Update generated Python Op docs.

Change: 146864267

3 files changed, 80 insertions, 0 deletions

diff --git a/tensorflow/g3doc/api_docs/python/constant_op.md b/tensorflow/g3doc/api_docs/python/constant_op.md
index 561e6c8d6c..62654874f4 100644
--- a/tensorflow/g3doc/api_docs/python/constant_op.md
+++ b/tensorflow/g3doc/api_docs/python/constant_op.md
@@ -633,6 +633,47 @@ Example:
 
 - - -
 
+### `tf.random_poisson(lam, shape, dtype=tf.float32, seed=None, name=None)` {#random_poisson}
+
+Draws `shape` samples from each of the given Poisson distribution(s).
+
+`lam` is the rate parameter describing the distribution(s).
+
+Example:
+
+  samples = tf.random_poisson([0.5, 1.5], [10])
+  # samples has shape [10, 2], where each slice [:, 0] and [:, 1] represents
+  # the samples drawn from each distribution
+
+  samples = tf.random_poisson([12.2, 3.3], [7, 5])
+  # samples has shape [7, 5, 2], where each slice [:, :, 0] and [:, :, 1]
+  # represents the 7x5 samples drawn from each of the two distributions
+
+##### Args:
+
+
+*  <b>`lam`</b>: A Tensor or Python value or N-D array of type `dtype`.
+    `lam` provides the rate parameter(s) describing the poisson
+    distribution(s) to sample.
+*  <b>`shape`</b>: A 1-D integer Tensor or Python array. The shape of the output samples
+    to be drawn per "rate"-parameterized distribution.
+*  <b>`dtype`</b>: The type of `lam` and the output: `float16`, `float32`, or
+    `float64`.
+*  <b>`seed`</b>: A Python integer. Used to create a random seed for the distributions.
+    See
+    [`set_random_seed`](../../api_docs/python/constant_op.md#set_random_seed)
+    for behavior.
+*  <b>`name`</b>: Optional name for the operation.
+
+##### Returns:
+
+
+*  <b>`samples`</b>: a `Tensor` of shape `tf.concat(shape, tf.shape(lam))` with
+    values of type `dtype`.
+
+
+- - -
+
 ### `tf.set_random_seed(seed)` {#set_random_seed}
 
 Sets the graph-level random seed.
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.random_poisson.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.random_poisson.md
new file mode 100644
index 0000000000..d56c967168
--- /dev/null
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.random_poisson.md
@@ -0,0 +1,38 @@
+### `tf.random_poisson(lam, shape, dtype=tf.float32, seed=None, name=None)` {#random_poisson}
+
+Draws `shape` samples from each of the given Poisson distribution(s).
+
+`lam` is the rate parameter describing the distribution(s).
+
+Example:
+
+  samples = tf.random_poisson([0.5, 1.5], [10])
+  # samples has shape [10, 2], where each slice [:, 0] and [:, 1] represents
+  # the samples drawn from each distribution
+
+  samples = tf.random_poisson([12.2, 3.3], [7, 5])
+  # samples has shape [7, 5, 2], where each slice [:, :, 0] and [:, :, 1]
+  # represents the 7x5 samples drawn from each of the two distributions
+
+##### Args:
+
+
+*  <b>`lam`</b>: A Tensor or Python value or N-D array of type `dtype`.
+    `lam` provides the rate parameter(s) describing the poisson
+    distribution(s) to sample.
+*  <b>`shape`</b>: A 1-D integer Tensor or Python array. The shape of the output samples
+    to be drawn per "rate"-parameterized distribution.
+*  <b>`dtype`</b>: The type of `lam` and the output: `float16`, `float32`, or
+    `float64`.
+*  <b>`seed`</b>: A Python integer. Used to create a random seed for the distributions.
+    See
+    [`set_random_seed`](../../api_docs/python/constant_op.md#set_random_seed)
+    for behavior.
+*  <b>`name`</b>: Optional name for the operation.
+
+##### Returns:
+
+
+*  <b>`samples`</b>: a `Tensor` of shape `tf.concat(shape, tf.shape(lam))` with
+    values of type `dtype`.
+
diff --git a/tensorflow/g3doc/api_docs/python/index.md b/tensorflow/g3doc/api_docs/python/index.md
index 1f123c90bd..f3e456aa90 100644
--- a/tensorflow/g3doc/api_docs/python/index.md
+++ b/tensorflow/g3doc/api_docs/python/index.md
@@ -64,6 +64,7 @@
   * [`random_crop`](../../api_docs/python/constant_op.md#random_crop)
   * [`random_gamma`](../../api_docs/python/constant_op.md#random_gamma)
   * [`random_normal`](../../api_docs/python/constant_op.md#random_normal)
+  * [`random_poisson`](../../api_docs/python/constant_op.md#random_poisson)
   * [`random_shuffle`](../../api_docs/python/constant_op.md#random_shuffle)
   * [`random_uniform`](../../api_docs/python/constant_op.md#random_uniform)
   * [`range`](../../api_docs/python/constant_op.md#range)