path: root/python310.diff

diff --git a/tensorflow/contrib/cudnn_rnn/python/kernel_tests/cudnn_rnn_test.py b/tensorflow/contrib/cudnn_rnn/python/kernel_tests/cudnn_rnn_test.py
index 8285ea0492..3a0764b7f7 100644
--- a/tensorflow/contrib/cudnn_rnn/python/kernel_tests/cudnn_rnn_test.py
+++ b/tensorflow/contrib/cudnn_rnn/python/kernel_tests/cudnn_rnn_test.py
@@ -18,7 +18,6 @@ from __future__ import division
 from __future__ import print_function
 
 import argparse
-import collections
 import functools
 import itertools
 import os
@@ -59,6 +58,7 @@ from tensorflow.python.training import momentum
 from tensorflow.python.training import rmsprop
 from tensorflow.python.training import saver as saver_lib
 from tensorflow.python.training.checkpointable import util as checkpointable_utils
+from tensorflow.python.util.compat import collections_abc
 
 
 CUDNN_LSTM = cudnn_rnn_ops.CUDNN_LSTM
@@ -1125,7 +1125,7 @@ class CudnnRNNTestTraining(test_util.TensorFlowTestCase):
     return numeric_grad.reshape(x_shape)
 
   def _GetShape(self, sess, inputs):
-    if not isinstance(inputs, collections.Iterable):
+    if not isinstance(inputs, collections_abc.Iterable):
       return sess.run(array_ops.shape(inputs))
     else:
       return sess.run([array_ops.shape(x) for x in inputs])
diff --git a/tensorflow/contrib/data/python/ops/scan_ops.py b/tensorflow/contrib/data/python/ops/scan_ops.py
index e911ad0fa0..3d04ae592f 100644
--- a/tensorflow/contrib/data/python/ops/scan_ops.py
+++ b/tensorflow/contrib/data/python/ops/scan_ops.py
@@ -17,8 +17,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
-
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.util import nest
 from tensorflow.python.data.util import sparse
@@ -26,6 +24,7 @@ from tensorflow.python.framework import function
 from tensorflow.python.framework import ops
 from tensorflow.python.framework import sparse_tensor
 from tensorflow.python.ops import gen_dataset_ops
+from tensorflow.python.util.compat import collections_abc
 
 
 class _ScanDataset(dataset_ops.Dataset):
@@ -102,7 +101,7 @@ class _ScanDataset(dataset_ops.Dataset):
             input_dataset.output_shapes, input_dataset.output_classes)
 
         ret = scan_func(nested_state_args, nested_input_args)
-        if not isinstance(ret, collections.Sequence) or len(ret) != 2:
+        if not isinstance(ret, collections_abc.Sequence) or len(ret) != 2:
           raise TypeError("The scan function must return a pair comprising the "
                           "new state and the output value.")
 
diff --git a/tensorflow/contrib/factorization/python/ops/factorization_ops.py b/tensorflow/contrib/factorization/python/ops/factorization_ops.py
index 8f73274c2a..185bb0de55 100644
--- a/tensorflow/contrib/factorization/python/ops/factorization_ops.py
+++ b/tensorflow/contrib/factorization/python/ops/factorization_ops.py
@@ -18,7 +18,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import numbers
 
 from six.moves import xrange  # pylint: disable=redefined-builtin
@@ -42,6 +41,7 @@ from tensorflow.python.ops import state_ops
 from tensorflow.python.ops import variable_scope
 from tensorflow.python.ops import variables
 from tensorflow.python.platform import resource_loader
+from tensorflow.python.util.compat import collections_abc
 
 _factorization_ops = loader.load_op_library(
     resource_loader.get_path_to_datafile("_factorization_ops.so"))
@@ -388,7 +388,7 @@ class WALSModel(object):
       return None
 
     init_mode = "list"
-    if isinstance(wt_init, collections.Iterable):
+    if isinstance(wt_init, collections_abc.Iterable):
       if num_shards == 1 and len(wt_init) == num_wts:
         wt_init = [wt_init]
       assert len(wt_init) == num_shards
diff --git a/tensorflow/contrib/graph_editor/util.py b/tensorflow/contrib/graph_editor/util.py
index 584f4509cc..c9feb6e940 100644
--- a/tensorflow/contrib/graph_editor/util.py
+++ b/tensorflow/contrib/graph_editor/util.py
@@ -19,11 +19,11 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import re
 from six import iteritems
 from tensorflow.python.framework import ops as tf_ops
 from tensorflow.python.ops import array_ops as tf_array_ops
+from tensorflow.python.util.compat import collections_abc
 
