diff --git a/WORKSPACE b/WORKSPACE
index f5e8bedf4aa..ea6b2cdb1c9 100644
--- a/WORKSPACE
+++ b/WORKSPACE
@@ -152,4 +152,3 @@ load(
 )
 
 nccl_configure(name = "local_config_nccl")
-
diff --git a/tensorflow_serving/apis/model_service_pb2.py b/tensorflow_serving/apis/model_service_pb2.py
index 76f1d606cb2..a641dd12404 100644
--- a/tensorflow_serving/apis/model_service_pb2.py
+++ b/tensorflow_serving/apis/model_service_pb2.py
@@ -18,19 +18,25 @@
 # python -m grpc.tools.protoc --python_out=. --grpc_python_out=. -I. tensorflow_serving/apis/model_service.proto
 
 import sys
+
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
+from google.protobuf import descriptor_pb2
 from google.protobuf import message as _message
 from google.protobuf import reflection as _reflection
 from google.protobuf import symbol_database as _symbol_database
-from google.protobuf import descriptor_pb2
+
 # @@protoc_insertion_point(imports)
 
 _sym_db = _symbol_database.Default()
 
 
-from tensorflow_serving.apis import get_model_status_pb2 as tensorflow__serving_dot_apis_dot_get__model__status__pb2
-from tensorflow_serving.apis import model_management_pb2 as tensorflow__serving_dot_apis_dot_model__management__pb2
+from tensorflow_serving.apis import (
+    get_model_status_pb2 as tensorflow__serving_dot_apis_dot_get__model__status__pb2,
+)
+from tensorflow_serving.apis import (
+    model_management_pb2 as tensorflow__serving_dot_apis_dot_model__management__pb2,
+)
 
 DESCRIPTOR = _descriptor.FileDescriptor(
     name='tensorflow_serving/apis/model_service.proto',
diff --git a/tensorflow_serving/apis/model_service_pb2_grpc.py b/tensorflow_serving/apis/model_service_pb2_grpc.py
index 44c578b8648..76b4e1d4bf8 100644
--- a/tensorflow_serving/apis/model_service_pb2_grpc.py
+++ b/tensorflow_serving/apis/model_service_pb2_grpc.py
@@ -19,14 +19,16 @@
 
 import grpc
 
-from tensorflow_serving.apis import get_model_status_pb2 as tensorflow__serving_dot_apis_dot_get__model__status__pb2
-from tensorflow_serving.apis import model_management_pb2 as tensorflow__serving_dot_apis_dot_model__management__pb2
+from tensorflow_serving.apis import (
+  get_model_status_pb2 as tensorflow__serving_dot_apis_dot_get__model__status__pb2,
+)
+from tensorflow_serving.apis import (
+  model_management_pb2 as tensorflow__serving_dot_apis_dot_model__management__pb2,
+)
 
 
-class ModelServiceStub(object):
-  """ModelService provides methods to query and update the state of the server,
-  e.g. which models/versions are being served.
-  """
+class ModelServiceStub:
+  """ModelService provides methods to query and update the state of the server, e.g. which models/versions are being served."""
 
   def __init__(self, channel):
     """Constructor.
@@ -50,25 +52,22 @@ def __init__(self, channel):
     )
 
 
-class ModelServiceServicer(object):
-  """ModelService provides methods to query and update the state of the server,
-  e.g. which models/versions are being served.
-  """
+class ModelServiceServicer:
+  """ModelService provides methods to query and update the state of the server e.g. which models/versions are being served."""
 
-  def GetModelStatus(self, request, context):
-    """Gets status of model. If the ModelSpec in the request does not specify
-    version, information about all versions of the model will be returned. If
-    the ModelSpec in the request does specify a version, the status of only
-    that version will be returned.
+  def GetModelStatus(self, request, context): # noqa: ARG002
+    """Gets status of model.
+
+    If the ModelSpec in the request does not specify version, information about all versions of the model will be returned. If the ModelSpec in the request does specify a version, the status of only that version will be returned.
     """
     context.set_code(grpc.StatusCode.UNIMPLEMENTED)
     context.set_details('Method not implemented!')
     raise NotImplementedError('Method not implemented!')
 
-  def HandleReloadConfigRequest(self, request, context):
-    """Reloads the set of served models. The new config supersedes the old one,
-    so if a model is omitted from the new config it will be unloaded and no
-    longer served.
+  def HandleReloadConfigRequest(self, request, context): # noqa: ARG002
+    """Reloads the set of served models.
+
+    The new config supersedes the old one, so if a model is omitted from the new config it will be unloaded and no longer served.
     """
     context.set_code(grpc.StatusCode.UNIMPLEMENTED)
     context.set_details('Method not implemented!')
diff --git a/tensorflow_serving/apis/prediction_service_pb2.py b/tensorflow_serving/apis/prediction_service_pb2.py
index e51a700f720..c0120472c57 100644
--- a/tensorflow_serving/apis/prediction_service_pb2.py
+++ b/tensorflow_serving/apis/prediction_service_pb2.py
@@ -22,23 +22,34 @@
 # source: tensorflow_serving/apis/prediction_service.proto
 
 import sys
+
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
+from google.protobuf import descriptor_pb2
 from google.protobuf import message as _message
 from google.protobuf import reflection as _reflection
 from google.protobuf import symbol_database as _symbol_database
-from google.protobuf import descriptor_pb2
+
 # @@protoc_insertion_point(imports)
 
 _sym_db = _symbol_database.Default()
 
 
-from tensorflow_serving.apis import classification_pb2 as tensorflow__serving_dot_apis_dot_classification__pb2
-from tensorflow_serving.apis import get_model_metadata_pb2 as tensorflow__serving_dot_apis_dot_get__model__metadata__pb2
-from tensorflow_serving.apis import inference_pb2 as tensorflow__serving_dot_apis_dot_inference__pb2
-from tensorflow_serving.apis import predict_pb2 as tensorflow__serving_dot_apis_dot_predict__pb2
-from tensorflow_serving.apis import regression_pb2 as tensorflow__serving_dot_apis_dot_regression__pb2
-
+from tensorflow_serving.apis import (
+  classification_pb2 as tensorflow__serving_dot_apis_dot_classification__pb2,
+)
+from tensorflow_serving.apis import (
+  get_model_metadata_pb2 as tensorflow__serving_dot_apis_dot_get__model__metadata__pb2,
+)
+from tensorflow_serving.apis import (
+  inference_pb2 as tensorflow__serving_dot_apis_dot_inference__pb2,
+)
+from tensorflow_serving.apis import (
+  predict_pb2 as tensorflow__serving_dot_apis_dot_predict__pb2,
+)
+from tensorflow_serving.apis import (
+  regression_pb2 as tensorflow__serving_dot_apis_dot_regression__pb2,
+)
 
 DESCRIPTOR = _descriptor.FileDescriptor(
   name='tensorflow_serving/apis/prediction_service.proto',
diff --git a/tensorflow_serving/apis/prediction_service_pb2_grpc.py b/tensorflow_serving/apis/prediction_service_pb2_grpc.py
index 082f94a39a0..aea06eb0676 100644
--- a/tensorflow_serving/apis/prediction_service_pb2_grpc.py
+++ b/tensorflow_serving/apis/prediction_service_pb2_grpc.py
@@ -18,17 +18,27 @@
 # python -m grpc.tools.protoc --python_out=. --grpc_python_out=. -I. tensorflow_serving/apis/prediction_service.proto
 import grpc
 
-from tensorflow_serving.apis import classification_pb2 as tensorflow__serving_dot_apis_dot_classification__pb2
-from tensorflow_serving.apis import get_model_metadata_pb2 as tensorflow__serving_dot_apis_dot_get__model__metadata__pb2
-from tensorflow_serving.apis import inference_pb2 as tensorflow__serving_dot_apis_dot_inference__pb2
-from tensorflow_serving.apis import predict_pb2 as tensorflow__serving_dot_apis_dot_predict__pb2
-from tensorflow_serving.apis import regression_pb2 as tensorflow__serving_dot_apis_dot_regression__pb2
+from tensorflow_serving.apis import (
+  classification_pb2 as tensorflow__serving_dot_apis_dot_classification__pb2,
+)
+from tensorflow_serving.apis import (
+  get_model_metadata_pb2 as tensorflow__serving_dot_apis_dot_get__model__metadata__pb2,
+)
+from tensorflow_serving.apis import (
+  inference_pb2 as tensorflow__serving_dot_apis_dot_inference__pb2,
+)
+from tensorflow_serving.apis import (
+  predict_pb2 as tensorflow__serving_dot_apis_dot_predict__pb2,
+)
+from tensorflow_serving.apis import (
+  regression_pb2 as tensorflow__serving_dot_apis_dot_regression__pb2,
+)
 
