Update app.py

app.py

@@ -132,22 +132,6 @@ model = AutoModelForCausalLM.from_pretrained(
 model.to(device)
 model.eval()
 
-mmtokenizer = _MMSentencePieceTokenizer("./mm_tokenizer_v0.2_hf/tokenizer.model")
-
-basic_model_config='./xcodec_mini_infer/final_ckpt/config.yaml',
-resume_path='./xcodec_mini_infer/final_ckpt/ckpt_00360000.pth',
-config_path='./xcodec_mini_infer/decoders/config.yaml',
-vocal_decoder_path='./xcodec_mini_infer/decoders/decoder_131000.pth',
-inst_decoder_path='./xcodec_mini_infer/decoders/decoder_151000.pth',
-
-codectool = CodecManipulator("xcodec", 0, 1)
-model_config = OmegaConf.load(basic_model_config)
-codec_model = eval(model_config.generator.name)(**model_config.generator.config).to(device)
-parameter_dict = torch.load(resume_path, map_location='cpu')
-codec_model.load_state_dict(parameter_dict['codec_model'])
-codec_model.to(device)
-codec_model.eval()
-
 def generate_music(
     stage1_model="m-a-p/YuE-s1-7B-anneal-en-cot",
     max_new_tokens=3000,
@@ -178,6 +162,14 @@ def generate_music(
     stage1_output_dir = os.path.join(output_dir, f"stage1")
     os.makedirs(stage1_output_dir, exist_ok=True)
 
+    mmtokenizer = _MMSentencePieceTokenizer("./mm_tokenizer_v0.2_hf/tokenizer.model")
+    
+    basic_model_config='./xcodec_mini_infer/final_ckpt/config.yaml',
+    resume_path='./xcodec_mini_infer/final_ckpt/ckpt_00360000.pth',
+    config_path='./xcodec_mini_infer/decoders/config.yaml',
+    vocal_decoder_path='./xcodec_mini_infer/decoders/decoder_131000.pth',
+    inst_decoder_path='./xcodec_mini_infer/decoders/decoder_151000.pth',
+    
     class BlockTokenRangeProcessor(LogitsProcessor):
         def __init__(self, start_id, end_id):
             self.blocked_token_ids = list(range(start_id, end_id))