[Bug] 测试模型时报错：object has no attribute 'json_log_path'

[zhangpeihao]

Checklist before your report.

• I have verified that the issue exists against the master branch of AdaSeq.
• I have read the relevant section in the contribution guide on reporting bugs.
• I have checked the issues list for similar or identical bug reports.
• I have checked the pull requests list for existing proposed fixes.
• I have checked the commit log to find out if the bug was already fixed in the master branch.

What happened?

运行测试模型代码保存：
object has no attribute 'json_log_path'

Python traceback

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发生异常: AttributeError
'AdaSeqTextLoggerHook' object has no attribute 'json_log_path'
  File "/codes/hg/raner-trainer/AdaSeq/adaseq/training/hooks/text_logger_hook.py", line 81, in _dump_log
    with open(self.json_log_path, 'a+') as f:
  File "/codes/hg/raner-trainer/AdaSeq/adaseq/training/default_trainer.py", line 142, in dump_log
    self._file_logger._dump_log(log_dict)
  File "/codes/hg/raner-trainer/AdaSeq/adaseq/training/default_trainer.py", line 164, in test
    self.dump_log(log_dict)
  File "/codes/hg/raner-trainer/AdaSeq/adaseq/commands/test.py", line 93, in test_model
    trainer.test(checkpoint_path)
  File "/codes/hg/raner-trainer/test.py", line 17, in main
    test_model(args.work_dir, args.device, args.checkpoint_path)
  File "/codes/hg/raner-trainer/test.py", line 28, in <module>

Operating system

Linux B760M-H-DDR4 6.8.0-44-generic #44-Ubuntu SMP PREEMPT_DYNAMIC Tue Aug 13 13:35:26 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux

Python version

3.8.20

Output of pip freeze

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addict==2.4.0
aiohappyeyeballs==2.4.4
aiohttp==3.10.11
aiosignal==1.3.1
aliyun-python-sdk-core==2.16.0
aliyun-python-sdk-kms==2.16.5
async-timeout==5.0.1
attrs==25.1.0
certifi==2025.1.31
cffi==1.17.1
charset-normalizer==3.4.1
crcmod==1.7
cryptography==44.0.0
datasets==3.1.0
dill==0.3.6
einops==0.8.0
filelock==3.16.1
frozenlist==1.5.0
fsspec==2024.9.0
gast==0.6.0
huggingface-hub==0.28.1
idna==3.10
Jinja2==3.1.5
jmespath==0.10.0
joblib==1.4.2
MarkupSafe==2.1.5
modelscope==1.22.3
mpmath==1.3.0
multidict==6.1.0
multiprocess==0.70.14
networkx==3.1
numpy==1.24.4
nvidia-cublas-cu12==12.1.3.1
nvidia-cuda-cupti-cu12==12.1.105
nvidia-cuda-nvrtc-cu12==12.1.105
nvidia-cuda-runtime-cu12==12.1.105
nvidia-cudnn-cu12==9.1.0.70
nvidia-cufft-cu12==11.0.2.54
nvidia-curand-cu12==10.3.2.106
nvidia-cusolver-cu12==11.4.5.107
nvidia-cusparse-cu12==12.1.0.106
nvidia-nccl-cu12==2.20.5
nvidia-nvjitlink-cu12==12.8.61
nvidia-nvtx-cu12==12.1.105
oss2==2.19.1
packaging==24.2
pandas==2.0.3
pillow==10.4.0
platformdirs==4.3.6
propcache==0.2.0
pyarrow==17.0.0
pycparser==2.22
pycryptodome==3.21.0
python-dateutil==2.9.0.post0
pytz==2025.1
PyYAML==6.0.2
regex==2024.11.6
requests==2.32.3
responses==0.18.0
safetensors==0.5.2
scikit-learn==1.3.2
scipy==1.10.1
seqeval==1.2.2
simplejson==3.19.3
six==1.17.0
sortedcontainers==2.4.0
sympy==1.13.3
threadpoolctl==3.5.0
tokenizers==0.20.3
tomli==2.2.1
torch==2.4.1
tqdm==4.67.1
transformers==4.46.3
triton==3.0.0
typing_extensions==4.12.2
tzdata==2025.1
urllib3==2.2.3
xxhash==3.5.0
yapf==0.43.0
yarl==1.15.2

How to reproduce

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python train.py -c ./dataset/address-ner-ccks-2021.yaml
python test.py -w experiments/address-ner-ccks-2021/250209105418.521539

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