1 files changed, 25 insertions, 13 deletions
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.contrib.distributions.Categorical.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.contrib.distributions.Categorical.md
index 7d3f2a3a25..0e15dca5bc 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.contrib.distributions.Categorical.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.contrib.distributions.Categorical.md
@@ -109,7 +109,7 @@ independent distributions of this kind the instance represents.
 
 - - -
 
-#### `tf.contrib.distributions.Categorical.cdf(value, name='cdf')` {#Categorical.cdf}
+#### `tf.contrib.distributions.Categorical.cdf(value, name='cdf', **condition_kwargs)` {#Categorical.cdf}
 
 Cumulative distribution function.
 
@@ -124,6 +124,7 @@ cdf(x) := P[X <= x]
 
 *  <b>`value`</b>: `float` or `double` `Tensor`.
 *  <b>`name`</b>: The name to give this op.
+*  <b>`**condition_kwargs`</b>: Named arguments forwarded to subclass implementation.
 
 ##### Returns:
 
@@ -143,7 +144,7 @@ The `DType` of `Tensor`s handled by this `Distribution`.
 
 #### `tf.contrib.distributions.Categorical.entropy(name='entropy')` {#Categorical.entropy}
 
-Shanon entropy in nats.
+Shannon entropy in nats.
 
 
 - - -
@@ -207,7 +208,7 @@ Same meaning as `event_shape`. May be only partially defined.
 
 - - -
 
-#### `tf.contrib.distributions.Categorical.log_cdf(value, name='log_cdf')` {#Categorical.log_cdf}
+#### `tf.contrib.distributions.Categorical.log_cdf(value, name='log_cdf', **condition_kwargs)` {#Categorical.log_cdf}
 
 Log cumulative distribution function.
 
@@ -226,6 +227,7 @@ a more accurate answer than simply taking the logarithm of the `cdf` when
 
 *  <b>`value`</b>: `float` or `double` `Tensor`.
 *  <b>`name`</b>: The name to give this op.
+*  <b>`**condition_kwargs`</b>: Named arguments forwarded to subclass implementation.
 
 ##### Returns:
 
@@ -236,7 +238,7 @@ a more accurate answer than simply taking the logarithm of the `cdf` when
 
 - - -
 
-#### `tf.contrib.distributions.Categorical.log_pdf(value, name='log_pdf')` {#Categorical.log_pdf}
+#### `tf.contrib.distributions.Categorical.log_pdf(value, name='log_pdf', **condition_kwargs)` {#Categorical.log_pdf}
 
 Log probability density function.
 
@@ -245,6 +247,7 @@ Log probability density function.
 
 *  <b>`value`</b>: `float` or `double` `Tensor`.
 *  <b>`name`</b>: The name to give this op.
+*  <b>`**condition_kwargs`</b>: Named arguments forwarded to subclass implementation.
 
 ##### Returns:
 
@@ -260,7 +263,7 @@ Log probability density function.
 
 - - -
 
-#### `tf.contrib.distributions.Categorical.log_pmf(value, name='log_pmf')` {#Categorical.log_pmf}
+#### `tf.contrib.distributions.Categorical.log_pmf(value, name='log_pmf', **condition_kwargs)` {#Categorical.log_pmf}
 
 Log probability mass function.
 
@@ -269,6 +272,7 @@ Log probability mass function.
 
 *  <b>`value`</b>: `float` or `double` `Tensor`.
 *  <b>`name`</b>: The name to give this op.
+*  <b>`**condition_kwargs`</b>: Named arguments forwarded to subclass implementation.
 
 ##### Returns:
 
@@ -284,7 +288,7 @@ Log probability mass function.
 
 - - -
 
-#### `tf.contrib.distributions.Categorical.log_prob(value, name='log_prob')` {#Categorical.log_prob}
+#### `tf.contrib.distributions.Categorical.log_prob(value, name='log_prob', **condition_kwargs)` {#Categorical.log_prob}
 
 Log probability density/mass function (depending on `is_continuous`).
 
@@ -293,6 +297,7 @@ Log probability density/mass function (depending on `is_continuous`).
 
 *  <b>`value`</b>: `float` or `double` `Tensor`.
 *  <b>`name`</b>: The name to give this op.
+*  <b>`**condition_kwargs`</b>: Named arguments forwarded to subclass implementation.
 
 ##### Returns:
 
@@ -303,7 +308,7 @@ Log probability density/mass function (depending on `is_continuous`).
 
 - - -
 
-#### `tf.contrib.distributions.Categorical.log_survival_function(value, name='log_survival_function')` {#Categorical.log_survival_function}
+#### `tf.contrib.distributions.Categorical.log_survival_function(value, name='log_survival_function', **condition_kwargs)` {#Categorical.log_survival_function}
 
 Log survival function.
 
