1 files changed, 25 insertions, 13 deletions
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.contrib.distributions.GammaWithSoftplusAlphaBeta.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.contrib.distributions.GammaWithSoftplusAlphaBeta.md
index 4eff4bd5a6..c9b283547a 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.contrib.distributions.GammaWithSoftplusAlphaBeta.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.contrib.distributions.GammaWithSoftplusAlphaBeta.md
@@ -63,7 +63,7 @@ Inverse scale parameter.
 
 - - -
 
-#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.cdf(value, name='cdf')` {#GammaWithSoftplusAlphaBeta.cdf}
+#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.cdf(value, name='cdf', **condition_kwargs)` {#GammaWithSoftplusAlphaBeta.cdf}
 
 Cumulative distribution function.
 
@@ -78,6 +78,7 @@ 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:
 
@@ -97,7 +98,7 @@ The `DType` of `Tensor`s handled by this `Distribution`.
 
 #### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.entropy(name='entropy')` {#GammaWithSoftplusAlphaBeta.entropy}
 
-Shanon entropy in nats.
+Shannon entropy in nats.
 
 Additional documentation from `Gamma`:
 
@@ -172,7 +173,7 @@ Same meaning as `event_shape`. May be only partially defined.
 
 - - -
 
-#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.log_cdf(value, name='log_cdf')` {#GammaWithSoftplusAlphaBeta.log_cdf}
+#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.log_cdf(value, name='log_cdf', **condition_kwargs)` {#GammaWithSoftplusAlphaBeta.log_cdf}
 
 Log cumulative distribution function.
 
@@ -191,6 +192,7 @@ 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:
 
@@ -201,7 +203,7 @@ a more accurate answer than simply taking the logarithm of the `cdf` when
 
 - - -
 
-#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.log_pdf(value, name='log_pdf')` {#GammaWithSoftplusAlphaBeta.log_pdf}
+#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.log_pdf(value, name='log_pdf', **condition_kwargs)` {#GammaWithSoftplusAlphaBeta.log_pdf}
 
 Log probability density function.
 
@@ -210,6 +212,7 @@ 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:
 
@@ -225,7 +228,7 @@ Log probability density function.
 
 - - -
 
-#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.log_pmf(value, name='log_pmf')` {#GammaWithSoftplusAlphaBeta.log_pmf}
+#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.log_pmf(value, name='log_pmf', **condition_kwargs)` {#GammaWithSoftplusAlphaBeta.log_pmf}
 
 Log probability mass function.
 
@@ -234,6 +237,7 @@ 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:
 
@@ -249,7 +253,7 @@ Log probability mass function.
 
 - - -
 
-#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.log_prob(value, name='log_prob')` {#GammaWithSoftplusAlphaBeta.log_prob}
+#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.log_prob(value, name='log_prob', **condition_kwargs)` {#GammaWithSoftplusAlphaBeta.log_prob}
 
 Log probability density/mass function (depending on `is_continuous`).
 
@@ -258,6 +262,7 @@ 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:
 
@@ -268,7 +273,7 @@ Log probability density/mass function (depending on `is_continuous`).
 
 - - -
 
-#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.log_survival_function(value, name='log_survival_function')` {#GammaWithSoftplusAlphaBeta.log_survival_function}
+#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.log_survival_function(value, name='log_survival_function', **condition_kwargs)` {#GammaWithSoftplusAlphaBeta.log_survival_function}
 
 Log survival function.
 
@@ -288,6 +293,7 @@ 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:
 
@@ -373,7 +379,7 @@ Dictionary of parameters used by this `Distribution`.
 
 - - -
 
-#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.pdf(value, name='pdf')` {#GammaWithSoftplusAlphaBeta.pdf}
+#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.pdf(value, name='pdf', **condition_kwargs)` {#GammaWithSoftplusAlphaBeta.pdf}
 
 Probability density function.
 
@@ -382,6 +388,7 @@ 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:
 
@@ -397,7 +404,7 @@ Probability density function.
 
 - - -
 
-#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.pmf(value, name='pmf')` {#GammaWithSoftplusAlphaBeta.pmf}
+#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.pmf(value, name='pmf', **condition_kwargs)` {#GammaWithSoftplusAlphaBeta.pmf}
 
 Probability mass function.
 
@@ -406,6 +413,7 @@ 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:
 
@@ -421,7 +429,7 @@ Probability mass function.
 
 - - -
 
-#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.prob(value, name='prob')` {#GammaWithSoftplusAlphaBeta.prob}
+#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.prob(value, name='prob', **condition_kwargs)` {#GammaWithSoftplusAlphaBeta.prob}
 
 Probability density/mass function (depending on `is_continuous`).
 
@@ -430,6 +438,7 @@ 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:
 
@@ -440,7 +449,7 @@ Probability density/mass function (depending on `is_continuous`).
 
 - - -
 
-#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.sample(sample_shape=(), seed=None, name='sample')` {#GammaWithSoftplusAlphaBeta.sample}
+#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.sample(sample_shape=(), seed=None, name='sample', **condition_kwargs)` {#GammaWithSoftplusAlphaBeta.sample}
 
 Generate samples of the specified shape.
 
@@ -453,6 +462,7 @@ 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:
 
@@ -462,7 +472,7 @@ sample.
 
 - - -
 
-#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.sample_n(n, seed=None, name='sample_n')` {#GammaWithSoftplusAlphaBeta.sample_n}
+#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.sample_n(n, seed=None, name='sample_n', **condition_kwargs)` {#GammaWithSoftplusAlphaBeta.sample_n}
 
 Generate `n` samples.
 
@@ -478,6 +488,7 @@ See the documentation for tf.random_gamma for more details.
     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:
 
@@ -499,7 +510,7 @@ Standard deviation.
 
 - - -
 
-#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.survival_function(value, name='survival_function')` {#GammaWithSoftplusAlphaBeta.survival_function}
+#### `tf.contrib.distributions.GammaWithSoftplusAlphaBeta.survival_function(value, name='survival_function', **condition_kwargs)` {#GammaWithSoftplusAlphaBeta.survival_function}
 
 Survival function.
 
@@ -516,6 +527,7 @@ 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: