update to latest keras api paths

Author: leewyang

examples/mnist/keras/mnist_mlp.py

@@ -11,12 +11,12 @@ def main_fun(args, ctx):
   import numpy
   import os
   import tensorflow as tf
-  import tensorflow.contrib.keras as keras
-  from tensorflow.contrib.keras.api.keras import backend as K
-  from tensorflow.contrib.keras.api.keras.models import Sequential, load_model, save_model
-  from tensorflow.contrib.keras.api.keras.layers import Dense, Dropout
-  from tensorflow.contrib.keras.api.keras.optimizers import RMSprop
-  from tensorflow.contrib.keras.python.keras.callbacks import LambdaCallback, TensorBoard
+  from tensorflow.python import keras
+  from tensorflow.python.keras import backend as K
+  from tensorflow.python.keras.models import Sequential, load_model, save_model
+  from tensorflow.python.keras.layers import Dense, Dropout
+  from tensorflow.python.keras.optimizers import RMSprop
+  from tensorflow.python.keras.callbacks import LambdaCallback, TensorBoard
   from tensorflow.python.saved_model import builder as saved_model_builder
   from tensorflow.python.saved_model import tag_constants
   from tensorflow.python.saved_model.signature_def_utils_impl import predict_signature_def
@@ -51,7 +51,7 @@ def generate_rdd_data(tf_feed, batch_size):
 
       # the data, shuffled and split between train and test sets
       if args.input_mode == 'tf':
-        from tensorflow.contrib.keras.api.keras.datasets import mnist
+        from tensorflow.python.keras.datasets import mnist
         (x_train, y_train), (x_test, y_test) = mnist.load_data()
         x_train = x_train.reshape(60000, 784)
         x_test = x_test.reshape(10000, 784)