together with a continue token. If the client needs a consistent list, it must restart their list without the continue field. Otherwise, the client may send another list request with the token received with the 410 error, the server will respond with a list starting from the next key, but from the latest snapshot, which is inconsistent from the previous list results - objects that are created, modified, or deleted after the first list request will be included in the response, as long as their keys...

together with a continue token. If the client needs a consistent list, it must restart their list without the continue field. Otherwise, the client may send another list request with the token received with the 410 error, the server will respond with a list starting from the next key, but from the latest snapshot, which is inconsistent from the previous list results - objects that are created, modified, or deleted after the first list request will be included in the response, as long as their keys...

// popList takes all Gs in q and returns them as a gList.
func (q *gQueue) popList() gList {
	stack := gList{q.head}
	*q = gQueue{}
	return stack
}

// A gList is a list of Gs linked through g.schedlink. A G can only be
// on one gQueue or gList at a time.
type gList struct {
	head guintptr
}

// empty reports whether l is empty.
func (l *gList) empty() bool {
	return l.head == 0
}

  if (attr->value_case() != tensorflow::AttrValue::kList) {
    status->status =
        InvalidArgument("Value for '", attr_name, "' is not a list");
    return;
  }
  const auto len = std::min(max_values, attr->list().s_size());
  char* p = static_cast<char*>(storage);
  for (int i = 0; i < len; ++i) {
    const string& s = attr->list().s(i);
    values[i] = p;
    lengths[i] = s.size();

      if (name_and_value.first == "_input_shapes") {
        auto& list = name_and_value.second.list();
        auto& signature = func_def->signature();
        // Some models have "_input_shapes" attribute, but with its value empty
        if (list.shape_size() > 0 &&
            list.shape_size() != signature.input_arg_size()) {
          return errors::FailedPrecondition(

#include "llvm/ADT/ArrayRef.h"
#include "llvm/ADT/STLExtras.h"
#include "llvm/ADT/Sequence.h"
#include "llvm/ADT/SmallSet.h"
#include "llvm/ADT/SmallVector.h"
#include "llvm/ADT/StringRef.h"
#include "llvm/ADT/ilist.h"
#include "llvm/Support/Casting.h"
#include "mlir/Dialect/Arith/IR/Arith.h"  // from @llvm-project
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project

        break;
      case tensorflow::AttrValue::kList:
        if (attr.list().s_size() > 0) {
          auto start = flex_builder->StartVector(key);
          for (const std::string& v : attr.list().s()) {
            flex_builder->Add(v);
          }
          flex_builder->EndVector(start, /*typed=*/true, /*fixed=*/false);
        } else if (attr.list().i_size() > 0) {