Add C0330 bad-continuation check to pylint.

PiperOrigin-RevId: 183270896

1 files changed, 25 insertions, 16 deletions

diff --git a/tensorflow/examples/label_image/label_image.py b/tensorflow/examples/label_image/label_image.py
index d62b73384c..1c1bd57d71 100644
--- a/tensorflow/examples/label_image/label_image.py
+++ b/tensorflow/examples/label_image/label_image.py
@@ -23,6 +23,7 @@ import sys
 import numpy as np
 import tensorflow as tf
 
+
 def load_graph(model_file):
   graph = tf.Graph()
   graph_def = tf.GraphDef()
@@ -34,22 +35,26 @@ def load_graph(model_file):
 
   return graph
 
-def read_tensor_from_image_file(file_name, input_height=299, input_width=299,
-				input_mean=0, input_std=255):
+
+def read_tensor_from_image_file(file_name,
+                                input_height=299,
+                                input_width=299,
+                                input_mean=0,
+                                input_std=255):
   input_name = "file_reader"
   output_name = "normalized"
   file_reader = tf.read_file(file_name, input_name)
   if file_name.endswith(".png"):
-    image_reader = tf.image.decode_png(file_reader, channels = 3,
-                                       name='png_reader')
+    image_reader = tf.image.decode_png(
+        file_reader, channels=3, name="png_reader")
   elif file_name.endswith(".gif"):
-    image_reader = tf.squeeze(tf.image.decode_gif(file_reader,
-                                                  name='gif_reader'))
+    image_reader = tf.squeeze(
+        tf.image.decode_gif(file_reader, name="gif_reader"))
   elif file_name.endswith(".bmp"):
-    image_reader = tf.image.decode_bmp(file_reader, name='bmp_reader')
+    image_reader = tf.image.decode_bmp(file_reader, name="bmp_reader")
   else:
-    image_reader = tf.image.decode_jpeg(file_reader, channels = 3,
-                                        name='jpeg_reader')
+    image_reader = tf.image.decode_jpeg(
+        file_reader, channels=3, name="jpeg_reader")
   float_caster = tf.cast(image_reader, tf.float32)
   dims_expander = tf.expand_dims(float_caster, 0)
   resized = tf.image.resize_bilinear(dims_expander, [input_height, input_width])
@@ -59,6 +64,7 @@ def read_tensor_from_image_file(file_name, input_height=299, input_width=299,
 
   return result
 
+
 def load_labels(label_file):
   label = []
   proto_as_ascii_lines = tf.gfile.GFile(label_file).readlines()
@@ -66,6 +72,7 @@ def load_labels(label_file):
     label.append(l.rstrip())
   return label
 
+
 if __name__ == "__main__":
   file_name = "tensorflow/examples/label_image/data/grace_hopper.jpg"
   model_file = \
@@ -110,11 +117,12 @@ if __name__ == "__main__":
     output_layer = args.output_layer
 
   graph = load_graph(model_file)
-  t = read_tensor_from_image_file(file_name,
-                                  input_height=input_height,
-                                  input_width=input_width,
-                                  input_mean=input_mean,
-                                  input_std=input_std)
+  t = read_tensor_from_image_file(
+      file_name,
+      input_height=input_height,
+      input_width=input_width,
+      input_mean=input_mean,
+      input_std=input_std)
 
   input_name = "import/" + input_layer
   output_name = "import/" + output_layer
@@ -122,8 +130,9 @@ if __name__ == "__main__":
   output_operation = graph.get_operation_by_name(output_name)
 
   with tf.Session(graph=graph) as sess:
-    results = sess.run(output_operation.outputs[0],
-                      {input_operation.outputs[0]: t})
+    results = sess.run(output_operation.outputs[0], {
+        input_operation.outputs[0]: t
+    })
   results = np.squeeze(results)
 
   top_k = results.argsort()[-5:][::-1]