FetchConstantMinMaxInputs<TF::FakeQuantWithMinMaxVarsPerChannelOp>>;

using PreparePerTensorFakeQuantWithMinMaxArgs = ConvertFakeQuantOpToQuantOps<
    TF::FakeQuantWithMinMaxArgsOp, /*PerAxis=*/false,
    FetchMinMaxAttrs<TF::FakeQuantWithMinMaxArgsOp>>;

// Removes the wrapper of the tf.FakeQuant* ops and creates the quant.qcast
// and quant.dcast pairs before tf.FakeQuant* ops are being foled.

using PreparePerTensorFakeQuantWithMinMaxArgs =
    InsertTFLQuantOpsAfterTFFakeQuantOp<
        TF::FakeQuantWithMinMaxArgsOp, /*PerAxis=*/false,
        FetchMinMaxAttrs<TF::FakeQuantWithMinMaxArgsOp>>;

// Removes the wrapper of the tf.FakeQuant* ops and creates the tfl.quantize
// and tfl.dequantize pairs before tf.FakeQuant* being foled.

#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops_a_m.h"

namespace mlir {
namespace TFL {

template <class TFFakeQuantOp>
struct FetchMinMaxAttrs {
  using AttrType = FloatAttr;
  bool operator()(TFFakeQuantOp tf_op, AttrType &min_value,
                  AttrType &max_value) const {
    min_value = tf_op.getMinAttr();
    max_value = tf_op.getMaxAttr();

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops_a_m.h"

namespace mlir {
namespace quant {

template <class TFFakeQuantOp>
struct FetchMinMaxAttrs {
  using AttrType = FloatAttr;
  bool operator()(TFFakeQuantOp tf_op, AttrType &min_value,
                  AttrType &max_value) const {
    min_value = tf_op.getMinAttr();
    max_value = tf_op.getMaxAttr();