Source code for textattack.goal_function_results.classification_goal_function_result

"""

ClassificationGoalFunctionResult Class
========================================

"""

import torch

import textattack
from textattack.shared import utils

from .goal_function_result import GoalFunctionResult


[docs]class ClassificationGoalFunctionResult(GoalFunctionResult): """Represents the result of a classification goal function.""" def __init__( self, attacked_text, raw_output, output, goal_status, score, num_queries, ground_truth_output, ): super().__init__( attacked_text, raw_output, output, goal_status, score, num_queries, ground_truth_output, goal_function_result_type="Classification", ) @property def _processed_output(self): """Takes a model output (like `1`) and returns the class labeled output (like `positive`), if possible. Also returns the associated color. """ output_label = self.raw_output.argmax() if self.attacked_text.attack_attrs.get("label_names") is not None: output = self.attacked_text.attack_attrs["label_names"][self.output] output = textattack.shared.utils.process_label_name(output) color = textattack.shared.utils.color_from_output(output, output_label) return output, color else: color = textattack.shared.utils.color_from_label(output_label) return output_label, color
[docs] def get_text_color_input(self): """A string representing the color this result's changed portion should be if it represents the original input.""" _, color = self._processed_output return color
[docs] def get_text_color_perturbed(self): """A string representing the color this result's changed portion should be if it represents the perturbed input.""" _, color = self._processed_output return color
[docs] def get_colored_output(self, color_method=None): """Returns a string representation of this result's output, colored according to `color_method`.""" output_label = self.raw_output.argmax() confidence_score = self.raw_output[output_label] if isinstance(confidence_score, torch.Tensor): confidence_score = confidence_score.item() output, color = self._processed_output # concatenate with label and convert confidence score to percent, like '33%' output_str = f"{output} ({confidence_score:.0%})" return utils.color_text(output_str, color=color, method=color_method)