 __all__ = [
     "make_list_of_op",
@@ -157,7 +157,7 @@ def transform_tree(tree, fn, iterable_type=tuple):
         res = tree.__new__(type(tree),
                            (transform_tree(child, fn) for child in tree))
       return res
-    elif isinstance(tree, collections.Sequence):
+    elif isinstance(tree, collections_abc.Sequence):
       res = tree.__new__(type(tree))
       res.__init__(transform_tree(child, fn) for child in tree)
       return res
diff --git a/tensorflow/contrib/labeled_tensor/python/ops/_typecheck.py b/tensorflow/contrib/labeled_tensor/python/ops/_typecheck.py
index 80fa17ec1f..9221e087bb 100644
--- a/tensorflow/contrib/labeled_tensor/python/ops/_typecheck.py
+++ b/tensorflow/contrib/labeled_tensor/python/ops/_typecheck.py
@@ -22,11 +22,11 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import functools
 import re
 
 from tensorflow.python.util import tf_inspect
+from tensorflow.python.util.compat import collections_abc
 
 # used for register_type_abbreviation and _type_repr below.
 _TYPE_ABBREVIATIONS = {}
@@ -115,7 +115,7 @@ class Sequence(_SingleArgumentType):
   """
 
   def __instancecheck__(self, instance):
-    return (isinstance(instance, collections.Sequence)
+    return (isinstance(instance, collections_abc.Sequence)
             and all(isinstance(x, self._type) for x in instance))
 
 
@@ -131,9 +131,9 @@ class Collection(_SingleArgumentType):
   """
 
   def __instancecheck__(self, instance):
-    return (isinstance(instance, collections.Iterable)
-            and isinstance(instance, collections.Sized)
-            and isinstance(instance, collections.Container)
+    return (isinstance(instance, collections_abc.Iterable)
+            and isinstance(instance, collections_abc.Sized)
+            and isinstance(instance, collections_abc.Container)
             and all(isinstance(x, self._type) for x in instance))
 
 
@@ -158,7 +158,7 @@ class Mapping(_TwoArgumentType):
 
   def __instancecheck__(self, instance):
     key_type, value_type = self._types  # pylint: disable=unbalanced-tuple-unpacking
-    return (isinstance(instance, collections.Mapping)
+    return (isinstance(instance, collections_abc.Mapping)
             and all(isinstance(k, key_type) for k in instance.keys())
             and all(isinstance(k, value_type) for k in instance.values()))
 
diff --git a/tensorflow/contrib/labeled_tensor/python/ops/core.py b/tensorflow/contrib/labeled_tensor/python/ops/core.py
index 0c6bba758b..884ab757f3 100644
--- a/tensorflow/contrib/labeled_tensor/python/ops/core.py
+++ b/tensorflow/contrib/labeled_tensor/python/ops/core.py
@@ -41,11 +41,12 @@ from tensorflow.python.framework import ops
 from tensorflow.python.framework import tensor_shape
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import math_ops
+from tensorflow.python.util.compat import collections_abc
 
 # pylint: disable=invalid-name
 
 # Types coercible to Axis.labels
-# We use this instead of collections.Sequence to exclude strings.
+# We use this instead of collections_abc.Sequence to exclude strings.
 LabelsLike = tc.Union(np.ndarray, range, list, tuple)
 
 # Types coercible to a tf.Dimension
@@ -195,7 +196,7 @@ def as_axis(axis_data):
   return axis
 
 
-class Axes(collections.Mapping):
+class Axes(collections_abc.Mapping):
   """Axis names and indices for a tensor.
 
   It is an ordered mapping, with keys given by axis name and values given
@@ -721,7 +722,7 @@ def transpose(labeled_tensor, axis_order=None, name=None):
 @tc.accepts(
     LabeledTensorLike,
     tc.Collection(
-        tc.Union(string_types, tc.Tuple(string_types, collections.Hashable))),
+        tc.Union(string_types, tc.Tuple(string_types, collections_abc.Hashable))),
     tc.Optional(string_types))
 def expand_dims(labeled_tensor, axes, name=None):
   """Insert dimensions of size 1.
@@ -1057,7 +1058,7 @@ def align(labeled_tensor_0, labeled_tensor_1, name=None):
 
 
 @tc.returns(types.FunctionType)
-@tc.accepts(string_types, collections.Callable)
+@tc.accepts(string_types, collections_abc.Callable)
 def define_unary_op(op_name, elementwise_function):
   """Define a unary operation for labeled tensors.
 
