Update generated Python Op docs.

Change: 144899411

tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.neg.md

@@ -1,16 +0,0 @@
-### `tf.neg(x, name=None)` {#neg}
-
-Computes numerical negative value element-wise.
-
-I.e., \\(y = -x\\).
-
-##### Args:
-
-
-*  <b>`x`</b>: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `int32`, `int64`, `complex64`, `complex128`.
-*  <b>`name`</b>: A name for the operation (optional).
-
-##### Returns:
-
-  A `Tensor`. Has the same type as `x`.
-

tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.nn.sparse_softmax_cross_entropy_with_logits.md

@@ -28,13 +28,13 @@ this function.**
 
   _sentinel: Used to prevent positional parameters. Internal, do not use.
 
-*  <b>`labels`</b>: `Tensor` of shape `[d_0, d_1, ..., d_{r-2}]` and dtype `int32` or
-    `int64`. Each entry in `labels` must be an index in `[0, num_classes)`.
-    Other values will raise an exception when this op is run on CPU, and
-    return `NaN` for corresponding corresponding loss and gradient rows
-    on GPU.
-*  <b>`logits`</b>: Unscaled log probabilities of rank `r` and shape
-    `[d_0, d_1, ..., d_{r-2}, num_classes]` and dtype `float32` or `float64`.
+*  <b>`labels`</b>: `Tensor` of shape `[d_0, d_1, ..., d_{r-1}]` (where `r` is rank of
+    `labels` and result) and dtype `int32` or `int64`. Each entry in `labels`
+    must be an index in `[0, num_classes)`. Other values will raise an
+    exception when this op is run on CPU, and return `NaN` for corresponding
+    loss and gradient rows on GPU.
+*  <b>`logits`</b>: Unscaled log probabilities of shape
+    `[d_0, d_1, ..., d_{r-1}, num_classes]` and dtype `float32` or `float64`.
 *  <b>`name`</b>: A name for the operation (optional).
 
 ##### Returns:

tensorflow/g3doc/api_docs/python/index.md

@@ -260,7 +260,6 @@
   * [`minimum`](../../api_docs/python/math_ops.md#minimum)
   * [`mod`](../../api_docs/python/math_ops.md#mod)
   * [`multiply`](../../api_docs/python/math_ops.md#multiply)
-  * [`neg`](../../api_docs/python/math_ops.md#neg)
   * [`negative`](../../api_docs/python/math_ops.md#negative)
   * [`norm`](../../api_docs/python/math_ops.md#norm)
   * [`polygamma`](../../api_docs/python/math_ops.md#polygamma)

tensorflow/g3doc/api_docs/python/math_ops.md

@@ -3720,24 +3720,3 @@ invert_permutation(x) ==> [2, 4, 3, 0, 1]
   A `Tensor`. Has the same type as `x`. 1-D.
 
 
-
-## Other Functions and Classes
-- - -
-
-### `tf.neg(x, name=None)` {#neg}
-
-Computes numerical negative value element-wise.
-
-I.e., \\(y = -x\\).
-
-##### Args:
-
-
-*  <b>`x`</b>: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `int32`, `int64`, `complex64`, `complex128`.
-*  <b>`name`</b>: A name for the operation (optional).
-
-##### Returns:
-
-  A `Tensor`. Has the same type as `x`.
-
-

tensorflow/g3doc/api_docs/python/nn.md

@@ -2370,13 +2370,13 @@ this function.**
 
   _sentinel: Used to prevent positional parameters. Internal, do not use.
 
-*  <b>`labels`</b>: `Tensor` of shape `[d_0, d_1, ..., d_{r-2}]` and dtype `int32` or
-    `int64`. Each entry in `labels` must be an index in `[0, num_classes)`.
-    Other values will raise an exception when this op is run on CPU, and
-    return `NaN` for corresponding corresponding loss and gradient rows
-    on GPU.
-*  <b>`logits`</b>: Unscaled log probabilities of rank `r` and shape
-    `[d_0, d_1, ..., d_{r-2}, num_classes]` and dtype `float32` or `float64`.
+*  <b>`labels`</b>: `Tensor` of shape `[d_0, d_1, ..., d_{r-1}]` (where `r` is rank of
+    `labels` and result) and dtype `int32` or `int64`. Each entry in `labels`
+    must be an index in `[0, num_classes)`. Other values will raise an
+    exception when this op is run on CPU, and return `NaN` for corresponding
+    loss and gradient rows on GPU.
+*  <b>`logits`</b>: Unscaled log probabilities of shape
+    `[d_0, d_1, ..., d_{r-1}, num_classes]` and dtype `float32` or `float64`.
 *  <b>`name`</b>: A name for the operation (optional).
 
 ##### Returns: