// The preprocess-op Pass.
//
namespace mlir {
namespace quant {

namespace {

using QuantMethod =
    ::tensorflow::quantization::QuantizationMethod::PresetMethod;
using QuantizationUnit = std::pair<Operation*, int>;
using QuantizationUnits = llvm::SetVector<QuantizationUnit>;
using ::tensorflow::quantization::OpSet;

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_types.h"
#include "tensorflow/core/util/quantization/uniform_quant_ops_attr.pb.h"

namespace mlir::quant {

using QuantMethod = tensorflow::quantization::QuantizationMethod::PresetMethod;

enum class OpType {
  kDynamicRangeOp,  // Dynamic Range kernels only have rhs attr.
  kUnaryOp,         // Unary ops have one min/max attr.
  kBinaryOp,        // Binary ops have lhs/rhs attr.

// The prepare-quantize Pass.
//
namespace mlir {
namespace quant {

namespace {

using QuantMethod = tensorflow::quantization::QuantizationMethod::PresetMethod;

// Applies prepare quantization on the model in TF dialect. This pass runs
// before the quantization pass and propagate the quantization parameters

#include "tensorflow/core/ir/importexport/convert_tensor.h"

namespace mlir {
namespace quant {
namespace {

using QuantMethod = tensorflow::quantization::QuantizationMethod::PresetMethod;
using ::tensorflow::quantization::OpSet;

constexpr absl::string_view kQuantizeCompositeFunctionsStepName =
    "_quantize_composite_functions";
constexpr StringRef kQuantizeFuncName = "quantize_i8";