code: def transform(
      self, bundle: DataBundle, for_inference: bool
  ) -> DataBundle:
      if not isinstance(bundle.x_train, np.ndarray):
          raise ValueError(
              "`RecognizerBlock` should be used on numpy features"
          )
      target = [
          int(str_idx)
          for str_idx, column_type in self.feature_types.items()
          if column_type != ColumnTypes.REDUNDANT
      ]
      bundle.x_train = bundle.x_train[..., target]
      if bundle.x_valid is not None:
          if not isinstance(bundle.x_valid, np.ndarray):
              raise ValueError(
                  "`RecognizerBlock` should be used on numpy features"
              )
          bundle.x_valid = bundle.x_valid[..., target]
      return bundle
  
imports: import numpy
  from typing import Any
  from typing import Dict
  from typing import Tuple
  from typing import Optional
  from dataclasses import dataclass
  from cftool.misc import print_warning
  from .file import FileParserBlock
  from ....schema import DataTypes
  from ....schema import DataBundle
  from ....schema import ColumnTypes
  from ....schema import INoInitDataBlock
label_desc: Use image node_id 2 for calling the RecognizerBlock obj's underlying member method code with example usage: obj.transform(bundle, for_inference) and returns: bundle