@@ -323,6 +328,7 @@ survival function, which are more accurate than `1 - cdf(x)` when `x >> 1`.
 
 *  <b>`value`</b>: `float` or `double` `Tensor`.
 *  <b>`name`</b>: The name to give this op.
+*  <b>`**condition_kwargs`</b>: Named arguments forwarded to subclass implementation.
 
 ##### Returns:
 
@@ -425,7 +431,7 @@ Dictionary of parameters used by this `Distribution`.
 
 - - -
 
-#### `tf.contrib.distributions.Categorical.pdf(value, name='pdf')` {#Categorical.pdf}
+#### `tf.contrib.distributions.Categorical.pdf(value, name='pdf', **condition_kwargs)` {#Categorical.pdf}
 
 Probability density function.
 
@@ -434,6 +440,7 @@ Probability density function.
 
 *  <b>`value`</b>: `float` or `double` `Tensor`.
 *  <b>`name`</b>: The name to give this op.
+*  <b>`**condition_kwargs`</b>: Named arguments forwarded to subclass implementation.
 
 ##### Returns:
 
@@ -449,7 +456,7 @@ Probability density function.
 
 - - -
 
-#### `tf.contrib.distributions.Categorical.pmf(value, name='pmf')` {#Categorical.pmf}
+#### `tf.contrib.distributions.Categorical.pmf(value, name='pmf', **condition_kwargs)` {#Categorical.pmf}
 
 Probability mass function.
 
@@ -458,6 +465,7 @@ Probability mass function.
 
 *  <b>`value`</b>: `float` or `double` `Tensor`.
 *  <b>`name`</b>: The name to give this op.
+*  <b>`**condition_kwargs`</b>: Named arguments forwarded to subclass implementation.
 
 ##### Returns:
 
@@ -473,7 +481,7 @@ Probability mass function.
 
 - - -
 
-#### `tf.contrib.distributions.Categorical.prob(value, name='prob')` {#Categorical.prob}
+#### `tf.contrib.distributions.Categorical.prob(value, name='prob', **condition_kwargs)` {#Categorical.prob}
 
 Probability density/mass function (depending on `is_continuous`).
 
@@ -482,6 +490,7 @@ Probability density/mass function (depending on `is_continuous`).
 
 *  <b>`value`</b>: `float` or `double` `Tensor`.
 *  <b>`name`</b>: The name to give this op.
+*  <b>`**condition_kwargs`</b>: Named arguments forwarded to subclass implementation.
 
 ##### Returns:
 
@@ -492,7 +501,7 @@ Probability density/mass function (depending on `is_continuous`).
 
 - - -
 
-#### `tf.contrib.distributions.Categorical.sample(sample_shape=(), seed=None, name='sample')` {#Categorical.sample}
+#### `tf.contrib.distributions.Categorical.sample(sample_shape=(), seed=None, name='sample', **condition_kwargs)` {#Categorical.sample}
 
 Generate samples of the specified shape.
 
@@ -505,6 +514,7 @@ sample.
 *  <b>`sample_shape`</b>: 0D or 1D `int32` `Tensor`. Shape of the generated samples.
 *  <b>`seed`</b>: Python integer seed for RNG
 *  <b>`name`</b>: name to give to the op.
+*  <b>`**condition_kwargs`</b>: Named arguments forwarded to subclass implementation.
 
 ##### Returns:
 
@@ -514,7 +524,7 @@ sample.
 
 - - -
 
-#### `tf.contrib.distributions.Categorical.sample_n(n, seed=None, name='sample_n')` {#Categorical.sample_n}
+#### `tf.contrib.distributions.Categorical.sample_n(n, seed=None, name='sample_n', **condition_kwargs)` {#Categorical.sample_n}
 
 Generate `n` samples.
 
@@ -525,6 +535,7 @@ Generate `n` samples.
     observations to sample.
 *  <b>`seed`</b>: Python integer seed for RNG
 *  <b>`name`</b>: name to give to the op.
+*  <b>`**condition_kwargs`</b>: Named arguments forwarded to subclass implementation.
 
 ##### Returns:
 
@@ -546,7 +557,7 @@ Standard deviation.
 
 - - -
 
-#### `tf.contrib.distributions.Categorical.survival_function(value, name='survival_function')` {#Categorical.survival_function}
+#### `tf.contrib.distributions.Categorical.survival_function(value, name='survival_function', **condition_kwargs)` {#Categorical.survival_function}
 
 Survival function.
 
@@ -563,6 +574,7 @@ survival_function(x) = P[X > x]
 
 *  <b>`value`</b>: `float` or `double` `Tensor`.
 *  <b>`name`</b>: The name to give this op.
+*  <b>`**condition_kwargs`</b>: Named arguments forwarded to subclass implementation.
 
 ##### Returns: