%3 = "tf.Shape"(%arg0) : (tensor<?x1x2x?xf32>) -> tensor<4xi32>
  %4 = "tf.StridedSlice"(%3, %0, %1, %2) {begin_mask = 0 : i64, ellipsis_mask = 0 : i64, end_mask = 0 : i64, new_axis_mask = 0 : i64, shrink_axis_mask = 0 : i64} : (tensor<4xi32>, tensor<1xi32>, tensor<1xi32>, tensor<1xi32>) -> tensor<2xi32>
  func.return %4 : tensor<2xi32>
  // CHECK: %[[SLICE:.*]] = "tf.StridedSlice"
  // CHECK: return %[[SLICE]]
}

// CHECK-DAG:       [[VAL_22:%.*]] = arith.constant dense<0> : tensor<3xi32>
// CHECK-DAG:       [[VAL_23:%.*]] = arith.constant dense<1> : tensor<3xi32>

}

func.func @strided_slice(%arg0: tensor<12x2x2x5xf32>, %arg1: tensor<1xi32>, %arg2: tensor<1xi32>, %arg3: tensor<1xi32>) -> tensor<1x2x2x5xf32> {

  return true;
}

OpFoldResult StridedSliceOp::fold(FoldAdaptor) {
  // Fold StridedSlice operation if it extracts statically known dimensions.
  //
  // For example,
  //
  //   %shape  = tf.Shape(%arg)                   // %arg: tensor<?x2x3x1xf32>
  //   %height = tf.StridedSlice(%shape, 1, 2, 1)
  //
  // In this case %height can be replaced with a constant 2.
  //
  // Or,

    %zero = "tf.Const"() {value = dense<0> : tensor<4xi32>} : () -> tensor<4xi32>
    %one = "tf.Const"() {value = dense<1> : tensor<4xi32>} : () -> tensor<4xi32>

    SameOperandsAndResultsScale,
    TFL_OperandHasRankAtMost<0, 5>,
    TFL_OperandHasRank<1, 1>,
    TFL_OperandHasRank<2, 1>,
    TFL_OperandHasRank<3, 1>
  ]> {
  let summary = "StridedSlice Op";

  let description = [{
    Return a strided slice from `input`.
  }];

  let arguments = (ins