Update inference/mastering_transfer.py

inference/mastering_transfer.py

@@ -62,30 +62,6 @@ class Mastering_Style_Transfer_Inference:
         ddp = trained_w_ddp
         self.reload_weights(ckpt_paths, ddp=ddp)
 
-        # load data loader for the inference procedure
-        inference_dataset = Song_Dataset_Inference(args)
-        self.data_loader = DataLoader(inference_dataset, \
-                                        batch_size=1, \
-                                        shuffle=False, \
-                                        num_workers=args.workers, \
-                                        drop_last=False)
-
-        ''' check stem-wise result '''
-        if not self.args.do_not_separate:
-            os.environ['MKL_THREADING_LAYER'] = 'GNU'
-            separate_file_names = [args.input_file_name, args.reference_file_name]
-            if self.args.interpolation:
-                separate_file_names.append(args.reference_file_name_2interpolate)
-            for cur_idx, cur_inf_dir in enumerate(sorted(glob(f"{args.target_dir}*/"))):
-                for cur_file_name in separate_file_names:
-                    cur_sep_file_path = os.path.join(cur_inf_dir, cur_file_name+'.wav')
-                    cur_sep_output_dir = os.path.join(cur_inf_dir, args.stem_level_directory_name)
-                    if os.path.exists(os.path.join(cur_sep_output_dir, self.args.separation_model, cur_file_name, 'drums.wav')):
-                        print(f'\talready separated current file : {cur_sep_file_path}')
-                    else:
-                        cur_cmd_line = f"demucs {cur_sep_file_path} -n {self.args.separation_model} -d {self.device} -o {cur_sep_output_dir}"
-                        os.system(cur_cmd_line)
-
 
     # reload model weights from the target checkpoint path
     def reload_weights(self, ckpt_paths, ddp=True):