 
-class PredictionServiceStub(object):
-  """open source marker; do not remove
-  PredictionService provides access to machine-learned models loaded by
-  model_servers.
+class PredictionServiceStub:
+  """PredictionService provides access to machine-learned models loaded by model_servers.
+
+  open source marker; do not remove
   """
 
   def __init__(self, channel):
@@ -64,43 +74,38 @@ def __init__(self, channel):
         )
 
 
-class PredictionServiceServicer(object):
-  """open source marker; do not remove
-  PredictionService provides access to machine-learned models loaded by
-  model_servers.
+class PredictionServiceServicer:
+  """PredictionService provides access to machine-learned models loaded by model_servers.
+
+  open source marker; do not remove
   """
 
-  def Classify(self, request, context):
-    """Classify.
-    """
+  def Classify(self, request, context): # noqa: ARG002
+    """Classify."""
     context.set_code(grpc.StatusCode.UNIMPLEMENTED)
     context.set_details('Method not implemented!')
     raise NotImplementedError('Method not implemented!')
 
-  def Regress(self, request, context):
-    """Regress.
-    """
+  def Regress(self, request, context): # noqa: ARG002
+    """Regress."""
     context.set_code(grpc.StatusCode.UNIMPLEMENTED)
     context.set_details('Method not implemented!')
     raise NotImplementedError('Method not implemented!')
 
-  def Predict(self, request, context):
-    """Predict -- provides access to loaded TensorFlow model.
-    """
+  def Predict(self, request, context): # noqa: ARG002
+    """Predict -- provides access to loaded TensorFlow model."""
     context.set_code(grpc.StatusCode.UNIMPLEMENTED)
     context.set_details('Method not implemented!')
     raise NotImplementedError('Method not implemented!')
 
-  def MultiInference(self, request, context):
-    """MultiInference API for multi-headed models.
-    """
+  def MultiInference(self, request, context): # noqa: ARG002
+    """MultiInference API for multi-headed models."""
     context.set_code(grpc.StatusCode.UNIMPLEMENTED)
     context.set_details('Method not implemented!')
     raise NotImplementedError('Method not implemented!')
 
-  def GetModelMetadata(self, request, context):
-    """GetModelMetadata - provides access to metadata for loaded models.
-    """
+  def GetModelMetadata(self, request, context): # noqa: ARG002
+    """GetModelMetadata - provides access to metadata for loaded models."""
     context.set_code(grpc.StatusCode.UNIMPLEMENTED)
     context.set_details('Method not implemented!')
     raise NotImplementedError('Method not implemented!')
diff --git a/tensorflow_serving/batching/test_util/matrix_half_plus_two_saved_model.py b/tensorflow_serving/batching/test_util/matrix_half_plus_two_saved_model.py
index d111459009c..2c405dbd459 100644
--- a/tensorflow_serving/batching/test_util/matrix_half_plus_two_saved_model.py
+++ b/tensorflow_serving/batching/test_util/matrix_half_plus_two_saved_model.py
@@ -14,6 +14,7 @@
 # ==============================================================================
 
 import tensorflow.compat.v1 as tf
+
 FLAGS = tf.app.flags.FLAGS
 
 tf.app.flags.DEFINE_string("output_dir", "/tmp/matrix_half_plus_two/1",
@@ -21,14 +22,15 @@
 
 
 def _generate_saved_model_for_matrix_half_plus_two(export_dir):
-  """Creates SavedModel for half plus two model that accepts batches of
-       3*3 matrices.
-       The model divides all elements in each matrix by 2 and adds 2 to them.
-       So, for one input matrix [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
-       the result will be [[2.5, 3, 3.5], [4, 4.5, 5], [5.5, 6, 6.5]].
-    Args:
-      export_dir: The directory where to write SavedModel files.
-    """
+  """Creates SavedModel for half plus two model that accepts batches of 3*3 matrices.
+
+     The model divides all elements in each matrix by 2 and adds 2 to them.
+     So, for one input matrix [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
+     the result will be [[2.5, 3, 3.5], [4, 4.5, 5], [5.5, 6, 6.5]].
+
+  Args:
+    export_dir: The directory where to write SavedModel files.
+  """
   builder = tf.saved_model.builder.SavedModelBuilder(export_dir)
   with tf.Session() as session:
     x = tf.placeholder(tf.float32, shape=[None, 3, 3], name="x")
diff --git a/tensorflow_serving/example/mnist_client.py b/tensorflow_serving/example/mnist_client.py
index fd90af69b2d..c4d4b5ba581 100644
--- a/tensorflow_serving/example/mnist_client.py
+++ b/tensorflow_serving/example/mnist_client.py
@@ -25,19 +25,16 @@
     mnist_client.py --num_tests=100 --server=localhost:9000
 """
 
-from __future__ import print_function
 
 import sys
 import threading
 
 import grpc
+import mnist_input_data
 import numpy
 import tensorflow as tf
 
-from tensorflow_serving.apis import predict_pb2
-from tensorflow_serving.apis import prediction_service_pb2_grpc
-import mnist_input_data
-
+from tensorflow_serving.apis import predict_pb2, prediction_service_pb2_grpc
 
 tf.compat.v1.app.flags.DEFINE_integer(
     'concurrency', 1, 'maximum number of concurrent inference requests')
@@ -48,7 +45,7 @@
 FLAGS = tf.compat.v1.app.flags.FLAGS
 
 
-class _ResultCounter(object):
+class _ResultCounter:
   """Counter for the prediction results."""
 
   def __init__(self, num_tests, concurrency):
@@ -92,6 +89,7 @@ def _create_rpc_callback(label, result_counter):
   Args:
     label: The correct label for the predicted example.
     result_counter: Counter for the prediction result.
+
   Returns:
     The callback function.
   """
diff --git a/tensorflow_serving/example/mnist_input_data.py b/tensorflow_serving/example/mnist_input_data.py
index 3e8021a2435..61b61d167ad 100644
--- a/tensorflow_serving/example/mnist_input_data.py
+++ b/tensorflow_serving/example/mnist_input_data.py
@@ -17,7 +17,6 @@
 
 """Functions for downloading and reading MNIST data."""
 
-from __future__ import print_function
 
 import gzip
 import os
@@ -42,7 +41,7 @@ def maybe_download(filename, work_directory):
   if not os.path.exists(filepath):
     filepath, _ = urllib.request.urlretrieve(SOURCE_URL + filename, filepath)
     statinfo = os.stat(filepath)
-    print('Successfully downloaded %s %d bytes.' % (filename, statinfo.st_size))
+    print(f'Successfully downloaded {filename} {statinfo.st_size} bytes.')
   return filepath
 
 
@@ -53,20 +52,19 @@ def _read32(bytestream):
 
 def extract_images(filename):
   """Extract the images into a 4D uint8 numpy array [index, y, x, depth]."""
-  print('Extracting %s' % filename)
+  print(f'Extracting {filename}')
   with gzip.open(filename) as bytestream:
     magic = _read32(bytestream)
     if magic != 2051:
       raise ValueError(
-          'Invalid magic number %d in MNIST image file: %s' %
-          (magic, filename))
+          f'Invalid magic number {magic} in MNIST image file: {filename}'
+      )
     num_images = _read32(bytestream)
     rows = _read32(bytestream)
     cols = _read32(bytestream)
     buf = bytestream.read(rows * cols * num_images)
     data = numpy.frombuffer(buf, dtype=numpy.uint8)
-    data = data.reshape(num_images, rows, cols, 1)
-    return data
+    return data.reshape(num_images, rows, cols, 1)
 
 
 def dense_to_one_hot(labels_dense, num_classes=10):
@@ -80,13 +78,13 @@ def dense_to_one_hot(labels_dense, num_classes=10):
 
 def extract_labels(filename, one_hot=False):
   """Extract the labels into a 1D uint8 numpy array [index]."""
-  print('Extracting %s' % filename)
+  print(f'Extracting {filename}')
   with gzip.open(filename) as bytestream:
     magic = _read32(bytestream)
     if magic != 2049:
       raise ValueError(
-          'Invalid magic number %d in MNIST label file: %s' %
-          (magic, filename))
+          f'Invalid magic number {magic} in MNIST label file: {filename}'
+      )
     num_items = _read32(bytestream)
     buf = bytestream.read(num_items)
     labels = numpy.frombuffer(buf, dtype=numpy.uint8)
@@ -95,19 +93,17 @@ def extract_labels(filename, one_hot=False):
     return labels
 
