import os

class Config:
    model_path = "models/mastering_converter.pt"
    encoder_path = "models/effects_encoder.pt"
    sample_rate = 44100
    path_to_config = "networks/configs.yaml"
    
    # Add more configurations as needed
    inference_only = True
    evaluate_only = False
    reload_enc = True
    reload_converter = True
    manual_reload_enc = False
    manual_reload_converter = False
    manual_reload_name_converter = "dasp_tcn_tuneenc_daspman_loudnessnorm"
    manual_reload_name_encoder = "dasp_tcn_tuneenc_daspman_loudnessnorm"
    manual_reload_enc_path = "models/effects_encoder.pt"
    reload_epoch_converter = 1000
    reload_epoch_enc = 1000
    
    # Add other configurations from the main.py file
    random_seed = 111
    train_ito = True
    max_iter_ito = 101
    ito_type = "blackbox"
    
    # You can add more configurations as needed

config = Config()