class_docstr: Converts the value of a field into a numpy array.
  
  Parameters
  ----------
  expected_ndim
      Expected number of dimensions. Throws an exception if the number of
      dimensions does not match.
  dtype
      numpy dtype to use.
class_docstr_tok: ["Converts","the","value","of","a","field","into","a","numpy","array",".","Parameters","--","--","--","--","--","expected_ndim","Expected","number","of","dimensions",".","Throws","an","exception","if","the","number","of","dimensions","does","not","match",".","dtype","numpy","dtype","to","use","."]
code: def transform(self, data: DataEntry) -> DataEntry:
      value = np.asarray(data[self.field], dtype=self.dtype)
  
      assert_data_error(
          value.ndim == self.expected_ndim,
          'Input for field "{self.field}" does not have the required'
          "dimension (field: {self.field}, ndim observed: {value.ndim}, "
          "expected ndim: {self.expected_ndim})",
          value=value,
          self=self,
      )
      data[self.field] = value
      return data
  
imports: from typing import Callable, Iterator, List, Optional, Tuple, Type
  import numpy
  from toolz import valmap
  from gluonts.core.component import validated, tensor_to_numpy
  from gluonts.dataset.common import DataEntry
  from gluonts.exceptions import assert_data_error
  from ._base import FlatMapTransformation, MapTransformation, SimpleTransformation
label_desc: Use image node_id 2 for calling the AsNumpyArray obj's underlying member method code with example usage: obj.transform(data) and returns: data