 
-class DataSet(object):
+class DataSet:
   """Class encompassing test, validation and training MNIST data set."""
 
   def __init__(self, images, labels, fake_data=False, one_hot=False):
     """Construct a DataSet. one_hot arg is used only if fake_data is true."""
-
     if fake_data:
       self._num_examples = 10000
       self.one_hot = one_hot
     else:
       assert images.shape[0] == labels.shape[0], (
-          'images.shape: %s labels.shape: %s' % (images.shape,
-                                                 labels.shape))
+          f'images.shape: {images.shape} labels.shape: {labels.shape}')
       self._num_examples = images.shape[0]
 
       # Convert shape from [num examples, rows, columns, depth]
@@ -157,7 +153,7 @@ def next_batch(self, batch_size, fake_data=False):
       self._epochs_completed += 1
       # Shuffle the data
       perm = numpy.arange(self._num_examples)
-      numpy.random.shuffle(perm)
+      numpy.random.default_rng().shuffle(perm)
       self._images = self._images[perm]
       self._labels = self._labels[perm]
       # Start next epoch
@@ -171,7 +167,7 @@ def next_batch(self, batch_size, fake_data=False):
 def read_data_sets(train_dir, fake_data=False, one_hot=False):
   """Return training, validation and testing data sets."""
 
-  class DataSets(object):
+  class DataSets:
     pass
 
   data_sets = DataSets()
diff --git a/tensorflow_serving/example/mnist_saved_model.py b/tensorflow_serving/example/mnist_saved_model.py
index 0bb3053893c..3cd608ed914 100644
--- a/tensorflow_serving/example/mnist_saved_model.py
+++ b/tensorflow_serving/example/mnist_saved_model.py
@@ -25,17 +25,14 @@
     export_dir
 """
 
-from __future__ import print_function
 
 import os
 import sys
 
+import mnist_input_data
 import tensorflow as tf
-
 from tensorflow.python.ops import lookup_ops
 
-import mnist_input_data
-
 tf.compat.v1.app.flags.DEFINE_integer('training_iteration', 1000,
                                       'number of training iterations.')
 tf.compat.v1.app.flags.DEFINE_integer('model_version', 1,
@@ -85,11 +82,12 @@ def main(_):
     train_step.run(feed_dict={x: batch[0], y_: batch[1]})
   correct_prediction = tf.equal(tf.argmax(y, 1), tf.argmax(y_, 1))
   accuracy = tf.math.reduce_mean(tf.cast(correct_prediction, 'float'))
-  print('training accuracy %g' % sess.run(
+  print(f'training accuracy {sess.run(
       accuracy, feed_dict={
           x: mnist.test.images,
           y_: mnist.test.labels
-      }))
+      }):g}'
+  )
   print('Done training!')
 
   # Export model
diff --git a/tensorflow_serving/example/resnet_client.py b/tensorflow_serving/example/resnet_client.py
index b531166a91d..f04d5dda548 100644
--- a/tensorflow_serving/example/resnet_client.py
+++ b/tensorflow_serving/example/resnet_client.py
@@ -27,15 +27,14 @@
     resnet_client.py
 """
 
-from __future__ import print_function
 
 import base64
 import io
 import json
 
 import numpy as np
-from PIL import Image
 import requests
+from PIL import Image
 
 # The server URL specifies the endpoint of your server running the ResNet
 # model with the name "resnet" and using the predict interface.
@@ -57,7 +56,7 @@ def main():
   if MODEL_ACCEPT_JPG:
     # Compose a JSON Predict request (send JPEG image in base64).
     jpeg_bytes = base64.b64encode(dl_request.content).decode('utf-8')
-    predict_request = '{"instances" : [{"b64": "%s"}]}' % jpeg_bytes
+    predict_request = f'{{"instances" : [{{"b64": "{jpeg_bytes}"}}]}}'
   else:
     # Compose a JOSN Predict request (send the image tensor).
     jpeg_rgb = Image.open(io.BytesIO(dl_request.content))
@@ -79,8 +78,7 @@ def main():
     total_time += response.elapsed.total_seconds()
     prediction = response.json()['predictions'][0]
 
-  print('Prediction class: {}, avg latency: {} ms'.format(
-      np.argmax(prediction), (total_time * 1000) / num_requests))
+  print(f'Prediction class: {np.argmax(prediction)}, avg latency: {(total_time * 1000) / num_requests} ms')
 
 
 if __name__ == '__main__':
diff --git a/tensorflow_serving/example/resnet_client_grpc.py b/tensorflow_serving/example/resnet_client_grpc.py
index 96e22ee8d2c..0d721815260 100644
--- a/tensorflow_serving/example/resnet_client_grpc.py
+++ b/tensorflow_serving/example/resnet_client_grpc.py
@@ -12,22 +12,18 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ==============================================================================
-"""Send JPEG image to tensorflow_model_server loaded with ResNet model.
+"""Send JPEG image to tensorflow_model_server loaded with ResNet model."""
 
-"""
-
-from __future__ import print_function
 
 import io
 
 import grpc
 import numpy as np
-from PIL import Image
 import requests
 import tensorflow as tf
+from PIL import Image
 
-from tensorflow_serving.apis import predict_pb2
-from tensorflow_serving.apis import prediction_service_pb2_grpc
+from tensorflow_serving.apis import predict_pb2, prediction_service_pb2_grpc
 
 # The image URL is the location of the image we should send to the server
 IMAGE_URL = 'https://tensorflow.org/images/blogs/serving/cat.jpg'
@@ -71,7 +67,7 @@ def main(_):
       tf.make_tensor_proto(data))
   result = stub.Predict(request, 10.0)  # 10 secs timeout
   result = result.outputs['activation_49'].float_val
-  print('Prediction class: {}'.format(np.argmax(result)))
+  print(f'Prediction class: {np.argmax(result)}')
 
 
 if __name__ == '__main__':
diff --git a/tensorflow_serving/example/resnet_warmup.py b/tensorflow_serving/example/resnet_warmup.py
index c7a6af151fb..082958e3890 100644
--- a/tensorflow_serving/example/resnet_warmup.py
+++ b/tensorflow_serving/example/resnet_warmup.py
@@ -14,36 +14,34 @@
 # ==============================================================================
 """Creates the tf_serving_warmup_requests file to warm up a ResNet SavedModel.
 
-   1. Invoke this script passing in the saved_model directory (including version
-        folder, the folder containing saved_model.pb) as an argument.
-   2. Restart tensorflow_model_server.
+1. Invoke this script passing in the saved_model directory (including version
+folder, the folder containing saved_model.pb) as an argument.
+2. Restart tensorflow_model_server.
 
-   If unsure of the model directory, look for the output:
-   'No warmup data file found at' in the tensorflow_model_server
-   startup log
+If unsure of the model directory, look for the output:
+'No warmup data file found at' in the tensorflow_model_server
+startup log
 
-   After the script is run, and tensorflow_model_server is restarted, to verify
-   it is working look for the output:
-   'Starting to read warmup data for model at' and 'Finished reading warmup data
-   for model at' in the tensorflow_model_server startup log
+After the script is run, and tensorflow_model_server is restarted, to verify
+it is working look for the output:
+'Starting to read warmup data for model at' and 'Finished reading warmup data
+for model at' in the tensorflow_model_server startup log
 
-   Usage example:
-     python resnet_warmup.py saved_model_dir
+Usage example:
+python resnet_warmup.py saved_model_dir
 """
 
-from __future__ import print_function
 
 import io
 import os
 import sys
 
 import numpy as np
-from PIL import Image
 import requests
 import tensorflow as tf
-from tensorflow_serving.apis import predict_pb2
-from tensorflow_serving.apis import prediction_log_pb2
+from PIL import Image
 
+from tensorflow_serving.apis import predict_pb2, prediction_log_pb2
 
 # IMAGE_URLS are the locations of the images we use to warmup the model
 IMAGE_URLS = ['https://tensorflow.org/images/blogs/serving/cat.jpg',
@@ -64,8 +62,8 @@ def main():
 
   model_dir = sys.argv[-1]
   if not os.path.isdir(model_dir):
-    print('The saved model directory: %s does not exist. '
-          'Specify the path of an existing model.' % model_dir)
+    print(f'The saved model directory: {model_dir} does not exist. '
+          'Specify the path of an existing model.')
     sys.exit(-1)
 
