def tfvariable_readonly(_):
  x = variables.Variable(1000.0, name='x')
  unused_y = variables.Variable(1000.0, name='y')
  old_x = x.value()
  with ops.control_dependencies([old_x]):
    new_value = math_ops.add(old_x, 42.0)
  array_ops.identity(new_value, name='result')


# TODO(b/147908587): Change x and the two constants back to have a scalar shape
#                    when the bug is fixed.
def tfvariable(_):

	}
}

func TestListValueContainsNestedList(t *testing.T) {
	lvA := NewListValue()
	lvA.Append(testValue(t, 1, int64(1)))
	lvA.Append(testValue(t, 2, int64(2)))

	lvB := NewListValue()
	lvB.Append(testValue(t, 3, int64(3)))

	elemA, elemB := testValue(t, 4, lvA), testValue(t, 5, lvB)
	lv := NewListValue()
	lv.Append(elemA)
	lv.Append(elemB)

	contained := lv.Contains(elemA.ExprValue())

  EXPECT_TRUE(statistics.has_value());
  EXPECT_EQ(statistics.value().min_max_statistics().global_min(), -5.0f);
  EXPECT_EQ(statistics.value().min_max_statistics().global_max(), 10.0f);

  collector.ClearData();
  statistics = collector.GetStatistics();
  EXPECT_FALSE(statistics.has_value());

  collector.Collect(
      /*min=*/1.0f, /*max=*/10.f, /*histogram=*/{});

DenseElementsAttr GetScalarOfType(Type ty, T raw_value) {
  RankedTensorType scalar_ty = RankedTensorType::get({}, ty);
  if (auto float_ty = mlir::dyn_cast<FloatType>(ty)) {
    FloatAttr attr = FloatAttr::get(float_ty, raw_value);
    return DenseElementsAttr::get(scalar_ty, attr);
  } else if (auto int_ty = mlir::dyn_cast<IntegerType>(ty)) {
    IntegerAttr attr = IntegerAttr::get(int_ty, raw_value);
    return DenseElementsAttr::get(scalar_ty, attr);

    }

    def testWriteNonNullValue() throws IOException {
        final File testValue = new File("dummyTestFileValue")
        fileOption.setValue(testValue)

        when:
        fileOption.write(writerContextMock)

        then:
        1 * writerContextMock.writeValueOption(optionName, testValue.absolutePath)
    }

  auto op_func_attr_array = op.getOpFuncAttrs().getValue();
  for (auto op_attr : op_func_attr_array) {
    auto key_value = mlir::dyn_cast<mlir::ArrayAttr>(op_attr);
    if (!key_value || key_value.getValue().size() != 2 ||
        !mlir::isa<mlir::StringAttr>(key_value.getValue()[0]) ||
        !mlir::isa<mlir::StringAttr>(key_value.getValue()[1]))
      return op.emitOpError() << "each op_func_attr should be a key-value "

/// converted type in outConvertedType.
///
/// Examples:
/// 1. realValue is a primitive value attribute:
/// (realValue: FloatAttr, quantizedElementType: UniformQuantizedType[i8:f32])
///   -> (IntegerAttr, outConvertedType: i8)
/// 2. realValue is an elements attribute:
/// (realValue: DenseElementsAttr[tensor<2x2xf32>],
///  quantizedElementType: UniformQuantizedType[i8:f32])

			namespaceTolerations:      []api.Toleration{},
			podTolerations:            []api.Toleration{{Key: "testKey", Operator: "Equal", Value: "testValue", Effect: "NoSchedule", TolerationSeconds: nil}},
			mergedTolerations:         []api.Toleration{{Key: "testKey", Operator: "Equal", Value: "testValue", Effect: "NoSchedule", TolerationSeconds: nil}},

  assert(op_attrs);
  op_attrs->clear();

  mlir::Builder builder(context);
  for (auto iter : op_attr_array) {
    auto key_value = mlir::cast<mlir::ArrayAttr>(iter).getValue();
    llvm::StringRef key = mlir::cast<mlir::StringAttr>(key_value[0]).getValue();
    mlir::Attribute value = key_value[1];
    op_attrs->push_back({key, value});
  }
}

mlir::ParseResult ParseExecuteOpCommon(mlir::OpAsmParser &parser,

			destValue := reflect.ValueOf(stmt.Dest)
			for destValue.Kind() == reflect.Ptr {
				destValue = destValue.Elem()
			}

			if stmt.ReflectValue != destValue {
				if !destValue.CanAddr() {
					destValueCanAddr := reflect.New(destValue.Type())
					destValueCanAddr.Elem().Set(destValue)
					stmt.Dest = destValueCanAddr.Interface()
					destValue = destValueCanAddr.Elem()
				}