//
// 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 "tensorflow/cc/framework/ops.h"
#include "tensorflow/cc/framework/scope.h"

namespace tensorflow {
namespace ops {

/// GradFunc is the signature for all gradient functions in GradOpRegistry.
/// Implementations should add operations to compute the gradient outputs of
/// 'op' (returned in 'grad_outputs') using 'scope' and 'grad_inputs'.
typedef Status (*GradFunc)(const Scope& scope, const Operation& op,

  // running calibration.
  absl::StatusOr<ModuleOp> ImportCalibratedSavedModel(
      absl::string_view calibrated_saved_model_path);

  absl::Nonnull<MLIRContext*> ctx_;

  // Contains function implementations from the python layer. Should be injected
  // from the python level using pybind11.
  absl::Nonnull<const tensorflow::quantization::PyFunctionLibrary*>
      py_function_lib_;

  // Path to the pre-calibrated SavedModel.

  //
  // Unlike wcscasecmp(), this function can handle NULL argument(s).
  // A NULL C string is considered different to any non-NULL wide C string,
  // including the empty string.
  // NB: The implementations on different platforms slightly differ.
  // On windows, this method uses _wcsicmp which compares according to LC_CTYPE
  // environment variable. On GNU platform this method uses wcscasecmp

Type ShuffleRankedTensorType(Type type, ArrayRef<int64_t> permutation);

bool AreCancellablePermutations(DenseIntElementsAttr perm0,
                                DenseIntElementsAttr perm1);

// Default implementation of `LayoutSensitiveInterface::UpdateDataFormat` for
// layout sensitive operations that do not have any additional layout dependent
// attributes besides `data_format` string.
template <typename Op>

// setting functional attributes of other composite ops e.g. control flow.
typedef struct TF_AbstractFunction TF_AbstractFunction;

// This allows the client to swap the implementation of the tracing engine.
// Any future call to TF_CreateFunction will use the implementation defined
// here.
void TF_SetTracingImplementation(const char* name, TF_Status*);

// Creates a new TensorFlow function. A Function is an execution context, and as

// access the assets of the original model. `saved_model_tags` uniquely
// identifies the `MetaGraphDef`. `quantization_config` determines the behavior
// of StableHLO Quantizer. `quantization_py_function_lib` contains python
// implementations of certain APIs that are required for calibration.
// `module_op` is the input graph to be quantized and it should contain
// StableHLO ops.
//
// Returns a quantized `ModuleOp` in StableHLO, potentially wrapped inside a

//     non-static members of the current object.
//   - 'statement' cannot return a value.
//   - You cannot stream a failure message to this macro.
//
// Note that even though the implementations of the following two
// macros are much alike, we cannot refactor them to use a common
// helper macro, due to some peculiarity in how the preprocessor
// works.  The AcceptsMacroThatExpandsToUnprotectedComma test in

//     non-static members of the current object.
//   - 'statement' cannot return a value.
//   - You cannot stream a failure message to this macro.
//
// Note that even though the implementations of the following two
// macros are much alike, we cannot refactor them to use a common
// helper macro, due to some peculiarity in how the preprocessor
// works.  The AcceptsMacroThatExpandsToUnprotectedComma test in

#include "tensorflow/core/protobuf/meta_graph.pb.h"

namespace tensorflow::quantization {

// Declares pure virtual member functions for a python-side derived class to
// override. This allows calling python implementations from the C++ layer.
// Member functions should be pure not stateful; they should not access or rely
// on member fields.
class PyFunctionLibrary {
 public:
  virtual ~PyFunctionLibrary() = default;