Update formatting.

PiperOrigin-RevId: 213963765

research/astronet/astronet/astro_cnn_model/astro_cnn_model_test.py

@@ -35,8 +35,7 @@ class AstroCNNModelTest(tf.test.TestCase):
 
     Args:
       shape: Numpy array or anything that can be converted to one.
-      tensor_or_array: tf.Tensor, tf.Variable, Numpy array or anything that can
-          be converted to one.
+      tensor_or_array: tf.Tensor, tf.Variable, or Numpy array.
     """
     if isinstance(tensor_or_array, (np.ndarray, np.generic)):
       self.assertAllEqual(shape, tensor_or_array.shape)

research/astronet/astronet/astro_fc_model/astro_fc_model_test.py

@@ -35,8 +35,7 @@ class AstroFCModelTest(tf.test.TestCase):
 
     Args:
       shape: Numpy array or anything that can be converted to one.
-      tensor_or_array: tf.Tensor, tf.Variable, Numpy array or anything that can
-          be converted to one.
+      tensor_or_array: tf.Tensor, tf.Variable, or Numpy array.
     """
     if isinstance(tensor_or_array, (np.ndarray, np.generic)):
       self.assertAllEqual(shape, tensor_or_array.shape)

research/astronet/astronet/astro_model/astro_model.py

@@ -73,7 +73,9 @@ class AstroModel(object):
   """A TensorFlow model for classifying astrophysical light curves."""
 
   def __init__(self, features, labels, hparams, mode):
-    """Basic setup. The actual TensorFlow graph is constructed in build().
+    """Basic setup.
+
+    The actual TensorFlow graph is constructed in build().
 
     Args:
       features: A dictionary containing "time_series_features" and
@@ -201,8 +203,7 @@ class AstroModel(object):
     if len(hidden_layers) == 1:
       pre_logits_concat = hidden_layers[0][1]
     else:
-      pre_logits_concat = tf.concat(
-          [layer[1] for layer in hidden_layers],
+      pre_logits_concat = tf.concat([layer[1] for layer in hidden_layers],
                                     axis=1,
                                     name="pre_logits_concat")
 

research/astronet/astronet/astro_model/astro_model_test.py

@@ -35,8 +35,7 @@ class AstroModelTest(tf.test.TestCase):
 
     Args:
       shape: Numpy array or anything that can be converted to one.
-      tensor_or_array: tf.Tensor, tf.Variable, Numpy array or anything that can
-          be converted to one.
+      tensor_or_array: tf.Tensor, tf.Variable, or Numpy array.
     """
     if isinstance(tensor_or_array, (np.ndarray, np.generic)):
       self.assertAllEqual(shape, tensor_or_array.shape)

research/astronet/astronet/data/generate_input_records.py

@@ -88,7 +88,6 @@ import tensorflow as tf
 
 from astronet.data import preprocess
 
-
 parser = argparse.ArgumentParser()
 
 _DR24_TCE_URL = ("https://exoplanetarchive.ipac.caltech.edu/cgi-bin/TblView/"
@@ -225,10 +224,10 @@ def main(argv):
     file_shards.append((train_tces[start:end], filename))
 
   # Validation and test sets each have a single shard.
-  file_shards.append((val_tces, os.path.join(FLAGS.output_dir,
-                                             "val-00000-of-00001")))
-  file_shards.append((test_tces, os.path.join(FLAGS.output_dir,
-                                              "test-00000-of-00001")))
+  file_shards.append((val_tces,
+                      os.path.join(FLAGS.output_dir, "val-00000-of-00001")))
+  file_shards.append((test_tces,
+                      os.path.join(FLAGS.output_dir, "test-00000-of-00001")))
   num_file_shards = len(file_shards)
 
   # Launch subprocesses for the file shards.

research/astronet/astronet/ops/input_ops.py

@@ -27,8 +27,7 @@ def prepare_feed_dict(model, features, labels=None, is_training=None):
   Args:
     model: An instance of AstroModel.
     features: Dictionary containing "time_series_features" and "aux_features".
-        Each is a dictionary of named numpy arrays of shape
-        [batch_size, length].
+      Each is a dictionary of named numpy arrays of shape [batch_size, length].
     labels: (Optional). Numpy array of shape [batch_size].
     is_training: (Optional). Python boolean to feed to the model.is_training
       Tensor (if None, no value is fed).

research/astronet/astronet/ops/testing.py

@@ -47,15 +47,10 @@ def fake_features(feature_spec, batch_size):
     Dictionary containing "time_series_features" and "aux_features". Each is a
         dictionary of named numpy arrays of shape [batch_size, length].
   """
-  features = {}
-  features["time_series_features"] = {
-      name: np.random.random([batch_size, spec["length"]])
-      for name, spec in feature_spec.items() if spec["is_time_series"]
-  }
-  features["aux_features"] = {
-      name: np.random.random([batch_size, spec["length"]])
-      for name, spec in feature_spec.items() if not spec["is_time_series"]
-  }
+  features = {"time_series_features": {}, "aux_features": {}}
+  for name, spec in feature_spec.items():
+    ftype = "time_series_features" if spec["is_time_series"] else "aux_features"
+    features[ftype][name] = np.random.random([batch_size, spec["length"]])
   return features
 
 

research/astronet/light_curve_util/cc/python/median_filter_test.py

@@ -44,5 +44,5 @@ class MedianFilterTest(absltest.TestCase):
     np.testing.assert_almost_equal(result, expected)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
   absltest.main()

research/astronet/light_curve_util/cc/python/phase_fold_test.py

@@ -66,5 +66,5 @@ class PhaseFoldAndSortLightCurveTest(absltest.TestCase):
     np.testing.assert_almost_equal(folded_flux, expected_flux)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
   absltest.main()

research/astronet/light_curve_util/cc/python/view_generator_test.py

@@ -76,5 +76,5 @@ class ViewGeneratorTest(absltest.TestCase):
     np.testing.assert_almost_equal(result, expected)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
   absltest.main()