class_docstr: Calculates and returns classification results, using thresholds.
class_docstr_tok: ["Calculates","and","returns","classification","results",",","using","thresholds","."]
code: def is_compatible(
      self, model: lit_model.Model, dataset: lit_dataset.Dataset
  ) -> bool:
      del dataset  # Unused during model classification
      return lit_utils.spec_contains(
          model.output_spec(), types.MulticlassPreds
      )
  
file_path: lit/lit_nlp/components/classification_results.py
imports: from collections.abc import Sequence
  import numbers
  from typing import cast, Optional
  from lit_nlp.api import components
  from lit_nlp.api import dataset
  from lit_nlp.api import dtypes
  from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.lib import utils
  import numpy
label_desc: Use image node_id 2 for calling the ClassificationInterpreter obj's underlying member method code with example usage: obj.is_compatible(model, dataset) and returns: lit_utils