// Sets `value` to the binary-serialized TensorShapeProto of the value of
// `attr_name` attribute of `oper`.
TF_CAPI_EXPORT extern void TF_OperationGetAttrTensorShapeProto(
    TF_Operation* oper, const char* attr_name, TF_Buffer* value,
    TF_Status* status);

// Fills in `values` with binary-serialized TensorShapeProto values of the

                                 const tensorflow::string& device_name,
                                 const tensorflow::string& variable_name);

TFE_Context* CreateContext(const std::string& serialized_server_def,
                           bool isolate_session_state,
                           int64_t init_timeout_in_ms);

tensorflow::ServerDef ReplaceTaskInServerDef(

                                       int* num_retvals, TF_Status* status);

// Add a function (serialized FunctionDef protocol buffer) to ctx so
// that it can be invoked using TFE_Execute.
TF_CAPI_EXPORT extern void TFE_ContextAddFunctionDef(
    TFE_Context* ctx, const char* serialized_function_def, size_t size,
    TF_Status* status);

// Adds a function (created from TF_GraphToFunction or

// Get a list of input OpInfo::TensorProperties given node name.
// Return the serialized list `properties`.
TF_CAPI_EXPORT extern void TF_GetInputPropertiesList(
    TF_GraphProperties* graph_properties, const char* name,
    TF_Buffer** properties, int num_values, TF_Status* status);

// Get a list of output OpInfo::TensorProperties given node name.
// Return the serialized list `properties`.
TF_CAPI_EXPORT extern void TF_GetOutputPropertiesList(

TF_CAPI_EXPORT extern void TFE_OpAttrsSerialize(const TFE_OpAttrs* attrs,
                                                TF_Buffer* buf,
                                                TF_Status* status);

// Set an op's attribute from a serialized AttrValue protocol buffer.
//
// Analogous to TF_SetAttrValueProto for building graph operations.
TF_CAPI_EXPORT extern void TFE_OpSetAttrValueProto(const TFE_Op* op,

#include "tensorflow/core/platform/refcount.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

class FunctionRecord;

// A traced function: this hides the complexity of converting the serialized
// representation between various supported formats e.g. FunctionDef and Mlir
// function.
class AbstractFunction : public core::RefCounted {
 protected:
  enum AbstractFunctionKind { kGraph, kMlir };

// Tensorflow's CPU implementation through constant folding.
TF_CAPI_EXPORT unsigned char TF_GetXlaConstantFoldingDisabled();
TF_CAPI_EXPORT void TF_SetXlaConstantFoldingDisabled(
    unsigned char should_enable);

// Create a serialized tensorflow.ConfigProto proto, where:
//
// a) ConfigProto.optimizer_options.global_jit_level is set to ON_1 if
// `enable_xla_compilation` is non-zero, and OFF otherwise.

  virtual Status AddDevices(std::vector<std::unique_ptr<Device>> devices) = 0;

  // Block until all pending nodes are finished.
  virtual Status AsyncWait() = 0;

  // Add a function (serialized FunctionDef protocol buffer) so that it can
  // be executed as an op. Return error if the function with the same name
  // already exists.
  virtual Status AddFunctionDef(const FunctionDef& fdef) = 0;