Update generated Python Op docs.

Change: 144144091

tensorflow/g3doc/api_docs/python/array_ops.md

@@ -904,7 +904,7 @@ pad(t, paddings, "SYMMETRIC") ==> [[2, 1, 1, 2, 3, 3, 2],
 
 - - -
 
-### `tf.concat_v2(values, axis, name='concat_v2')` {#concat_v2}
+### `tf.concat(values, axis, name='concat')` {#concat}
 
 Concatenates tensors along one dimension.
 
@@ -929,20 +929,20 @@ For example:
 ```python
 t1 = [[1, 2, 3], [4, 5, 6]]
 t2 = [[7, 8, 9], [10, 11, 12]]
-tf.concat_v2([t1, t2], 0) ==> [[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]]
+tf.concat([t1, t2], 0) ==> [[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]]
-tf.concat_v2([t1, t2], 1) ==> [[1, 2, 3, 7, 8, 9], [4, 5, 6, 10, 11, 12]]
+tf.concat([t1, t2], 1) ==> [[1, 2, 3, 7, 8, 9], [4, 5, 6, 10, 11, 12]]
 
 # tensor t3 with shape [2, 3]
 # tensor t4 with shape [2, 3]
-tf.shape(tf.concat_v2([t3, t4], 0)) ==> [4, 3]
+tf.shape(tf.concat([t3, t4], 0)) ==> [4, 3]
-tf.shape(tf.concat_v2([t3, t4], 1)) ==> [2, 6]
+tf.shape(tf.concat([t3, t4], 1)) ==> [2, 6]
 ```
 
 Note: If you are concatenating along a new axis consider using stack.
 E.g.
 
 ```python
-tf.concat_v2([tf.expand_dims(t, axis) for t in tensors], axis)
+tf.concat([tf.expand_dims(t, axis) for t in tensors], axis)
 ```
 
 can be rewritten as
@@ -3131,3 +3131,12 @@ Compute gradients for a FakeQuantWithMinMaxVarsPerChannel operation.
     `sum_per_d(gradients * (inputs > max))`.
 
 
+
+## Other Functions and Classes
+- - -
+
+### `tf.concat_v2(values, axis, name='concat_v2')` {#concat_v2}
+
+
+
+

tensorflow/g3doc/api_docs/python/contrib.learn.md

@@ -1973,9 +1973,13 @@ variable.
 
 - - -
 
-### `tf.contrib.learn.evaluate(graph, output_dir, checkpoint_path, eval_dict, update_op=None, global_step_tensor=None, supervisor_master='', log_every_steps=10, feed_fn=None, max_steps=None)` {#evaluate}
+### `tf.contrib.learn.evaluate(*args, **kwargs)` {#evaluate}
 
-Evaluate a model loaded from a checkpoint.
+Evaluate a model loaded from a checkpoint. (deprecated)
+
+THIS FUNCTION IS DEPRECATED. It will be removed after 2017-02-15.
+Instructions for updating:
+graph_actions.py will be deleted. Use tf.train.* utilities instead. You can use learn/estimators/estimator.py as an example.
 
 Given `graph`, a directory to write summaries to (`output_dir`), a checkpoint
 to restore variables from, and a `dict` of `Tensor`s to evaluate, run an eval
@@ -2029,9 +2033,13 @@ and written to `output_dir`.
 
 - - -
 
-### `tf.contrib.learn.infer(restore_checkpoint_path, output_dict, feed_dict=None)` {#infer}
+### `tf.contrib.learn.infer(*args, **kwargs)` {#infer}
 
-Restore graph from `restore_checkpoint_path` and run `output_dict` tensors.
+Restore graph from `restore_checkpoint_path` and run `output_dict` tensors. (deprecated)
+
+THIS FUNCTION IS DEPRECATED. It will be removed after 2017-02-15.
+Instructions for updating:
+graph_actions.py will be deleted. Use tf.train.* utilities instead. You can use learn/estimators/estimator.py as an example.
 
