// CHECK: tfl.logical_or %arg0, %arg1
  %0 = "tfl.logical_or"(%arg0, %arg1) : (tensor<? x i1>, tensor<? x i1>) -> tensor<? x i1>
  func.return %0#0 : tensor<? x i1>
}

// -----

func.func @testLogicalOrWrongOperandType(tensor<? x i32>, tensor<? x i32>) -> tensor<? x i32> {
^bb0(%arg0: tensor<? x i32>, %arg1: tensor<? x i32>):

// CHECK-LABEL: logicalAnd
// CHECK:  tfl.logical_and %arg0, %arg1 : tensor<8xi1>
// CHECK:  return
}

func.func @logicalNot(%arg0: tensor<8xi1>) -> tensor<8xi1> {
  %0 = "tf.LogicalNot"(%arg0) : (tensor<8xi1>) -> tensor<8xi1>
  func.return %0 : tensor<8xi1>
// CHECK-LABEL: logicalNot
// CHECK:  "tfl.logical_not"(%arg0) : (tensor<8xi1>) -> tensor<8xi1>
}

func.func @logicalOr(%arg0: tensor<8xi1>, %arg1: tensor<8xi1>) -> tensor<8xi1> {

/// possible.
/// The function currently asserts that the `result_type` to be a f32 tensor
/// type.
/// TODO: Extend this function to handle integral tensor for ops like
/// "tfl.logical_not".
Attribute ConstFoldUnaryOp(Type result_type, Attribute operand,
                           llvm::function_ref<APFloat(APFloat)> calculate) {
  assert(IsF32ShapedType(result_type) || IsBF16ShapedType(result_type));

}

def TFL_LogicalNotOp : TFL_Op<"logical_not", [
    Pure,
    SameOperandsAndResultShape]> {
  let summary = "Logical NOT operator";

  let description = [{
    Element-wise logical NOT operation.
  }];

  let arguments = (ins TFL_BoolTensor:$lhs);

  let results = (outs TFL_BoolTensor:$output);
}

def TFL_LogicalOrOp : TFL_Op<"logical_or", [Pure]> {

// CHECK: return %arg0
}

// CHECK-LABEL: testDoubleLogicalNot
func.func @testDoubleLogicalNot(%arg0: tensor<8x16x32x64xi1>) -> tensor<8x16x32x64xi1> {
  %0 = "tf.LogicalNot"(%arg0) : (tensor<8x16x32x64xi1>) -> tensor<8x16x32x64xi1>
  %1 = "tf.LogicalNot"(%0) : (tensor<8x16x32x64xi1>) -> tensor<8x16x32x64xi1>
  func.return %1: tensor<8x16x32x64xi1>

// CHECK: return %arg0
}

// CHECK-LABEL: testDoubleNeg