#define GEN_PASS_DEF_INSERTWEIGHTPARAMPASS
#include "tensorflow/compiler/mlir/quantization/stablehlo/passes/passes.h.inc"

namespace {

using ::stablehlo::quantization::Method;
using ::stablehlo::quantization::QuantizedType;
using ::stablehlo::quantization::WeightOnlyPtq;

// Inserts quantization parameters of weights for weight-only quantization and
// dynamic range quantization of `stablehlo.convolution` and
// `stablehlo.dot_general`.

#include "tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_utils.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/ops/uniform_op_quant_spec.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/quantization_options.pb.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_types.h"
#include "tensorflow/core/util/quantization/uniform_quant_ops_attr.pb.h"

namespace mlir::quant {

#include "tensorflow/compiler/mlir/quantization/stablehlo/quantization_config.pb.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/calibrator/calibration_statistics.pb.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/exported_model.pb.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/quantization_options.pb.h"
#include "tensorflow/core/framework/graph.pb.h"

#include "tensorflow/compiler/mlir/lite/quantization/ir/QuantOps.h"  // IWYU pragma: keep
#include "tensorflow/compiler/mlir/quantization/stablehlo/cc/config.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/cc/post_calibration.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/passes/testing/passes.h"  // IWYU pragma: keep
#include "tensorflow/compiler/mlir/quantization/stablehlo/quantization_config.pb.h"

  let results = (outs quant_RealOrStorageValueType);
  let hasFolder = 1;
}

// A QuantizeRegion (region) represents a quantization unit which wraps
// high-precision ops with quantization specifications for all the inputs
// and outputs. Some quantization specifications can be undetermined and
// derived from other ports by the target specification of the kernel.

==============================================================================*/

// This file provides a list of supported quantization algorithms in the format
// of "apply<Name of the Quantization Algorithm>Quantization".
// After applying the function, a quantize/dequantize functions are created
// where the body of each function contains a specific quantization algorithm.
// The input of the quantize function has one operand of

#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/quantization/stablehlo/quantization_config.pb.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/calibrator/calibration_statistics.pb.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/python/py_function_lib.h"

namespace stablehlo::quantization {

// Reads the calibration statistics from the given directory.

// The hlo->tf conversion is done in three steps; pre-quantization,
// quantization, and post-quantization. Quantization is optional, enabled only
// when `pass_config.enable_stablehlo_quantizer` is `true`. If quantization is
// not run, it only performs the hlo->tf conversion.
//
// All parameters except for `pass_config`, `pass_manager`, `status_handler`,
// and `module` are only required for quantization. See the comments of

#include "tensorflow/compiler/mlir/quantization/stablehlo/cc/calibration/component.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/cc/component.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/cc/context.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/cc/post_calibration.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/cc/pre_calibration.h"

// CHECK-NEXT:       buffer: 1,
// CHECK-NEXT:       name: "arg0",
// CHECK-NEXT:       quantization: {
// CHECK-EMPTY:
// CHECK-NEXT:       },
// CHECK-NEXT:       has_rank: true
// CHECK-NEXT:     }, {
// CHECK-NEXT:       shape: [ 1 ],
// CHECK-NEXT:       buffer: 2,
// CHECK-NEXT:       name: "arg1",
// CHECK-NEXT:       quantization: {
// CHECK-EMPTY:
// CHECK-NEXT:       },
// CHECK-NEXT:       has_rank: true