   # Create the assets.extra directory, assuming model_dir is the versioned
@@ -100,8 +98,8 @@ def main():
           predict_log=prediction_log_pb2.PredictLog(request=request))
       writer.write(log.SerializeToString())
 
-  print('Created the file \'%s\', restart tensorflow_model_server to warmup '
-        'the ResNet SavedModel.' % warmup_file)
+  print(f'Created the file \'{warmup_file}\', restart tensorflow_model_server to warmup '
+        'the ResNet SavedModel.')
 
 if __name__ == '__main__':
   main()
diff --git a/tensorflow_serving/experimental/example/half_plus_two_with_rpop.py b/tensorflow_serving/experimental/example/half_plus_two_with_rpop.py
index 07fe685d139..936c14311b9 100644
--- a/tensorflow_serving/experimental/example/half_plus_two_with_rpop.py
+++ b/tensorflow_serving/experimental/example/half_plus_two_with_rpop.py
@@ -29,7 +29,9 @@
 
 import tensorflow.compat.v1 as tf
 
-from tensorflow_serving.experimental.tensorflow.ops.remote_predict.python.ops import remote_predict_ops
+from tensorflow_serving.experimental.tensorflow.ops.remote_predict.python.ops import (
+  remote_predict_ops,
+)
 
 tf.app.flags.DEFINE_string("output_dir", "/tmp/half_plus_two_with_rpop/1/",
                            "Savedmodel export path")
@@ -127,12 +129,8 @@ def main(_):
                                           FLAGS.target_address,
                                           FLAGS.remote_model_name)
   print(
-      "SavedModel generated at: %(dir)s with target_address: %(target_address)s"
-      ", remote_model_name: %(remote_model_name)s. " % {
-          "dir": FLAGS.output_dir,
-          "target_address": FLAGS.target_address,
-          "remote_model_name": FLAGS.remote_model_name
-      })
+      f"SavedModel generated at: {FLAGS.output_dir} with target_address: {FLAGS.target_address}"
+      f", remote_model_name: {FLAGS.remote_model_name}. ")
 
 
 if __name__ == "__main__":
diff --git a/tensorflow_serving/experimental/example/half_plus_two_with_rpop_client.py b/tensorflow_serving/experimental/example/half_plus_two_with_rpop_client.py
index 261c8a029dc..8e7800ad1dc 100644
--- a/tensorflow_serving/experimental/example/half_plus_two_with_rpop_client.py
+++ b/tensorflow_serving/experimental/example/half_plus_two_with_rpop_client.py
@@ -36,13 +36,11 @@
 tensorflow_model_server --port=8500 --model_config_file=/tmp/config_file.txt
 
 """
-from __future__ import print_function
 
 import grpc
 import tensorflow.compat.v1 as tf
 
-from tensorflow_serving.apis import predict_pb2
-from tensorflow_serving.apis import prediction_service_pb2_grpc
+from tensorflow_serving.apis import predict_pb2, prediction_service_pb2_grpc
 
 tf.app.flags.DEFINE_string('server', 'localhost:8500',
                            'PredictionService host:port')
diff --git a/tensorflow_serving/experimental/example/remote_predict_client.py b/tensorflow_serving/experimental/example/remote_predict_client.py
index ccf98a12c2c..7c06b57650a 100644
--- a/tensorflow_serving/experimental/example/remote_predict_client.py
+++ b/tensorflow_serving/experimental/example/remote_predict_client.py
@@ -17,11 +17,12 @@
 Example client code which calls the Remote Predict Op directly.
 """
 
-from __future__ import print_function
 
 import tensorflow.compat.v1 as tf
 
-from tensorflow_serving.experimental.tensorflow.ops.remote_predict.python.ops import remote_predict_ops
+from tensorflow_serving.experimental.tensorflow.ops.remote_predict.python.ops import (
+  remote_predict_ops,
+)
 
 tf.app.flags.DEFINE_string("input_tensor_aliases", "x",
                            "Aliases of input tensors")
@@ -40,7 +41,7 @@
 FLAGS = tf.app.flags.FLAGS
 
 
-def main(unused_argv):
+def main(unused_argv): # noqa: ARG001
   print("Call remote_predict_op")
   results = remote_predict_ops.run(
       [FLAGS.input_tensor_aliases],
diff --git a/tensorflow_serving/experimental/tensorflow/ops/remote_predict/__init__.py b/tensorflow_serving/experimental/tensorflow/ops/remote_predict/__init__.py
index c1597decea2..11a4bde193b 100644
--- a/tensorflow_serving/experimental/tensorflow/ops/remote_predict/__init__.py
+++ b/tensorflow_serving/experimental/tensorflow/ops/remote_predict/__init__.py
@@ -16,10 +16,11 @@
 
 @@run
 """
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
+
 from tensorflow.python.util.all_util import remove_undocumented
-from tensorflow_serving.experimental.tensorflow.ops.remote_predict.python.ops.remote_predict_ops import run
+
+from tensorflow_serving.experimental.tensorflow.ops.remote_predict.python.ops.remote_predict_ops import (
+    run,
+)
 
 remove_undocumented(__name__)
diff --git a/tensorflow_serving/experimental/tensorflow/ops/remote_predict/ops/remote_predict_op.cc b/tensorflow_serving/experimental/tensorflow/ops/remote_predict/ops/remote_predict_op.cc
index def975ac60d..0710192f3e7 100644
--- a/tensorflow_serving/experimental/tensorflow/ops/remote_predict/ops/remote_predict_op.cc
+++ b/tensorflow_serving/experimental/tensorflow/ops/remote_predict/ops/remote_predict_op.cc
@@ -87,7 +87,7 @@ fail_op_on_rpc_error: If set true, the Op fails if the rpc fails, and returns
   Set true by default.
 max_rpc_deadline_millis: The rpc deadline for remote predict. The actual
 deadline is min(incoming_rpc_deadline, max_rpc_deadline_millis).
-signature_name: the signature def for remote graph inference, defaulting to 
+signature_name: the signature def for remote graph inference, defaulting to
 "serving_default".
 target_address: Address of the server hosting the remote graph.
 model_name: Model name of the remote TF graph.
@@ -102,7 +102,7 @@ output_tensor_aliases: Tensor of strings for the output tensor alias names to
 status_code: Returns the status code of the rpc call; basically converting
   tensorflow::error::Code to it's int value, so 0 means OK.
 status_error_message: Returns the error message in the rpc status.
-output_tensors: Tensors returned by the Predict call on the remote graph, which 
+output_tensors: Tensors returned by the Predict call on the remote graph, which
   are in the same order as output_tensor_aliases.
 output_types: A list of types of the output tensors. Length of this list should
   be equal to the length of 'output_tensor_aliases'.
diff --git a/tensorflow_serving/experimental/tensorflow/ops/remote_predict/python/ops/remote_predict_ops.py b/tensorflow_serving/experimental/tensorflow/ops/remote_predict/python/ops/remote_predict_ops.py
index b2854503459..5c613455c8d 100644
--- a/tensorflow_serving/experimental/tensorflow/ops/remote_predict/python/ops/remote_predict_ops.py
+++ b/tensorflow_serving/experimental/tensorflow/ops/remote_predict/python/ops/remote_predict_ops.py
@@ -14,16 +14,18 @@
 # ==============================================================================
 """Operations for RemotePredict."""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import os.path
+
 import tensorflow.compat.v1 as tf
 
-from tensorflow_serving.experimental.tensorflow.ops.remote_predict.ops import gen_remote_predict_op
+from tensorflow_serving.experimental.tensorflow.ops.remote_predict.ops import (
+  gen_remote_predict_op,
+)
+
 # pylint: disable=wildcard-import
-from tensorflow_serving.experimental.tensorflow.ops.remote_predict.ops.gen_remote_predict_op import *
+from tensorflow_serving.experimental.tensorflow.ops.remote_predict.ops.gen_remote_predict_op import *  # noqa: F403
+
 # pylint: enable=wildcard-import
 
