diff --git a/tensorflow/core/ops/compat/ops_history.v0.pbtxt b/tensorflow/core/ops/compat/ops_history.v0.pbtxt
index 2dc59179b82..2dba61efe78 100644
--- a/tensorflow/core/ops/compat/ops_history.v0.pbtxt
+++ b/tensorflow/core/ops/compat/ops_history.v0.pbtxt
@@ -23173,115 +23173,6 @@ op {
     }
   }
 }
-op {
-  name: "SparseSparseMaximum"
-  input_arg {
-    name: "a_indices"
-    type: DT_INT64
-  }
-  input_arg {
-    name: "a_values"
-    type_attr: "T"
-  }
-  input_arg {
-    name: "a_shape"
-    type: DT_INT64
-  }
-  input_arg {
-    name: "b_indices"
-    type: DT_INT64
-  }
-  input_arg {
-    name: "b_values"
-    type_attr: "T"
-  }
-  input_arg {
-    name: "b_shape"
-    type: DT_INT64
-  }
-  output_arg {
-    name: "output_indices"
-    type: DT_INT64
-  }
-  output_arg {
-    name: "output_values"
-    type_attr: "T"
-  }
-  attr {
-    name: "T"
-    type: "type"
-    allowed_values {
-      list {
-        type: DT_FLOAT
-        type: DT_DOUBLE
-        type: DT_INT32
-        type: DT_INT64
-        type: DT_UINT8
-        type: DT_INT16
-        type: DT_INT8
-        type: DT_UINT16
-        type: DT_HALF
-      }
-    }
-  }
-}
-op {
-  name: "SparseSparseMinimum"
-  input_arg {
-    name: "a_indices"
-    type: DT_INT64
-  }
-  input_arg {
-    name: "a_values"
-    type_attr: "T"
-  }
-  input_arg {
-    name: "a_shape"
-    type: DT_INT64
-  }
-  input_arg {
-    name: "b_indices"
-    type: DT_INT64
-  }
-  input_arg {
-    name: "b_values"
-    type_attr: "T"
-  }
-  input_arg {
-    name: "b_shape"
-    type: DT_INT64
-  }
-  output_arg {
-    name: "output_indices"
-    type: DT_INT64
-  }
-  output_arg {
-    name: "output_values"
-    type_attr: "T"
-  }
-  attr {
-    name: "T"
-    type: "type"
-    allowed_values {
-      list {
-        type: DT_FLOAT
-        type: DT_DOUBLE
-        type: DT_INT64
-        type: DT_INT32
-        type: DT_UINT8
-        type: DT_UINT16
-        type: DT_INT16
-        type: DT_INT8
-        type: DT_COMPLEX64
-        type: DT_COMPLEX128
-        type: DT_QINT8
-        type: DT_QUINT8
-        type: DT_QINT32
-        type: DT_HALF
-      }
-    }
-  }
-}
 op {
   name: "SparseSplit"
   input_arg {
diff --git a/tensorflow/core/ops/ops.pbtxt b/tensorflow/core/ops/ops.pbtxt
index 3668ecf5aae..afd6507b0d8 100644
--- a/tensorflow/core/ops/ops.pbtxt
+++ b/tensorflow/core/ops/ops.pbtxt
@@ -13696,135 +13696,6 @@ op {
   summary: "Computes softmax cross entropy cost and gradients to backpropagate."
   description: "Unlike `SoftmaxCrossEntropyWithLogits`, this operation does not accept\na matrix of label probabilities, but rather a single label per row\nof features.  This label is considered to have probability 1.0 for the\ngiven row.\n\nInputs are the logits, not probabilities."
 }
-op {
-  name: "SparseSparseMaximum"
-  input_arg {
-    name: "a_indices"
-    description: "2-D.  `N x R` matrix with the indices of non-empty values in a\nSparseTensor, in the canonical lexicographic ordering."
-    type: DT_INT64
-  }
-  input_arg {
-    name: "a_values"
-    description: "1-D.  `N` non-empty values corresponding to `a_indices`."
-    type_attr: "T"
-  }
-  input_arg {
-    name: "a_shape"
-    description: "1-D.  Shape of the input SparseTensor."
-    type: DT_INT64
-  }
-  input_arg {
-    name: "b_indices"
-    description: "counterpart to `a_indices` for the other operand."
-    type: DT_INT64
-  }
-  input_arg {
-    name: "b_values"
-    description: "counterpart to `a_values` for the other operand; must be of the same dtype."
-    type_attr: "T"
-  }
-  input_arg {
-    name: "b_shape"
-    description: "counterpart to `a_shape` for the other operand; the two shapes must be equal."
-    type: DT_INT64
-  }
-  output_arg {
-    name: "output_indices"
-    description: "2-D.  The indices of the output SparseTensor."
-    type: DT_INT64
-  }
-  output_arg {
-    name: "output_values"
-    description: "1-D.  The values of the output SparseTensor."
-    type_attr: "T"
-  }
-  attr {
-    name: "T"
-    type: "type"
-    allowed_values {
-      list {
-        type: DT_FLOAT
-        type: DT_DOUBLE
-        type: DT_INT32
-        type: DT_INT64
-        type: DT_UINT8
-        type: DT_INT16
-        type: DT_INT8
-        type: DT_UINT16
-        type: DT_HALF
-      }
-    }
-  }
-  summary: "Returns the element-wise max of two SparseTensors."
-  description: "Assumes the two SparseTensors have the same shape, i.e., no broadcasting."
-}
-op {
-  name: "SparseSparseMinimum"
-  input_arg {
-    name: "a_indices"
-    description: "2-D.  `N x R` matrix with the indices of non-empty values in a\nSparseTensor, in the canonical lexicographic ordering."
-    type: DT_INT64
-  }
-  input_arg {
-    name: "a_values"
-    description: "1-D.  `N` non-empty values corresponding to `a_indices`."
-    type_attr: "T"
-  }
-  input_arg {
-    name: "a_shape"
-    description: "1-D.  Shape of the input SparseTensor."
-    type: DT_INT64
-  }
-  input_arg {
-    name: "b_indices"
-    description: "counterpart to `a_indices` for the other operand."
-    type: DT_INT64
-  }
-  input_arg {
-    name: "b_values"
-    description: "counterpart to `a_values` for the other operand; must be of the same dtype."
-    type_attr: "T"
-  }
-  input_arg {
-    name: "b_shape"
-    description: "counterpart to `a_shape` for the other operand; the two shapes must be equal."
-    type: DT_INT64
-  }
-  output_arg {
-    name: "output_indices"
-    description: "2-D.  The indices of the output SparseTensor."
-    type: DT_INT64
-  }
-  output_arg {
-    name: "output_values"
-    description: "1-D.  The values of the output SparseTensor."
-    type_attr: "T"
-  }
-  attr {
-    name: "T"
-    type: "type"
-    allowed_values {
-      list {
-        type: DT_FLOAT
-        type: DT_DOUBLE
-        type: DT_INT64
-        type: DT_INT32
-        type: DT_UINT8
-        type: DT_UINT16
-        type: DT_INT16
-        type: DT_INT8
-        type: DT_COMPLEX64
-        type: DT_COMPLEX128
-        type: DT_QINT8
-        type: DT_QUINT8
-        type: DT_QINT32
-        type: DT_HALF
-      }
-    }
-  }
-  summary: "Returns the element-wise min of two SparseTensors."
-  description: "Assumes the two SparseTensors have the same shape, i.e., no broadcasting."
-}
 op {
   name: "SparseSplit"
   input_arg {