// requires its type (e.g. "AddV2") to be set independently.
TF_AbstractOp* TF_NewAbstractOp(TF_ExecutionContext* ctx);
void TF_DeleteAbstractOp(TF_AbstractOp*);

// TODO(srbs): Add APIs for specifying attrs etc.
// `op_type` must outlive `op`.
void TF_AbstractOpSetOpType(TF_AbstractOp* op, const char* const op_type,
                            TF_Status* s);
// `op_name` must outlive `op`.

  // separate static method which returns a status.
  Variable(TFE_TensorHandle* handle, TF_DataType type)
      : handle_(handle), type_(type) {}

  // Helper for constructing a resource handle and wrapping it in a `Variable`
  // object.
  static Variable* Create(TFE_Context* context, TF_DataType type,
                          const int64_t* dims, const int num_dims,

              TFE_TensorHandle* axis);

// If there is a device of type `device_type`, returns true
// and sets 'device_name' accordingly.
// `device_type` must be either "GPU" or "TPU".
bool GetDeviceName(TFE_Context* ctx, tensorflow::string* device_name,
                   const char* device_type);

// Create a ServerDef with the given `job_name` and add `num_tasks` tasks in it.

// returned and both error counters are set to zero.
//
// Otherwise, while traversing the tree, undeleted_file_count and
// undeleted_dir_count are updated if an entry of the corresponding type could
// not be deleted. The returned error status represents the reason that any one
// of these entries could not be deleted.
//
// Typical status codes:

typedef jarray jintArray;
typedef jarray jlongArray;
typedef jarray jfloatArray;
typedef jarray jdoubleArray;
typedef jarray jobjectArray;

typedef jobject jweak;

#define TENSORFLOW_C_EXPERIMENTAL_FILESYSTEM_PLUGINS_GCS_CLEANUP_H_

#include <type_traits>
#include <utility>

namespace tf_gcs_filesystem {

// A move-only RAII object that calls a stored cleanup functor when
// destroyed. Cleanup<F> is the return type of gtl::MakeCleanup(F).
template <typename F>
class Cleanup {
 public:
  Cleanup() : released_(true), f_() {}

// A create function. This will never actually get called in this test, it's
// just nice to know that it compiles.
void* create(TF_OpKernelConstruction* ctx) {
  TF_DataType type;
  TF_Status* s = TF_NewStatus();
  TF_OpKernelConstruction_GetAttrType(ctx, "foobar", &type, s);
  TF_DeleteStatus(s);
  return NULL;
}

// A compute function. This will never actually get called in this test, it's
// just nice to know that it compiles.

  virtual tensorflow::Status Shape(
      tensorflow::PartialTensorShape* shape) const = 0;

  // Returns tensor (full) type.
  // While there is no immediate plan to deprecate dtype and shape in favor
  // of only using full type type information, this is a future possibility.
  //
  // Note that map_dtype_to_child_of_tensor() from core/framework/types.h

TF_CAPI_EXPORT extern void TF_CreateAndSetPjRtCApiClient(
    const char* device_type, TF_Status* status, PJRT_NamedValue* create_options,
    int num_options);

// Resets the PjRt client for a device. After this, `TF_GetPjRtCClient` will
// returns an error for that device.
TF_CAPI_EXPORT extern void TF_ResetPjRtCClient(const char* device_type,
                                               TF_Status* status);

// Represents either a MlirTensor or a GraphTensor.
// This base class does not expose any public methods other than to distinguish
// which subclass it actually is. The user is responsible to use the right
// type of AbstractTensor in their context (do not pass an MlirTensor to a
// GraphContext and vice-versa).
class TracingTensorHandle : public AbstractTensorHandle {
 protected: