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| from transformers_interpret import SequenceClassificationExplainer | |
| from captum.attr import visualization as viz | |
| class CustomExplainer(SequenceClassificationExplainer): | |
| def __init__(self, model, tokenizer): | |
| super().__init__(model, tokenizer) | |
| def visualize(self, html_filepath: str = None, true_class: str = None): | |
| """ | |
| Visualizes word attributions. If in a notebook table will be displayed inline. | |
| Otherwise pass a valid path to `html_filepath` and the visualization will be saved | |
| as a html file. | |
| If the true class is known for the text that can be passed to `true_class` | |
| """ | |
| tokens = [token.replace("Ġ", "") for token in self.decode(self.input_ids)] | |
| attr_class = self.id2label[self.selected_index] | |
| if self._single_node_output: | |
| if true_class is None: | |
| true_class = round(float(self.pred_probs)) | |
| predicted_class = round(float(self.pred_probs)) | |
| attr_class = round(float(self.pred_probs)) | |
| else: | |
| if true_class is None: | |
| true_class = self.selected_index | |
| predicted_class = self.predicted_class_name | |
| score_viz = self.attributions.visualize_attributions( # type: ignore | |
| self.pred_probs, | |
| predicted_class, | |
| true_class, | |
| attr_class, | |
| tokens, | |
| ) | |
| print(score_viz) | |
| html = viz.visualize_text([score_viz]) | |
| if html_filepath: | |
| if not html_filepath.endswith(".html"): | |
| html_filepath = html_filepath + ".html" | |
| with open(html_filepath, "w") as html_file: | |
| html_file.write("<meta charset='UTF-8'>" + html.data) | |
| return html | |
| def merge_attributions(self, token_level_attributions): | |
| final = [] | |
| scores = [] | |
| for i, elem in enumerate(token_level_attributions): | |
| token = elem[0] | |
| score = elem[1] | |
| if token.startswith("##"): | |
| final[-1] = final[-1] + token.replace("##", "") | |
| scores[-1] = scores[-1] + score | |
| else: | |
| final.append(token) | |
| scores.append(score) | |
| attr = [(final[i], scores[i]) for i in range(len(final))] | |
| return attr | |
| def visualize_wordwise(self, sentence: str, path: str, true_class: str): | |
| pred_class = self.predicted_class_name | |
| if pred_class == true_class: | |
| legend_sent = f"against {pred_class}" | |
| else: | |
| legend_sent = f"against {pred_class} and towards {true_class}" | |
| attribution_weights = self.merge_attributions(self(sentence)) | |
| min_weight = min([float(abs(w)) for _, w in attribution_weights]) | |
| max_weight = max([float(abs(w)) for _, w in attribution_weights]) | |
| attention_html = [] | |
| for word, weight in attribution_weights: | |
| hue = 5 if weight < 0 else 147 | |
| sat = "100%" if weight < 0 else "50%" | |
| # Logarithmic mapping to scale weight values | |
| scaled_weight = (min_weight + abs(weight)) / (max_weight - min_weight) | |
| # Adjust brightness and saturation for better contrast | |
| lightness = f"{100 - 50 * scaled_weight}%" | |
| color = f"hsl({hue},{sat},{lightness})" | |
| attention_html.append( | |
| f"<span class='word-box' style='background-color: {color};''>{word}</span><span> </span>") | |
| #attention_html = html.unescape("".join(attention_html)) | |
| final_html = f""" | |
| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <title>Attention Visualization</title> | |
| <style> | |
| span {{ | |
| font-family: sans-serif; | |
| font-size: 16px; | |
| }} | |
| </style> | |
| <style> | |
| /* Color legend */ | |
| .color-legend {{ | |
| display: inline-block; | |
| margin: 10px 0; | |
| padding: 10px 15px; | |
| border: 1px solid #ccc; | |
| border-radius: 5px; | |
| }} | |
| .word-box {{ | |
| display: inline-block; | |
| border-radius: 5px; | |
| padding: 0.2em; | |
| }} | |
| .color-legend span {{ | |
| display: inline-block; | |
| margin: 0 5px; | |
| }} | |
| .positive-weight {{ | |
| color: green; | |
| }} | |
| .negative-weight {{ | |
| color: red; | |
| }} | |
| .color-legend span:first-child {{ | |
| margin-left: 0; | |
| }} | |
| </style> | |
| <meta charset="utf-8" /> | |
| </head> | |
| <body> | |
| <div class="color-legend"> | |
| <p>PREDICTED LABEL: <b>{pred_class}</b><br>TRUE LABEL: <b>{true_class}</b></p> | |
| <p><span class='word-box' style='background-color: hsl(5,100%,50%)';>Disagreement</span> ({legend_sent})</p> | |
| <p><span class='word-box' style='background-color: hsl(147,50%,50%)';>Agreement</span> (towards {pred_class})</p> | |
| </div> | |
| <div>{attention_html}</div> | |
| </body> | |
| </html> | |
| """ | |
| with open(path, "w", encoding="utf-8") as f: | |
| f.write(final_html) | |