Repository: open-compass/opencompass
Issue: [Bug] 提示新写的Dataset未注册
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 have modified the code (config is not considered code), or I'm working on my own tasks/models/datasets.

### Environment

{'CUDA available': True,
 'CUDA_HOME': None,
 'GCC': 'gcc (GCC) 4.8.5 20150623 (Red Hat 4.8.5-44)',
 'GPU 0,1,2,3,4,5,6,7': 'NVIDIA A100-SXM4-80GB',
 'MMEngine': '0.10.5',
 'MUSA available': False,
 '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: AVX2\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_$
6,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': '3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0]',
 'TorchVision': '0.20.1+cu124',
 'lmdeploy': "not installed:No module named 'lmdeploy'",
 'numpy_random_seed': 2147483648,
 'opencompass': '0.3.7+',
 'sys.platform': 'linux',
 'transformers': '4.47.0'}

### Reproduces the problem - code/configuration sample
xxx.py:
```python
@LOAD_DATASET.register_module()
class XXXDataset(BaseDataset):

    @staticmethod
    def load(path):
        datasets = []
        # 省略读数据文件的步骤
        return Dataset.from_list(datasets[:4])
```

my_eval_api.py:
```
from xxx import XXXDataset
```

`xxx.py`和`my_eval_api.py`在同一目录下


### Reproduces the problem - command or script

运行：
`python run.py my_eval_api.py --debug`
可以正确运行。
但是如果去掉`--debug`就会报以下错误：
```
KeyError: 'xxx.XXXDataset is not in the opencompass::load_dataset registry. Please check whether the value of `xxx.XXXDataset ` is correct or it was registered as expected. More details can be found at https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#import-the-custom-module'
```
我没有把XXXDataset放到`opencompass/opencompass/datasets/`下面，而是在其他地方单独建了个目录放置我的所有配置文件和XXXDataset文件，因为我认为是不应该去修改源码来支持自定义数据集的，加上`--debug`可正确运行也支持了我的想法，但是不知道为什么去掉就会报错？

### Reproduces the problem - error message

同上

### Other information

我认为自定义Dataset是不应该直接在源码中修改的，应该在任何一个地方，只要继承自BaseDataset并通过@LOAD_DATASET.register_module()装饰应该就可以。这样也可以支持非编辑模式的安装使用：`  pip install opencompass`。
自定义Evaluator也一样。


作者可以解答一下吗？当通过pip安装的时候应该如何自定义Dataset和Evaluator？