@@ -1126,7 +1127,7 @@ sigmoid = define_unary_op('sigmoid', math_ops.sigmoid)
 
 
 @tc.returns(types.FunctionType)
-@tc.accepts(string_types, collections.Callable)
+@tc.accepts(string_types, collections_abc.Callable)
 def define_binary_op(op_name, elementwise_function):
   """Define a binary operation that broadcasts labeled tensors.
 
diff --git a/tensorflow/contrib/labeled_tensor/python/ops/ops.py b/tensorflow/contrib/labeled_tensor/python/ops/ops.py
index 3ba1026383..2424784f90 100644
--- a/tensorflow/contrib/labeled_tensor/python/ops/ops.py
+++ b/tensorflow/contrib/labeled_tensor/python/ops/ops.py
@@ -17,7 +17,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import types
 
 import numpy as np
@@ -33,6 +32,7 @@ from tensorflow.python.ops import math_ops
 from tensorflow.python.ops import numerics
 from tensorflow.python.ops import random_ops
 from tensorflow.python.training import input  # pylint: disable=redefined-builtin
+from tensorflow.python.util.compat import collections_abc
 
 
 @tc.returns(core.LabeledTensor)
@@ -51,7 +51,7 @@ def _gather_1d_on_axis(labeled_tensor, indexer, axis, name=None):
 @tc.returns(core.LabeledTensor)
 @tc.accepts(core.LabeledTensorLike,
             tc.Mapping(string_types,
-                       tc.Union(slice, collections.Hashable, list)),
+                       tc.Union(slice, collections_abc.Hashable, list)),
             tc.Optional(string_types))
 def select(labeled_tensor, selection, name=None):
   """Slice out a subset of the tensor.
@@ -110,8 +110,8 @@ def select(labeled_tensor, selection, name=None):
         slices[axis_name] = slice(start, stop)
 
       # Needs to be after checking for slices, since slice objects claim to be
-      # instances of collections.Hashable but hash() on them fails.
-      elif isinstance(value, collections.Hashable):
+      # instances of collections_abc.Hashable but hash() on them fails.
+      elif isinstance(value, collections_abc.Hashable):
         slices[axis_name] = axis.index(value)
 
       elif isinstance(value, list):
@@ -399,7 +399,7 @@ def rename_axis(labeled_tensor, existing_name, new_name, name=None):
 
 
 @tc.returns(tc.List(core.LabeledTensor))
-@tc.accepts(string_types, collections.Callable, int, bool,
+@tc.accepts(string_types, collections_abc.Callable, int, bool,
             tc.Collection(core.LabeledTensorLike), bool,
             tc.Optional(string_types))
 def _batch_helper(default_name,
@@ -605,7 +605,7 @@ def random_crop(labeled_tensor, shape_map, seed=None, name=None):
 
 # TODO(shoyer): Allow the user to select the axis over which to map.
 @tc.returns(core.LabeledTensor)
-@tc.accepts(collections.Callable, core.LabeledTensorLike,
+@tc.accepts(collections_abc.Callable, core.LabeledTensorLike,
             tc.Optional(string_types))
 def map_fn(fn, labeled_tensor, name=None):
   """Map on the list of tensors unpacked from labeled_tensor.
@@ -659,7 +659,7 @@ def map_fn(fn, labeled_tensor, name=None):
 
 
 @tc.returns(core.LabeledTensor)
-@tc.accepts(collections.Callable, core.LabeledTensorLike,
+@tc.accepts(collections_abc.Callable, core.LabeledTensorLike,
             core.LabeledTensorLike, tc.Optional(string_types))
 def foldl(fn, labeled_tensor, initial_value, name=None):
   """Left fold on the list of tensors unpacked from labeled_tensor.
@@ -752,7 +752,7 @@ def squeeze(labeled_tensor, axis_names=None, name=None):
 
 # pylint: disable=invalid-name
 ReduceAxis = tc.Union(string_types,
-                      tc.Tuple(string_types, collections.Hashable))
+                      tc.Tuple(string_types, collections_abc.Hashable))
 ReduceAxes = tc.Optional(tc.Union(ReduceAxis, tc.Collection(ReduceAxis)))
 # pylint: enable=invalid-name
 
