From d330f4746289ea36e9c99412377d3a50e1dde2c1 Mon Sep 17 00:00:00 2001 From: Jamie Hardt Date: Wed, 3 Sep 2025 11:36:38 -0700 Subject: [PATCH] Added some logging code --- ucsinfer/__main__.py | 26 ++++++++++++++++---------- 1 file changed, 16 insertions(+), 10 deletions(-) diff --git a/ucsinfer/__main__.py b/ucsinfer/__main__.py index 9ef05b2..63b0959 100644 --- a/ucsinfer/__main__.py +++ b/ucsinfer/__main__.py @@ -1,6 +1,7 @@ import os import sys import csv +import logging from sentence_transformers import SentenceTransformer import tqdm @@ -13,12 +14,23 @@ from .util import ffmpeg_description, parse_ucs @click.group(epilog="For more information see " "") -# @click.option('--verbose', flag_value='verbose', help='Verbose output') -def ucsinfer(): +@click.option('--verbose', '-v', flag_value='verbose', help='Verbose output') +def ucsinfer(verbose): """ Tools for applying UCS categories to sounds using large-language Models """ - pass + + if verbose: + logging.basicConfig(format="%(levelname)s: %(message)s", + level=logging.DEBUG) + else: + import warnings + warnings.filterwarnings( + action='ignore', module='torch', category=FutureWarning, + message=r"`encoder_attention_mask` is deprecated.*") + + logging.basicConfig(format="%(levelname)s: %(message)s", + level=logging.WARN) @ucsinfer.command('recommend') @@ -44,7 +56,7 @@ def recommend(text, paths, model, interactive, skip_ucs): "Description" text metadata is extracted from audio files given as PATHS, or text can be provided directly using the "--text" option. The selected model is then used to attempt to classify the given text according to - the synonyms and explanations definied for each UCS subcategory. A list + the synonyms an explanations definied for each UCS subcategory. A list of ranked subcategories is printed to the terminal for each PATH. """ m = SentenceTransformer(model) @@ -246,10 +258,4 @@ def evaluate(dataset, offset, limit, model, no_foley): if __name__ == '__main__': os.environ['TOKENIZERS_PARALLELISM'] = 'false' - # sentence_transformers generates an error in PyTorch upon loading - import warnings - warnings.filterwarnings(action='ignore', module='torch', - category=FutureWarning, - message=r"`encoder_attention_mask` is deprecated.*") - ucsinfer()