class_docstr: Config object that specifies quantization behavior for a given operator pattern.
  For a detailed example usage, see :class:`~torch.ao.quantization.backend_config.BackendConfig`.
class_docstr_tok: ["Config","object","that","specifies","quantization","behavior","for","a","given","operator","pattern",".","For","a","detailed","example","usage",",","see",":","class",":","`","~torch.ao.quantization.backend_config.BackendConfig","`","."]
docstr: Add a set of supported data types passed as arguments to quantize ops in the
  reference model spec.
code: def add_dtype_config(
      self, dtype_config: DTypeConfig
  ) -> BackendPatternConfig:
      """
      Add a set of supported data types passed as arguments to quantize ops in the
      reference model spec.
      """
      self.dtype_configs.append(dtype_config)
      return self
  
imports: from __future__ import annotations
  from dataclasses import dataclass
  from typing import Any, Callable, Dict, List, Optional, Type, Union
  import torch
  from torch.ao.quantization.utils import Pattern
  from enum import Enum
label_desc: Use image node_id 5 for calling the BackendPatternConfig obj's underlying member method code with example usage: obj.add_dtype_config(dtype_config) and returns: self