allennlp.interpret.saliency_interpreters¶
-
class
allennlp.interpret.saliency_interpreters.saliency_interpreter.SaliencyInterpreter(predictor: allennlp.predictors.predictor.Predictor)[source]¶ Bases:
allennlp.common.registrable.RegistrableA
SaliencyInterpreterinterprets an AllenNLP Predictor’s outputs by assigning a saliency score to each input token.-
saliency_interpret_from_json(self, inputs: Dict[str, Any]) → Dict[str, Any][source]¶ This function finds a modification to the input text that would change the model’s prediction in some desired manner (e.g., an adversarial attack).
- Parameters
- inputs
JsonDict The input you want to interpret (the same as the argument to a Predictor, e.g., predict_json()).
- inputs
- Returns
- interpretation
JsonDict Contains the normalized saliency values for each input token. The dict has entries for each instance in the inputs JsonDict, e.g.,
{instance_1: ..., instance_2:, ... }. Each one of those entries has entries for the saliency of the inputs, e.g.,{grad_input_1: ..., grad_input_2: ... }.
- interpretation
-
-
class
allennlp.interpret.saliency_interpreters.simple_gradient.SimpleGradient(predictor: allennlp.predictors.predictor.Predictor)[source]¶ Bases:
allennlp.interpret.saliency_interpreters.saliency_interpreter.SaliencyInterpreter
-
class
allennlp.interpret.saliency_interpreters.integrated_gradient.IntegratedGradient(predictor: allennlp.predictors.predictor.Predictor)[source]¶ Bases:
allennlp.interpret.saliency_interpreters.saliency_interpreter.SaliencyInterpreterInterprets the prediction using Integrated Gradients (https://arxiv.org/abs/1703.01365)
-
saliency_interpret_from_json(self, inputs: Dict[str, Any]) → Dict[str, Any][source]¶ This function finds a modification to the input text that would change the model’s prediction in some desired manner (e.g., an adversarial attack).
- Parameters
- inputs
JsonDict The input you want to interpret (the same as the argument to a Predictor, e.g., predict_json()).
- inputs
- Returns
- interpretation
JsonDict Contains the normalized saliency values for each input token. The dict has entries for each instance in the inputs JsonDict, e.g.,
{instance_1: ..., instance_2:, ... }. Each one of those entries has entries for the saliency of the inputs, e.g.,{grad_input_1: ..., grad_input_2: ... }.
- interpretation
-
-
class
allennlp.interpret.saliency_interpreters.smooth_gradient.SmoothGradient(predictor: allennlp.predictors.predictor.Predictor)[source]¶ Bases:
allennlp.interpret.saliency_interpreters.saliency_interpreter.SaliencyInterpreterInterprets the prediction using SmoothGrad (https://arxiv.org/abs/1706.03825)
-
saliency_interpret_from_json(self, inputs: Dict[str, Any]) → Dict[str, Any][source]¶ This function finds a modification to the input text that would change the model’s prediction in some desired manner (e.g., an adversarial attack).
- Parameters
- inputs
JsonDict The input you want to interpret (the same as the argument to a Predictor, e.g., predict_json()).
- inputs
- Returns
- interpretation
JsonDict Contains the normalized saliency values for each input token. The dict has entries for each instance in the inputs JsonDict, e.g.,
{instance_1: ..., instance_2:, ... }. Each one of those entries has entries for the saliency of the inputs, e.g.,{grad_input_1: ..., grad_input_2: ... }.
- interpretation
-