return argumentOp->getOperand(0);
  }

  return {};
}

}  // namespace detail

// This class adds property that the operation is idempotent.
// This means a unary to unary operation "f" that satisfies f(f(x)) = f(x),
// or a binary operation "g" that satisfies g(x, x) = x.
template <typename ConcreteType>
class IsIdempotent : public TraitBase<ConcreteType, IsIdempotent> {
 public:

type In struct {
	JPathExpr *JSONPath `parser:"@@"`
	ListExpr  *ListExpr `parser:"| @@"`
}

// Grammar for Operand:
//
// operand → multOp ( ("-" | "+") multOp )*
// multOp  → unary ( ("/" | "*" | "%") unary )*
// unary   → "-" unary | primary
// primary → Value | Variable | "(" expression ")"
//

// An Operand is a single term followed by an optional sequence of
// terms separated by +/-
type Operand struct {

  if (op->getNumOperands() != 1) {
    return rewriter.notifyMatchFailure(
        op, "Function only supports unary einsum op");
  }
  RankedTensorType lhs =
      mlir::dyn_cast_or_null<RankedTensorType>(op.getOperand(0).getType());
  if (!lhs) {
    return failure();
  }
  // unary einsum op is only supported to the case where the operation can be
  // replaced using reduce_sum and/or transpose

            // - Labels themselves: `@label` in return`@label` or `label@`while...
            is KtLabelReferenceExpression ->
                false

            // - The operation symbol itself in binary and unary operations: `!!`, `+`...
            is KtOperationReferenceExpression ->
                false

            // All other expressions are used if their parent expression uses them.
            else ->

	RM_RMM              // Round to Nearest, ties to Max Magnitude
)

// All unary instructions which write to their arguments (as opposed to reading
// from them) go here. The assembly parser uses this information to populate
// its AST in a semantically reasonable way.
//
// Any instructions not listed here are assumed to either be non-unary or to read
// from its argument.
var unaryDst = map[obj.As]bool{
	ARDCYCLE:    true,

  }

  const std::string type_index_name =
      ::tensorflow::port::MaybeAbiDemangle(a.TypeId().name());

  return ::tensorflow::errors::Internal(
      "No unary variant binary_op function found for op ADD Variant "
      "type_name: ",
      type_index_name, " for device type: ", cc_ctx->device()->name());
}

void TF_AddNVariant(TF_OpKernelContext* ctx,

            ConstantValueKind.Boolean -> CompileTimeType.BOOLEAN
            ConstantValueKind.String -> CompileTimeType.STRING

            else -> CompileTimeType.ANY
        }
    }

    // Unary operators
    private fun FirLiteralExpression.evaluate(function: FirSimpleFunction): FirLiteralExpression? {
        if (value == null) return null
        (value as? String)?.let { opr ->
            evalUnaryOp(

namespace mlir::quant {

using QuantMethod = tensorflow::quantization::QuantizationMethod::PresetMethod;

enum class OpType {
  kDynamicRangeOp,  // Dynamic Range kernels only have rhs attr.
  kUnaryOp,         // Unary ops have one min/max attr.
  kBinaryOp,        // Binary ops have lhs/rhs attr.
  kQuantizationOp,  // Quantization ops have input/output attr.
};

// For each op type, the following axis carries axis information:

                                             #v1, \
                                             pred, \
                                             v1), on_failure)

// Unary predicate assertion macros.
#define EXPECT_PRED_FORMAT1(pred_format, v1) \
  GTEST_PRED_FORMAT1_(pred_format, v1, GTEST_NONFATAL_FAILURE_)
#define EXPECT_PRED1(pred, v1) \
  GTEST_PRED1_(pred, v1, GTEST_NONFATAL_FAILURE_)

        file("build/reports/pmd/test.xml").assertContents(containsClass("org.gradle.Class1Test"))
        output.contains "\tUsing multiple unary operators may be a bug"
        output.contains "\tEnsure you override both equals() and hashCode()"
    }

    void "can configure number of threads on good code"() {
        goodCode()
        buildFile << """