Avoid deprecation warning related to the use of `collections.Sequence`. It will stop working in Python 3.8.

PiperOrigin-RevId: 316965801
Change-Id: Ia44313b1920653a0dd0a94d404ac914b08239c43

tensorflow/python/keras/engine/data_adapter.py

@@ -19,7 +19,6 @@ from __future__ import division
 from __future__ import print_function
 
 import abc
-import collections
 import contextlib
 import functools
 import itertools
@@ -57,7 +56,6 @@ try:
   from scipy import sparse as scipy_sparse  # pylint: disable=g-import-not-at-top
 except ImportError:
   scipy_sparse = None
-
 try:
   import pandas as pd  # pylint: disable=g-import-not-at-top
 except ImportError:
@@ -786,7 +784,6 @@ class GeneratorDataAdapter(DataAdapter):
     # Since we have to know the dtype of the python generator when we build the
     # dataset, we have to look at a batch to infer the structure.
     peek, x = self._peek_and_restore(x)
-    assert_not_namedtuple(peek)
     peek = self._standardize_batch(peek)
     peek = _process_tensorlike(peek)
 
@@ -1070,21 +1067,6 @@ def broadcast_sample_weight_modes(target_structure, sample_weight_modes):
   return sample_weight_modes
 
 
-def assert_not_namedtuple(x):
-  if (isinstance(x, tuple) and
-      # TODO(b/144192902): Use a namedtuple checking utility.
-      hasattr(x, "_fields") and
-      isinstance(x._fields, collections.Sequence) and
-      all(isinstance(f, six.string_types) for f in x._fields)):
-    raise ValueError(
-        "Received namedtuple ({}) with fields `{}` as input. namedtuples "
-        "cannot, in general, be unambiguously resolved into `x`, `y`, "
-        "and `sample_weight`. For this reason Keras has elected not to "
-        "support them. If you would like the value to be unpacked, "
-        "please explicitly convert it to a tuple before passing it to "
-        "Keras.".format(x.__class__, x._fields))
-
-
 class DataHandler(object):
   """Handles iterating over epoch-level `tf.data.Iterator` objects."""
 

tensorflow/python/keras/layers/recurrent.py

@@ -19,8 +19,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
-
 import numpy as np
 
 from tensorflow.python.distribute import distribution_strategy_context as ds_context
@@ -49,6 +47,11 @@ from tensorflow.python.util import nest
 from tensorflow.python.util.tf_export import keras_export
 from tensorflow.tools.docs import doc_controls
 
+try:
+  from collections import abc as collections_abc  # pylint: disable=g-import-not-at-top
+except ImportError:  # For Python 2
+  import collections as collections_abc  # pylint: disable=g-import-not-at-top
+
 
 RECURRENT_DROPOUT_WARNING_MSG = (
     'RNN `implementation=2` is not supported when `recurrent_dropout` is set. '
@@ -828,7 +831,7 @@ class RNN(Layer):
     # input shape: `(samples, time (padded with zeros), input_dim)`
     # note that the .build() method of subclasses MUST define
     # self.input_spec and self.state_spec with complete input shapes.
-    if (isinstance(inputs, collections.Sequence)
+    if (isinstance(inputs, collections_abc.Sequence)
         and not isinstance(inputs, tuple)):
       # get initial_state from full input spec
       # as they could be copied to multiple GPU.