import logging import pymongo.errors from .log import install_general_log_handlers install_general_log_handlers() from .config import config from .database import mongo_client_from_config, reviews_collection, sample_reviews_polar, sample_reviews_varied from .analysis import NLTKSentimentAnalyzer, TensorflowCategorySentimentAnalyzer, TensorflowPolarSentimentAnalyzer from .analysis.base import TrainingFailedError from .tokenizer import PlainTokenizer, LowercaseTokenizer, NLTKWordTokenizer, PottsTokenizer, PottsTokenizerWithNegation from .gathering import Caches log = logging.getLogger(__name__) def main(): log.info("Started unimore-bda-6 in %s mode!", "DEBUG" if __debug__ else "PRODUCTION") log.debug("Validating configuration...") config.proxies.resolve() log.debug("Ensuring there are no leftover caches...") Caches.ensure_clean() with mongo_client_from_config() as db: try: db.admin.command("ping") except pymongo.errors.ServerSelectionTimeoutError: log.fatal("MongoDB database is not available, exiting...") exit(1) reviews = reviews_collection(db) for sample_func in [sample_reviews_varied, sample_reviews_polar]: slog = logging.getLogger(f"{__name__}.{sample_func.__name__}") slog.debug("Selected sample_func: %s", sample_func.__name__) for SentimentAnalyzer in [ TensorflowPolarSentimentAnalyzer, TensorflowCategorySentimentAnalyzer, NLTKSentimentAnalyzer, ]: slog = logging.getLogger(f"{__name__}.{sample_func.__name__}.{SentimentAnalyzer.__name__}") slog.debug("Selected SentimentAnalyzer: %s", SentimentAnalyzer.__name__) for Tokenizer in [ PlainTokenizer, LowercaseTokenizer, NLTKWordTokenizer, PottsTokenizer, PottsTokenizerWithNegation, ]: slog = logging.getLogger(f"{__name__}.{sample_func.__name__}.{SentimentAnalyzer.__name__}.{Tokenizer.__name__}") slog.debug("Selected Tokenizer: %s", Tokenizer.__name__) run_counter = 0 while True: slog = logging.getLogger(f"{__name__}.{sample_func.__name__}.{SentimentAnalyzer.__name__}.{Tokenizer.__name__}.{run_counter}") run_counter += 1 slog.debug("Run #%d", run_counter) try: slog.debug("Instantiating %s with %s...", SentimentAnalyzer.__name__, Tokenizer.__name__) sa = SentimentAnalyzer(tokenizer=Tokenizer()) except TypeError: slog.warning("%s is not supported by %s, skipping run...", SentimentAnalyzer.__name__, Tokenizer.__name__) break with Caches.from_database_samples(collection=reviews, sample_func=sample_func) as datasets: try: slog.info("Training sentiment analyzer: %s", sa) sa.train(training_dataset_func=datasets.training, validation_dataset_func=datasets.validation) except TrainingFailedError: slog.error("Training failed, trying again with a different dataset...") continue else: slog.info("Training succeeded!") slog.info("Evaluating sentiment analyzer: %s", sa) evaluation_results = sa.evaluate(evaluation_dataset_func=datasets.evaluation) slog.info("Evaluation results: %s", evaluation_results) break if __name__ == "__main__": main()