examples/nx_denoise/step_3_evaluation.py

#!/usr/bin/python3
# -*- coding: utf-8 -*-
import argparse
import logging
import os
from pathlib import Path
import sys
import uuid

pwd = os.path.abspath(os.path.dirname(__file__))
sys.path.append(os.path.join(pwd, "../../"))

import librosa
import numpy as np
import pandas as pd
from scipy.io import wavfile
import torch
import torch.nn as nn
import torchaudio
from tqdm import tqdm


def get_args():
    parser = argparse.ArgumentParser()
    parser.add_argument("--valid_dataset", default="valid.xlsx", type=str)
    parser.add_argument("--model_dir", default="serialization_dir/best", type=str)
    parser.add_argument("--evaluation_audio_dir", default="evaluation_audio_dir", type=str)

    parser.add_argument("--limit", default=10, type=int)

    args = parser.parse_args()
    return args


def logging_config():
    fmt = "%(asctime)s - %(name)s - %(levelname)s  %(filename)s:%(lineno)d >  %(message)s"

    logging.basicConfig(format=fmt,
                        datefmt="%m/%d/%Y %H:%M:%S",
                        level=logging.INFO)
    stream_handler = logging.StreamHandler()
    stream_handler.setLevel(logging.INFO)
    stream_handler.setFormatter(logging.Formatter(fmt))

    logger = logging.getLogger(__name__)

    return logger


def main():
    return


if __name__ == '__main__':
    main()