@@ -874,7 +874,7 @@ def matmul(a, b, name=None):
 
 
 @tc.returns(types.FunctionType)
-@tc.accepts(string_types, collections.Callable)
+@tc.accepts(string_types, collections_abc.Callable)
 def define_reduce_op(op_name, reduce_fn):
   """Define a reduction op for labeled tensors.
 
diff --git a/tensorflow/contrib/layers/python/layers/feature_column.py b/tensorflow/contrib/layers/python/layers/feature_column.py
index 3ae07cedab..c08cadd045 100644
--- a/tensorflow/contrib/layers/python/layers/feature_column.py
+++ b/tensorflow/contrib/layers/python/layers/feature_column.py
@@ -155,6 +155,7 @@ from tensorflow.python.ops import variables
 from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.util import deprecation
 from tensorflow.python.util import nest
+from tensorflow.python.util.compat import collections_abc
 
 
 # Imports the core `InputLayer` symbol in contrib during development.
@@ -1409,7 +1410,7 @@ def shared_embedding_columns(sparse_id_columns,
       least one element of `sparse_id_columns` is not a `SparseColumn` or a
       `WeightedSparseColumn`.
   """
-  if (not isinstance(sparse_id_columns, collections.Sequence) or
+  if (not isinstance(sparse_id_columns, collections_abc.Sequence) or
       isinstance(sparse_id_columns, six.string_types)):
     raise TypeError(
         "sparse_id_columns must be a non-string sequence (ex: list or tuple) "
diff --git a/tensorflow/contrib/learn/python/learn/estimators/_sklearn.py b/tensorflow/contrib/learn/python/learn/estimators/_sklearn.py
index 1f0e4663d0..dadb95508b 100644
--- a/tensorflow/contrib/learn/python/learn/estimators/_sklearn.py
+++ b/tensorflow/contrib/learn/python/learn/estimators/_sklearn.py
@@ -19,12 +19,12 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import os
 
 import numpy as np
 import six
 
+from tensorflow.python.util.compat import collections_abc
 
 def _pprint(d):
   return ', '.join(['%s=%s' % (key, str(value)) for key, value in d.items()])
@@ -55,7 +55,7 @@ class _BaseEstimator(object):
     for key in param_names:
       value = getattr(self, key, None)
 
-      if isinstance(value, collections.Callable):
+      if isinstance(value, collections_abc.Callable):
         continue
 
       # XXX: should we rather test if instance of estimator?
diff --git a/tensorflow/contrib/tensor_forest/hybrid/python/hybrid_model.py b/tensorflow/contrib/tensor_forest/hybrid/python/hybrid_model.py
index a427a02b7c..7d23d950c4 100644
--- a/tensorflow/contrib/tensor_forest/hybrid/python/hybrid_model.py
+++ b/tensorflow/contrib/tensor_forest/hybrid/python/hybrid_model.py
@@ -17,8 +17,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
-
 from tensorflow.contrib import layers
 from tensorflow.contrib.framework.python.ops import variables as framework_variables
 
@@ -28,6 +26,7 @@ from tensorflow.python.ops import nn_ops
 from tensorflow.python.ops import variables
 
 from tensorflow.python.training import adagrad
+from tensorflow.python.util.compat import collections_abc
 
 
 class HybridModel(object):
@@ -65,7 +64,7 @@ class HybridModel(object):
 
     # If this is a collection of layers, return the mean of their inference
     # results.
-    if isinstance(layer, collections.Iterable):
+    if isinstance(layer, collections_abc.Iterable):
       return math_ops.reduce_mean(
           array_ops.stack([l.inference_graph(data) for l in layer]), 0)
     # If this is a single layer, return its inference result.
diff --git a/tensorflow/python/data/util/nest.py b/tensorflow/python/data/util/nest.py
index 32e08021dc..751da5fb33 100644
--- a/tensorflow/python/data/util/nest.py
+++ b/tensorflow/python/data/util/nest.py
@@ -36,12 +36,11 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections as _collections
-
 import six as _six
 
 from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow
 from tensorflow.python.framework import sparse_tensor as _sparse_tensor
+from tensorflow.python.util.compat import collections_abc as _collections_abc
 
