Update generated Python Op docs.

Change: 123081047

tensorflow/g3doc/api_docs/python/functions_and_classes/tf.string_to_hash_bucket_fast.md

@@ -4,11 +4,15 @@ Converts each string in the input Tensor to its hash mod by a number of buckets.
 
 The hash function is deterministic on the content of the string within the
 process and will never change. However, it is not suitable for cryptography.
+This function may be used when CPU time is scarce and inputs are trusted or
+unimportant. There is a risk of adversaries constructing inputs that all hash
+to the same bucket. To prevent this problem, use a strong hash function with
+`tf.string_to_hash_bucket_strong`.
 
 ##### Args:
 
 
-*  <b>`input`</b>: A `Tensor` of type `string`. The strings to assing a hash bucket.
+*  <b>`input`</b>: A `Tensor` of type `string`. The strings to assign a hash bucket.
 *  <b>`num_buckets`</b>: An `int` that is `>= 1`. The number of buckets.
 *  <b>`name`</b>: A name for the operation (optional).
 

tensorflow/g3doc/api_docs/python/functions_and_classes/tf.string_to_hash_bucket_strong.md

@@ -0,0 +1,30 @@
+### `tf.string_to_hash_bucket_strong(input, num_buckets, key, name=None)` {#string_to_hash_bucket_strong}
+
+Converts each string in the input Tensor to its hash mod by a number of buckets.
+
+The hash function is deterministic on the content of the string within the
+process. The hash function is a keyed hash function, where attribute `key`
+defines the key of the hash function. `key` is an array of 2 elements.
+
+A strong hash is important when inputs may be malicious, e.g. URLs with
+additional components. Adversaries could try to make their inputs hash to the
+same bucket for a denial-of-service attack or to skew the results. A strong
+hash prevents this by making it dificult, if not infeasible, to compute inputs
+that hash to the same bucket. This comes at a cost of roughly 4x higher compute
+time than tf.string_to_hash_bucket_fast.
+
+##### Args:
+
+
+*  <b>`input`</b>: A `Tensor` of type `string`. The strings to assign a hash bucket.
+*  <b>`num_buckets`</b>: An `int` that is `>= 1`. The number of buckets.
+*  <b>`key`</b>: A list of `ints`.
+    The key for the keyed hash function passed as a list of two uint64
+    elements.
+*  <b>`name`</b>: A name for the operation (optional).
+
+##### Returns:
+
+  A `Tensor` of type `int64`.
+  A Tensor of the same shape as the input `string_tensor`.
+

tensorflow/g3doc/api_docs/python/index.md

@@ -260,6 +260,7 @@
   * [`reduce_join`](../../api_docs/python/string_ops.md#reduce_join)
   * [`string_to_hash_bucket`](../../api_docs/python/string_ops.md#string_to_hash_bucket)
   * [`string_to_hash_bucket_fast`](../../api_docs/python/string_ops.md#string_to_hash_bucket_fast)
+  * [`string_to_hash_bucket_strong`](../../api_docs/python/string_ops.md#string_to_hash_bucket_strong)
 
 * **[Histograms](../../api_docs/python/histogram_ops.md)**:
   * [`histogram_fixed_width`](../../api_docs/python/histogram_ops.md#histogram_fixed_width)

tensorflow/g3doc/api_docs/python/string_ops.md

@@ -20,11 +20,15 @@ Converts each string in the input Tensor to its hash mod by a number of buckets.
 
 The hash function is deterministic on the content of the string within the
 process and will never change. However, it is not suitable for cryptography.
+This function may be used when CPU time is scarce and inputs are trusted or
+unimportant. There is a risk of adversaries constructing inputs that all hash
+to the same bucket. To prevent this problem, use a strong hash function with
+`tf.string_to_hash_bucket_strong`.
 
 ##### Args:
 
 
-*  <b>`input`</b>: A `Tensor` of type `string`. The strings to assing a hash bucket.
+*  <b>`input`</b>: A `Tensor` of type `string`. The strings to assign a hash bucket.
 *  <b>`num_buckets`</b>: An `int` that is `>= 1`. The number of buckets.
 *  <b>`name`</b>: A name for the operation (optional).
 
@@ -34,6 +38,39 @@ process and will never change. However, it is not suitable for cryptography.
   A Tensor of the same shape as the input `string_tensor`.
 
 
+- - -
+
+### `tf.string_to_hash_bucket_strong(input, num_buckets, key, name=None)` {#string_to_hash_bucket_strong}
+
+Converts each string in the input Tensor to its hash mod by a number of buckets.
+
+The hash function is deterministic on the content of the string within the
+process. The hash function is a keyed hash function, where attribute `key`
+defines the key of the hash function. `key` is an array of 2 elements.
+
+A strong hash is important when inputs may be malicious, e.g. URLs with
+additional components. Adversaries could try to make their inputs hash to the
+same bucket for a denial-of-service attack or to skew the results. A strong
+hash prevents this by making it dificult, if not infeasible, to compute inputs
+that hash to the same bucket. This comes at a cost of roughly 4x higher compute
+time than tf.string_to_hash_bucket_fast.
+
+##### Args:
+
+
+*  <b>`input`</b>: A `Tensor` of type `string`. The strings to assign a hash bucket.
+*  <b>`num_buckets`</b>: An `int` that is `>= 1`. The number of buckets.
+*  <b>`key`</b>: A list of `ints`.
+    The key for the keyed hash function passed as a list of two uint64
+    elements.
+*  <b>`name`</b>: A name for the operation (optional).
+
+##### Returns:
+
+  A `Tensor` of type `int64`.
+  A Tensor of the same shape as the input `string_tensor`.
+
+
 - - -
 
 ### `tf.string_to_hash_bucket(string_tensor, num_buckets, name=None)` {#string_to_hash_bucket}