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-rw-r--r--tensorflow/g3doc/api_docs/python/constant_op.md48
-rw-r--r--tensorflow/g3doc/api_docs/python/contrib.distributions.md22
-rw-r--r--tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.contrib.distributions.Chi2.md11
-rw-r--r--tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.contrib.distributions.Gamma.md11
-rw-r--r--tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.random_gamma.md45
-rw-r--r--tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.train.SummaryWriter.md14
-rw-r--r--tensorflow/g3doc/api_docs/python/index.md1
-rw-r--r--tensorflow/g3doc/api_docs/python/train.md14
8 files changed, 150 insertions, 16 deletions
diff --git a/tensorflow/g3doc/api_docs/python/constant_op.md b/tensorflow/g3doc/api_docs/python/constant_op.md
index bdd39690a6..ccd881cca8 100644
--- a/tensorflow/g3doc/api_docs/python/constant_op.md
+++ b/tensorflow/g3doc/api_docs/python/constant_op.md
@@ -537,6 +537,54 @@ Example:
- - -
+### `tf.random_gamma(shape, alpha, beta=None, dtype=tf.float32, seed=None, name=None)` {#random_gamma}
+
+Draws `shape` samples from each of the given Gamma distribution(s).
+
+`alpha` is the shape parameter describing the distribution(s), and `beta` is
+the inverse scale parameter(s).
+
+Example:
+
+ samples = tf.random_gamma([10], [0.5, 1.5])
+ # samples has shape [10, 2], where each slice [:, 0] and [:, 1] represents
+ # the samples drawn from each distribution
+
+ samples = tf.random_gamma([7, 5], [0.5, 1.5])
+ # samples has shape [7, 5, 2], where each slice [:, :, 0] and [:, :, 1]
+ # represents the 7x5 samples drawn from each of the two distributions
+
+ samples = tf.random_gamma([30], [[1.],[3.],[5.]], beta=[[3., 4.]])
+ # samples has shape [30, 3, 2], with 30 samples each of 3x2 distributions.
+
+##### Args:
+
+
+* <b>`shape`</b>: A 1-D integer Tensor or Python array. The shape of the output samples
+ to be drawn per alpha/beta-parameterized distribution.
+* <b>`alpha`</b>: A Tensor or Python value or N-D array of type `dtype`. `alpha`
+ provides the shape parameter(s) describing the gamma distribution(s) to
+ sample. Must be broadcastable with `beta`.
+* <b>`beta`</b>: A Tensor or Python value or N-D array of type `dtype`. Defaults to 1.
+ `beta` provides the inverse scale parameter(s) of the gamma
+ distribution(s) to sample. Must be broadcastable with `alpha`.
+* <b>`dtype`</b>: The type of alpha, beta, 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(alpha + beta))` 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/contrib.distributions.md b/tensorflow/g3doc/api_docs/python/contrib.distributions.md
index 5bf9a4edb0..08f753b28e 100644
--- a/tensorflow/g3doc/api_docs/python/contrib.distributions.md
+++ b/tensorflow/g3doc/api_docs/python/contrib.distributions.md
@@ -1050,14 +1050,17 @@ Pdf of observations in `x` under these Gamma distribution(s).
#### `tf.contrib.distributions.Chi2.sample(n, seed=None, name='sample')` {#Chi2.sample}
-Generate `n` samples.
+Draws `n` samples from the Gamma distribution(s).
+
+See the doc for tf.random_gamma for further detail.
##### Args:
-* <b>`n`</b>: scalar. Number of samples to draw from each distribution.
-* <b>`seed`</b>: Python integer seed for RNG
-* <b>`name`</b>: name to give to the op.
+* <b>`n`</b>: Python integer, the number of observations to sample from each
+ distribution.
+* <b>`seed`</b>: Python integer, the random seed for this operation.
+* <b>`name`</b>: Optional name for the operation.
##### Returns:
@@ -1646,14 +1649,17 @@ Pdf of observations in `x` under these Gamma distribution(s).
#### `tf.contrib.distributions.Gamma.sample(n, seed=None, name='sample')` {#Gamma.sample}
-Generate `n` samples.
+Draws `n` samples from the Gamma distribution(s).
+
+See the doc for tf.random_gamma for further detail.
##### Args:
-* <b>`n`</b>: scalar. Number of samples to draw from each distribution.
-* <b>`seed`</b>: Python integer seed for RNG
-* <b>`name`</b>: name to give to the op.
+* <b>`n`</b>: Python integer, the number of observations to sample from each
+ distribution.
+* <b>`seed`</b>: Python integer, the random seed for this operation.
+* <b>`name`</b>: Optional name for the operation.
##### Returns:
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.contrib.distributions.Chi2.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.contrib.distributions.Chi2.md
index 5d568cee76..d104424bea 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.contrib.distributions.Chi2.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.contrib.distributions.Chi2.md
@@ -249,14 +249,17 @@ Pdf of observations in `x` under these Gamma distribution(s).
#### `tf.contrib.distributions.Chi2.sample(n, seed=None, name='sample')` {#Chi2.sample}
-Generate `n` samples.
+Draws `n` samples from the Gamma distribution(s).
+
+See the doc for tf.random_gamma for further detail.
##### Args:
-* <b>`n`</b>: scalar. Number of samples to draw from each distribution.
