builder.getFunctionType(input_types, return_types);

  std::string function_name = absl::StrCat("func_", subgraph.subgraph_id_);

  func::FuncOp new_func = func::FuncOp::create(builder.getUnknownLoc(),
                                               function_name, function_type);
  new_func.setVisibility(func::FuncOp::Visibility::Private);
  new_func.addEntryBlock();

                builder->getNamedAttr(key, conv_dimension_numbers_attr);
            attrs.push_back(named_attr);
          }
          break;
        }
        default: {
          emitWarning(builder->getUnknownLoc(),
                      "seralization not supported for : ")
              << key;
          break;
        }
      }
    }
    return attrs;
  }
};

  rewriter.setInsertionPointToStart(&new_func.getBody().front());

  auto one_val = DenseElementsAttr::get(type, kOne);
  auto one_cst =
      rewriter.create<stablehlo::ConstantOp>(rewriter.getUnknownLoc(), one_val);

  auto half_val = DenseElementsAttr::get(type, kHalf);
  auto half_cst =
      rewriter.create<stablehlo::ConstantOp>(one_cst.getLoc(), half_val);

}

quant::QuantParams DefaultQuantParamsPass::GetDefaultQuantParams(
    Builder builder) {
  if (!default_quant_params_) {
    default_quant_params_ = quantfork::fakeQuantAttrsToType(
        builder.getUnknownLoc(),
        /*numBits=*/8, default_min_, default_max_, /*narrowRange=*/false,
        builder.getF32Type(), is_signed_);
  }
  return default_quant_params_;
}

                                                 ElementsAttr axis_stats,
                                                 IntegerAttr axis) {
  auto stats_op = b.create<quantfork::StatisticsOp>(
      b.getUnknownLoc(), res, layer_stats, axis_stats, axis);
  res.replaceAllUsesWith(stats_op);
  stats_op.getOperation()->replaceUsesOfWith(stats_op, res);
}

void ImportQuantStatsPass::ImportAsStatsOps(OpBuilder b, Operation *op,

        builder_(context_.get()) {
    RegisterDialects(*context_);
    // TODO(aminim) figure out the location story here
    module_ = ModuleOp::create(builder_.getUnknownLoc());
    func_ = func::FuncOp::create(
        builder_.getUnknownLoc(), name,
        builder_.getFunctionType(std::nullopt, std::nullopt));
    module_->push_back(func_);
    builder_ = OpBuilder::atBlockBegin(func_.addEntryBlock());
  }

      GetOrCreateSessionInitializerOp(module_op);

  OpBuilder builder(module_op.getContext());
  builder.setInsertionPointAfter(session_init_op);

  const Location loc = builder.getUnknownLoc();
  const auto func_type = builder.getFunctionType(/*inputs=*/{}, /*results=*/{});

  auto init_func = builder.create<func::FuncOp>(
      loc, /*sym_name=*/"init_func_restore_op", func_type);

    }
    node_to_output_map[node_name].push_back(
        {output_count++, tensor_index, call_op_return});
  }

  Value scalar_one =
      CreateScalarConstValue<float>(builder, builder.getUnknownLoc(), 1.0);
  llvm::SmallVector<Value> returning_values(output_count, Value());
  for (const auto& node_name : node_to_output_map.keys()) {
    auto node_output_tensors = node_to_output_map[node_name];

void QuantizationDriver::QuantizeArg(BlockArgument arg,
                                     const QuantizedType quantized_type) {
  builder_.setInsertionPointToStart(arg.getOwner());
  QuantizeValue(arg, quantized_type, builder_.getUnknownLoc());
}

void QuantizationDriver::QuantizeValue(Value value,
                                       QuantizedType quantized_type,
                                       const Location loc) {

            output_zero_point_value);

    Value conv_output_value = op.getResult();
    auto output_uniform_quantized_tensor_type = RankedTensorType::getChecked(
        rewriter.getUnknownLoc(),
        /*shape=*/
        mlir::cast<TensorType>(conv_output_value.getType()).getShape(),
        output_uniform_quantized_type);

    SmallVector<Type> new_conv_output_types = {