Repository: open-compass/opencompass
Issue: [Bug] SuperGLUE_BoolQ_ppl Unable to load file
Root cause: Configuration Error

### Prerequisite

- [X] I have searched [Issues](https://github.com/open-compass/opencompass/issues/) and [Discussions](https://github.com/open-compass/opencompass/discussions) but cannot get the expected help.
- [X] The bug has not been fixed in the [latest version](https://github.com/open-compass/opencompass).

### Type

I'm evaluating with the officially supported tasks/models/datasets.

### Environment

```
{'CUDA available': True,
 'CUDA_HOME': '/usr/local/cuda',
 'GCC': 'gcc (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0',
 'GPU 0,1,2,3,4,5,6,7': 'NVIDIA A800-SXM4-80GB',
 'MMEngine': '0.10.5',
 'MUSA available': False,
 'NVCC': 'Cuda compilation tools, release 11.7, V11.7.64',
 'OpenCV': '4.10.0',
 'PyTorch': '2.5.1+cu124',
 'PyTorch compiling details': 'PyTorch built with:\n'
                              '  - GCC 9.3\n'
                              '  - C++ Version: 201703\n'
                              '  - Intel(R) oneAPI Math Kernel Library Version '
                              '2024.2-Product Build 20240605 for Intel(R) 64 '
                              'architecture applications\n'
                              '  - Intel(R) MKL-DNN v3.5.3 (Git Hash '
                              '66f0cb9eb66affd2da3bf5f8d897376f04aae6af)\n'
                              '  - OpenMP 201511 (a.k.a. OpenMP 4.5)\n'
                              '  - LAPACK is enabled (usually provided by '
                              'MKL)\n'
                              '  - NNPACK is enabled\n'
                              '  - CPU capability usage: AVX512\n'
                              '  - CUDA Runtime 12.4\n'
                              '  - NVCC architecture flags: '
                              '-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90\n'
                              '  - CuDNN 90.1\n'
                              '  - Magma 2.6.1\n'
                              '  - Build settings: BLAS_INFO=mkl, '
                              'BUILD_TYPE=Release, CUDA_VERSION=12.4, '
                              'CUDNN_VERSION=9.1.0, '
                              'CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, '
                              'CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 '
                              '-fabi-version=11 -fvisibility-inlines-hidden '
                              '-DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO '
                              '-DLIBKINETO_NOROCTRACER -DLIBKINETO_NOXPUPTI=ON '
                              '-DUSE_FBGEMM -DUSE_PYTORCH_QNNPACK '
                              '-DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE '
                              '-O2 -fPIC -Wall -Wextra -Werror=return-type '
                              '-Werror=non-virtual-dtor -Werror=bool-operation '
                              '-Wnarrowing -Wno-missing-field-initializers '
                              '-Wno-type-limits -Wno-array-bounds '
                              '-Wno-unknown-pragmas -Wno-unused-parameter '
                              '-Wno-strict-overflow -Wno-strict-aliasing '
                              '-Wno-stringop-overflow -Wsuggest-override '
                              '-Wno-psabi -Wno-error=old-style-cast '
                              '-Wno-missing-braces -fdiagnostics-color=always '
                              '-faligned-new -Wno-unused-but-set-variable '
                              '-Wno-maybe-uninitialized -fno-math-errno '
                              '-fno-trapping-math -Werror=format '
                              '-Wno-stringop-overflow, LAPACK_INFO=mkl, '
                              'PERF_WITH_AVX=1, PERF_WITH_AVX2=1, '
                              'TORCH_VERSION=2.5.1, USE_CUDA=ON, USE_CUDNN=ON, '
                              'USE_CUSPARSELT=1, USE_EXCEPTION_PTR=1, '
                              'USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, '
                              'USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, '
                              'USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, '
                              'USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, \n',
 'Python': '3.10.16 (main, Dec 11 2024, 16:24:50) [GCC 11.2.0]',
 'TorchVision': '0.20.1+cu124',
 'lmdeploy': "not installed:No module named 'lmdeploy'",
 'numpy_random_seed': 2147483648,
 'opencompass': '0.3.9+f322043',
 'sys.platform': 'linux',
 'transformers': '4.47.1'}
```

### Reproduces the problem - code/configuration sample

```opencompass --models hf_internlm2_5_1_8b_chat --datasets SuperGLUE_BoolQ_ppl```

### Reproduces the problem - command or script

See above script

### Reproduces the problem - error message

resolve_pattern(
  File "/xxx/anaconda3/envs/opencompass/lib/python3.10/site-packages/datasets/data_files.py", line 411, in resolve_pattern
    raise FileNotFoundError(error_msg)
FileNotFoundError: Unable to find 'xxx/opencompass/opencompass/boolq'

### Other information

_No response_

Hi, any updates? I encouter the same problem! Thanks.

Is any update?

Thanks.

Hello,

any update for now?

Thanks.

Thanks for following up. Unfortunately, the issue has not been resolved, and I gave up using opencompass for the evaluation, and instead used a script I wrote myself for the boolq task.

I am also having the same issue.

One hacky solution I use is to change the `/opencompass/configs/datasets/SuperGLUE_BoolQ/SuperGLUE_BoolQ_ppl_314b96.py` file (or the corresponding config file you are using), basically change the `data_files` to `./data/boolq/validation.jsonl`.

You can then download the file from `https://huggingface.co/datasets/google/boolq/viewer/default/validation?views%5B%5D=validation` by 

```
from datasets import load_dataset
import json

# Load the BoolQ dataset (validation split)
dataset = load_dataset("google/boolq", split="validation")

# Save to JSONL
output_file = "boolq_validation.jsonl"
with open(output_file, "w") as f:
    for example in dataset:
        json.dump(example, f)
        f.write("\n")

print(f"Saved {len(dataset)} examples to {output_file}")
```

Then rename it to `validation.jsonl` and put it under `data/` folder.

Note that in the preprocess function for boolq, it is tricky as it uses `label` instead of `answer`, and also use the string match to decide whether it is 1 or 0 (for my case), so I modify the `validation.jsonl` file accordingly. 

Then you can run your opencompass with `dry-run` to preprocess the data, and run it without `dry-run` to do the actual evaluation.

Hope this helps!