//     probe for gadgets inside core TensorFlow. We can even protect the area
//     of memory where the copies reside to not allow any more writes to it
//     after all copies are created.
template <typename T>
static std::unique_ptr<const T> CopyToCore(const T* plugin_ops,
                                           size_t plugin_size) {
  if (plugin_ops == nullptr) return nullptr;

class TPUAnnotateDynamicShapeInputsPass
    : public impl::TPUAnnotateDynamicShapeInputsPassBase<
          TPUAnnotateDynamicShapeInputsPass> {
  void runOnOperation() override;
};

// Finds op that created a given value. If the value is a BlockArgument, this
// returns the owner of the Block.
Operation* GetOpOfValue(Value value) {
  if (auto block_arg = mlir::dyn_cast<BlockArgument>(value))

    };
    auto del_dealloc = [&](int pos) {
      deltas.emplace_back(pos + 1, tensor.size);
    };

    if (global.first_use < remat.begin) {
      // The tensor is created before the source range.
      if (global.last_use < remat.insert) {
        // It currently gets deallocated before the newly inserted range, so we
        // need to extend its lifetime: It will now be deallocated at its last

    return isa<NameLoc>(loc) ||
           (isa<CallSiteLoc>(loc) &&
            isa<NameLoc>(mlir::cast<CallSiteLoc>(loc).getCallee()));
  });
}

// Finds the pattern of the location created by `ImporterBase::GetLocation`
// in `tensorflow/compiler/mlir/tensorflow/translate/import_model.cc`.
void FindQuantizationUnitsRecursively(Location loc,
                                      SmallVector<QuantizationUnit>& units) {

  builder.setInsertionPoint(&terminator);
  builder.create<tf_executor::YieldOp>(terminator.getLoc(),
                                       terminator.getOperands());
  terminator.erase();

  builder.setInsertionPoint(island_op);
  IRMapping mapping;
  for (int i : llvm::seq<int>(0, num_replicas)) {
    // Create new island for replica.
    auto replica = builder.create<tf_executor::IslandOp>(

      moved_ops_list.push_back(new_if_op.getOperation());
    }
  }
}

// Create the Yield ops for both branches with merged results.
// `builder` is the OpBuilder.
// `if_op_segment` refers to the segment of IfRegions to be merged.
// `return_indices` refers to the return indices to be kept in merged IfRegion
// `new_if_op` refers to the created new IfRegion
void CreateYieldOps(

  TF_Run(session, run_options, nullptr, nullptr, 0, nullptr, nullptr, 0,
         nullptr, 0, run_metadata, s);
  EXPECT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(s)) << TF_Message(s);
  EXPECT_EQ("Session was not created with a graph before Run()!",
            string(TF_Message(s)));
  TF_DeleteBuffer(run_metadata);
  TF_DeleteBuffer(run_options);

  TF_DeleteDeprecatedSession(session, s);

    // Create tensor attribute for this variable.
    absl::StatusOr<ElementsAttr> tensor_attr_or =
        ConvertTensor(tensor, &builder);
    if (!tensor_attr_or.ok()) {
      return module.emitOpError()
             << "failed to convert tensor (name: " << name.str() << ")";
    }
    ElementsAttr tensor_attr = tensor_attr_or.value();

    builder.create<tf_saved_model::GlobalTensorOp>(

namespace mlir {
namespace TF {

namespace {

// Creates ConstOp for int32_t value.
ConstOp createI32ConstOp(int32_t value, Location loc,
                         PatternRewriter* rewriter) {
  auto int_attr = IntegerAttr::get(rewriter->getIntegerType(32), value);
  return rewriter->create<ConstOp>(loc, int_attr);
}

// Creates ConstantOp for array of int32_t.

  AbstractTensorPtr tensor(ctx->CreateStringScalar(s));
  if (tensor.get() == nullptr) {
    return errors::Internal(
        "Failed to create scalar string tensor for checkpoint restore");
  }

  out->reset(ctx->CreateLocalHandle(tensor.get()));
  return Status();
}

// Creates a Rank 1 string tensorhandle containing a single string `s`
Status CreateStringVectorTensorHandle(ImmediateExecutionContext* ctx,