// resulting per-device and per-output TFE_TensorHandles into one
  // ParallelTensor per output of the original operation.
  //
  // Attributes are forwarded to executed operations unmodified.
  //
  // The returned optional has a value if and only if `status` evaluates to
  // TF_OK. Bad statuses are forwarded from underlying `TFE_Execute` calls, or
  // if sanity checks on dtypes/metadata fail.

//   {"/job:localhost/replica:0/task:0/device:GPU:0",
//    "/job:localhost/replica:0/task:0/device:GPU:1"}
// Then executing an operation on CUSTOM:0 will execute it on GPU:0 and GPU:1.
//
// Implicit copies onto `device_name` are allowed, replicating the value once
// per device in `underlying_devices`. Implicit copies off of the device throw
// an error.
//
// All component tensors must have the same dtype. Currently they must also have

};

// If `persistent_tape` is true, op_tape is not changed and none of the
// backwards functions are deleted.
// If `persistent_tape` is false, op_tape is cleared and backwards functions
// not needed for gradient computation are deleted. Backwards functions that
// are needed, are copied and returned in BackpropInitialState.
template <typename BackwardFunction, typename TapeTensor>

// called.
//
// Pass "library_filename" to a platform-specific mechanism for dynamically
// loading a library. The rules for determining the exact location of the
// library are platform-specific and are not documented here.
//
// On success, returns the newly created library handle and places OK in status.
// The caller owns the library handle.
//

/// that plugins provide (some are mandatory, some are optional, with or without
/// a default implementation).
///
/// Each plugin implements the operations that are supported and TensorFlow will
/// properly handle the cases when an operation is not supported (i.e., return
/// the corresponding `Status` value).
///
/// REQUIRED OPERATIONS: All required operations are marked as such, including

  // Following are helper functions to assist integrating TFRT with current
  // TF eager runtime.
  // TODO(b/172877902): These helper functions are currently used to support
  // PyFuncOp on TFRT, and might be useful for ops that directly use low
  // level TF APIs. Remove/replace the following functions when TFRT native
  // ops are implemented.

namespace gradients {
namespace internal {

// Helper functions which delegate to `AbstractOperation`, update
// the state of the ForwardOperation and call the tape as appropriate.
// These APIs are mainly to facilitate testing and are subject to change.

// Records the op name in the `ForwardOperation`.
Status Reset(AbstractOperation*, const char* op, const char* raw_device_name,
             ForwardOperation*);

/// 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
/// the names will lose the `Modular` part. Until that point, the `Modular*`
/// classes here are experimental and subject to breaking changes.
/// For documentation on these methods, consult `core/platform/filesystem.h`.

  // 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_;
};

// Implementation detail for the unified execution APIs for Eager and tracing
// backends (graph/MLIR).
//
// This defines a set of abstract classes that are intended to provide the
// functionality of the opaque C types exposed in the public APIs defined in the
// `c_api_unified_experimental.h` header.
// =============================================================================