code: def infer_dtype_from_object(dtype) -> type:
      """
      Get a numpy dtype.type-style object for a dtype object.
  
      This methods also includes handling of the datetime64[ns] and
      datetime64[ns, TZ] objects.
  
      If no dtype can be found, we return ``object``.
  
      Parameters
      ----------
      dtype : dtype, type
          The dtype object whose numpy dtype.type-style
          object we want to extract.
  
      Returns
      -------
      type
      """
      if isinstance(dtype, type) and issubclass(dtype, np.generic):
          # Type object from a dtype
  
          return dtype
      elif isinstance(dtype, (np.dtype, ExtensionDtype)):
          # dtype object
          try:
              _validate_date_like_dtype(dtype)
          except TypeError:
              # Should still pass if we don't have a date-like
              pass
          if hasattr(dtype, "numpy_dtype"):
              # TODO: Implement this properly
              # https://github.com/pandas-dev/pandas/issues/52576
              return dtype.numpy_dtype.type
          return dtype.type
  
      try:
          dtype = pandas_dtype(dtype)
      except TypeError:
          pass
  
      if isinstance(dtype, ExtensionDtype):
          return dtype.type
      elif isinstance(dtype, str):
          # TODO(jreback)
          # should deprecate these
          if dtype in ["datetimetz", "datetime64tz"]:
              return DatetimeTZDtype.type
          elif dtype in ["period"]:
              raise NotImplementedError
  
          if dtype in ["datetime", "timedelta"]:
              dtype += "64"
          try:
              return infer_dtype_from_object(getattr(np, dtype))
          except (AttributeError, TypeError):
              # Handles cases like _get_dtype(int) i.e.,
              # Python objects that are valid dtypes
              # (unlike user-defined types, in general)
              #
              # TypeError handles the float16 type code of 'e'
              # further handle internal types
              pass
  
      return infer_dtype_from_object(np.dtype(dtype))
  
imports: from __future__ import annotations
  from typing import TYPE_CHECKING, Any, Callable
  import warnings
  import numpy
  from pandas._libs import Interval, Period, algos, lib
  from pandas._libs.tslibs import conversion
  from pandas.util._exceptions import find_stack_level
  from pandas.core.dtypes.base import _registry
  from pandas.core.dtypes.dtypes import CategoricalDtype, DatetimeTZDtype, ExtensionDtype, IntervalDtype, PeriodDtype, SparseDtype
  from pandas.core.dtypes.generic import ABCIndex
  from pandas.core.dtypes.inference import is_array_like, is_bool, is_complex, is_dataclass, 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
label_desc: Use image node_id 37 for calling a global function with example usage: infer_dtype_from_object(dtype) and returns: infer_dtype_from_object, dtype, dtype, dtype, dtype, DatetimeTZDtype, infer_dtype_from_object