code: def _has_same_dtype(
      qspec_a: QuantizationSpecBase, qspec_b: QuantizationSpecBase
  ):
      return (
          hasattr(qspec_a, "dtype")
          and hasattr(qspec_b, "dtype")
          and qspec_a.dtype == qspec_b.dtype
      )
  
imports: import torch
  from torch._subclasses import FakeTensor
  from torch.ao.quantization.fx.prepare import _insert_obs_or_fq, _save_state, _is_activation_post_process_node, _create_obs_or_fq_from_qspec
  from torch.fx import GraphModule, Graph, Node
  from torch.fx.node import Argument
  from torch.ao.quantization import QConfigMapping
  from torch.ao.quantization.qconfig import QConfigAny
  from torch.ao.quantization.fx.custom_config import PrepareCustomConfig
  from typing import Dict, Tuple, Union, Any, Optional
  from torch.ao.quantization.quantizer import EdgeOrNode, SharedQuantizationSpec, QuantizationSpecBase
  from torch.ao.quantization import ObserverOrFakeQuantize
label_desc: Use image node_id 5 for calling a global function with example usage: _has_same_dtype(qspec_a, qspec_b) and returns: unknown