diff --git a/tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td b/tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
index 7beccaf6ad7..68617ee0241 100644
--- a/tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
+++ b/tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
@@ -4035,6 +4035,10 @@ receive 0, 0, and 1, respectively. The appropriate bits in `begin_mask` and
 
   TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
   TF_DerivedOperandTypeAttr Index = TF_DerivedOperandTypeAttr<1>;
+
+  let verifier = [{
+    return Verify(*this);
+  }];
 }
 
 def TF_SubOp : TF_Op<"Sub", [Broadcastable, NoSideEffect]>,
diff --git a/tensorflow/compiler/mlir/tensorflow/ir/tf_ops.cc b/tensorflow/compiler/mlir/tensorflow/ir/tf_ops.cc
index 8d28ec26507..826389b09aa 100644
--- a/tensorflow/compiler/mlir/tensorflow/ir/tf_ops.cc
+++ b/tensorflow/compiler/mlir/tensorflow/ir/tf_ops.cc
@@ -21,11 +21,13 @@ limitations under the License.
 #include <string>
 #include <type_traits>
 
+#include "llvm/ADT/STLExtras.h"
 #include "llvm/ADT/Sequence.h"
 #include "llvm/ADT/SmallVector.h"
 #include "llvm/ADT/StringExtras.h"
 #include "llvm/ADT/StringRef.h"
 #include "llvm/ADT/StringSwitch.h"
+#include "llvm/ADT/iterator_range.h"
 #include "llvm/Support/FormatVariadic.h"
 #include "mlir/Dialect/StandardOps/Ops.h"  // TF:local_config_mlir
 #include "mlir/Dialect/Traits.h"  // TF:local_config_mlir
@@ -1029,6 +1031,66 @@ void SubOp::getCanonicalizationPatterns(OwningRewritePatternList &results,
   results.insert<SubOfNeg>(context);
 }
 
