code: def test_addition_of_int_and_uint_for_symmetric(activation_fn):
      model = nn.Sequential(
          OrderedDict(
              {
                  "previous_activation": nn.LeakyReLU(),
                  "res_block": ResidualBlock(activation_fn()),
              }
          )
      )
      data = torch.randn(1, 1, 28, 28)
  
      prepared_model, _ = quantize_model(model, data)
  
      # relu shares observer with input, so input is affine as well
      symmetric_acts = [
          prepared_model.activation_post_process_0,
          prepared_model.activation_post_process_1,
          prepared_model.activation_post_process_3,
      ]
      for act in symmetric_acts:
          assert act.qscheme == torch.per_tensor_symmetric
      # output of conv block is still affine
      assert (
          prepared_model.activation_post_process_2.qscheme
          == torch.per_tensor_affine
      )
  
imports: import operator
  from collections import OrderedDict
  from typing import List
  import pytest
  import torch
  import torch.ao.nn.quantized.reference
  import torch.ao.quantization
  import torch.nn
  import torch.nn.intrinsic
  import torch.nn.intrinsic.qat
  import torch.nn.qat
  import torch.nn.quantized
  from coremltools.optimize.torch.quantization import LinearQuantizer, LinearQuantizerConfig
  from coremltools.optimize.torch.quantization._backend_config import _mod_activations
  from coremltools.optimize.torch.quantization._qconfig_mapping import _QConfigMappingBuilder
  from coremltools.optimize.torch.quantization._utils import find_module, is_activation_post_process
  from coremltools.optimize.torch.quantization.modules import fused_modules
  from coremltools.optimize.torch.quantization.modules import qat_modules
  from coremltools.optimize.torch.quantization.modules import quantized_modules
  from coremltools.optimize.torch.quantization.quantization_config import QuantizationScheme
label_desc: Use image node_id 15 for calling a global function with example usage: test_addition_of_int_and_uint_for_symmetric(activation_fn) without return types