title: Data-augmentation generators not working with TensorFlow 2.0
body: <p>I am trying to train model with image data-augmentation generators on TensorFlow 2.0, after downloading Kaggle's cats_vs_dogs dataset using below code.</p>
  
  <pre class="lang-py prettyprint-override"><code>train_datagen = ImageDataGenerator(rescale=1. / 255,
                                     rotation_range=40,
                                     width_shift_range=0.2,
                                     height_shift_range=0.2,
                                     shear_range=0.2,
                                     zoom_range=0.2,
                                     horizontal_flip=True)
  
  test_datagen = ImageDataGenerator(rescale=1. / 255)
  
  train_generator = train_datagen.flow_from_directory(train_dir,  
                                                      target_size=(150, 150), 
                                                      batch_size=32,
                                                      class_mode='binary')
  
  validation_generator = test_datagen.flow_from_directory(validation_dir,  
                                                      target_size=(150, 150), 
                                                      batch_size=32,
                                                      class_mode='binary')
  
  history = model.fit_generator(train_generator,
                                steps_per_epoch=100,
                                epochs=100,
                                validation_data=validation_generator,
                                validation_steps=50)
  </code></pre>
  
  <p>But on first epoch, getting this error: </p>
  
  <pre class="lang-py prettyprint-override"><code>Found 2000 images belonging to 2 classes.
  Found 1000 images belonging to 2 classes.
  WARNING:tensorflow:From &lt;ipython-input-18-e571f2719e1b&gt;:27: Model.fit_generator (from tensorflow.python.keras.engine.training) is deprecated and will be removed in a future version.
  Instructions for updating:
  Please use Model.fit, which supports generators.
  WARNING:tensorflow:sample_weight modes were coerced from
    ...
      to  
    ['...']
  WARNING:tensorflow:sample_weight modes were coerced from
    ...
      to  
    ['...']
  Train for 100 steps, validate for 50 steps
  Epoch 1/100
   63/100 [=================&gt;............] - ETA: 59s - loss: 0.7000 - accuracy: 0.5000 WARNING:tensorflow:Your input ran out of data; interrupting training. Make sure that your dataset or generator can generate at least `steps_per_epoch * epochs` batches (in this case, 10000 batches). You may need to use the repeat() function when building your dataset.
  </code></pre>
  
  <p>How should I modify the above code base for TensorFlow 2?</p>