code: def _get_observer_dict(mod, target_dict, prefix=""):
      r"""Traverse the modules and save all observers into dict.
      This is mainly used for quantization accuracy debug
      Args:
          mod: the top module we want to save all observers
          prefix: the prefix for the current module
          target_dict: the dictionary used to save all the observers
      """
  
      def get_prefix(prefix):
          return prefix if prefix == "" else prefix + "."
  
      if hasattr(mod, "activation_post_process"):
          target_dict[
              get_prefix(prefix) + "activation_post_process"
          ] = mod.activation_post_process
      for name, child in mod.named_children():
          module_prefix = get_prefix(prefix) + name if prefix else name
          _get_observer_dict(child, target_dict, module_prefix)
  
imports: import copy
  import itertools
  import warnings
  import torch
  import torch.nn
  import torch.ao.nn.quantized
  from torch.ao.nn.intrinsic import _FusedModule
  from torch.ao.quantization.quantization_mappings import get_default_dynamic_quant_module_mappings, get_default_static_quant_module_mappings, get_default_static_quant_reference_module_mappings, get_default_qat_module_mappings, get_default_qconfig_propagation_list, no_observer_set, _has_special_act_post_process, _get_special_act_post_process
  from .utils import get_qparam_dict, has_no_children_ignoring_parametrizations
  from torch.ao.quantization.stubs import DeQuantStub, QuantWrapper
  from torch.ao.quantization.qconfig import _add_module_to_qconfig_obs_ctr, default_dynamic_qconfig, float16_dynamic_qconfig, float_qparams_weight_only_qconfig, float_qparams_weight_only_qconfig_4bit, _activation_is_memoryless
  from torch.nn.utils.parametrize import type_before_parametrizations
  from torch.ao.quantization.observer import _is_activation_post_process
  from torch.ao.quantization.observer import _is_activation_post_process
label_desc: Use image node_id 20 for calling a global function with example usage: _get_observer_dict(mod, target_dict, prefix) and returns: unknown