From a2009115dfa777243f277d8abb702aec42c4178a Mon Sep 17 00:00:00 2001
From: "A. Unique TensorFlower" <nobody@tensorflow.org>
Date: Thu, 26 May 2016 09:03:01 -0800
Subject: [PATCH] Update ops-related pbtxt files. Change: 123329408

---
 .../core/ops/compat/ops_history.v0.pbtxt      | 25 ++++++++++++
 tensorflow/core/ops/ops.pbtxt                 | 38 +++++++++++++++++--
 2 files changed, 59 insertions(+), 4 deletions(-)

diff --git a/tensorflow/core/ops/compat/ops_history.v0.pbtxt b/tensorflow/core/ops/compat/ops_history.v0.pbtxt
index 1ab52b252aa..0a15d861c2c 100644
--- a/tensorflow/core/ops/compat/ops_history.v0.pbtxt
+++ b/tensorflow/core/ops/compat/ops_history.v0.pbtxt
@@ -3175,6 +3175,31 @@ op {
     }
   }
 }
+op {
+  name: "BatchCholeskyGrad"
+  input_arg {
+    name: "l"
+    type_attr: "T"
+  }
+  input_arg {
+    name: "grad"
+    type_attr: "T"
+  }
+  output_arg {
+    name: "output"
+    type_attr: "T"
+  }
+  attr {
+    name: "T"
+    type: "type"
+    allowed_values {
+      list {
+        type: DT_FLOAT
+        type: DT_DOUBLE
+      }
+    }
+  }
+}
 op {
   name: "BatchFFT"
   input_arg {
diff --git a/tensorflow/core/ops/ops.pbtxt b/tensorflow/core/ops/ops.pbtxt
index 57e4e716038..2c0c6f30d3c 100644
--- a/tensorflow/core/ops/ops.pbtxt
+++ b/tensorflow/core/ops/ops.pbtxt
@@ -1397,6 +1397,36 @@ op {
   summary: "Calculates the Cholesky decomposition of a batch of square matrices."
   description: "The input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions\nform square matrices, with the same constraints as the single matrix Cholesky\ndecomposition above. The output is a tensor of the same shape as the input\ncontaining the Cholesky decompositions for all input submatrices `[..., :, :]`."
 }
+op {
+  name: "BatchCholeskyGrad"
+  input_arg {
+    name: "l"
+    description: "Output of batch Cholesky algorithm l = batch_cholesky(A). Shape is `[..., M, M]`.\nAlgorithm depends only on lower triangular part of the innermost matrices of\nthis tensor."
+    type_attr: "T"
+  }
+  input_arg {
+    name: "grad"
+    description: "df/dl where f is some scalar function. Shape is `[..., M, M]\'.\nAlgorithm depends only on lower triangular part of the innermost matrices of\nthis tensor."
+    type_attr: "T"
+  }
+  output_arg {
+    name: "output"
+    description: "Symmetrized version of df/dA . Shape is `[..., M, M]\'"
+    type_attr: "T"
+  }
+  attr {
+    name: "T"
+    type: "type"
+    allowed_values {
+      list {
+        type: DT_FLOAT
+        type: DT_DOUBLE
+      }
+    }
+  }
+  summary: "Calculates the reverse mode backpropagated gradient of the Cholesky algorithm."
+  description: "For an explanation see \"Differentiation of the Cholesky algorithm\" by\nIain Murray http://arxiv.org/abs/1602.07527."
+}
 op {
   name: "BatchFFT"
   input_arg {
@@ -2482,17 +2512,17 @@ op {
   name: "CholeskyGrad"
   input_arg {
     name: "l"
-    description: "Output of Cholesky algorithm l = chol(A). Shape is `[M, M]`. Algorithm depends only on lower triangular part of this matrix."
+    description: "Output of Cholesky algorithm l = chol(A). Shape is `[M, M]`.\nAlgorithm depends only on lower triangular part of this matrix."
     type_attr: "T"
   }
   input_arg {
     name: "grad"
-    description: "df/dl where f is some scalar function. Shape is `[M, M]\'. Algorithm depends only on lower triangular part of this matrix."
+    description: "df/dl where f is some scalar function. Shape is `[M, M]\'.\nAlgorithm depends only on lower triangular part of this matrix."
     type_attr: "T"
   }
   output_arg {
     name: "output"
-    description: "Symmetrized version of df/dA . Shape is `[M, M]\'"
+    description: "Symmetrized version of df/dA . Shape is `[M, M]\'."
     type_attr: "T"
   }
   attr {
@@ -2506,7 +2536,7 @@ op {
     }
   }
   summary: "Calculates the reverse mode backpropagated gradient of the Cholesky algorithm."
-  description: "For an explanation see \"Differentiation of the Cholesky algorithm\" by Iain Murray http://arxiv.org/abs/1602.07527."
+  description: "For an explanation see \"Differentiation of the Cholesky algorithm\" by\nIain Murray http://arxiv.org/abs/1602.07527."
 }
 op {
   name: "Complex"