replace tf.types.xxx with tf.xxx

examples/1 - Introduction/basic_operations.py

@@ -23,8 +23,8 @@ with tf.Session() as sess:
 # The value returned by the constructor represents the output
 # of the Variable op. (define as input when running session)
 # tf Graph input
-a = tf.placeholder(tf.types.int16)
-b = tf.placeholder(tf.types.int16)
+a = tf.placeholder(tf.int16)
+b = tf.placeholder(tf.int16)
 
 # Define some operations
 add = tf.add(a, b)

notebooks/1 - Introduction/basic_operations.ipynb

@@ -76,8 +76,8 @@
     "# The value returned by the constructor represents the output\n",
     "# of the Variable op. (define as input when running session)\n",
     "# tf Graph input\n",
-    "a = tf.placeholder(tf.types.int16)\n",
-    "b = tf.placeholder(tf.types.int16)"
+    "a = tf.placeholder(tf.int16)\n",
+    "b = tf.placeholder(tf.int16)"
    ]
   },
   {

notebooks/3 - Neural Networks/alexnet.ipynb

@@ -91,7 +91,7 @@
     "# tf Graph input\n",
     "x = tf.placeholder(tf.float32, [None, n_input])\n",
     "y = tf.placeholder(tf.float32, [None, n_classes])\n",
-    "keep_prob = tf.placeholder(tf.types.float32) # dropout (keep probability)"
+    "keep_prob = tf.placeholder(tf.float32) # dropout (keep probability)"
    ]
   },
   {

notebooks/3 - Neural Networks/convolutional_network.ipynb

@@ -91,7 +91,7 @@
     "# tf Graph input\n",
     "x = tf.placeholder(tf.float32, [None, n_input])\n",
     "y = tf.placeholder(tf.float32, [None, n_classes])\n",
-    "keep_prob = tf.placeholder(tf.types.float32) #dropout (keep probability)"
+    "keep_prob = tf.placeholder(tf.float32) #dropout (keep probability)"
    ]
   },
   {