func Unalias(t types.Type) types.Type { return types.Unalias(t) }

// newAlias is an internal alias around types.NewAlias.
// Direct usage is discouraged as the moment.
// Try to use NewAlias instead.
func newAlias(tname *types.TypeName, rhs types.Type) *Alias {
	a := types.NewAlias(tname, rhs)
	// TODO(go.dev/issue/65455): Remove kludgy workaround to set a.actual as a side-effect.
	Unalias(a)
	return a
}

            solutions == [
                'Assign a value to \'destFile\'',
                'Mark property \'destFile\' as optional',
            ]
            additionalData.asMap == [
                'typeName' : 'CustomTask',
                'propertyName' : 'destFile',
            ]
        }
        verifyAll(receivedProblem(1)) {
            fqid == 'validation:property-validation:value-not-set'

            it.id("id", "label", GradleCoreProblemGroup.validation())
                .additionalData(TypeValidationDataSpec.class) {
                    it.propertyName("property")
                    it.typeName("type")
                    it.parentPropertyName("parent")
                    it.pluginId("id")
                }
        }

        when:
        def json = gson.toJson([problem])

enum QuantizationTrait { kFullQuantization, kDynamicRangeQuantization };

// Base struct for quantization.
template <QuantizationTrait quantization_trait, typename ConcreteT,
          typename RootOpT = DequantizeOp>
struct TFLQuantizationBase
    : public quant::QuantizationPattern<ConcreteT, QuantizeOp, DequantizeOp,
                                        NumericVerifyOp, RootOpT> {

inline const char kMlirPh1BridgeCounterNonTpu[] = "cpu/gpu";
inline const char kXlaOutsideCompilation[] = "_xla_outside_compilation";

// Copies attributes that satisfy the given predicate from `from` to `to`.
template <typename Predicate>
void CopyAttributes(Operation *from, Operation *to, Predicate P) {
  for (const NamedAttribute &attr : from->getAttrs())
    if (P(attr)) to->setAttr(attr.getName(), attr.getValue());
}

		res := hf(ctx, i)
		if res == nil {
			return nil
		}
		return []O{*res}
	}
	o := buildCollectionOptions(opts...)
	if o.name == "" {
		o.name = fmt.Sprintf("Collection[%v,%v]", ptr.TypeName[I](), ptr.TypeName[O]())
	}
	return newManyCollection[I, O](c, hm, o)
}

// NewManyCollection transforms a Collection[I] to a Collection[O] by applying the provided transformation function.

namespace mlir {
namespace odml {

// Ensure an attribute named attr_name exists and it is of type AttrType.
// If so, sets the `out_attr` pointer to point to the casted attribute.
template <typename AttrType>
bool EnsureAttribute(const DictionaryAttr& composite_attributes,
                     const std::string& attr_name, AttrType* out_attr) {
  Attribute attr = composite_attributes.get(attr_name);

struct TPUPartitionedOpConversionPass
    : public impl::TPUPartitionedOpConversionPassBase<
          TPUPartitionedOpConversionPass> {
  void runOnOperation() override;
};

template <typename T>
LogicalResult ReplacePartitionedOp(IntegerAttr num_cores_per_replica, T op) {
  constexpr bool is_input =
      std::is_same_v<std::decay_t<T>, TF::TPUPartitionedInputOp>;
  static_assert(

// ShapeContainerT is any type with the following methods:
//   bool hasRank()
//   ArrayRef<int64_t> getShape()
// This includes mlir::TF::ShapeAttr and mlir::ShapedType.
template <typename ShapeContainerT>
void SetTensorShapeProto(ShapeContainerT shape, TensorShapeProto* proto) {
  if (shape.hasRank()) {
    for (int64_t dim : shape.getShape()) {

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/core/util/matmul_bcast.h"

namespace mlir {
namespace TF {

namespace {

// Replace TF BatchMatMul by TF Einsum op
template <typename BatchMatMulOpType>
class ConvertTFBatchMatMulToEinsumOp
    : public OpRewritePattern<BatchMatMulOpType> {
  using OpRewritePattern<BatchMatMulOpType>::OpRewritePattern;

  LogicalResult matchAndRewrite(BatchMatMulOpType op,