Make sure image iterator classes subclass the tf.keras Sequence class if it is available

Author: fchollet

keras_preprocessing/__init__.py

@@ -40,4 +40,4 @@ def get_keras_submodule(name):
  return _KERAS_UTILS
 
 
-__version__ = '1.1.0'
+__version__ = '1.1.1'

keras_preprocessing/image/dataframe_iterator.py

@@ -89,6 +89,15 @@ class DataFrameIterator(BatchFromFilesMixin, Iterator):
  'binary', 'categorical', 'input', 'multi_output', 'raw', 'sparse', None
  }
 
+ def __new__(cls, *args, **kwargs):
+ try:
+ from tensorflow.keras.utils import Sequence as TFSequence
+ if TFSequence not in cls.__bases__:
+ cls.__bases__ = cls.__bases__ + (TFSequence,)
+ except ImportError:
+ pass
+ return super(DataFrameIterator, cls).__new__(cls)
+
  def __init__(self,
  dataframe,
  directory=None,

keras_preprocessing/image/directory_iterator.py

@@ -64,6 +64,15 @@ class DirectoryIterator(BatchFromFilesMixin, Iterator):
  """
  allowed_class_modes = {'categorical', 'binary', 'sparse', 'input', None}
 
+ def __new__(cls, *args, **kwargs):
+ try:
+ from tensorflow.keras.utils import Sequence as TFSequence
+ if TFSequence not in cls.__bases__:
+ cls.__bases__ = cls.__bases__ + (TFSequence,)
+ except ImportError:
+ pass
+ return super(DirectoryIterator, cls).__new__(cls)
+
  def __init__(self,
  directory,
  image_data_generator,

keras_preprocessing/image/numpy_array_iterator.py

@@ -42,6 +42,15 @@ class NumpyArrayIterator(Iterator):
  dtype: Dtype to use for the generated arrays.
  """
 
+ def __new__(cls, *args, **kwargs):
+ try:
+ from tensorflow.keras.utils import Sequence as TFSequence
+ if TFSequence not in cls.__bases__:
+ cls.__bases__ = cls.__bases__ + (TFSequence,)
+ except ImportError:
+ pass
+ return super(NumpyArrayIterator, cls).__new__(cls)
+
  def __init__(self,
  x,
  y,