+//===----------------------------------------------------------------------===//
+// StridedSliceOp
+//===----------------------------------------------------------------------===//
+
+// Verifies that,
+//
+// - begin, end and strides operands are 1D and they have the same number of
+//   elements. Here, the number of elements should be less than 32 to support
+//   32-bit mask attributes.
+// - None of the strides values are zero.
+//
+static LogicalResult Verify(StridedSliceOp op) {
+  // Expected size for operands begin, end and strides vector operands.
+  int64_t expected_size = -1;
+
+  for (Value *val : llvm::drop_begin(op.getOperands(), 1)) {
+    auto operand_ty = val->getType().dyn_cast<ShapedType>();
+    if (!operand_ty || !operand_ty.hasStaticShape()) {
+      // TensorFlow constant ops may have non-static shape because the shape is
+      // not propagated during constant folding. If the defining op for this
+      // operand is a constant op, use the constant op's attribute to get the
+      // actual shape.
+      DenseIntElementsAttr attr;
+      if (!matchPattern(val, m_Constant(&attr))) continue;
+      operand_ty = attr.getType();
+    }
+
+    if (operand_ty.getRank() != 1)
+      return op.emitOpError()
+             << "requires begin, end and strides to be 1D tensors";
+
+    int64_t length = operand_ty.getDimSize(0);
+    if (length == -1) continue;
+
+    if (expected_size == -1) {
+      // This op uses 32-bit masks.
+      if (length >= 32)
+        return op.emitOpError(
+            "requires begin, end and strides operands with less than 32 "
+            "elements");
+
+      expected_size = length;
+    } else if (length != expected_size) {
+      return op.emitOpError() << "requires begin, end and strides to have the "
+                                 "same number of elements";
+    }
+  }
+
+  // If strides are constants, verify that none of the element is zero.
+  DenseIntElementsAttr strides;
+  if (matchPattern(op.strides(), m_Constant(&strides))) {
+    if (llvm::is_contained(strides.getValues<APInt>(), 0))
+      return op.emitOpError("requires non-zero strides");
+  }
+
+  // TODO(hinsu): Validate attributes.
+
+  return success();
+}
+
 //===----------------------------------------------------------------------===//
 // TensorListReserveOp
 //===----------------------------------------------------------------------===//
diff --git a/tensorflow/compiler/mlir/tensorflow/tests/tf-ops.mlir b/tensorflow/compiler/mlir/tensorflow/tests/tf-ops.mlir
index b702f5fe88c..e207e3d3562 100644
--- a/tensorflow/compiler/mlir/tensorflow/tests/tf-ops.mlir
+++ b/tensorflow/compiler/mlir/tensorflow/tests/tf-ops.mlir
@@ -1173,3 +1173,56 @@ func @testPack(%arg0: tensor<4x8xf32>, %arg1: tensor<4x8xf32>, %axis: tensor<i32
   %0 = "tf.Pack"(%arg0, %arg1) {axis = 3 : i64, N = 2: i64} : (tensor<4x8xf32>, tensor<4x8xf32>) -> tensor<*xf32>
   return %0 : tensor<*xf32>
 }
+
+// -----
+
+// Valid StridedSlice operation.
+func @testStridedSlice(%input: tensor<4x8xf32>, %begin: tensor<2xi64>, %end: tensor<2xi64>, %strides: tensor<2xi64>) -> tensor<?x?xf32> {
+  %0 = "tf.StridedSlice"(%input, %begin, %end, %strides) : (tensor<4x8xf32>, tensor<2xi64>, tensor<2xi64>, tensor<2xi64>) -> tensor<?x?xf32>
+  return %0 : tensor<?x?xf32>
+}
+
+// -----
+
+func @testStridedSlice(%input: tensor<4x8xf32>, %begin: tensor<i64>, %end: tensor<i64>, %strides: tensor<i64>) -> tensor<?x?xf32> {
+  // expected-error @+1 {{requires begin, end and strides to be 1D tensors}}
+  %0 = "tf.StridedSlice"(%input, %begin, %end, %strides) : (tensor<4x8xf32>, tensor<i64>, tensor<i64>, tensor<i64>) -> tensor<?x?xf32>
+  return %0 : tensor<?x?xf32>
+}
+
+// -----
+
+func @testStridedSlice(%input: tensor<4x8xf32>, %begin: tensor<32xi64>, %end: tensor<2xi64>, %strides: tensor<2xi64>) -> tensor<?x?xf32> {
+  // expected-error @+1 {{with less than 32 elements}}
+  %0 = "tf.StridedSlice"(%input, %begin, %end, %strides) : (tensor<4x8xf32>, tensor<32xi64>, tensor<2xi64>, tensor<2xi64>) -> tensor<?x?xf32>
+  return %0 : tensor<?x?xf32>
+}
+
+// -----
+
+func @testStridedSlice(%input: tensor<4x8xf32>, %begin: tensor<?xi64>, %end: tensor<3xi64>, %strides: tensor<2xi64>) -> tensor<?x?xf32> {
+  // expected-error @+1 {{to have the same number of elements}}
+  %0 = "tf.StridedSlice"(%input, %begin, %end, %strides) : (tensor<4x8xf32>, tensor<?xi64>, tensor<3xi64>, tensor<2xi64>) -> tensor<?x?xf32>
+  return %0 : tensor<?x?xf32>
+}
+
+// -----
+
+func @testStridedSlice(%input: tensor<4x8xf32>) -> tensor<?x?xf32> {
+  %begin = "tf.Const"() { value = dense<[0, 0]> : tensor<2xi64> } : () -> tensor<?xi64>
+  %end = "tf.Const"() { value = dense<[5, 10]> : tensor<2xi64> } : () -> tensor<?xi64>
+  %strides = "tf.Const"() { value = dense<[2, 3, 4]> : tensor<3xi64> } : () -> tensor<?xi64>
+
+  // expected-error @+1 {{to have the same number of elements}}
+  %1 = "tf.StridedSlice"(%input, %begin, %end, %strides) : (tensor<4x8xf32>, tensor<?xi64>, tensor<?xi64>, tensor<?xi64>) -> tensor<?x?xf32>
+}
+
+// -----
+
+func @testStridedSlice(%input: tensor<4x8xf32>, %begin: tensor<2xi32>, %end: tensor<2xi32>) -> tensor<?x?xf32> {
+  %strides = "tf.Const"() { value = dense<[2, 0]> : tensor<2xi32> } : () -> tensor<2xi32>
+
+  // expected-error @+1 {{requires non-zero strides}}
+  %1 = "tf.StridedSlice"(%input, %begin, %end, %strides) : (tensor<4x8xf32>, tensor<2xi32>, tensor<2xi32>, tensor<2xi32>) -> tensor<?x?xf32>
+  return %1 : tensor<?x?xf32>
+}