 _remote_predict_op_module = tf.load_op_library(
diff --git a/tensorflow_serving/g3doc/saved_model_warmup.md b/tensorflow_serving/g3doc/saved_model_warmup.md
index 1d4345ae758..838d0966ff8 100644
--- a/tensorflow_serving/g3doc/saved_model_warmup.md
+++ b/tensorflow_serving/g3doc/saved_model_warmup.md
@@ -48,5 +48,3 @@ Warmup data can be added in two ways:
     `YourSavedModel/assets.extra/tf_serving_warmup_requests` based on the
     validation requests provided via
     [RequestSpec](https://www.tensorflow.org/tfx/guide/infra_validator#requestspec).
-
-
diff --git a/tensorflow_serving/model_servers/profiler_client.py b/tensorflow_serving/model_servers/profiler_client.py
index c4573842980..65bb98f361c 100644
--- a/tensorflow_serving/model_servers/profiler_client.py
+++ b/tensorflow_serving/model_servers/profiler_client.py
@@ -14,12 +14,8 @@
 # ==============================================================================
 """Simple client to send profiling request to ModelServer."""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import tensorflow as tf
-
 from tensorflow.python.profiler import profiler_client
 
 
diff --git a/tensorflow_serving/model_servers/tensorflow_model_server_test.py b/tensorflow_serving/model_servers/tensorflow_model_server_test.py
index 8ad8f91b153..0220f7ae361 100644
--- a/tensorflow_serving/model_servers/tensorflow_model_server_test.py
+++ b/tensorflow_serving/model_servers/tensorflow_model_server_test.py
@@ -15,9 +15,6 @@
 
 """Tests for tensorflow_model_server."""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import json
 import os
@@ -25,7 +22,6 @@
 import sys
 import time
 
-
 # During the creation of the 'tensorflow_serving' package, bazel emits a python
 # 'tensorflow' module which contains its dependencies (e.g. example.proto).
 # Since bazel python libraries take precedence in sys.path and the created
@@ -37,19 +33,20 @@
 
 
 import grpc
-from six.moves import range
 import tensorflow.compat.v1 as tf
-
 from tensorflow.python.platform import flags
 from tensorflow.python.profiler import profiler_client
 from tensorflow.python.saved_model import signature_constants
-from tensorflow_serving.apis import classification_pb2
-from tensorflow_serving.apis import get_model_metadata_pb2
-from tensorflow_serving.apis import get_model_status_pb2
-from tensorflow_serving.apis import inference_pb2
-from tensorflow_serving.apis import model_service_pb2_grpc
-from tensorflow_serving.apis import prediction_service_pb2_grpc
-from tensorflow_serving.apis import regression_pb2
+
+from tensorflow_serving.apis import (
+  classification_pb2,
+  get_model_metadata_pb2,
+  get_model_status_pb2,
+  inference_pb2,
+  model_service_pb2_grpc,
+  prediction_service_pb2_grpc,
+  regression_pb2,
+)
 from tensorflow_serving.model_servers.test_util import tensorflow_model_server_test_base
 
 FLAGS = flags.FLAGS
@@ -74,7 +71,7 @@ def __BuildModelConfigFile(self):
     in the configuration template file and writes it out to another file
     used by the test.
     """
-    with open(self._GetGoodModelConfigTemplate(), 'r') as template_file:
+    with open(self._GetGoodModelConfigTemplate()) as template_file:
       config = template_file.read().replace('${TEST_HALF_PLUS_TWO_DIR}',
                                             self._GetSavedModelBundlePath())
       config = config.replace('${TEST_HALF_PLUS_THREE_DIR}',
@@ -314,7 +311,6 @@ def testBadModelConfig(self):
 
   def testModelConfigReload(self):
     """Test model server polls filesystem for model configuration."""
-
     base_config_proto = """
     model_config_list: {{
       config: {{
@@ -368,7 +364,6 @@ def testModelConfigReload(self):
 
   def testModelConfigReloadWithZeroPollPeriod(self):
     """Test model server does not poll filesystem for model config."""
-
     base_config_proto = """
     model_config_list: {{
       config: {{
@@ -442,7 +437,7 @@ def testClassifyREST(self):
                                                      model_path)[2].split(':')
 
     # Prepare request
-    url = 'http://{}:{}/v1/models/default:classify'.format(host, port)
+    url = f'http://{host}:{port}/v1/models/default:classify'
     json_req = {'signature_name': 'classify_x_to_y', 'examples': [{'x': 2.0}]}
 
     # Send request
@@ -450,7 +445,7 @@ def testClassifyREST(self):
     try:
       resp_data = tensorflow_model_server_test_base.CallREST(url, json_req)
     except Exception as e:  # pylint: disable=broad-except
-      self.fail('Request failed with error: {}'.format(e))
+      self.fail(f'Request failed with error: {e}')
 
     # Verify response
     self.assertEqual(json.loads(resp_data.decode()), {'results': [[['', 3.0]]]})
@@ -462,7 +457,7 @@ def testRegressREST(self):
                                                      model_path)[2].split(':')
 
     # Prepare request
-    url = 'http://{}:{}/v1/models/default:regress'.format(host, port)
+    url = f'http://{host}:{port}/v1/models/default:regress'
     json_req = {'signature_name': 'regress_x_to_y', 'examples': [{'x': 2.0}]}
 
     # Send request
@@ -470,7 +465,7 @@ def testRegressREST(self):
     try:
       resp_data = tensorflow_model_server_test_base.CallREST(url, json_req)
     except Exception as e:  # pylint: disable=broad-except
-      self.fail('Request failed with error: {}'.format(e))
+      self.fail(f'Request failed with error: {e}')
 
     # Verify response
     self.assertEqual(json.loads(resp_data.decode()), {'results': [3.0]})
@@ -482,7 +477,7 @@ def testPredictREST(self):
                                                      model_path)[2].split(':')
 
     # Prepare request
-    url = 'http://{}:{}/v1/models/default:predict'.format(host, port)
+    url = f'http://{host}:{port}/v1/models/default:predict'
     json_req = {'instances': [2.0, 3.0, 4.0]}
 
     # Send request
@@ -490,7 +485,7 @@ def testPredictREST(self):
     try:
       resp_data = tensorflow_model_server_test_base.CallREST(url, json_req)
     except Exception as e:  # pylint: disable=broad-except
-      self.fail('Request failed with error: {}'.format(e))
+      self.fail(f'Request failed with error: {e}')
 
     # Verify response
     self.assertEqual(
@@ -503,7 +498,7 @@ def testPredictColumnarREST(self):
                                                      model_path)[2].split(':')
 
     # Prepare request
-    url = 'http://{}:{}/v1/models/default:predict'.format(host, port)
+    url = f'http://{host}:{port}/v1/models/default:predict'
     json_req = {'inputs': [2.0, 3.0, 4.0]}
 
     # Send request
@@ -511,7 +506,7 @@ def testPredictColumnarREST(self):
     try:
       resp_data = tensorflow_model_server_test_base.CallREST(url, json_req)
     except Exception as e:  # pylint: disable=broad-except
-      self.fail('Request failed with error: {}'.format(e))
+      self.fail(f'Request failed with error: {e}')
 
     # Verify response
     self.assertEqual(
@@ -524,14 +519,14 @@ def testGetStatusREST(self):
                                                      model_path)[2].split(':')
 
     # Prepare request
-    url = 'http://{}:{}/v1/models/default'.format(host, port)
+    url = f'http://{host}:{port}/v1/models/default'
 
     # Send request
     resp_data = None
     try:
       resp_data = tensorflow_model_server_test_base.CallREST(url, None)
     except Exception as e:  # pylint: disable=broad-except
-      self.fail('Request failed with error: {}'.format(e))
+      self.fail(f'Request failed with error: {e}')
 
     # Verify response
     self.assertEqual(
@@ -553,14 +548,14 @@ def testGetModelMetadataREST(self):
                                                      model_path)[2].split(':')
 
     # Prepare request
-    url = 'http://{}:{}/v1/models/default/metadata'.format(host, port)
+    url = f'http://{host}:{port}/v1/models/default/metadata'
 
     # Send request
     resp_data = None
     try:
       resp_data = tensorflow_model_server_test_base.CallREST(url, None)
     except Exception as e:  # pylint: disable=broad-except
-      self.fail('Request failed with error: {}'.format(e))
+      self.fail(f'Request failed with error: {e}')
 
     try:
       model_metadata_file = self._GetModelMetadataFile()
@@ -576,7 +571,7 @@ def testGetModelMetadataREST(self):
                 json.loads(resp_data.decode())),
             tensorflow_model_server_test_base.SortedObject(expected_metadata))
     except Exception as e:  # pylint: disable=broad-except
-      self.fail('Request failed with error: {}'.format(e))
+      self.fail(f'Request failed with error: {e}')
 
   def testPrometheusEndpoint(self):
     """Test ModelStatus implementation over REST API with columnar inputs."""
@@ -587,14 +582,14 @@ def testPrometheusEndpoint(self):
         monitoring_config_file=self._GetMonitoringConfigFile())[2].split(':')
 
