class_docstr: Implements lit.Model interface for testing.
  
  This class allows flexible input spec to allow different testing scenarios.
class_docstr_tok: ["Implements","lit.Model","interface","for","testing",".","This","class","allows","flexible","input","spec","to","allow","different","testing","scenarios","."]
docstr: Return 0.0 regression values for all examples.
  
  Args:
    inputs: input examples
    *args: unused
    **kw: unused
  
  Returns:
    predictions
docstr_tok: ["Return","0.0","regression","values","for","all","examples",".","Args",":","inputs",":","input","examples","*","args",":","unused","*","*","kw",":","unused","Returns",":","predictions"]
code: def predict(
      self, inputs: Iterable[JsonDict], *args, **kw
  ) -> Iterator[JsonDict]:
      """Return 0.0 regression values for all examples.
  
      Args:
        inputs: input examples
        *args: unused
        **kw: unused
  
      Returns:
        predictions
      """
      return map(lambda x: {"scores": 0.0}, inputs)
  
imports: from collections.abc import Iterable, Iterator
  from lit_nlp.api import model
  from lit_nlp.api import types
  import numpy
  import numpy.testing
label_desc: Use image node_id 5 for calling the RegressionModelForTesting obj's underlying member method code with example usage: obj.predict(inputs) and returns: map