 
 def _sorted(dict_):
@@ -72,7 +71,7 @@ def _sequence_like(instance, args):
     return type(instance)((key, result[key]) for key in _six.iterkeys(instance))
   elif (isinstance(instance, tuple) and
         hasattr(instance, "_fields") and
-        isinstance(instance._fields, _collections.Sequence) and
+        isinstance(instance._fields, _collections_abc.Sequence) and
         all(isinstance(f, _six.string_types) for f in instance._fields)):
     # This is a namedtuple
     return type(instance)(*args)
diff --git a/tensorflow/python/feature_column/feature_column.py b/tensorflow/python/feature_column/feature_column.py
index 7aa46af828..78042d2c95 100644
--- a/tensorflow/python/feature_column/feature_column.py
+++ b/tensorflow/python/feature_column/feature_column.py
@@ -162,6 +162,7 @@ from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.training import checkpoint_utils
 from tensorflow.python.util import nest
 from tensorflow.python.util.tf_export import tf_export
+from tensorflow.python.util.compat import collections_abc
 
 
 def _internal_input_layer(features,
@@ -2291,7 +2292,7 @@ def _clean_feature_columns(feature_columns):
   if isinstance(feature_columns, _FeatureColumn):
     feature_columns = [feature_columns]
 
-  if isinstance(feature_columns, collections.Iterator):
+  if isinstance(feature_columns, collections_abc.Iterator):
     feature_columns = list(feature_columns)
 
   if isinstance(feature_columns, dict):
diff --git a/tensorflow/python/framework/ops.py b/tensorflow/python/framework/ops.py
index cae171efa2..d24dc0bd1c 100644
--- a/tensorflow/python/framework/ops.py
+++ b/tensorflow/python/framework/ops.py
@@ -57,6 +57,7 @@ from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.util import compat
 from tensorflow.python.util import decorator_utils
 from tensorflow.python.util import tf_contextlib
+from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 
@@ -1158,7 +1159,7 @@ def internal_convert_n_to_tensor(values,
     RuntimeError: If a registered conversion function returns an invalid
       value.
   """
-  if not isinstance(values, collections.Sequence):
+  if not isinstance(values, collections_abc.Sequence):
     raise TypeError("values must be a list.")
   ret = []
   if ctx is None: ctx = context.context()
@@ -1298,7 +1299,7 @@ def internal_convert_n_to_tensor_or_indexed_slices(values,
     RuntimeError: If a registered conversion function returns an invalid
       value.
   """
-  if not isinstance(values, collections.Sequence):
+  if not isinstance(values, collections_abc.Sequence):
     raise TypeError("values must be a list.")
   ret = []
   for i, value in enumerate(values):
diff --git a/tensorflow/python/kernel_tests/conv_ops_3d_test.py b/tensorflow/python/kernel_tests/conv_ops_3d_test.py
index 0b531125f3..d4e6a33cc3 100644
--- a/tensorflow/python/kernel_tests/conv_ops_3d_test.py
+++ b/tensorflow/python/kernel_tests/conv_ops_3d_test.py
@@ -18,7 +18,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import math
 
 import numpy as np
@@ -32,6 +31,7 @@ from tensorflow.python.ops import gradients_impl
 from tensorflow.python.ops import nn_ops
 import tensorflow.python.ops.nn_grad  # pylint: disable=unused-import
 from tensorflow.python.platform import test
+from tensorflow.python.util.compat import collections_abc
 
 
 def GetTestConfigs():
@@ -78,7 +78,7 @@ class Conv3DTest(test.TestCase):
       t1 = constant_op.constant(x1, shape=tensor_in_sizes, dtype=dtype)
       t2 = constant_op.constant(x2, shape=filter_in_sizes, dtype=dtype)
 
-      if isinstance(stride, collections.Iterable):
+      if isinstance(stride, collections_abc.Iterable):
         strides = [1] + list(stride) + [1]
       else:
         strides = [1, stride, stride, stride, 1]
@@ -136,7 +136,7 @@ class Conv3DTest(test.TestCase):
     with self.test_session(use_gpu=use_gpu):
       t1 = constant_op.constant(x1, shape=tensor_in_sizes)
       t2 = constant_op.constant(x2, shape=filter_in_sizes)
-      if isinstance(stride, collections.Iterable):
+      if isinstance(stride, collections_abc.Iterable):
         strides = list(stride)
       else:
         strides = [stride, stride, stride]
@@ -376,7 +376,7 @@ class Conv3DTest(test.TestCase):
         filter_planes, filter_rows, filter_cols, in_depth, out_depth
     ]
 
