bda-6-steffo/unimore_bda_6/__main__.py

import logging
import tensorflow

from .config import config, DATA_SET_SIZE
from .database import mongo_reviews_collection_from_config, polar_dataset, varied_dataset
from .analysis.nltk_sentiment import NLTKSentimentAnalyzer
from .analysis.tf_text import TensorflowSentimentAnalyzer
from .tokenizer import NLTKWordTokenizer, PottsTokenizer, PottsTokenizerWithNegation, LowercaseTokenizer
from .log import install_log_handler

log = logging.getLogger(__name__)


def main():
    if len(tensorflow.config.list_physical_devices(device_type="GPU")) == 0:
        log.warning("Tensorflow reports no GPU acceleration available.")
    else:
        log.debug("Tensorflow successfully found GPU acceleration!")

    for dataset_func in [polar_dataset, varied_dataset]:
        for SentimentAnalyzer in [
            # NLTKSentimentAnalyzer,
            TensorflowSentimentAnalyzer,
        ]:
            for Tokenizer in [
                # NLTKWordTokenizer,
                # PottsTokenizer,
                # PottsTokenizerWithNegation,
                LowercaseTokenizer,
            ]:
                tokenizer = Tokenizer()
                model = SentimentAnalyzer(tokenizer=tokenizer)

                with mongo_reviews_collection_from_config() as reviews:
                    reviews_training = dataset_func(collection=reviews, amount=DATA_SET_SIZE.__wrapped__)
                    reviews_evaluation = dataset_func(collection=reviews, amount=DATA_SET_SIZE.__wrapped__)

                    log.info("Training model %s", model)
                    model.train(reviews_training)
                    log.info("Evaluating model %s", model)
                    correct, evaluated = model.evaluate(reviews_evaluation)
                    log.info("%d evaluated, %d correct, %0.2d %% accuracy", evaluated, correct, correct / evaluated * 100)

                # try:
                #     print("Manual testing for %s" % model)
                #     print("Input an empty string to continue to the next model.")
                #     while inp := input():
                #         print(model.use(inp))
                # except KeyboardInterrupt:
                #     pass


if __name__ == "__main__":
    install_log_handler()
    config.proxies.resolve()
    main()