1 files changed, 54 insertions, 0 deletions
diff --git a/tensorflow/core/ops/ops.pbtxt b/tensorflow/core/ops/ops.pbtxt
index 468434bd28..2839575ec7 100644
--- a/tensorflow/core/ops/ops.pbtxt
+++ b/tensorflow/core/ops/ops.pbtxt
@@ -23384,6 +23384,60 @@ op {
   description: "Computes the eigenvalues and (optionally) eigenvectors of each inner matrix in\n`input` such that `input[..., :, :] = v[..., :, :] * diag(e[..., :])`.\n\n```python\n# a is a tensor.\n# e is a tensor of eigenvalues.\n# v is a tensor of eigenvectors.\ne, v = self_adjoint_eig(a)\ne = self_adjoint_eig(a, compute_v=False)\n```"
 }
 op {
+  name: "Selu"
+  input_arg {
+    name: "features"
+    type_attr: "T"
+  }
+  output_arg {
+    name: "activations"
+    type_attr: "T"
+  }
+  attr {
+    name: "T"
+    type: "type"
+    allowed_values {
+      list {
+        type: DT_HALF
+        type: DT_FLOAT
+        type: DT_DOUBLE
+      }
+    }
+  }
+  summary: "Computes scaled exponential linear: `scale * alpha * (exp(features) - 1)` if < 0, `scale * features` otherwise."
+  description: "See [Self-Normalizing Neural Networks](https://arxiv.org/abs/1706.02515)"
+}
+op {
+  name: "SeluGrad"
+  input_arg {
+    name: "gradients"
+    description: "The backpropagated gradients to the corresponding Selu operation."
+    type_attr: "T"
+  }
+  input_arg {
+    name: "outputs"
+    description: "The outputs of the corresponding Selu operation."
+    type_attr: "T"
+  }
+  output_arg {
+    name: "backprops"
+    description: "The gradients: `gradients * (outputs + scale * alpha)` if outputs < 0,\n`scale * gradients` otherwise."
+    type_attr: "T"
+  }
+  attr {
+    name: "T"
+    type: "type"
+    allowed_values {
+      list {
+        type: DT_HALF
+        type: DT_FLOAT
+        type: DT_DOUBLE
+      }
+    }
+  }
+  summary: "Computes gradients for the scaled exponential linear (Selu) operation."
+}
+op {
   name: "SerializeManySparse"
   input_arg {
     name: "sparse_indices"