# Copyright (c) 2023 Amphion. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import argparse import os import torch from models.vocoders.vocoder_inference import VocoderInference from utils.util import load_config def build_inference(args, cfg, infer_type="infer_from_dataset"): supported_inference = { "GANVocoder": VocoderInference, } inference_class = supported_inference[cfg.model_type] return inference_class(args, cfg, infer_type) def cuda_relevant(deterministic=False): torch.cuda.empty_cache() # TF32 on Ampere and above torch.backends.cuda.matmul.allow_tf32 = True torch.backends.cudnn.enabled = True torch.backends.cudnn.allow_tf32 = True # Deterministic torch.backends.cudnn.deterministic = deterministic torch.backends.cudnn.benchmark = not deterministic torch.use_deterministic_algorithms(deterministic) def build_parser(): r"""Build argument parser for inference.py. Anything else should be put in an extra config YAML file. """ parser = argparse.ArgumentParser() parser.add_argument( "--config", type=str, required=True, help="JSON/YAML file for configurations.", ) parser.add_argument( "--infer_mode", type=str, required=None, ) parser.add_argument( "--infer_datasets", nargs="+", default=None, ) parser.add_argument( "--feature_folder", type=str, default=None, ) parser.add_argument( "--audio_folder", type=str, default=None, ) parser.add_argument( "--vocoder_dir", type=str, required=True, help="Vocoder checkpoint directory. Searching behavior is the same as " "the acoustics one.", ) parser.add_argument( "--output_dir", type=str, default="result", help="Output directory. Default: ./result", ) parser.add_argument( "--log_level", type=str, default="warning", help="Logging level. Default: warning", ) parser.add_argument( "--keep_cache", action="store_true", default=False, help="Keep cache files. Only applicable to inference from files.", ) return parser def main(): # Parse arguments args = build_parser().parse_args() # Parse config cfg = load_config(args.config) # CUDA settings cuda_relevant() # Build inference trainer = build_inference(args, cfg, args.infer_mode) # Run inference trainer.inference() if __name__ == "__main__": main()