[Bug]: Vall-e Inference- LlamaDecoderLayer.__init__() got an unexpected keyword argument 'layer_idx' w

[acul3]

error when loading vall-e inference

# put your cheackpoint file (.bin) in the root path of AmphionVALLEv2
# or use your own pretrained weights
ar_model_path = 'ckpts/valle_ar_mls_196000.bin'  # huggingface-cli download amphion/valle valle_ar_mls_196000.bin valle_nar_mls_164000.bin --local-dir ckpts
nar_model_path = 'ckpts/valle_nar_mls_164000.bin'
speechtokenizer_path = 'ckpts/speechtokenizer_hubert_avg'

from models.tts.valle_v2.valle_inference import ValleInference
# change to device='cuda' to use CUDA GPU for fast inference
# change "use_vocos" to True would give better sound quality
# If you meet problem with network, you could set "use_vocos=False", though would give bad quality
model = ValleInference(ar_path=ar_model_path, nar_path=nar_model_path, speechtokenizer_path=speechtokenizer_path, device="cpu")

lead error

[/content/Amphion/models/tts/valle_v2/valle_nar.py](https://localhost:8080/#) in __init__(self, config)
     42     def __init__(self, config: LlamaConfig):
     43         """Override to adaptive layer norm"""
---> 44         super().__init__(config=config, layer_idx=0)  # init attention, mlp, etc.
     45         self.input_layernorm = LlamaAdaptiveRMSNorm(
     46             config.hidden_size, eps=config.rms_norm_eps, dim_cond=config.hidden_size

TypeError: LlamaDecoderLayer.__init__() got an unexpected keyword argument 'layer_idx'

cc : @jiaqili3

[acul3]

Solved

update transformers to latest version do the trick