class_docstr: Implements lit.Model interface for testing classification models.
  
  Returns the same output for every input.
class_docstr_tok: ["Implements","lit.Model","interface","for","testing","classification","models",".","Returns","the","same","output","for","every","input","."]
code: def output_spec(self):
      return {
          "probas": lit_types.MulticlassPreds(
              parent="label", vocab=["0", "1"], null_idx=0
          ),
          "input_embs": lit_types.TokenEmbeddings(align="tokens"),
          "input_embs_grad": lit_types.TokenGradients(
              align="tokens",
              grad_for="input_embs",
              grad_target_field_key="grad_class",
          ),
          "tokens": lit_types.Tokens(),
          "grad_class": lit_types.CategoryLabel(vocab=["0", "1"]),
      }
  
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 2 for calling the ClassificationModelForTesting obj's underlying member method code with example usage: obj.output_spec() and returns: dict