sentiment_inference.py

# -*- coding: utf-8 -*-
# file: sentiment_inference.py
# time: 2021/5/21 0021
# author: yangheng <hy345@exeter.ac.uk>
# github: https://github.com/yangheng95
# Copyright (C) 2021. All Rights Reserved.
# Usage: Evaluate on given text or inference dataset
import os

from pyabsa import APCCheckpointManager, ABSADatasetList, available_checkpoints

os.environ["PYTHONIOENCODING"] = "UTF8"

# checkpoint_map = available_checkpoints(from_local=True)

# examples = [
#     'The [ASP]battery-life[ASP], and this [ASP]battery[ASP] is ok',
#     'The [ASP] battery-life [ASP] is bad',
#     'The [ASP] battery-life [ASP] is good',
#     'The [ASP] battery-life [ASP] ',
#     'Strong build though which really adds to its [ASP]durability[ASP] .',  # !sent! Positive
#     'Strong [ASP]build[ASP] though which really adds to its durability . !sent! Positive',
#     'The [ASP]battery life[ASP] is excellent - 6-7 hours without charging . !sent! Positive',
#     'I have had my computer for 2 weeks already and it [ASP]works[ASP] perfectly . !sent! Positive',
#     'And I may be the only one but I am really liking [ASP]Windows 8[ASP] . !sent! Positive',
# ]
sent_classifier = APCCheckpointManager.get_sentiment_classifier(
    checkpoint="english",
    auto_device=True,  # Use CUDA if available
    offline=False,
    cal_perplexity=True,
)

# text = 'everything is always cooked to perfection , the [ASP]service[ASP] is excellent , the [ASP]decor[ASP] cool and understated . !sent! 1 1'
# sent_classifier.infer(text, print_result=True)

# inference_sets = examples
#
# for ex in examples:
#     result = sent_classifier.infer(ex, print_result=True)

inference_sets = ABSADatasetList.English
results = sent_classifier.batch_infer(
    target_file=inference_sets,
    print_result=True,
    save_result=True,
    ignore_error=False,
)
# print(results)