 If `restore_checkpoint_path` is supplied, restore from checkpoint. Otherwise,
 init all variables.
@@ -2061,14 +2069,22 @@ init all variables.
 
 ### `tf.contrib.learn.run_feeds(*args, **kwargs)` {#run_feeds}
 
-See run_feeds_iter(). Returns a `list` instead of an iterator.
+See run_feeds_iter(). Returns a `list` instead of an iterator. (deprecated)
+
+THIS FUNCTION IS DEPRECATED. It will be removed after 2017-02-15.
+Instructions for updating:
+graph_actions.py will be deleted. Use tf.train.* utilities instead. You can use learn/estimators/estimator.py as an example.
 
 
 - - -
 
-### `tf.contrib.learn.run_n(output_dict, feed_dict=None, restore_checkpoint_path=None, n=1)` {#run_n}
+### `tf.contrib.learn.run_n(*args, **kwargs)` {#run_n}
 
-Run `output_dict` tensors `n` times, with the same `feed_dict` each run.
+Run `output_dict` tensors `n` times, with the same `feed_dict` each run. (deprecated)
+
+THIS FUNCTION IS DEPRECATED. It will be removed after 2017-02-15.
+Instructions for updating:
+graph_actions.py will be deleted. Use tf.train.* utilities instead. You can use learn/estimators/estimator.py as an example.
 
 ##### Args:
 
@@ -2088,9 +2104,13 @@ Run `output_dict` tensors `n` times, with the same `feed_dict` each run.
 
 - - -
 
-### `tf.contrib.learn.train(graph, output_dir, train_op, loss_op, global_step_tensor=None, init_op=None, init_feed_dict=None, init_fn=None, log_every_steps=10, supervisor_is_chief=True, supervisor_master='', supervisor_save_model_secs=600, keep_checkpoint_max=5, supervisor_save_summaries_steps=100, feed_fn=None, steps=None, fail_on_nan_loss=True, monitors=None, max_steps=None)` {#train}
+### `tf.contrib.learn.train(*args, **kwargs)` {#train}
 
-Train a model.
+Train a model. (deprecated)
+
+THIS FUNCTION IS DEPRECATED. It will be removed after 2017-02-15.
+Instructions for updating:
+graph_actions.py will be deleted. Use tf.train.* utilities instead. You can use learn/estimators/estimator.py as an example.
 
 Given `graph`, a directory to write outputs to (`output_dir`), and some ops,
 run a training loop. The given `train_op` performs one step of training on the

tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.contrib.learn.train.md

@@ -1,6 +1,10 @@
-### `tf.contrib.learn.train(graph, output_dir, train_op, loss_op, global_step_tensor=None, init_op=None, init_feed_dict=None, init_fn=None, log_every_steps=10, supervisor_is_chief=True, supervisor_master='', supervisor_save_model_secs=600, keep_checkpoint_max=5, supervisor_save_summaries_steps=100, feed_fn=None, steps=None, fail_on_nan_loss=True, monitors=None, max_steps=None)` {#train}
+### `tf.contrib.learn.train(*args, **kwargs)` {#train}
 
-Train a model.
+Train a model. (deprecated)
+
+THIS FUNCTION IS DEPRECATED. It will be removed after 2017-02-15.
+Instructions for updating:
+graph_actions.py will be deleted. Use tf.train.* utilities instead. You can use learn/estimators/estimator.py as an example.
 
 Given `graph`, a directory to write outputs to (`output_dir`), and some ops,
 run a training loop. The given `train_op` performs one step of training on the

tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.contrib.learn.evaluate.md

@@ -1,6 +1,10 @@
-### `tf.contrib.learn.evaluate(graph, output_dir, checkpoint_path, eval_dict, update_op=None, global_step_tensor=None, supervisor_master='', log_every_steps=10, feed_fn=None, max_steps=None)` {#evaluate}
+### `tf.contrib.learn.evaluate(*args, **kwargs)` {#evaluate}
 
-Evaluate a model loaded from a checkpoint.
+Evaluate a model loaded from a checkpoint. (deprecated)
+
+THIS FUNCTION IS DEPRECATED. It will be removed after 2017-02-15.
+Instructions for updating:
+graph_actions.py will be deleted. Use tf.train.* utilities instead. You can use learn/estimators/estimator.py as an example.
 