-    if isinstance(stride, collections.Iterable):
+    if isinstance(stride, collections_abc.Iterable):
       strides = [1] + list(stride) + [1]
     else:
       strides = [1, stride, stride, stride, 1]
diff --git a/tensorflow/python/kernel_tests/conv_ops_test.py b/tensorflow/python/kernel_tests/conv_ops_test.py
index 75a1f8fa97..34a72c4a0c 100644
--- a/tensorflow/python/kernel_tests/conv_ops_test.py
+++ b/tensorflow/python/kernel_tests/conv_ops_test.py
@@ -42,6 +42,7 @@ from tensorflow.python.ops import variables
 import tensorflow.python.ops.nn_grad  # pylint: disable=unused-import
 from tensorflow.python.platform import test
 from tensorflow.python.platform import tf_logging
+from tensorflow.python.util.compat import collections_abc
 
 
 def GetShrunkInceptionShapes(shrink=10):
@@ -271,7 +272,7 @@ class Conv2DTest(test.TestCase):
     with test_util.device(use_gpu):
       t1 = constant_op.constant(x1, shape=tensor_in_sizes)
       t2 = constant_op.constant(x2, shape=filter_in_sizes)
-      if isinstance(stride, collections.Iterable):
+      if isinstance(stride, collections_abc.Iterable):
         strides = list(stride)
       else:
         strides = [stride, stride]
diff --git a/tensorflow/python/ops/clip_ops.py b/tensorflow/python/ops/clip_ops.py
index 75c459a9cf..9fef7085ee 100644
--- a/tensorflow/python/ops/clip_ops.py
+++ b/tensorflow/python/ops/clip_ops.py
@@ -18,8 +18,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
-
 import six
 
 from tensorflow.python.framework import constant_op
@@ -29,6 +27,7 @@ from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import gen_array_ops
 from tensorflow.python.ops import gen_nn_ops
 from tensorflow.python.ops import math_ops
+from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 
@@ -173,7 +172,7 @@ def global_norm(t_list, name=None):
   Raises:
     TypeError: If `t_list` is not a sequence.
   """
-  if (not isinstance(t_list, collections.Sequence)
+  if (not isinstance(t_list, collections_abc.Sequence)
       or isinstance(t_list, six.string_types)):
     raise TypeError("t_list should be a sequence")
   t_list = list(t_list)
@@ -244,7 +243,7 @@ def clip_by_global_norm(t_list, clip_norm, use_norm=None, name=None):
   Raises:
     TypeError: If `t_list` is not a sequence.
   """
-  if (not isinstance(t_list, collections.Sequence)
+  if (not isinstance(t_list, collections_abc.Sequence)
       or isinstance(t_list, six.string_types)):
     raise TypeError("t_list should be a sequence")
   t_list = list(t_list)
diff --git a/tensorflow/python/ops/data_flow_ops.py b/tensorflow/python/ops/data_flow_ops.py
index 62c5adc385..1c3374c7d1 100644
--- a/tensorflow/python/ops/data_flow_ops.py
+++ b/tensorflow/python/ops/data_flow_ops.py
@@ -18,7 +18,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import hashlib
 import threading
 
