message: Replaced deprecated functions in exmaples
  Replaced deprecated functions `fit_generator` and 'predict_generator` with `fit` and `predict` respectively.
  `fit` and `predict` support generators.
diff: @@ -503,7 +503,7 @@ class DataFrameIterator(image.DataFrameIterator, Iterator):
  - `"raw"`: numpy array of values in `y_col` column(s),
  - `"sparse"`: 1D numpy array of integer labels, - `None`, no targets
  are returned (the generator will only yield batches of image data,
  - which is useful to use in `model.predict_generator()`).
  + which is useful to use in `model.predict()`).
  batch_size: Integer, size of a batch.
  shuffle: Boolean, whether to shuffle the data between epochs.
  seed: Random seed for data shuffling.
  @@ -743,7 +743,7 @@ class ImageDataGenerator(image.ImageDataGenerator):
  seed=seed)
  # combine generators into one which yields image and masks
  train_generator = zip(image_generator, mask_generator)
  - model.fit_generator(
  + model.fit(
  train_generator,
  steps_per_epoch=2000,
  epochs=50)
  @@ -909,7 +909,7 @@ class ImageDataGenerator(image.ImageDataGenerator):
  will be images identical to input images (mainly used to work with
  autoencoders). - If None, no labels are returned (the generator
  will only yield batches of image data, which is useful to use with
  - `model.predict_generator()`). Please note that in case of
  + `model.predict()`). Please note that in case of
  class_mode None, the data still needs to reside in a subdirectory
  of `directory` for it to work correctly.
  batch_size: Size of the batches of data (default: 32).
  @@ -1027,7 +1027,7 @@ class ImageDataGenerator(image.ImageDataGenerator):
  - `"raw"`: numpy array of values in `y_col` column(s),
  - `"sparse"`: 1D numpy array of integer labels, - `None`, no targets
  are returned (the generator will only yield batches of image data,
  - which is useful to use in `model.predict_generator()`).
  + which is useful to use in `model.predict()`).
  batch_size: size of the batches of data (default: 32).
  shuffle: whether to shuffle the data (default: True)
  seed: optional random seed for shuffling and transformations.
  