BLD: upgrade pylint for python 3

tensorflow_addons/custom_ops/image/cc/kernels/euclidean_distance_transform_op.h

@@ -38,8 +38,8 @@ class EuclideanDistanceTransformGenerator {
   int64 height_, width_;
 
  public:
-  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
-  EuclideanDistanceTransformGenerator(typename TTypes<T, 4>::ConstTensor input)
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE EuclideanDistanceTransformGenerator(
+      typename TTypes<T, 4>::ConstTensor input)
       : input_(input) {
     height_ = input_.dimensions()[1];
     width_ = input_.dimensions()[2];

tensorflow_addons/image/utils.py

@@ -35,12 +35,11 @@ def to_4D_image(image):
     Returns:
       4D tensor with the same type.
     """
-    # yapf:disable
     with tf.control_dependencies([
-        tf.debugging.assert_rank_in(
-            image, [2, 3, 4], message='`image` must be 2/3/4D tensor')
+            tf.debugging.assert_rank_in(  # pylint: disable=bad-continuation
+                image, [2, 3, 4],
+                message='`image` must be 2/3/4D tensor')
     ]):
-        # yapf: enable
         ndims = image.get_shape().ndims
         if ndims is None:
             return _dynamic_to_4D_image(image)
@@ -81,12 +80,12 @@ def from_4D_image(image, ndims):
     Returns:
       `ndims`-D tensor with the same type.
     """
-    # yapf:disable
     with tf.control_dependencies([
-        tf.debugging.assert_rank(
-            image, 4, message='`image` must be 4D tensor')
+            tf.debugging.assert_rank(  # pylint: disable=bad-continuation
+                image,
+                4,
+                message='`image` must be 4D tensor')
     ]):
-        # yapf:enable
         if isinstance(ndims, tf.Tensor):
             return _dynamic_from_4D_image(image, ndims)
         elif ndims == 2:

tensorflow_addons/optimizers/weight_decay_optimizers.py

@@ -226,7 +226,7 @@ def extend_with_decoupled_weight_decay(base_optimizer):
 
     optimizer = tfa.optimizers.AdamW(learning_rate=lr, weight_decay=wd)
     ```
-    
+
     Note: you might want to register your own custom optimizer using
     `tf.keras.utils.get_custom_objects()`.
 

tensorflow_addons/seq2seq/beam_search_decoder.py

@@ -514,8 +514,13 @@ def _maybe_sort_array_beams(self, t, parent_ids, sequence_length):
                 self._beam_width):
             return t
         t = t.stack()
+        # yapf:disable
         with tf.control_dependencies(
-            [_check_batch_beam(t, self._batch_size, self._beam_width)]):
+                [_check_batch_beam(  # pylint: disable=bad-continuation
+                    t,
+                    self._batch_size,
+                    self._beam_width)]):
+            # yapf:enable
             return gather_tree_from_array(t, parent_ids, sequence_length)
 
     def step(self, time, inputs, state, training=None, name=None):

tools/ci_build/install/ci_requirements.txt

@@ -1,4 +1,4 @@
-# TODO: Upgrade pylint to 2.0 when python >= 3.4
-pylint == 1.6.4
+pylint == 1.9 ; python_version <= '2.7'
+pylint == 2.3.1 ; python_version > '2.7'
 docformatter == 1.1
 yapf == 0.26.0

tools/ci_build/install/install_ci_dependency.sh

@@ -36,11 +36,11 @@ if [[ ! -d "tensorflow_addons" ]]; then
     exit 1
 fi
 
-# Install python
+# Install python dependencies:
 CI_REQUIREMENT="$SCRIPT_DIR/ci_requirements.txt"
 pip install ${QUIET_FLAG} -r ${CI_REQUIREMENT}
 
-# Check clang-format
+# Check clang-format:
 CLANG_FORMAT=${CLANG_FORMAT:-clang-format-3.8}
 which ${CLANG_FORMAT} > /dev/null
 if [[ $? != "0" ]]; then

tools/ci_build/pylintrc

@@ -70,6 +70,7 @@ disable=design,
         # TODO: remove not-callable when pylint can understand tf export paradigm
         not-callable,
         similarities,
+        unsupported-assignment-operation,
         useless-object-inheritance
 
 # Enable the message, report, category or checker with the given id(s). You can