     # Prepare request
-    url = 'http://{}:{}/monitoring/prometheus/metrics'.format(host, port)
+    url = f'http://{host}:{port}/monitoring/prometheus/metrics'
 
     # Send request
     resp_data = None
     try:
       resp_data = tensorflow_model_server_test_base.CallREST(url, None)
     except Exception as e:  # pylint: disable=broad-except
-      self.fail('Request failed with error: {}'.format(e))
+      self.fail(f'Request failed with error: {e}')
 
     # Verify that there should be some metric type information.
     self.assertIn('# TYPE',
@@ -604,7 +599,7 @@ def testPredictUDS(self):
     """Test saved model prediction over a Unix domain socket."""
     _ = TensorflowModelServerTest.RunServer('default',
                                             self._GetSavedModelBundlePath())
-    model_server_address = 'unix:%s' % GRPC_SOCKET_PATH
+    model_server_address = f'unix:{GRPC_SOCKET_PATH}'
     self.VerifyPredictRequest(
         model_server_address,
         expected_output=3.0,
@@ -655,9 +650,9 @@ def test_tf_saved_model_save_multiple_signatures(self):
     base_path = os.path.join(self.get_temp_dir(), 'tf_saved_model_save')
     export_path = os.path.join(base_path, '00000123')
     root = tf.train.Checkpoint()
-    root.f = tf.function(lambda x: {'y': 1.},
+    root.f = tf.function(lambda _: {'y': 1.},
                          input_signature=[tf.TensorSpec(None, tf.float32)])
-    root.g = tf.function(lambda x: {'y': 2.},
+    root.g = tf.function(lambda _: {'y': 2.},
                          input_signature=[tf.TensorSpec(None, tf.float32)])
     tf.saved_model.experimental.save(
         root, export_path,
@@ -735,22 +730,19 @@ def test_distrat_sequential_keras_saved_model_save(self):
 
   def test_profiler_service_with_valid_trace_request(self):
     """Test integration with profiler service by sending tracing requests."""
-
     # Start model server
     model_path = self._GetSavedModelBundlePath()
     _, grpc_addr, rest_addr = TensorflowModelServerTest.RunServer(
         'default', model_path)
 
     # Prepare predict request
-    url = 'http://{}/v1/models/default:predict'.format(rest_addr)
+    url = f'http://{rest_addr}/v1/models/default:predict'
     json_req = '{"instances": [2.0, 3.0, 4.0]}'
 
     # In a subprocess, send a REST predict request every second for 3 seconds
-    exec_command = ("wget {} --content-on-error=on -O- --post-data  '{}' "
-                    "--header='Content-Type:application/json'").format(
-                        url, json_req)
-    repeat_command = 'for n in {{1..3}}; do {} & sleep 1; done;'.format(
-        exec_command)
+    exec_command = (f"wget {url} --content-on-error=on -O- --post-data  '{json_req}' "
+                    "--header='Content-Type:application/json'")
+    repeat_command = f'for n in {{1..3}}; do {exec_command} & sleep 1; done;'
     proc = subprocess.Popen(
         repeat_command,
         shell=True,
@@ -770,7 +762,7 @@ def test_profiler_service_with_valid_trace_request(self):
 
     #  Log stdout & stderr of subprocess issuing predict requests for debugging
     out, err = proc.communicate()
-    print("stdout: '{}' | stderr: '{}'".format(out, err))
+    print(f"stdout: '{out}' | stderr: '{err}'")
 
   def test_tf_text(self):
     """Test TF Text."""
diff --git a/tensorflow_serving/model_servers/tensorflow_model_server_test_client.py b/tensorflow_serving/model_servers/tensorflow_model_server_test_client.py
index 11274737ec7..e71a22fdce2 100644
--- a/tensorflow_serving/model_servers/tensorflow_model_server_test_client.py
+++ b/tensorflow_serving/model_servers/tensorflow_model_server_test_client.py
@@ -14,18 +14,13 @@
 # ==============================================================================
 """Manual test client for tensorflow_model_server."""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import grpc
 import tensorflow as tf
-
 from tensorflow.core.framework import types_pb2
 from tensorflow.python.platform import flags
-from tensorflow_serving.apis import predict_pb2
-from tensorflow_serving.apis import prediction_service_pb2_grpc
 
+from tensorflow_serving.apis import predict_pb2, prediction_service_pb2_grpc
 
 tf.compat.v1.app.flags.DEFINE_string('server', 'localhost:8500',
                                      'inception_inference service host:port')
diff --git a/tensorflow_serving/model_servers/test_util/tensorflow_model_server_test_base.py b/tensorflow_serving/model_servers/test_util/tensorflow_model_server_test_base.py
index 1a0b250a12d..b97ce643456 100644
--- a/tensorflow_serving/model_servers/test_util/tensorflow_model_server_test_base.py
+++ b/tensorflow_serving/model_servers/test_util/tensorflow_model_server_test_base.py
@@ -15,9 +15,6 @@
 
 """Tests for tensorflow_model_server."""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import atexit
 import json
@@ -28,15 +25,13 @@
 import time
 
 import grpc
-from six.moves import range
-from six.moves import urllib
 import tensorflow as tf
-
+from six.moves import urllib
 from tensorflow.core.framework import types_pb2
 from tensorflow.python.platform import flags
 from tensorflow.python.saved_model import signature_constants
-from tensorflow_serving.apis import predict_pb2
-from tensorflow_serving.apis import prediction_service_pb2_grpc
+
+from tensorflow_serving.apis import predict_pb2, prediction_service_pb2_grpc
 
 FLAGS = flags.FLAGS
 
@@ -50,8 +45,7 @@
 def SetVirtualCpus(num_virtual_cpus):
   """Create virtual CPU devices if they haven't yet been created."""
   if num_virtual_cpus < 1:
-    raise ValueError('`num_virtual_cpus` must be at least 1 not %r' %
-                     (num_virtual_cpus,))
+    raise ValueError(f'`num_virtual_cpus` must be at least 1 not {num_virtual_cpus!r}')
   physical_devices = tf.config.experimental.list_physical_devices('CPU')
   if not physical_devices:
     raise RuntimeError('No CPUs found')
@@ -64,8 +58,9 @@ def SetVirtualCpus(num_virtual_cpus):
         physical_devices[0], virtual_devices)
   else:
     if len(configs) < num_virtual_cpus:
-      raise RuntimeError('Already configured with %d < %d virtual CPUs' %
-                         (len(configs), num_virtual_cpus))
+      raise RuntimeError(
+        f'Already configured with {len(configs)} < {num_virtual_cpus} virtual CPUs'
+      )
 
 
 def PickUnusedPort():
@@ -85,7 +80,7 @@ def WaitForServerReady(port):
 
     try:
       # Send empty request to missing model
-      channel = grpc.insecure_channel('localhost:{}'.format(port))
+      channel = grpc.insecure_channel(f'localhost:{port}')
       stub = prediction_service_pb2_grpc.PredictionServiceStub(channel)
       stub.Predict(request, RPC_TIMEOUT)
     except grpc.RpcError as error:
@@ -97,18 +92,17 @@ def WaitForServerReady(port):
 
 def CallREST(url, req, max_attempts=60):
   """Returns HTTP response body from a REST API call."""
-  for attempt in range(max_attempts):
+  for attempt in range(max_attempts): # noqa: RET503
     try:
-      print('Attempt {}: Sending request to {} with data:\n{}'.format(
-          attempt, url, req))
+      print(f'Attempt {attempt}: Sending request to {url} with data:\n{req}')
       json_data = json.dumps(req).encode('utf-8') if req is not None else None
       resp = urllib.request.urlopen(urllib.request.Request(url, data=json_data))
       resp_data = resp.read()
-      print('Received response:\n{}'.format(resp_data))
+      print(f'Received response:\n{resp_data}')
       resp.close()
       return resp_data
     except Exception as e:  # pylint: disable=broad-except
-      print('Failed attempt {}. Error: {}'.format(attempt, e))
+      print(f'Failed attempt {attempt}. Error: {e}')
       if attempt == max_attempts - 1:
         raise
       print('Retrying...')
@@ -123,8 +117,7 @@ def SortedObject(obj):
     return sorted(SortedObject(x) for x in obj)
   if isinstance(obj, tuple):
     return list(sorted(SortedObject(x) for x in obj))
-  else:
-    return obj
+  return obj
 