@@ -38,6 +37,7 @@ from tensorflow.python.ops import math_ops
 # go/tf-wildcard-import
 # pylint: disable=wildcard-import
 from tensorflow.python.ops.gen_data_flow_ops import *
+from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 # pylint: enable=wildcard-import
@@ -61,7 +61,7 @@ def _as_shape_list(shapes,
   """Convert shapes to a list of tuples of int (or None)."""
   del dtypes
   if unknown_dim_allowed:
-    if (not isinstance(shapes, collections.Sequence) or not shapes or
+    if (not isinstance(shapes, collections_abc.Sequence) or not shapes or
         any(shape is None or isinstance(shape, int) for shape in shapes)):
       raise ValueError(
           "When providing partial shapes, a list of shapes must be provided.")
diff --git a/tensorflow/python/ops/gradients_impl.py b/tensorflow/python/ops/gradients_impl.py
index 7385cb7585..6bd61172a9 100644
--- a/tensorflow/python/ops/gradients_impl.py
+++ b/tensorflow/python/ops/gradients_impl.py
@@ -51,6 +51,7 @@ from tensorflow.python.ops import resource_variable_ops
 from tensorflow.python.ops import spectral_grad  # pylint: disable=unused-import
 from tensorflow.python.ops import tensor_array_ops
 from tensorflow.python.platform import tf_logging as logging
+from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 # Warn the user if we convert a sparse representation to dense with at
@@ -750,7 +751,7 @@ def _HasAnyNotNoneGrads(grads, op):
   for out_grad in out_grads:
     if isinstance(out_grad, (ops.Tensor, ops.IndexedSlices)):
       return True
-    if out_grad and isinstance(out_grad, collections.Sequence):
+    if out_grad and isinstance(out_grad, collections_abc.Sequence):
       if any([g is not None for g in out_grad]):
         return True
   return False
@@ -957,7 +958,7 @@ def _AggregatedGrads(grads,
         assert control_flow_util.IsLoopSwitch(op)
         continue
     # Grads have to be Tensors or IndexedSlices
-    if (isinstance(out_grad, collections.Sequence) and not all([
+    if (isinstance(out_grad, collections_abc.Sequence) and not all([
         isinstance(g, (ops.Tensor, ops.IndexedSlices))
         for g in out_grad
         if g is not None
diff --git a/tensorflow/python/ops/sparse_ops.py b/tensorflow/python/ops/sparse_ops.py
index c3b16a7bd5..7054a9c500 100644
--- a/tensorflow/python/ops/sparse_ops.py
+++ b/tensorflow/python/ops/sparse_ops.py
@@ -39,6 +39,7 @@ from tensorflow.python.ops import math_ops
 from tensorflow.python.ops.gen_sparse_ops import *
 # pylint: enable=wildcard-import
 from tensorflow.python.util import deprecation
+from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 
@@ -1162,10 +1163,10 @@ def sparse_merge(sp_ids, sp_values, vocab_size, name=None,
                       type(vocab_size))
     vocab_size = [vocab_size]
   else:
-    if not isinstance(sp_ids, collections.Iterable):
+    if not isinstance(sp_ids, collections_abc.Iterable):
       raise TypeError("sp_ids has to be a SparseTensor or list thereof. "
                       "Found %s" % type(sp_ids))
-    if not isinstance(vocab_size, collections.Iterable):
+    if not isinstance(vocab_size, collections_abc.Iterable):
       raise TypeError("vocab_size has to be a list of Tensors or Python ints. "
                       "Found %s" % type(vocab_size))
     for dim in vocab_size:
diff --git a/tensorflow/python/training/checkpointable/data_structures.py b/tensorflow/python/training/checkpointable/data_structures.py
index 69ed253fb2..2ef8d4820e 100644
--- a/tensorflow/python/training/checkpointable/data_structures.py
+++ b/tensorflow/python/training/checkpointable/data_structures.py
@@ -26,6 +26,7 @@ from tensorflow.python.keras.utils import layer_utils
 from tensorflow.python.ops import variables
 from tensorflow.python.training.checkpointable import base as checkpointable_lib
 from tensorflow.python.training.checkpointable import data_structures_base
+from tensorflow.python.util.compat import collections_abc
 
 
 # TODO(allenl): We could track regular Python data structures which get assigned
@@ -130,7 +131,7 @@ class CheckpointableDataStructure(
     return self is other
 
 
-class List(CheckpointableDataStructure, collections.Sequence):
+class List(CheckpointableDataStructure, collections_abc.Sequence):
   """An append-only sequence type which is checkpointable.
 
   Maintains checkpoint dependencies on its contents (which must also be
@@ -207,7 +208,7 @@ class List(CheckpointableDataStructure, collections.Sequence):
     return "List(%s)" % (repr(self._storage),)
 
 
-class Mapping(CheckpointableDataStructure, collections.Mapping):
+class Mapping(CheckpointableDataStructure, collections_abc.Mapping):
   """An append-only checkpointable mapping data structure with string keys.
 
   Maintains checkpoint dependencies on its contents (which must also be
diff --git a/tensorflow/python/training/input.py b/tensorflow/python/training/input.py
index caa26581e8..f268f6af8f 100644
--- a/tensorflow/python/training/input.py
+++ b/tensorflow/python/training/input.py
@@ -23,8 +23,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
-
 from six.moves import xrange  # pylint: disable=redefined-builtin
 
 from tensorflow.python.eager import context
@@ -44,6 +42,7 @@ from tensorflow.python.ops import sparse_ops
 from tensorflow.python.ops import variable_scope as vs
 from tensorflow.python.summary import summary
 from tensorflow.python.training import queue_runner
+from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 
@@ -573,7 +572,7 @@ def _store_sparse_tensors_join(tensor_list_list, enqueue_many, keep_input):
 