 Given `graph`, a directory to write summaries to (`output_dir`), a checkpoint
 to restore variables from, and a `dict` of `Tensor`s to evaluate, run an eval

tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.contrib.learn.run_feeds.md

@@ -1,4 +1,8 @@
 ### `tf.contrib.learn.run_feeds(*args, **kwargs)` {#run_feeds}
 
-See run_feeds_iter(). Returns a `list` instead of an iterator.
+See run_feeds_iter(). Returns a `list` instead of an iterator. (deprecated)
+
+THIS FUNCTION IS DEPRECATED. It will be removed after 2017-02-15.
+Instructions for updating:
+graph_actions.py will be deleted. Use tf.train.* utilities instead. You can use learn/estimators/estimator.py as an example.
 

tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.contrib.learn.run_n.md

@@ -1,6 +1,10 @@
-### `tf.contrib.learn.run_n(output_dict, feed_dict=None, restore_checkpoint_path=None, n=1)` {#run_n}
+### `tf.contrib.learn.run_n(*args, **kwargs)` {#run_n}
 
-Run `output_dict` tensors `n` times, with the same `feed_dict` each run.
+Run `output_dict` tensors `n` times, with the same `feed_dict` each run. (deprecated)
+
+THIS FUNCTION IS DEPRECATED. It will be removed after 2017-02-15.
+Instructions for updating:
+graph_actions.py will be deleted. Use tf.train.* utilities instead. You can use learn/estimators/estimator.py as an example.
 
 ##### Args:
 

tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.concat.md

@@ -0,0 +1,58 @@
+### `tf.concat(values, axis, name='concat')` {#concat}
+
+Concatenates tensors along one dimension.
+
+Concatenates the list of tensors `values` along dimension `axis`.  If
+`values[i].shape = [D0, D1, ... Daxis(i), ...Dn]`, the concatenated
+result has shape
+
+    [D0, D1, ... Raxis, ...Dn]
+
+where
+
+    Raxis = sum(Daxis(i))
+
+That is, the data from the input tensors is joined along the `axis`
+dimension.
+
+The number of dimensions of the input tensors must match, and all dimensions
+except `axis` must be equal.
+
+For example:
+
+```python
+t1 = [[1, 2, 3], [4, 5, 6]]
+t2 = [[7, 8, 9], [10, 11, 12]]
+tf.concat([t1, t2], 0) ==> [[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]]
+tf.concat([t1, t2], 1) ==> [[1, 2, 3, 7, 8, 9], [4, 5, 6, 10, 11, 12]]
+
+# tensor t3 with shape [2, 3]
+# tensor t4 with shape [2, 3]
+tf.shape(tf.concat([t3, t4], 0)) ==> [4, 3]
+tf.shape(tf.concat([t3, t4], 1)) ==> [2, 6]
+```
+
+Note: If you are concatenating along a new axis consider using stack.
+E.g.
+
+```python
+tf.concat([tf.expand_dims(t, axis) for t in tensors], axis)
+```
+
+can be rewritten as
+
+```python
+tf.stack(tensors, axis=axis)
+```
+
+##### Args:
+
+
+*  <b>`values`</b>: A list of `Tensor` objects or a single `Tensor`.
+*  <b>`axis`</b>: 0-D `int32` `Tensor`.  Dimension along which to concatenate.
+*  <b>`name`</b>: A name for the operation (optional).
+
+##### Returns:
+
+  A `Tensor` resulting from concatenation of the input tensors.
+

tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.concat_v2.md

@@ -1,58 +1,4 @@
 ### `tf.concat_v2(values, axis, name='concat_v2')` {#concat_v2}
 
