// a "member" that will participate in the union-find cluster construction.
//
// A block argument can also become a member (or even a root member), however
// only operations will become a part of the outline `tf_device.cluster`, block
// arguments will stay as block arguments, and will later become cluster
// function inputs.
struct Member {
  Member(unsigned root, Source source, Operation *insertion_point,

	// Verify that the collections actually accessed during testing actually match
	// the collections declared as inputs for each of the analyzers
	t.Run("CheckMetadataInputs", func(t *testing.T) {
		g := NewWithT(t)
	outer:
		for _, a := range All() {
			var isMultiClusterAnalyzer bool
			for _, mc := range AllMultiCluster() {
				if a.Metadata().Name == mc.Metadata().Name {
					isMultiClusterAnalyzer = true
					break
				}

  let summary = "Unfold large splat constant tensors.";
  let constructor = "CreateUnfoldLargeSplatConstantPass()";
  let dependentDialects = ["TFL::TensorFlowLiteDialect"];
}

def WhileOutlinePass : Pass<"tfl-while-loop-outline", "mlir::ModuleOp"> {
  let summary = "Hoist while op regions into functions";
  let constructor = "CreateWhileOutlinePass()";
  let dependentDialects = ["TF::TensorFlowDialect"];
}

	// unused sums marked with TrimGoSum. If there are no changes to make,
	// just return without opening go.sum.
	dirty := false
Outer:
	for m, hs := range goSum.m {
		for _, h := range hs {
			st := goSum.status[modSum{m, h}]
			if st.dirty && (!st.used || keep[m]) {
				dirty = true
				break Outer
			}
		}
	}
	if !dirty {
		return nil
	}
	if readonly {
		return ErrGoSumDirty
	}

                    // `outerClassId`.
                    if (receiverExpression == expression) {
                        // If there is still an outer class, then return symbol of that class
                        outerClassId?.let { return listOfNotNull(it.toTargetPsi(session, symbolBuilder)) }
                        // Otherwise, it should be a package, so we return that

			}

			// Merge the above result with the whole listener
			merge.Merge(dstListener, retVal)
		}
	}
	// If we already applied the patch, we skip merge.Merge() in the outer function
	return applyPatch, nil
}

func patchNetworkFilters(patchContext networking.EnvoyFilter_PatchContext,
	patches map[networking.EnvoyFilter_ApplyTo][]*model.EnvoyFilterConfigPatchWrapper,

    bool legacy_float_scale = false);

// Gets quantization scale specs (e.g. fixed output range, same result and
// operand scales) from the default quantization interfaces. The op should
// outlive returned spec for its interface methods to be properly referenced.
std::unique_ptr<OpQuantScaleSpec> GetDefaultQuantScaleSpec(Operation* op);

// The function might contain more stats ops than required, and it will

	// operator deletes a suggested configuration object and later creates it
	// but with a variant spec and then does no updates of the object
	// (generation is 1), the technique outlined above will incorrectly
	// determine that the object should be auto-updated.
	AutoUpdateAnnotationKey = "apf.kubernetes.io/autoupdate-spec"
)

// +genclient
// +genclient:nonNamespaced

	// Whether the volume permission is set to read-only or not
	// This value is passed from volume.spec
	ReadOnly bool
	// Inner volume spec name, which is the PV name if used, otherwise
	// it is the same as the outer volume spec name.
	InnerVolumeSpecName string
}

// VolumeMap represents the map of volumes.
type VolumeMap map[string]VolumeInfo

// RuntimeConditionType is the types of required runtime conditions.

			}

			x := instructionInfo{objAddr: inst.Addr, length: length, disasm: inst.Text}
			if len(frames) > 0 {
				// We could consider using the outer-most caller's source
				// location so we give the some hint as to where the
				// inlining happened that led to this instruction. So for
				// example, suppose we have the following (inlined) call