quant_spec.set_tensor_type(QuantizationComponentSpec::TENSORTYPE_INT_8);

  std::optional<TF::PartitionedCallOp> dequantize_op = ApplyUniformQuantization(
      pattern_rewriter, cast<TF::ConstOp>(value.getDefiningOp()), quant_spec);
  EXPECT_TRUE(dequantize_op.has_value());
  EXPECT_EQ(dequantize_op.value().func().getName().str(),
            "composite_dequantize_uniform");
}

}  // namespace

                                     ShapedType result_type,
                                     StringRef func_name,
                                     Value& func_input_arg) {
  Operation* input_op = input_val.getDefiningOp();

  Operation* insertion_point = input_op->getParentOfType<func::FuncOp>();
  if (!insertion_point) insertion_point = input_op->getParentOfType<ModuleOp>();
  rewriter.setInsertionPointAfter(insertion_point);

    getUsedValuesDefinedAbove(op.getRegions(), live_ins);
    // Inserts if any of the `live_ins` depends on the ops in the cluster.
    if (llvm::any_of(live_ins, [&](Value value) {
          Operation* defining_op = value.getDefiningOp();
          if (!defining_op) {
            return false;
          }
          return c.ops.contains(defining_op) ||
                 ops_depend_on_cluster.contains(defining_op);
        })) {

        add_op != nullptr &&
        !isa<stablehlo::ConstantOp>(add_op->getOperand(1).getDefiningOp())) {
      LLVM_DEBUG(llvm::dbgs() << "Expected a `stablehlo.constant` as the "
                              << "rhs of `stablehlo.add`.\n");
    }

    // Make sure the filter is a constant or a constant transpose.
    Operation* filter_op = filter.getDefiningOp();
    const bool is_constant = isa_and_nonnull<stablehlo::ConstantOp>(filter_op);

      // The input of the quantize op has already been quantized, i.e.
      // rescale.
      return failure();
    }

    Operation* operand_op = operand.getDefiningOp();
    if (operand_op == nullptr) {
      // When `QuantizeOpT`'s operand does not have a defining op, it means it
      // is a `BlockArgument`. The pattern does not match if there is no op to
      // quantize.

  auto new_value = converter.materializeArgumentConversion(
      rewriter, result.getLoc(), type, {result});
  rewriter.replaceAllUsesExcept(result, new_value, new_value.getDefiningOp());
}

// Wrap operands in an an unrealized cast to create a cast to buffer any type
// changes to the operand, and apply type converter to operands:
//   V0 = op(operand)
//   ==>

  // This value isn't an expressed type (float), skip.
  if (!new_type) return;

  Block &block = value.getParentRegion()->front();
  Operation *op = value.getDefiningOp();
  if (op) {
    builder.setInsertionPoint(&block, ++Block::iterator(op));
  } else {
    builder.setInsertionPointToStart(&block);
  }
  TypeAttr type_attr = TypeAttr::get(new_type);

    }
  }

  erase_list.push_back(op);

  for (auto& use : op->getOpOperands()) {
    if (auto op_result = mlir::dyn_cast<mlir::OpResult>(use.get())) {
      Operation* def = op_result.getDefiningOp();
      if (!dead_ops.insert(def).second) continue;
      RecursiveRemove(def, erase_list, dead_ops);
    }
  }
}

void RemoveVariables(llvm::ArrayRef<VarHandleOp> vars) {

          assert(user->use_empty());
          user->erase();
        }
      }
    }

    for (auto operand : cluster.getOperands()) {
      mlir::Operation* def = operand.getDefiningOp();
      if (operand.hasOneUse() &&
          llvm::isa_and_nonnull<mlir::TF::TPUPartitionedInputV2Op>(def)) {
        operand.dropAllUses();
        def->erase();
      }
    }

      return;
    }

    // Invariant:
    // isa<quantfork::QuantizeCastOp>(dq_arg.getDefiningOp()) -->
    // getdq_arg.getType() != q_op.getResult().getType()
    //
    // as otherwise qdq pair would have been optimized away.
    auto qd_arg_def_q_op =
        dyn_cast_or_null<quantfork::QuantizeCastOp>(dq_arg.getDefiningOp());
    if (!qd_arg_def_q_op) {
      return;
    }

    qd_arg_def_q_op.emitWarning()