string key(v2_reader_->key());
    (*var_to_shape_map)[key] = TensorShape(entry.shape());
    (*var_to_data_type_map)[key] = DataType(entry.dtype());
  }
  // The returned pointers are owned by the caller.
  return std::make_pair(std::move(var_to_shape_map),
                        std::move(var_to_data_type_map));
}

}  // namespace checkpoint

};
#endif  // !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)

namespace tensorflow {

// Set the shapes and types of the output's handle.
//
// The lengths of the arrays pointed to by `shapes`, `ranks`, and `types` must
// all be equal to `num_shapes_and_types`. If `ranks[i] != -1`, (i.e., if the
// rank is known), then it must be equal to the length of `shapes[i]`; if

    return errors::Unimplemented(tensorflow::strings::StrCat(
        "Filesystem for ", fname, " does not support Stat()"));

  if (stat == nullptr)
    return errors::InvalidArgument("FileStatistics pointer must not be NULL");

  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);
  std::string translated_name = TranslateName(fname);
  TF_FileStatistics stats;

// parsed.
//
// Furthermore, as `INSTANTIATE_TEST_SUITE_P` needs to be at global level and we
// don't want to have a `std::vector<std::string>` at global level, we use a
// static pointer to such a vector: we construct it via `SchemeVector()` below
// and when tests are instantiated we process it using `GetSchemes()`.
static std::vector<std::string>* SchemeVector() {

  TFE_DeleteExecutor(executor);
  TFE_DeleteContext(ctx);
}

void ExecuteAdd(bool async, bool forward_input, bool tfrt) {
#ifdef PLATFORM_WINDOWS
  // On windows, we flakily get a failure due to pointer instability.
  // Disable the 4 tests using this helper until we fix the issue.
  return;
#else
  TF_Status* status = TF_NewStatus();
  TFE_ContextOptions* opts = TFE_NewContextOptions();

// This function will block till the operation that produces `h` has
// completed. This is only valid on local TFE_TensorHandles. The pointer
// returned will be on the device in which the TFE_TensorHandle resides (so e.g.
// for a GPU tensor this will return a pointer to GPU memory). The pointer is
// only guaranteed to be valid until TFE_DeleteTensorHandle is called on this
// TensorHandle. Only supports POD data types.

  // Check if the remote task is alive.
  virtual Status CheckRemoteAlive(const std::string& remote_task_name,
                                  bool* is_alive) = 0;

  // Get pointer to the coordination service agent instance.
  virtual tsl::CoordinationServiceAgent* GetCoordinationServiceAgent() = 0;
};
}  // namespace tensorflow

//
// This function will block till the operation that produces `h` has completed.
TF_CAPI_EXPORT extern const char* TFE_TensorHandleBackingDeviceName(
    TFE_TensorHandle* h, TF_Status* status);

// Return a pointer to a new TFE_TensorHandle that shares the underlying tensor
// with `h`. On success, `status` is set to OK. On failure, `status` reflects
// the error and a nullptr is returned.

/// address of the opaque data pointer, hence the wrapper pointer is marked
/// `const`.
///
/// For consistency, the arguments on all these functions follow the same
/// pattern: first we have the opaque pointer argument ("this" above), then the
/// input arguments, then the in-out arguments (if any) and we finish the
/// argument list with the out arguments. We only use the return type for an out

#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
#include "tensorflow/core/platform/errors.h"

namespace tensorflow {
namespace gradients {
namespace {

// TODO(b/172558015): Using the pointer address as the identifier for the tensor
// may lead to collisions. Introduce another way to get a unique id for this
// tensor.
int64_t ToId(const AbstractTensorHandle* t) {