class_docstr: Label-encoding of the target dimensions.
class_docstr_tok: ["Label-encoding","of","the","target","dimensions","."]
code: def transform(self, data: DataEntry) -> DataEntry:
      data[self.field_name] = np.arange(
          0, data[self.target_field].shape[0]
      )
      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 TargetDimIndicator obj's underlying member method code with example usage: obj.transform(data) and returns: data