[fix] encoding

data_sampler.py

@@ -6,16 +6,13 @@ import random
 DEFAULT_ROOT_DIR = "examples/input_params"
 
 
-
 class DataSampler:
     def __init__(self, root_dir=DEFAULT_ROOT_DIR):
         self.root_dir = root_dir
-        
-        # glob
         self.input_params_files = list(Path(self.root_dir).glob("*.json"))
 
     def load_json(self, file_path):
-        with open(file_path, "r") as f:
+        with open(file_path, "r", encoding="utf-8") as f:
             return json.load(f)
 
     def sample(self):

models/lyrics_utils/zh_num2words.py

@@ -1166,7 +1166,7 @@ if __name__ == "__main__":
     )
 
     ndone = 0
-    with open(args.ifile, "r", encoding="utf8") as istream, open(args.ofile, "w+", encoding="utf8") as ostream:
+    with open(args.ifile, "r", encoding="utf-8") as istream, open(args.ofile, "w+", encoding="utf-8") as ostream:
         if args.format == "tsv":
             reader = csv.DictReader(istream, delimiter="\t")
             assert "TEXT" in reader.fieldnames

pipeline_ace_step.py

@@ -1172,7 +1172,7 @@ class ACEStepPipeline:
         for output_audio_path in output_paths:
             input_params_json_save_path = output_audio_path.replace(f".{format}", "_input_params.json")
             input_params_json["audio_path"] = output_audio_path
-            with open(input_params_json_save_path, "w") as f:
+            with open(input_params_json_save_path, "w", encoding="utf-8") as f:
                 json.dump(input_params_json, f, indent=4, ensure_ascii=False)
 
         return output_paths + [input_params_json]

trainer.py

@@ -74,7 +74,7 @@ class Pipeline(LightningModule):
                 from peft import LoraConfig
             except ImportError:
                 raise ImportError("Please install peft library to use LoRA training")
-            with open(lora_config_path) as f:
+            with open(lora_config_path, encoding="utf-8") as f:
                 lora_config = json.load(f)
             lora_config = LoraConfig(**lora_config)
             transformers.add_adapter(adapter_config=lora_config)
@@ -626,7 +626,7 @@ class Pipeline(LightningModule):
                 os.makedirs(save_dir, exist_ok=True)
             torchaudio.save(f"{save_dir}/target_wav_{key}_{i}.flac", target_wav.float().cpu(), sr)
             torchaudio.save(f"{save_dir}/pred_wav_{key}_{i}.flac", pred_wav.float().cpu(), sr)
-            with open(f"{save_dir}/key_prompt_lyric_{key}_{i}.txt", "w") as f:
+            with open(f"{save_dir}/key_prompt_lyric_{key}_{i}.txt", "w", encoding="utf-8") as f:
                 f.write(key_prompt_lyric)
             i += 1