[Code-To-Text] Issues loading a re-trained model

[lapplislazuli]

Hello,

I run the model training as described in the repository and everything is working fine.
But once I try to do the inference with my newly trained model, i get the following error:

01/14/2021 11:32:57 - INFO - main -   Namespace(adam_epsilon=1e-08, beam_size=10, config_name='', dev_filename=None, do_eval=False, do_lower_case=False, do_test=True, do_train=False, eval_batch_size=32, eval_steps=-1, gradient_accumulation_steps=1, learning_rate=5e-05, load_model_path=None, local_rank=-1, max_grad_norm=1.0, max_source_length=256, max_steps=-1, max_target_length=128, model_name_or_path='/models/pytorch_model.bin', model_type='roberta', no_cuda=True, num_train_epochs=10, output_dir='/experiment/output', seed=42, test_filename='/dataset/test.jsonl', tokenizer_name='', train_batch_size=32, train_filename=None, train_steps=-1, warmup_steps=0, weight_decay=0.0)
01/14/2021 11:32:57 - WARNING - main -   Process rank: -1, device: cpu, n_gpu: 0, distributed training: False
Traceback (most recent call last):
  File "./run.py", line 518, in <module>
    main()
  File "./run.py", line 255, in main
    config = config_class.from_pretrained(args.config_name if args.config_name else args.model_name_or_path)
  File "/root/anaconda/envs/code-to-text/lib/python3.7/site-packages/transformers/configuration_utils.py", line 347, in from_pretrained
    config_dict, kwargs = cls.get_config_dict(pretrained_model_name_or_path, **kwargs)
  File "/root/anaconda/envs/code-to-text/lib/python3.7/site-packages/transformers/configuration_utils.py", line 391, in get_config_dict
    config_dict = cls._dict_from_json_file(resolved_config_file)
  File "/root/anaconda/envs/code-to-text/lib/python3.7/site-packages/transformers/configuration_utils.py", line 474, in _dict_from_json_file
    text = reader.read()
  File "/root/anaconda/envs/code-to-text/lib/python3.7/codecs.py", line 322, in decode
    (result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x80 in position 0: invalid start byte
ERROR conda.cli.main_run:execute(33): Subprocess for 'conda run ['python3.7', './run.py', '--do_test', '--model_type', 'roberta', '--model_name_or_path', '/models/pytorch_model.bin', '--test_filename', '/dataset/test.jsonl', '--output_dir', '/experiment/output', '--max_source_length', '256', '--no_cuda','--max_target_length', '128', '--beam_size', '10', '--train_batch_size', '32', '--eval_batch_size', '32', '--learning_rate', '5e-5', '--num_train_epochs', '10']' command failed.  (See above for error)

At the moment I am only trying to run the java-specific model.

Inferrence using the microsoft\codebert-base works fine.

I am using the following anaconda environment, maybe something is wrong there:

name: code-to-text
channels:
  - conda-forge
  - defaults
dependencies:
  - _r-xgboost-mutex=2.0=cpu_0
  - idna=2.10
  - pip=20.3
  - pycparser=2.20
  - pyopenssl=20.0.0
  - python_abi=3.7
  - requests=2.25.0
  - six=1.15.0
  - tqdm=4.51.0
  - wheel=0.35.1
  - pytorch=1.4.0
  - pip:
    - click==7.1.2
    - filelock==3.0.12
    - joblib==0.17.0
    - numpy==1.19.3
    - packaging==20.4
    - protobuf==3.14.0
    - pyparsing==2.4.7
    - regex==2020.11.13
    - sacremoses==0.0.43
    - sentencepiece==0.1.91
    - tokenizers==0.9.3
    - transformers==3.5.0
    - urllib3==1.26.2

I would appreciate if something is wrong there.
If you want, I can make a PR for the conda environment if it seems appropriate.

[guody5]

You also need to enter these command (including training command) in the inference:

lang=ruby #programming language
lr=5e-5
batch_size=32
beam_size=10
source_length=256
target_length=128
data_dir=../dataset
output_dir=model/$lang
train_file=$data_dir/$lang/train.jsonl
dev_file=$data_dir/$lang/valid.jsonl
epochs=10 
pretrained_model=microsoft/codebert-base #Roberta: roberta-base
batch_size=64
dev_file=$data_dir/$lang/valid.jsonl
test_file=$data_dir/$lang/test.jsonl
test_model=$output_dir/checkpoint-best-bleu/pytorch_model.bin #checkpoint for test

[lapplislazuli]

@guody5 thank your for your answer,
but if I run it with all parameters, I will have to do the training?

I want to run just inference, like in the Readme.
Training+Inference works, but just Inference for a trained model fails.

[guoday]

lang=ruby #programming language
lr=5e-5
batch_size=32
beam_size=10
source_length=256
target_length=128
data_dir=../dataset
output_dir=model/$lang
train_file=$data_dir/$lang/train.jsonl
dev_file=$data_dir/$lang/valid.jsonl
epochs=10 
pretrained_model=microsoft/codebert-base #Roberta: roberta-base
batch_size=64
dev_file=$data_dir/$lang/valid.jsonl
test_file=$data_dir/$lang/test.jsonl
test_model=$output_dir/checkpoint-best-bleu/pytorch_model.bin #checkpoint for test
python run.py --do_test --model_type roberta --model_name_or_path microsoft/codebert-base --load_model_path $test_model --dev_filename $dev_file --test_filename $test_file --output_dir $output_dir --max_source_length $source_length --max_target_length $target_length --beam_size $beam_size --eval_batch_size $batch_size

[guoday]

In your error logs:
model_name_or_path should be "microsoft/codebert-base" but get '/models/pytorch_model.bin'

[guoday]

According to your log, you should run the following command:

python run.py --do_test --model_type roberta --model_name_or_path microsoft/codebert-base --load_model_path /models/pytorch_model.bin --test_filename /dataset/test.jsonl --output_dir /experiment/output --max_source_length 256 --max_target_length 128 --beam_size 10 --eval_batch_size 32

[lapplislazuli]

@guoday Thank you very much!
Works like a charm. I did not read properly that pretrained model and load_model were seperate things.