diff --git a/tensorflow/core/ops/compat/ops_history.v1.pbtxt b/tensorflow/core/ops/compat/ops_history.v1.pbtxt
index a19ff5770f8..2f1bafef2aa 100644
--- a/tensorflow/core/ops/compat/ops_history.v1.pbtxt
+++ b/tensorflow/core/ops/compat/ops_history.v1.pbtxt
@@ -4019,6 +4019,29 @@ op {
     }
   }
 }
+op {
+  name: "Cholesky"
+  input_arg {
+    name: "input"
+    type_attr: "T"
+  }
+  output_arg {
+    name: "output"
+    type_attr: "T"
+  }
+  attr {
+    name: "T"
+    type: "type"
+    allowed_values {
+      list {
+        type: DT_DOUBLE
+        type: DT_FLOAT
+        type: DT_COMPLEX64
+        type: DT_COMPLEX128
+      }
+    }
+  }
+}
 op {
   name: "CholeskyGrad"
   input_arg {
@@ -11506,6 +11529,47 @@ op {
     }
   }
 }
+op {
+  name: "MatrixTriangularSolve"
+  input_arg {
+    name: "matrix"
+    type_attr: "T"
+  }
+  input_arg {
+    name: "rhs"
+    type_attr: "T"
+  }
+  output_arg {
+    name: "output"
+    type_attr: "T"
+  }
+  attr {
+    name: "lower"
+    type: "bool"
+    default_value {
+      b: true
+    }
+  }
+  attr {
+    name: "adjoint"
+    type: "bool"
+    default_value {
+      b: false
+    }
+  }
+  attr {
+    name: "T"
+    type: "type"
+    allowed_values {
+      list {
+        type: DT_DOUBLE
+        type: DT_FLOAT
+        type: DT_COMPLEX64
+        type: DT_COMPLEX128
+      }
+    }
+  }
+}
 op {
   name: "Max"
   input_arg {
diff --git a/tensorflow/core/ops/ops.pbtxt b/tensorflow/core/ops/ops.pbtxt
index b520e3fa5ef..e3bb192a020 100644
--- a/tensorflow/core/ops/ops.pbtxt
+++ b/tensorflow/core/ops/ops.pbtxt
@@ -3985,11 +3985,13 @@ op {
       list {
         type: DT_DOUBLE
         type: DT_FLOAT
+        type: DT_COMPLEX64
+        type: DT_COMPLEX128
       }
     }
   }
   summary: "Computes the Cholesky decomposition of one or more 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 `[..., :, :]`."
+  description: "The input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions\nform square matrices.\n\nThe input has to be symmetric and positive definite. Only the lower-triangular\npart of the input will be used for this operation. The upper-triangular part\nwill not be read.\n\nThe output is a tensor of the same shape as the input\ncontaining the Cholesky decompositions for all input submatrices `[..., :, :]`.\n\n**Note**: The gradient computation on GPU is faster for large matrices but\nnot for large batch dimensions when the submatrices are small. In this\ncase it might be faster to use the CPU."
 }
 op {
   name: "CholeskyGrad"
@@ -11222,6 +11224,8 @@ op {
       list {
         type: DT_DOUBLE
         type: DT_FLOAT
+        type: DT_COMPLEX64
+        type: DT_COMPLEX128
       }
     }
   }