From f654568388e0f5b729a1ca5dfa841ae242acc9d7 Mon Sep 17 00:00:00 2001
From: "A. Unique TensorFlower" <gardener@tensorflow.org>
Date: Thu, 26 Jan 2017 12:31:01 -0800
Subject: Update generated Python Op docs. Change: 145706499

---
 .../shard1/tf.constant_initializer.md                     | 15 +++++++++++----
 tensorflow/g3doc/api_docs/python/state_ops.md             | 15 +++++++++++----
 2 files changed, 22 insertions(+), 8 deletions(-)

(limited to 'tensorflow')

diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.constant_initializer.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.constant_initializer.md
index 2e8cac5930..fa95f791bf 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.constant_initializer.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.constant_initializer.md
@@ -18,6 +18,9 @@ Args:
     elements of the initialized variable will be set to the corresponding
     value in the `value` argument.
   dtype: The data type.
+  verify_shape: Boolean that enables verification of the shape of `value`. If
+    `True`, the initializer will throw an error if the shape of `value` is not
+    compatible with the shape of the initialized tensor.
 
 Examples:
   The following example can be rewritten using a numpy.ndarray instead
@@ -34,7 +37,6 @@ Examples:
   >>> init = tf.constant_initializer(value)
 
   >>> print('fitting shape:')
-  >>> tf.reset_default_graph()
   >>> with tf.Session():
   >>>   x = tf.get_variable('x', shape=[2, 4], initializer=init)
   >>>   x.initializer.run()
@@ -45,7 +47,6 @@ Examples:
    [ 4.  5.  6.  7.]]
 
   >>> print('larger shape:')
-  >>> tf.reset_default_graph()
   >>> with tf.Session():
   >>>   x = tf.get_variable('x', shape=[3, 4], initializer=init)
   >>>   x.initializer.run()
@@ -57,11 +58,17 @@ Examples:
    [ 7.  7.  7.  7.]]
 
   >>> print('smaller shape:')
-  >>> tf.reset_default_graph()
   >>> with tf.Session():
   >>>   x = tf.get_variable('x', shape=[2, 3], initializer=init)
 
   ValueError: Too many elements provided. Needed at most 6, but received 8
+
+  >>> print('shape verification:')
+  >>> init_verify = tf.constant_initializer(value, verify_shape=True)
+  >>> with tf.Session():
+  >>>   x = tf.get_variable('x', shape=[3, 4], initializer=init_verify)
+
+  TypeError: Expected Tensor's shape: (3, 4), got (8,).
 ```
 - - -
 
@@ -72,7 +79,7 @@ Examples:
 
 - - -
 
-#### `tf.constant_initializer.__init__(value=0, dtype=tf.float32)` {#constant_initializer.__init__}
+#### `tf.constant_initializer.__init__(value=0, dtype=tf.float32, verify_shape=False)` {#constant_initializer.__init__}
 
 
 
diff --git a/tensorflow/g3doc/api_docs/python/state_ops.md b/tensorflow/g3doc/api_docs/python/state_ops.md
index 9f7eb2a419..4201ca8754 100644
--- a/tensorflow/g3doc/api_docs/python/state_ops.md
+++ b/tensorflow/g3doc/api_docs/python/state_ops.md
@@ -2535,6 +2535,9 @@ Args:
     elements of the initialized variable will be set to the corresponding
     value in the `value` argument.
   dtype: The data type.
+  verify_shape: Boolean that enables verification of the shape of `value`. If
+    `True`, the initializer will throw an error if the shape of `value` is not
+    compatible with the shape of the initialized tensor.
 
 Examples:
   The following example can be rewritten using a numpy.ndarray instead
@@ -2551,7 +2554,6 @@ Examples:
   >>> init = tf.constant_initializer(value)
 
   >>> print('fitting shape:')
-  >>> tf.reset_default_graph()
   >>> with tf.Session():
   >>>   x = tf.get_variable('x', shape=[2, 4], initializer=init)
   >>>   x.initializer.run()
@@ -2562,7 +2564,6 @@ Examples:
    [ 4.  5.  6.  7.]]
 
   >>> print('larger shape:')
-  >>> tf.reset_default_graph()
   >>> with tf.Session():
   >>>   x = tf.get_variable('x', shape=[3, 4], initializer=init)
   >>>   x.initializer.run()
@@ -2574,11 +2575,17 @@ Examples:
    [ 7.  7.  7.  7.]]
 
   >>> print('smaller shape:')
-  >>> tf.reset_default_graph()
   >>> with tf.Session():
   >>>   x = tf.get_variable('x', shape=[2, 3], initializer=init)
 
   ValueError: Too many elements provided. Needed at most 6, but received 8
+
+  >>> print('shape verification:')
+  >>> init_verify = tf.constant_initializer(value, verify_shape=True)
+  >>> with tf.Session():
+  >>>   x = tf.get_variable('x', shape=[3, 4], initializer=init_verify)
+
+  TypeError: Expected Tensor's shape: (3, 4), got (8,).
 ```
 - - -
 
@@ -2589,7 +2596,7 @@ Examples:
 
 - - -
 
-#### `tf.constant_initializer.__init__(value=0, dtype=tf.float32)` {#constant_initializer.__init__}
+#### `tf.constant_initializer.__init__(value=0, dtype=tf.float32, verify_shape=False)` {#constant_initializer.__init__}
 
 
 
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