How to generate "predict_dev.jsonl"

[Chen-PengF]

when I run the file "main.py/main.sh", an error has occurred as follow:

[Chen-PengF]

File "Span-ASTE-main/aste/main.py", line 239, in eval
with open(path) as f:
FileNotFoundError: [Errno 2] No such file or directory: 'model_outputs/14lap_0/predict_dev.jsonl'

[chiayewken]

Hi, please use wrapper.py, I have updated the colab demo and demo.ipynb to the latest version

[Chen-PengF]

Hi, please use wrapper.py, I have updated the colab demo and demo.ipynb to the latest version
Hi, but I have run the setup.py before wrapper.py, and there is still an error as follows:

File "/home/miniconda3/envs/span/lib/python3.7/site-packages/allennlp/common/params.py", line 352, in pop_choice
raise ConfigurationError(message)
allennlp.common.checks.ConfigurationError: span_model not in acceptable choices for dataset_reader.type: ['conll2003', 'interleaving', 'sequence_tagging', 'sharded', 'babi', 'text_classification_json']. You should either use the --include-package flag to make sure the correct module is loaded, or use a fully qualified class name in your config file like {"model": "my_module.models.MyModel"} to have it imported automatically.

Is this a version of allennlp problem?

[chiayewken]

Hi, it may be an environment issue, can I check that you are using Python 3.7 and ran setup.sh based on the installation instructions?

Also, are you using the demo notebook, if not, can you provide the exact command and you ran?

[Chen-PengF]

Thank you for your help.
1、This is my Python environment: Python 3.7.13 (default, Mar 29 2022, 02:18:16) [GCC 7.5.0] :: Anaconda, Inc. on Linux
2、I ran: bash setup.sh and show the picture for you [](https://pan.baidu.com/s/1pS-lIg43Uj3NH2EYwHHGaQ?pwd=hsfv
提取码：hsfv)

[Chen-PengF]

3、I run "python wrapper.py" for file wrapper.py

[chiayewken]

For training instructions, you can use the model as shown in the demo notebook or command-line style here:

python aste/wrapper.py run_train_many \
--save_dir_template "outputs/14lap/seed_{}" \
--random_seeds [0,1,2,3,4] \
--path_train data/triplet_data/14lap/train.txt \
--path_dev data/triplet_data/14lap/dev.txt