// should allow registering a plugin graph optimizer with TensorFlow.
//
// Conventions:
//   * Struct prefix indicates whether struct fields should be filled by the
//     plugin or core implementation:
//     * Struct that should be filled by the plugin: `TP_OptimizerConfigs`,
//       `TP_Optimizer`, `TP_OptimizerRegistrationParams`
//     * Struct that should be filled by the proper: `TF_GrapplerItem`,

                                              TF_Operation* input);

// Request that `desc` be co-located on the device where `op`
// is placed.
//
// Use of this is discouraged since the implementation of device placement is
// subject to change. Primarily intended for internal libraries
TF_CAPI_EXPORT extern void TF_ColocateWith(TF_OperationDescription* desc,
                                           TF_Operation* op);

TF_CAPI_EXPORT void TF_SetXlaMinClusterSize(int size);

// Gets/Sets TF/XLA flag for whether(true) or not(false) to disable constant
// folding. This is for testing to ensure that XLA is being tested rather than
// Tensorflow's CPU implementation through constant folding.
TF_CAPI_EXPORT unsigned char TF_GetXlaConstantFoldingDisabled();
TF_CAPI_EXPORT void TF_SetXlaConstantFoldingDisabled(
    unsigned char should_enable);

TF_CAPI_EXPORT extern void TFE_HostAddressSpace(TFE_Context* ctx,
                                                TF_Buffer* buf);

// APIs for generically dealing with op attributes (e.g. when forwarding them
// through custom device implementations).
//
// TODO(allenl): Currently these are black boxes, but we should have some way to
// inspect values. This would let people e.g. copy over most attributes and then
// modify some based on their values.

///
/// DEFAULT IMPLEMENTATIONS: Some operations have default implementations that
/// TensorFlow uses in case the plugin doesn't supply its own version. An
/// operation `foo` might have a default implementation which uses `bar` and
/// `foobar`. If the plugin supplies `bar` and `foobar`, TensorFlow can use the
/// default implementation of `foo`.
///

//
// A TensorHandle is management class around a Tensor which may track additional
// metadata and synchronization.
//
// This allows us to hide concrete implementations of TensorHandle from header
// files. The interface lists the common functionality that must be provided by
// any concrete implementation. However, in cases where the true concrete class
// is needed a static_cast can be applied.

#include <memory>

#include "tensorflow/c/experimental/filesystem/filesystem_interface.h"
#include "tensorflow/core/platform/file_system.h"

/// This file builds classes needed to hold a filesystem implementation in the
/// modular world. Once all TensorFlow filesystems are converted to use the
/// plugin based approach, this file will replace the one in core/platform and

// (1) TF_Output or TFE_TensorHandle* as arguments to TF_AddInput,
//     TF_AddInputList
// (2) TF_ColocateWith, TF_AddControlInput etc. do not make sense.
// (3) Implementation detail: Avoid use of NodeBuilder/NodeDefBuilder since
//     the additional sanity checks there seem unnecessary;
typedef struct TFE_Op TFE_Op;

TF_CAPI_EXPORT extern TFE_Op* TFE_NewOp(TFE_Context* ctx,

  // appropriate.
  virtual tensorflow::FullTypeDef FullType() const = 0;

  // The default debug string includes a shape, dtype and FullType.
  // Implementations are free to override it with something more informative.
  virtual std::string DebugString() const;

  AbstractTensorHandleKind getKind() const { return kind_; }

 private:
  const AbstractTensorHandleKind kind_;

// the datatype for boolean tensors.
#ifndef TF_Bool
#define TF_Bool unsigned char
#endif  // TF_Bool

// Macro used to calculate struct size for maintaining ABI stability across
// different struct implementations.
#ifndef TF_OFFSET_OF_END
#define TF_OFFSET_OF_END(TYPE, MEMBER) \
  (offsetof(TYPE, MEMBER) + sizeof(((TYPE *)0)->MEMBER))
#endif  // TF_OFFSET_OF_END