// here. This is the default behavior if `pack` is null when passed to
  // TFE_RegisterCustomDevice.
  TFE_TensorHandle* (*pack)(TFE_Context* context, TFE_TensorHandle** handles,
                            int num_handles, TF_Status* s,
                            void* device_info) = nullptr;

  // Pins the op to `device` based on inputs to `op`. Returns true

    unsigned char enable);
TF_CAPI_EXPORT unsigned char TF_SetTfXlaCpuGlobalJit(unsigned char enable);

// Sets XLA's auto jit mode according to the specified string, which is parsed
// as if passed in XLA_FLAGS. This has global effect.
TF_CAPI_EXPORT void TF_SetXlaAutoJitMode(const char* mode);

// Returns whether the single GPU or general XLA auto jit optimizations are

  // a tensor with the result.
  virtual Gradient* AggregateGradients(
      gtl::ArraySlice<Gradient*> gradient_tensors) const = 0;

  // Calls the passed-in backward function.
  //
  // `unneeded_gradients` contains sorted list of input indices for which a
  // gradient is not required.
  virtual Status CallBackwardFunction(

// Disables tracing of RunMetadata on the ops executed from this context.
TF_CAPI_EXPORT extern void TFE_ContextDisableRunMetadata(TFE_Context* ctx);

// Populates the passed-in buffer with a serialized RunMetadata protocol buffer
// containing any run metadata information accumulated so far and clears this
// information.
// If async mode is enabled, this call blocks till all currently pending ops are

                                      std::unique_ptr<CustomDevice> device) = 0;

  // Return FunctionLibraryDefinition. Transformations need to use it to use it
  // to invoke MLIR compiler passes.
  virtual FunctionLibraryDefinition* FuncLibDef() = 0;

  // Resets the global rendezvous used for functions.
  virtual void ResetGlobalRendezvousForFunction() = 0;