std::move(mixed_handles), status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK);
  // Can't take the shape of a parallel tensor with varying numbers of axes, but
  // running operations on them is OK.
  TF_ASSERT_OK(unknown_length_vector->Shape(&shape));
  EXPECT_THAT(*shape, ElementsAre(-1));
  std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> size_op(

class OpDeleter {
 public:
  void operator()(TFE_Op* to_delete) const { TFE_DeleteOp(to_delete); }
};

using OpPtr = std::unique_ptr<TFE_Op, OpDeleter>;

class StatusDeleter {
 public:
  void operator()(TF_Status* to_delete) const { TF_DeleteStatus(to_delete); }
};

using StatusPtr = std::unique_ptr<TF_Status, StatusDeleter>;

class ExecutorDeleter {
 public:
  void operator()(TFE_Executor* to_delete) const {

  TF_Operation* operations[]{placeholder_op, reduce_op};
  TF_Output y{reduce_op, 0};
  const char* output_name = "y";
  std::unique_ptr<TF_Function, decltype(&TF_DeleteFunction)> function(
      TF_GraphToFunction(
          /* fn_body */ body.get(), /* fn_name */ function_name,
          /* append_hash_to_fn_name */ 0, /* num_opers */ 2,
          /* opers */ operations, /* ninputs */ 1, /* inputs */ &x,

#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_helper.h"

namespace tensorflow {
namespace parallel_device {
namespace {

class OpDeleter {
 public:
  void operator()(TFE_Op* to_delete) const { TFE_DeleteOp(to_delete); }
};

using OpPtr = std::unique_ptr<TFE_Op, OpDeleter>;

using MaybeParallelTensorOwned =
    absl::variant<std::unique_ptr<ParallelTensor>, TensorHandlePtr>;

        strings::StrCat("Plugin ABI (", pluginABI, ") for ", where,
                        " operations doesn't match expected core ABI (",
                        coreABI, "). Plugin cannot be loaded."));
  return OkStatus();
}

// Checks if the plugin and core ABI numbers match, for all operations.
//
// If the numbers don't match, plugin cannot be loaded.
//
// Uses the simpler `CheckABI(int, int, StringPiece)`.

        ptr[i] = strs[i].c_str();
      }
    }
    return ptr;
  }

  // An explicit `num_opers` is needed so that we can distinguish between the
  // case of no operations specified (-1) and the case of an empty set of
  // operations specified (0).
  void DefineT(int num_opers, const std::vector<TF_Operation*>& opers,
               const std::vector<TF_Output>& inputs,
               const std::vector<TF_Output>& outputs,

  TF_DeleteAbstractTensor(arg0);
  TF_DeleteAbstractTensor(arg1);

  // Finalize the function by providing the returned values.
  TF_AbstractFunction* func;
  {
    // We want to return the output of both add operations, create a new list
    // and populate it.
    TF_OutputList* func_outputs = TF_NewOutputList();
    TF_OutputListPushBack(func_outputs, add_output1, s);
    ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);