', 'MULTIRC', 'RTE', 'WiC', 'WSC',
+      'BoolQ', 'ReCoRD', 'AX-g',
   ], 'The type of GLUE task.')
 
   flags.DEFINE_string('train_input_path', None,
@@ -160,4 +160,4 @@ def validate_flags(flags_obj: flags.FlagValues,
       _validate_path(flags_obj.model_config_file, 'model_config_file')
       logging.info(
           'Using the pretrained checkpoint from %s and model_config_file from '
-          '%s.', flags_obj.init_checkpoint, flags_obj.model_config_file)
\ No newline at end of file
+          '%s.', flags_obj.init_checkpoint, flags_obj.model_config_file)

official/nlp/finetuning/superglue/run_superglue.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-"""Runs prediction to generate submission files for GLUE tasks."""
+"""Runs prediction to generate submission files for SuperGLUE tasks."""
 import functools
 import json
 import os
@@ -27,14 +27,13 @@ import tensorflow as tf
 
 from official.common import distribute_utils
 # Imports registered experiment configs.
-from official.common import registry_imports  # pylint: disable=unused-import
 from official.core import exp_factory
 from official.core import task_factory
 from official.core import train_lib
 from official.core import train_utils
 from official.modeling.hyperparams import params_dict
 from official.nlp.finetuning import binary_helper
-from official.nlp.finetuning.superglue import flags as glue_flags
+from official.nlp.finetuning.superglue import flags as superglue_flags
 
 
 # Device configs.
@@ -81,13 +80,13 @@ def _override_exp_config_by_file(exp_config, exp_config_files):
 
 def _override_exp_config_by_flags(exp_config, input_meta_data):
   """Overrides an `ExperimentConfig` object by flags."""
-  if FLAGS.task_name in ('AX-b'):
+  if FLAGS.task_name in 'AX-b':
     override_task_cfg_fn = functools.partial(
         binary_helper.override_sentence_prediction_task_config,
         num_classes=input_meta_data['num_labels'],
         metric_type='matthews_corrcoef')
   elif FLAGS.task_name in ('CB', 'COPA', 'RTE', 'WiC', 'WSC', 'BoolQ',
-                           'ReCoRD','AX-g'):
+                           'ReCoRD', 'AX-g'):
     override_task_cfg_fn = functools.partial(
         binary_helper.override_sentence_prediction_task_config,
         num_classes=input_meta_data['num_labels'])
@@ -152,7 +151,7 @@ def _write_submission_file(task, seq_length):
   checkpoint = tf.train.Checkpoint(model=model)
   checkpoint.read(ckpt_file).expect_partial()
 
-  write_fn = binary_helper.write_glue_classification
+  write_fn = binary_helper.write_superglue_classification
   write_fn_map = {
       'RTE':
           functools.partial(
@@ -176,7 +175,7 @@ def main(argv):
   if len(argv) > 1:
     raise app.UsageError('Too many command-line arguments.')
 
-  glue_flags.validate_flags(FLAGS, file_exists_fn=tf.io.gfile.exists)
+  superglue_flags.validate_flags(FLAGS, file_exists_fn=tf.io.gfile.exists)
 
   gin.parse_config_files_and_bindings(FLAGS.gin_file, FLAGS.gin_params)
   distribution_strategy = distribute_utils.get_distribution_strategy(
@@ -218,7 +217,7 @@ def main(argv):
 
 
 if __name__ == '__main__':
-  glue_flags.define_flags()
+  superglue_flags.define_flags()
   flags.mark_flag_as_required('mode')
   flags.mark_flag_as_required('task_name')
-  app.run(main)
\ No newline at end of file
+  app.run(main)