 
 def GetArgsKey(*args, **kwargs):
@@ -188,9 +181,8 @@ def RunServer(
       return TensorflowModelServerTestBase.model_servers_dict[args_key]
     port = PickUnusedPort()
     rest_api_port = PickUnusedPort()
-    print(('Starting test server on port: {} for model_name: '
-           '{}/model_config_file: {}'.format(port, model_name,
-                                             model_config_file)))
+    print(f'Starting test server on port: {port} for model_name: '
+           f'{model_name}/model_config_file: {model_config_file}')
 
     command = os.path.join(
         TensorflowModelServerTestBase.TestSrcDirPath(model_server_path),
diff --git a/tensorflow_serving/servables/tensorflow/testdata/bad_model_config.txt b/tensorflow_serving/servables/tensorflow/testdata/bad_model_config.txt
index 6649d3fd44a..887d07c4356 100644
--- a/tensorflow_serving/servables/tensorflow/testdata/bad_model_config.txt
+++ b/tensorflow_serving/servables/tensorflow/testdata/bad_model_config.txt
@@ -1 +1 @@
-improperly formatted file
\ No newline at end of file
+improperly formatted file
diff --git a/tensorflow_serving/servables/tensorflow/testdata/export_bad_half_plus_two.py b/tensorflow_serving/servables/tensorflow/testdata/export_bad_half_plus_two.py
index b5b7bde74c7..5ba302957b9 100644
--- a/tensorflow_serving/servables/tensorflow/testdata/export_bad_half_plus_two.py
+++ b/tensorflow_serving/servables/tensorflow/testdata/export_bad_half_plus_two.py
@@ -34,7 +34,7 @@ def Export():
     # Calculate, y = a*x + b
     # here we use a placeholder 'x' which is fed at inference time.
     x = tf.placeholder(tf.float32)
-    y = tf.add(tf.multiply(a, x), b)
+    y = tf.add(tf.multiply(a, x), b) # noqa: F841
 
     # Export the model without signatures.
     # Note that the model is intentionally exported without using exporter,
diff --git a/tensorflow_serving/servables/tensorflow/testdata/export_counter.py b/tensorflow_serving/servables/tensorflow/testdata/export_counter.py
index c4ada219c92..e25526701a2 100644
--- a/tensorflow_serving/servables/tensorflow/testdata/export_counter.py
+++ b/tensorflow_serving/servables/tensorflow/testdata/export_counter.py
@@ -18,9 +18,6 @@
 reset_counter, to test Predict service.
 """
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import tensorflow as tf
 
@@ -97,7 +94,7 @@ def export_model(output_dir):
     save_model(sess, signature_def_map, output_dir)
 
 
-def main(unused_argv):
+def main(unused_argv): # noqa: ARG001
   export_model("/tmp/saved_model_counter/00000123")
 
