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Runtime error
| import gradio as gr | |
| import pandas as pd | |
| import tempfile | |
| import itertools | |
| import torch | |
| import numpy as np | |
| from numpy import dot | |
| from numpy.linalg import norm, multi_dot | |
| from transformers import AutoTokenizer, AutoModelForSequenceClassification, Trainer | |
| def get_score(sentence1): | |
| class SimpleDataset: | |
| def __init__(self, tokenized_texts): | |
| self.tokenized_texts = tokenized_texts | |
| def __len__(self): | |
| return len(self.tokenized_texts["input_ids"]) | |
| def __getitem__(self, idx): | |
| return {k: v[idx] for k, v in self.tokenized_texts.items()} | |
| model_name = "j-hartmann/emotion-english-distilroberta-base" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModelForSequenceClassification.from_pretrained(model_name) | |
| trainer = Trainer(model=model) | |
| lines_s = [sentence1] | |
| tokenized_texts = tokenizer(lines_s, truncation=True, padding=True) | |
| pred_dataset = SimpleDataset(tokenized_texts) | |
| predictions = trainer.predict(pred_dataset) | |
| preds = predictions.predictions.argmax(-1) | |
| labels = pd.Series(preds).map(model.config.id2label) | |
| scores = (np.exp(predictions[0])/np.exp(predictions[0]).sum(-1,keepdims=True)).max(1) | |
| temp = (np.exp(predictions[0])/np.exp(predictions[0]).sum(-1, keepdims=True)).tolist() | |
| stress = [] | |
| fear = [] | |
| joy = [] | |
| neutral = [] | |
| sadness = [] | |
| for i in range(len(lines_s)): | |
| stress.append(round(temp[i][0], 3)) | |
| fear.append(round(temp[i][2], 3)) | |
| joy.append(round(temp[i][3], 3)) | |
| neutral.append(round(temp[i][4], 3)) | |
| sadness.append(round(temp[i][5], 3)) | |
| df = pd.DataFrame(list(zip(lines_s, labels, stress, fear, joy, neutral, sadness)), | |
| columns=['text', 'maxLabel', 'stress', 'fear', 'joy', 'neutral', 'sadness']) | |
| return df | |
| gr.Interface(get_score,gr.inputs.Textbox(lines=1, placeholder="This tool is awesome!", default="", label="Text 1"),"dataframe", | |
| title="Patient Mental Health Sentiment Analysis",description="Input patient's verbal texts and the model returns the emotional state using this model: https://huggingface.co/j-hartmann/emotion-english-distilroberta-base.", layout="vertical").launch(debug=True) | |