 def _restore_sparse_tensors(stored_list, sparse_info_list):
   """Restore SparseTensors after dequeue in batch, batch_join, etc."""
-  received_sequence = isinstance(stored_list, collections.Sequence)
+  received_sequence = isinstance(stored_list, collections_abc.Sequence)
   if not received_sequence:
     stored_list = (stored_list,)
   tensors = [
diff --git a/tensorflow/python/util/compat.py b/tensorflow/python/util/compat.py
index a24a52eea9..2be8ee8413 100644
--- a/tensorflow/python/util/compat.py
+++ b/tensorflow/python/util/compat.py
@@ -38,6 +38,11 @@ import six as _six
 
 from tensorflow.python.util.tf_export import tf_export
 
+try:
+  # This import only works on python 3.3 and above.
+  import collections.abc as collections_abc  # pylint: disable=unused-import
+except ImportError:
+  import collections as collections_abc  # pylint: disable=unused-import
 
 def as_bytes(bytes_or_text, encoding='utf-8'):
   """Converts either bytes or unicode to `bytes`, using utf-8 encoding for text.
diff --git a/tensorflow/python/util/nest.py b/tensorflow/python/util/nest.py
index 1104768ae8..a8af478ab3 100644
--- a/tensorflow/python/util/nest.py
+++ b/tensorflow/python/util/nest.py
@@ -31,11 +31,10 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections as _collections
-
 import six as _six
 
 from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow
+from tensorflow.python.util.compat import collections_abc as _collections_abc
 
 
 def _sorted(dict_):
@@ -103,13 +102,13 @@ def _yield_value(iterable):
 
 
 def is_sequence(seq):
-  """Returns a true if its input is a collections.Sequence (except strings).
+  """Returns a true if its input is a collections.abc.Sequence (except strings).
 
   Args:
     seq: an input sequence.
 
   Returns:
-    True if the sequence is a not a string and is a collections.Sequence or a
+    True if the sequence is a not a string and is a collections.abc.Sequence or a
     dict.
   """
   return _pywrap_tensorflow.IsSequence(seq)
@@ -725,7 +724,7 @@ def yield_flat_paths(nest):
         yield (key,) + sub_path
   elif isinstance(nest, _six.string_types):
     yield ()
-  elif isinstance(nest, _collections.Sequence):
+  elif isinstance(nest, _collections_abc.Sequence):
     for idx, value in enumerate(nest):
       for sub_path in yield_flat_paths(value):
         yield (idx,) + sub_path
@@ -756,4 +755,4 @@ def flatten_with_joined_string_paths(structure, separator="/"):
   return list(zip(flat_string_paths, flatten(structure)))
 
 
-_pywrap_tensorflow.RegisterSequenceClass(_collections.Sequence)
+_pywrap_tensorflow.RegisterSequenceClass(_collections_abc.Sequence)
diff --git a/tensorflow/python/util/protobuf/compare.py b/tensorflow/python/util/protobuf/compare.py
index a0e6bf65cf..4e80540560 100644
--- a/tensorflow/python/util/protobuf/compare.py
+++ b/tensorflow/python/util/protobuf/compare.py
@@ -62,7 +62,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 
 import six
 
@@ -71,6 +70,7 @@ from google.protobuf import descriptor_pool
 from google.protobuf import message
 from google.protobuf import text_format
 
+from ..compat import collections_abc
 
 def assertProtoEqual(self, a, b, check_initialized=True,  # pylint: disable=invalid-name
                      normalize_numbers=False, msg=None):
@@ -176,7 +176,7 @@ def NormalizeNumberFields(pb):
 
 
 def _IsMap(value):
-  return isinstance(value, collections.Mapping)
+  return isinstance(value, collections_abc.Mapping)
 
 
 def _IsRepeatedContainer(value):
diff --git a/tensorflow/python/keras/callbacks.py b/tensorflow/python/keras/callbacks.py
index a6dbe2ba71..0dd9617a8e 100644
--- a/tensorflow/python/keras/callbacks.py
+++ b/tensorflow/python/keras/callbacks.py
@@ -20,7 +20,7 @@ from __future__ import division
 from __future__ import print_function
 
 from collections import deque
-from collections import Iterable
+from collections.abc import Iterable
 from collections import OrderedDict
 import csv
 import json