code: def pandas_dtype(dtype):
      """
      Converts input into a pandas only dtype object or a numpy dtype object.
  
      Parameters
      ----------
      dtype : object to be converted
  
      Returns
      -------
      np.dtype or a pandas dtype
  
      Raises
      ------
      TypeError if not a dtype
      """
      # short-circuit
      if isinstance(dtype, np.ndarray):
          return dtype.dtype
      elif isinstance(
          dtype, (np.dtype, PandasExtensionDtype, ExtensionDtype)
      ):
          return dtype
  
      # registered extension types
      result = registry.find(dtype)
      if result is not None:
          return result
  
      # try a numpy dtype
      # raise a consistent TypeError if failed
      try:
          npdtype = np.dtype(dtype)
      except Exception:
          # we don't want to force a repr of the non-string
          if not isinstance(dtype, string_types):
              raise TypeError("data type not understood")
          raise TypeError("data type '{}' not understood".format(dtype))
  
      # Any invalid dtype (such as pd.Timestamp) should raise an error.
      # np.dtype(invalid_type).kind = 0 for such objects. However, this will
      # also catch some valid dtypes such as object, np.object_ and 'object'
      # which we safeguard against by catching them earlier and returning
      # np.dtype(valid_dtype) before this condition is evaluated.
      if is_hashable(dtype) and dtype in [
          object,
          np.object_,
          "object",
          "O",
      ]:
          # check hashability to avoid errors/DeprecationWarning when we get
          # here and `dtype` is an array
          return npdtype
      elif npdtype.kind == "O":
          raise TypeError("dtype '{}' not understood".format(dtype))
  
      return npdtype
  
imports: import warnings
  import numpy
  from pandas._libs import algos, lib
  from pandas._libs.tslibs import conversion
  from pandas.compat import PY3, PY36, string_types
  from pandas.core.dtypes.dtypes import CategoricalDtype, DatetimeTZDtype, ExtensionDtype, IntervalDtype, PandasExtensionDtype, PeriodDtype, registry
  from pandas.core.dtypes.generic import ABCCategorical, ABCDateOffset, ABCDatetimeIndex, ABCIndexClass, ABCPeriodArray, ABCPeriodIndex, ABCSeries
  from pandas.core.dtypes.inference import is_array_like, is_bool, is_complex, is_decimal, is_dict_like, is_file_like, is_float, is_hashable, is_integer, is_interval, is_iterator, is_list_like, is_named_tuple, is_nested_list_like, is_number, is_re, is_re_compilable, is_scalar, is_sequence, is_string_like
label_desc: Use image node_id 51 for calling a global function with example usage: pandas_dtype(dtype) and returns: npdtype, dtype, result, npdtype, dtype