class_docstr: Estimate MNE object sizes.
class_docstr_tok: ["Estimate","MNE","object","sizes","."]
docstr: Hash the object.
  
  Returns
  -------
  hash : int
      The hash
docstr_tok: ["Hash","the","object",".","Returns","--","--","--","-","hash",":","int","The","hash"]
code: def __hash__(self):
      """Hash the object.
  
      Returns
      -------
      hash : int
          The hash
      """
      from ..epochs import BaseEpochs
      from ..evoked import Evoked
      from ..io import BaseRaw
  
      if isinstance(self, Evoked):
          return object_hash(dict(info=self.info, data=self.data))
      elif isinstance(self, (BaseEpochs, BaseRaw)):
          _check_preload(self, "Hashing ")
          return object_hash(dict(info=self.info, data=self._data))
      else:
          raise RuntimeError(
              "Hashing unknown object type: %s" % type(self)
          )
  
imports: import json
  import logging
  from collections import OrderedDict
  from copy import deepcopy
  import numpy
  from ._logging import verbose, warn
  from .check import _check_pandas_installed, _check_preload, _validate_type
  from .numerics import _time_mask, object_hash, object_size
label_desc: Use image node_id 3 for calling the SizeMixin obj's underlying member method code with example usage: obj.__hash__() and returns: object_hash, object_hash