class_docstr: Moves keys from meta to data. It is useful when a dataset of paired samples
  is loaded and certain keys should be moved from meta to data.
  
  Args:
      keys: keys to be transferred from meta to data
      meta_key: the meta key where all the meta-data is stored
      allow_missing_keys: don't raise exception if key is missing
  
  Example:
      When the fastMRI dataset is loaded, "kspace" is stored in the data dictionary,
      but the ground-truth image with the key "reconstruction_rss" is stored in the meta data.
      In this case, ExtractDataKeyFromMetaKeyd moves "reconstruction_rss" to data.
docstr: Args:
      data: is a dictionary containing (key,value) pairs from the
          loaded dataset
  
  Returns:
      the new data dictionary
docstr_tok: ["Args",":","data",":","is","a","dictionary","containing","(","key",",","value",")","pairs","from","the","loaded","dataset","Returns",":","the","new","data","dictionary"]
code: def __call__(
      self, data: Mapping[Hashable, NdarrayOrTensor]
  ) -> dict[Hashable, Tensor]:
      """
      Args:
          data: is a dictionary containing (key,value) pairs from the
              loaded dataset
  
      Returns:
          the new data dictionary
      """
      d = dict(data)
      for key in self.keys:
          if key in d[self.meta_key]:
              d[key] = d[self.meta_key][key]  # type: ignore
          elif not self.allow_missing_keys:
              raise KeyError(
                  f"Key `{key}` of transform `{self.__class__.__name__}` was missing in the meta data"
                  " and allow_missing_keys==False."
              )
      return d
  
imports: from __future__ import annotations
  from collections.abc import Hashable, Mapping, Sequence
  import numpy
  from numpy import ndarray
  from torch import Tensor
  from monai.apps.reconstruction.transforms.array import EquispacedKspaceMask, RandomKspaceMask
  from monai.config import DtypeLike, KeysCollection
  from monai.config.type_definitions import NdarrayOrTensor
  from monai.transforms import InvertibleTransform
  from monai.transforms.croppad.array import SpatialCrop
  from monai.transforms.intensity.array import NormalizeIntensity
  from monai.transforms.transform import MapTransform, RandomizableTransform
  from monai.utils import FastMRIKeys
  from monai.utils.type_conversion import convert_to_tensor
label_desc: Use image node_id 2 for calling the ExtractDataKeyFromMetaKeyd obj's underlying member method code with example usage: obj.__call__(data) and returns: d