class_docstr: Model-provided salience interpreter.
class_docstr_tok: ["Model-provided","salience","interpreter","."]
code: def run(
      self,
      inputs: list[JsonDict],
      model: lit_model.Model,
      dataset: lit_dataset.Dataset,
      model_outputs: Optional[list[JsonDict]] = None,
      config: Optional[JsonDict] = None,
  ) -> Optional[list[JsonDict]]:
      del dataset
      del config
  
      fields = self.find_fields(model)
  
      # Run model, if needed.
      if model_outputs is None:
          model_outputs = list(model.predict(inputs))
      assert len(model_outputs) == len(inputs)
  
      return [
          self._run_single(ex, mo, fields, model)
          for ex, mo in zip(inputs, model_outputs)
      ]
  
file_path: lit/lit_nlp/components/model_salience.py
imports: from typing import Optional, Union
  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
label_desc: Use image node_id 4 for calling the ModelSalience obj's underlying member method code with example usage: obj.run(inputs, model, dataset, model_outputs, config) and returns: unknown