-Concatenates tensors along one dimension.
-
-Concatenates the list of tensors `values` along dimension `axis`.  If
-`values[i].shape = [D0, D1, ... Daxis(i), ...Dn]`, the concatenated
-result has shape
-
-    [D0, D1, ... Raxis, ...Dn]
-
-where
-
-    Raxis = sum(Daxis(i))
-
-That is, the data from the input tensors is joined along the `axis`
-dimension.
-
-The number of dimensions of the input tensors must match, and all dimensions
-except `axis` must be equal.
-
-For example:
-
-```python
-t1 = [[1, 2, 3], [4, 5, 6]]
-t2 = [[7, 8, 9], [10, 11, 12]]
-tf.concat_v2([t1, t2], 0) ==> [[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]]
-tf.concat_v2([t1, t2], 1) ==> [[1, 2, 3, 7, 8, 9], [4, 5, 6, 10, 11, 12]]
-
-# tensor t3 with shape [2, 3]
-# tensor t4 with shape [2, 3]
-tf.shape(tf.concat_v2([t3, t4], 0)) ==> [4, 3]
-tf.shape(tf.concat_v2([t3, t4], 1)) ==> [2, 6]
-```
-
-Note: If you are concatenating along a new axis consider using stack.
-E.g.
-
-```python
-tf.concat_v2([tf.expand_dims(t, axis) for t in tensors], axis)
-```
-
-can be rewritten as
-
-```python
-tf.stack(tensors, axis=axis)
-```
-
-##### Args:
 
 
-*  <b>`values`</b>: A list of `Tensor` objects or a single `Tensor`.
-*  <b>`axis`</b>: 0-D `int32` `Tensor`.  Dimension along which to concatenate.
-*  <b>`name`</b>: A name for the operation (optional).
-
-##### Returns:
-
-  A `Tensor` resulting from concatenation of the input tensors.
-

tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.contrib.learn.infer.md

@@ -1,6 +1,10 @@
-### `tf.contrib.learn.infer(restore_checkpoint_path, output_dict, feed_dict=None)` {#infer}
+### `tf.contrib.learn.infer(*args, **kwargs)` {#infer}
 
-Restore graph from `restore_checkpoint_path` and run `output_dict` tensors.
+Restore graph from `restore_checkpoint_path` and run `output_dict` tensors. (deprecated)
+
+THIS FUNCTION IS DEPRECATED. It will be removed after 2017-02-15.
+Instructions for updating:
+graph_actions.py will be deleted. Use tf.train.* utilities instead. You can use learn/estimators/estimator.py as an example.
 
 If `restore_checkpoint_path` is supplied, restore from checkpoint. Otherwise,
 init all variables.

tensorflow/g3doc/api_docs/python/index.md

@@ -139,6 +139,7 @@
   * [`broadcast_dynamic_shape`](../../api_docs/python/array_ops.md#broadcast_dynamic_shape)
   * [`broadcast_static_shape`](../../api_docs/python/array_ops.md#broadcast_static_shape)
   * [`cast`](../../api_docs/python/array_ops.md#cast)
+  * [`concat`](../../api_docs/python/array_ops.md#concat)
   * [`concat_v2`](../../api_docs/python/array_ops.md#concat_v2)
   * [`depth_to_space`](../../api_docs/python/array_ops.md#depth_to_space)
   * [`dequantize`](../../api_docs/python/array_ops.md#dequantize)
@@ -362,6 +363,7 @@
   * [`scan`](../../api_docs/python/functional_ops.md#scan)
 
 * **[TensorArray Operations](../../api_docs/python/tensor_array_ops.md)**:
+  * [`concat`](../../api_docs/python/tensor_array_ops.md#concat)
   * [`gather`](../../api_docs/python/tensor_array_ops.md#gather)
   * [`identity`](../../api_docs/python/tensor_array_ops.md#identity)
   * [`split`](../../api_docs/python/tensor_array_ops.md#split)