1 files changed, 50 insertions, 0 deletions
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.clip_by_global_norm.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.clip_by_global_norm.md
new file mode 100644
index 0000000000..a40f621bf4
--- /dev/null
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.clip_by_global_norm.md
@@ -0,0 +1,50 @@
+### `tf.clip_by_global_norm(t_list, clip_norm, use_norm=None, name=None)` {#clip_by_global_norm}
+
+Clips values of multiple tensors by the ratio of the sum of their norms.
+
+Given a tuple or list of tensors `t_list`, and a clipping ratio `clip_norm`,
+this operation returns a list of clipped tensors `list_clipped`
+and the global norm (`global_norm`) of all tensors in `t_list`. Optionally,
+if you've already computed the global norm for `t_list`, you can specify
+the global norm with `use_norm`.
+
+To perform the clipping, the values `t_list[i]` are set to:
+
+    t_list[i] * clip_norm / max(global_norm, clip_norm)
+
+where:
+
+    global_norm = sqrt(sum([l2norm(t)**2 for t in t_list]))
+
+If `clip_norm > global_norm` then the entries in `t_list` remain as they are,
+otherwise they're all shrunk by the global ratio.
+
+Any of the entries of `t_list` that are of type `None` are ignored.
+
+This is the correct way to perform gradient clipping (for example, see
+[Pascanu et al., 2012](http://arxiv.org/abs/1211.5063)
+([pdf](http://arxiv.org/pdf/1211.5063.pdf))).
+
+However, it is slower than `clip_by_norm()` because all the parameters must be
+ready before the clipping operation can be performed.
+
+##### Args:
+
+
+*  <b>`t_list`</b>: A tuple or list of mixed `Tensors`, `IndexedSlices`, or None.
+*  <b>`clip_norm`</b>: A 0-D (scalar) `Tensor` > 0. The clipping ratio.
+*  <b>`use_norm`</b>: A 0-D (scalar) `Tensor` of type `float` (optional). The global
+    norm to use. If not provided, `global_norm()` is used to compute the norm.
+*  <b>`name`</b>: A name for the operation (optional).
+
+##### Returns:
+
+
+*  <b>`list_clipped`</b>: A list of `Tensors` of the same type as `list_t`.
+*  <b>`global_norm`</b>: A 0-D (scalar) `Tensor` representing the global norm.
+
+##### Raises:
+
+
+*  <b>`TypeError`</b>: If `t_list` is not a sequence.
+