docstr: Convert a string representation or a numpy dtype to NumericDtype.
docstr_tok: ["Convert","a","string","representation","or","a","numpy","dtype","to","NumericDtype","."]
code: def _standardize_dtype(
      cls, dtype: NumericDtype | str | np.dtype
  ) -> NumericDtype:
      """
      Convert a string representation or a numpy dtype to NumericDtype.
      """
      if isinstance(dtype, str) and (
          dtype.startswith(("Int", "UInt", "Float"))
      ):
          # Avoid DeprecationWarning from NumPy about np.dtype("Int64")
          # https://github.com/numpy/numpy/pull/7476
          dtype = dtype.lower()
  
      if not isinstance(dtype, NumericDtype):
          mapping = cls._get_dtype_mapping()
          try:
              dtype = mapping[np.dtype(dtype)]
          except KeyError as err:
              raise ValueError(
                  f"invalid dtype specified {dtype}"
              ) from err
      return dtype
  
imports: from __future__ import annotations
  import numbers
  from typing import TYPE_CHECKING, Any, Callable
  import numpy
  from pandas._libs import lib, missing
  from pandas.errors import AbstractMethodError
  from pandas.util._decorators import cache_readonly
  from pandas.core.dtypes.common import is_integer_dtype, is_string_dtype, pandas_dtype
  from pandas.core.arrays.masked import BaseMaskedArray, BaseMaskedDtype
label_desc: Use image node_id 7 for calling the NumericDtype obj's underlying member method code with example usage: obj._standardize_dtype(cls, dtype) and returns: dtype