-* <b>`seed`</b>: Python integer seed for RNG
-* <b>`name`</b>: name to give to the op.
+* <b>`n`</b>: Python integer, the number of observations to sample from each
+ distribution.
+* <b>`seed`</b>: Python integer, the random seed for this operation.
+* <b>`name`</b>: Optional name for the operation.
##### Returns:
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.contrib.distributions.Gamma.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.contrib.distributions.Gamma.md
index 881fd6628d..8a704e1e7d 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.contrib.distributions.Gamma.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.contrib.distributions.Gamma.md
@@ -273,14 +273,17 @@ Pdf of observations in `x` under these Gamma distribution(s).
#### `tf.contrib.distributions.Gamma.sample(n, seed=None, name='sample')` {#Gamma.sample}
-Generate `n` samples.
+Draws `n` samples from the Gamma distribution(s).
+
+See the doc for tf.random_gamma for further detail.
##### Args:
-* <b>`n`</b>: scalar. Number of samples to draw from each distribution.
-* <b>`seed`</b>: Python integer seed for RNG
-* <b>`name`</b>: name to give to the op.
+* <b>`n`</b>: Python integer, the number of observations to sample from each
+ distribution.
+* <b>`seed`</b>: Python integer, the random seed for this operation.
+* <b>`name`</b>: Optional name for the operation.
##### Returns:
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.random_gamma.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.random_gamma.md
new file mode 100644
index 0000000000..1873ced0a2
--- /dev/null
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.random_gamma.md
@@ -0,0 +1,45 @@
+### `tf.random_gamma(shape, alpha, beta=None, dtype=tf.float32, seed=None, name=None)` {#random_gamma}
+
+Draws `shape` samples from each of the given Gamma distribution(s).
+
+`alpha` is the shape parameter describing the distribution(s), and `beta` is
+the inverse scale parameter(s).
+
+Example:
+
+ samples = tf.random_gamma([10], [0.5, 1.5])
+ # samples has shape [10, 2], where each slice [:, 0] and [:, 1] represents
+ # the samples drawn from each distribution
+
+ samples = tf.random_gamma([7, 5], [0.5, 1.5])
+ # samples has shape [7, 5, 2], where each slice [:, :, 0] and [:, :, 1]
+ # represents the 7x5 samples drawn from each of the two distributions
+
+ samples = tf.random_gamma([30], [[1.],[3.],[5.]], beta=[[3., 4.]])
+ # samples has shape [30, 3, 2], with 30 samples each of 3x2 distributions.
+
+##### Args:
+
+
+* <b>`shape`</b>: A 1-D integer Tensor or Python array. The shape of the output samples
+ to be drawn per alpha/beta-parameterized distribution.
+* <b>`alpha`</b>: A Tensor or Python value or N-D array of type `dtype`. `alpha`
+ provides the shape parameter(s) describing the gamma distribution(s) to
+ sample. Must be broadcastable with `beta`.
+* <b>`beta`</b>: A Tensor or Python value or N-D array of type `dtype`. Defaults to 1.
+ `beta` provides the inverse scale parameter(s) of the gamma
+ distribution(s) to sample. Must be broadcastable with `alpha`.
+* <b>`dtype`</b>: The type of alpha, beta, 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(alpha + beta))` with
+ values of type `dtype`.
+
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.train.SummaryWriter.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.train.SummaryWriter.md
index a7f5aef5f1..8d32d95f79 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.train.SummaryWriter.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.train.SummaryWriter.md
@@ -168,3 +168,17 @@ Flushes the event file to disk and close the file.
Call this method when you do not need the summary writer anymore.
+
+#### Other Methods
+- - -
+
+#### `tf.train.SummaryWriter.reopen()` {#SummaryWriter.reopen}
+
+Reopens the summary writer.
+
+Can be called after `close()` to add more events in the same directory.
+The events will go into a new events file.
+
+Does nothing if the summary writer was not closed.
+
+
diff --git a/tensorflow/g3doc/api_docs/python/index.md b/tensorflow/g3doc/api_docs/python/index.md
index 8c713b90c0..2aad7565e6 100644
--- a/tensorflow/g3doc/api_docs/python/index.md
+++ b/tensorflow/g3doc/api_docs/python/index.md
@@ -58,6 +58,7 @@
* [`ones`](../../api_docs/python/constant_op.md#ones)
* [`ones_like`](../../api_docs/python/constant_op.md#ones_like)
* [`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_shuffle`](../../api_docs/python/constant_op.md#random_shuffle)
* [`random_uniform`](../../api_docs/python/constant_op.md#random_uniform)
diff --git a/tensorflow/g3doc/api_docs/python/train.md b/tensorflow/g3doc/api_docs/python/train.md
index 3cdb0abe1c..7bae49b4a6 100644
--- a/tensorflow/g3doc/api_docs/python/train.md
+++ b/tensorflow/g3doc/api_docs/python/train.md
@@ -3272,6 +3272,20 @@ Call this method when you do not need the summary writer anymore.
+#### Other Methods
+- - -
+
+#### `tf.train.SummaryWriter.reopen()` {#SummaryWriter.reopen}
+
+Reopens the summary writer.
+
+Can be called after `close()` to add more events in the same directory.
+The events will go into a new events file.
+
+Does nothing if the summary writer was not closed.
+
+
+
- - -
### `tf.train.summary_iterator(path)` {#summary_iterator}