 
diff --git a/tensorflow_serving/servables/tensorflow/testdata/parse_example_tflite.README b/tensorflow_serving/servables/tensorflow/testdata/parse_example_tflite.README
index d3fcb3d8d85..1b6a59f2654 100644
--- a/tensorflow_serving/servables/tensorflow/testdata/parse_example_tflite.README
+++ b/tensorflow_serving/servables/tensorflow/testdata/parse_example_tflite.README
@@ -19,4 +19,3 @@ and is updated using
 bazel run -c opt parse_example_tflite_with_string
 cp /tmp/parse_example_tflite parse_example_tflite/00000123/model.tflite
 ```
-
diff --git a/tensorflow_serving/servables/tensorflow/testdata/parse_example_tflite.py b/tensorflow_serving/servables/tensorflow/testdata/parse_example_tflite.py
index 17790e90b2d..86397ada26d 100644
--- a/tensorflow_serving/servables/tensorflow/testdata/parse_example_tflite.py
+++ b/tensorflow_serving/servables/tensorflow/testdata/parse_example_tflite.py
@@ -34,7 +34,6 @@
 import sys
 
 import tensorflow.compat.v1 as tf
-
 from tensorflow.lite.tools.signature import signature_def_utils
 
 FLAGS = None
@@ -87,14 +86,13 @@ def _generate_tflite_for_parse_example_with_string(export_dir):
     k = tf.saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY
     tflite_model = signature_def_utils.set_signature_defs(
         tflite_model, {k: predict_signature_def})
-    open(export_dir + "/model.tflite", "wb").write(tflite_model)
+    with open(export_dir + "/model.tflite", "wb") as fp:
+      fp.write(tflite_model)
 
 
 def main(_):
   _generate_tflite_for_parse_example_with_string(FLAGS.output_dir)
-  print("TFLite model generated at: %(dir)s" % {
-      "dir": FLAGS.output_dir
-  })
+  print(f"TFLite model generated at: {FLAGS.output_dir}")
 
 
 if __name__ == "__main__":
diff --git a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_three/00000123/assets/foo.txt b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_three/00000123/assets/foo.txt
index f9ff0366880..56c3e54a43f 100644
--- a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_three/00000123/assets/foo.txt
+++ b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_three/00000123/assets/foo.txt
@@ -1 +1 @@
-asset-file-contents
\ No newline at end of file
+asset-file-contents
diff --git a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two.py b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two.py
index fe05c062cf0..36755af3082 100644
--- a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two.py
+++ b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two.py
@@ -45,16 +45,12 @@
   --device=gpu
 """
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import argparse
 import os
 import sys
 
 import tensorflow.compat.v1 as tf
-
 from tensorflow.lite.tools.signature import signature_def_utils
 from tensorflow.python.lib.io import file_io
 
@@ -199,7 +195,8 @@ def get_serving_signatures(self):
     }
 
   @tf.function(input_signature=[tf.TensorSpec(shape=[1], dtype=tf.float32)])
-  def predict(self, x=tf.constant([0], shape=[1], dtype=tf.float32)):
+  def predict(self, x=None):
+    x = tf.constant([0], shape=[1], dtype=tf.float32) if x is None else x
     return {"y": self.compute(x, self.b)}
 
   @tf.function(
@@ -386,7 +383,8 @@ def _generate_saved_model_for_half_plus_two(
         k = tf.saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY
         tflite_model = signature_def_utils.set_signature_defs(
             tflite_model, {k: predict_signature_def})
-      open(export_dir + "/model.tflite", "wb").write(tflite_model)
+      with open(export_dir + "/model.tflite", "wb") as fp:
+        fp.write(tflite_model)
     else:
       if use_main_op:
         builder.add_meta_graph_and_variables(
@@ -412,57 +410,39 @@ def _generate_saved_model_for_half_plus_two(
 def main(_):
   _generate_saved_model_for_half_plus_two(
       FLAGS.output_dir, device_type=FLAGS.device)
-  print("SavedModel generated for %(device)s at: %(dir)s" % {
-      "device": FLAGS.device,
-      "dir": FLAGS.output_dir
-  })
+  print(f"SavedModel generated for {FLAGS.device} at: {FLAGS.output_dir}")
 
   _generate_saved_model_for_half_plus_two(
-      "%s_%s" % (FLAGS.output_dir_tf2, FLAGS.device),
+      f"{FLAGS.output_dir_tf2}_{FLAGS.device}",
       tf2=True,
       device_type=FLAGS.device)
   print(
-      "SavedModel TF2 generated for %(device)s at: %(dir)s" % {
-          "device": FLAGS.device,
-          "dir": "%s_%s" % (FLAGS.output_dir_tf2, FLAGS.device),
-      })
+      "SavedModel TF2 generated for {device} at: {dir}".format(
+          device=FLAGS.device,
+          dir=f"{FLAGS.output_dir_tf2}_{FLAGS.device}",
+        ))
 
   _generate_saved_model_for_half_plus_two(
       FLAGS.output_dir_pbtxt, as_text=True, device_type=FLAGS.device)
-  print("SavedModel generated for %(device)s at: %(dir)s" % {
-      "device": FLAGS.device,
-      "dir": FLAGS.output_dir_pbtxt
-  })
+  print(f"SavedModel generated for {FLAGS.device} at: {FLAGS.output_dir_pbtxt}")
 
   _generate_saved_model_for_half_plus_two(
       FLAGS.output_dir_main_op, use_main_op=True, device_type=FLAGS.device)
-  print("SavedModel generated for %(device)s at: %(dir)s " % {
-      "device": FLAGS.device,
-      "dir": FLAGS.output_dir_main_op
-  })
+  print(f"SavedModel generated for {FLAGS.device} at: {FLAGS.output_dir_main_op} ")
 
   _generate_saved_model_for_half_plus_two(
       FLAGS.output_dir_tflite, as_tflite=True, device_type=FLAGS.device)
-  print("SavedModel in TFLite format generated for %(device)s at: %(dir)s " % {
-      "device": FLAGS.device,
-      "dir": FLAGS.output_dir_tflite,
-  })
+  print(f"SavedModel in TFLite format generated for {FLAGS.device} at: {FLAGS.output_dir_tflite} ")
 
   _generate_saved_model_for_half_plus_two(
       FLAGS.output_dir_mlmd, include_mlmd=True, device_type=FLAGS.device)
-  print("SavedModel with MLMD generated for %(device)s at: %(dir)s " % {
-      "device": FLAGS.device,
-      "dir": FLAGS.output_dir_mlmd,
-  })
+  print(f"SavedModel with MLMD generated for {FLAGS.device} at: {FLAGS.output_dir_mlmd} ")
 
   _generate_saved_model_for_half_plus_two(
       FLAGS.output_dir_tflite_with_sigdef, device_type=FLAGS.device,
       as_tflite_with_sigdef=True)
   print("SavedModel in TFLite format with SignatureDef generated for "
-        "%(device)s at: %(dir)s " % {
-            "device": FLAGS.device,
-            "dir": FLAGS.output_dir_tflite_with_sigdef,
-        })
+        f"{FLAGS.device} at: {FLAGS.output_dir_tflite_with_sigdef} ")
 
 
 if __name__ == "__main__":
diff --git a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_2_versions/00000123/assets/foo.txt b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_2_versions/00000123/assets/foo.txt
index f9ff0366880..56c3e54a43f 100644
--- a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_2_versions/00000123/assets/foo.txt
+++ b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_2_versions/00000123/assets/foo.txt
@@ -1 +1 @@
-asset-file-contents
\ No newline at end of file
+asset-file-contents
diff --git a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_2_versions/00000124/assets/foo.txt b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_2_versions/00000124/assets/foo.txt
index f9ff0366880..56c3e54a43f 100644
--- a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_2_versions/00000124/assets/foo.txt
+++ b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_2_versions/00000124/assets/foo.txt
@@ -1 +1 @@
-asset-file-contents
\ No newline at end of file
+asset-file-contents
diff --git a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_cpu/00000123/assets/foo.txt b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_cpu/00000123/assets/foo.txt
index f9ff0366880..56c3e54a43f 100644
--- a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_cpu/00000123/assets/foo.txt
+++ b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_cpu/00000123/assets/foo.txt
@@ -1 +1 @@
-asset-file-contents
\ No newline at end of file
+asset-file-contents
diff --git a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_gpu_trt/00000123/assets/foo.txt b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_gpu_trt/00000123/assets/foo.txt
index f9ff0366880..56c3e54a43f 100644
--- a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_gpu_trt/00000123/assets/foo.txt
+++ b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_gpu_trt/00000123/assets/foo.txt
@@ -1 +1 @@
-asset-file-contents
\ No newline at end of file
+asset-file-contents
diff --git a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_mkl/00000123/assets/foo.txt b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_mkl/00000123/assets/foo.txt
index f9ff0366880..56c3e54a43f 100644
--- a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_mkl/00000123/assets/foo.txt
+++ b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_mkl/00000123/assets/foo.txt
@@ -1 +1 @@
-asset-file-contents
\ No newline at end of file
+asset-file-contents
diff --git a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_mlmd/00000123/assets.extra/mlmd_uuid b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_mlmd/00000123/assets.extra/mlmd_uuid
index afc2417480e..cffaea71d35 100644
--- a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_mlmd/00000123/assets.extra/mlmd_uuid
+++ b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_mlmd/00000123/assets.extra/mlmd_uuid
@@ -1 +1 @@
-test_mlmd_uuid
\ No newline at end of file
+test_mlmd_uuid
diff --git a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_mlmd/00000123/assets/foo.txt b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_mlmd/00000123/assets/foo.txt
index f9ff0366880..56c3e54a43f 100644
--- a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_mlmd/00000123/assets/foo.txt
+++ b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_mlmd/00000123/assets/foo.txt
@@ -1 +1 @@
-asset-file-contents
\ No newline at end of file
+asset-file-contents
diff --git a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_tf2_cpu/00000123/assets/foo.txt b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_tf2_cpu/00000123/assets/foo.txt
index f9ff0366880..56c3e54a43f 100644
--- a/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_tf2_cpu/00000123/assets/foo.txt
+++ b/tensorflow_serving/servables/tensorflow/testdata/saved_model_half_plus_two_tf2_cpu/00000123/assets/foo.txt
@@ -1 +1 @@
-asset-file-contents
\ No newline at end of file
+asset-file-contents
diff --git a/tensorflow_serving/servables/tensorflow/testdata/tf_text_regression.README b/tensorflow_serving/servables/tensorflow/testdata/tf_text_regression.README
index faf81a58f1a..038352e0c66 100644
--- a/tensorflow_serving/servables/tensorflow/testdata/tf_text_regression.README
+++ b/tensorflow_serving/servables/tensorflow/testdata/tf_text_regression.README
@@ -16,4 +16,3 @@
 This model is used to test the integration with TF Text, and is updated using
 this script:
 https://github.com/tensorflow/text/blob/master/oss_scripts/model_server/save_models.py
-
diff --git a/tensorflow_serving/tools/docker/Dockerfile.devel-gpu b/tensorflow_serving/tools/docker/Dockerfile.devel-gpu
index d33bca9642b..862ec1cd0a6 100644
--- a/tensorflow_serving/tools/docker/Dockerfile.devel-gpu
+++ b/tensorflow_serving/tools/docker/Dockerfile.devel-gpu
@@ -187,4 +187,3 @@ FROM binary_build as clean_build
 RUN bazel clean --expunge --color=yes && \
     rm -rf /root/.cache
 CMD ["/bin/bash"]
-
diff --git a/tensorflow_serving/tools/docker/Dockerfile.gpu b/tensorflow_serving/tools/docker/Dockerfile.gpu
index 80b210d5058..fe92f8ab636 100644
--- a/tensorflow_serving/tools/docker/Dockerfile.gpu
+++ b/tensorflow_serving/tools/docker/Dockerfile.gpu
@@ -87,4 +87,3 @@ tensorflow_model_server --port=8500 --rest_api_port=8501 \
 && chmod +x /usr/bin/tf_serving_entrypoint.sh
 
 ENTRYPOINT ["/usr/bin/tf_serving_entrypoint.sh"]
-
diff --git a/tensorflow_serving/tools/pip_package/setup.py b/tensorflow_serving/tools/pip_package/setup.py
index d7b21224ae7..820c9199cc4 100644
--- a/tensorflow_serving/tools/pip_package/setup.py
+++ b/tensorflow_serving/tools/pip_package/setup.py
@@ -25,8 +25,7 @@
 
 import sys
 
-from setuptools import find_packages
-from setuptools import setup
+from setuptools import find_packages, setup
 
 DOCLINES = __doc__.split('\n')
 
diff --git a/tensorflow_serving/util/net_http/client/test_client/public/httpclient.h b/tensorflow_serving/util/net_http/client/test_client/public/httpclient.h
index 52b624d9c07..14cb4e51cff 100644
--- a/tensorflow_serving/util/net_http/client/test_client/public/httpclient.h
+++ b/tensorflow_serving/util/net_http/client/test_client/public/httpclient.h
@@ -46,4 +46,3 @@ inline std::unique_ptr<TestHTTPClientInterface> CreateEvHTTPConnection(
 }  // namespace tensorflow
 
 #endif  // THIRD_PARTY_TENSORFLOW_SERVING_UTIL_NET_HTTP_CLIENT_TEST_CLIENT_PUBLIC_HTTPCLIENT_H_
-
diff --git a/tools/gen_status_stamp.sh b/tools/gen_status_stamp.sh
index f8c840d6d8d..32a73498caa 100755
--- a/tools/gen_status_stamp.sh
+++ b/tools/gen_status_stamp.sh
@@ -35,5 +35,3 @@ if [ -d .git ] || git rev-parse --git-dir > /dev/null 2>&1; then
 else
   echo "BUILD_SCM_REVISION no_git"
 fi;
-
-