现已无法直接按步骤安装环境

[TheLolita]

[giter159]

I suggest you to create a new virtual environment and in accordance with the steps in sequence, and you may need to add some package according to the prompt, for example: easydict, transformers, scikit - learn, pandas

[dkgee]

按说明创建的新的虚拟的python3.6环境，pip install -r requirements.txt 一安装就包各种错。真是无语……

[giter159]

按说明创建的新的虚拟的python3.6环境，pip install -r requirements.txt 一安装就包各种错。真是无语……

you may need to add some package according to the prompt

[dkgee]

其他什么都正常，就是这个requirements.txt里面依赖和python3.6环境不兼容，各种报错啊 mkl-fft>=1.2.0 # 版本不对 python3.8却能正常安装 mkl-random==1.2.0 # 版本不对 mkl-service==2.3.0 # 找不到 sklearn==0.0 # 报错

[giter159]

其他什么都正常，就是这个requirements.txt里面依赖和python3.6环境不兼容，各种报错啊 mkl-fft>=1.2.0 # 版本不对 python3.8却能正常安装 mkl-random==1.2.0 # 版本不对 mkl-service==2.3.0 # 找不到 sklearn==0.0 # 报错

absl-py 2.1.0 aiohttp 3.9.3 aiosignal 1.3.1 astunparse 1.6.3 async-timeout 4.0.3 attrs 23.2.0 blessed 1.20.0 blinker 1.7.0 boto3 1.34.72 botocore 1.34.72 Brotli 1.1.0 cached-property 1.5.2 cachetools 5.3.3 certifi 2024.2.2 cffi 1.16.0 charset-normalizer 3.3.2 click 8.1.7 contourpy 1.1.1 cryptography 42.0.5 cycler 0.12.1 easydict 1.12 filelock 3.13.1 flatbuffers 23.5.26 fonttools 4.49.0 frozenlist 1.4.1 fsspec 2024.2.0 gast 0.4.0 google-auth 2.28.1 google-auth-oauthlib 0.4.6 google-pasta 0.2.0 gpustat 1.1.1 grpcio 1.54.3 h5py 3.10.0 huggingface-hub 0.21.2 idna 3.6 importlib-metadata 7.0.1 importlib_resources 6.1.2 Jinja2 3.1.3 jmespath 1.0.1 joblib 1.3.2 keras 2.11.0 kiwisolver 1.4.5 libclang 16.0.6 Markdown 3.5.2 MarkupSafe 2.1.5 matplotlib 3.7.5 mpmath 1.3.0 multidict 6.0.5 networkx 3.1 nltk 3.8.1 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 8.9.2.26 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-ml-py 12.535.133 nvidia-nccl-cu12 2.19.3 nvidia-nvjitlink-cu12 12.3.101 nvidia-nvtx-cu12 12.1.105 oauthlib 3.2.2 opt-einsum 3.3.0 packaging 23.2 pandas 2.0.3 pillow 10.2.0 pip 24.0 protobuf 3.19.6 psutil 5.9.8 pyasn1 0.5.1 pyasn1-modules 0.3.0 pycparser 2.21 PyJWT 2.8.0 pyOpenSSL 24.0.0 pyparsing 3.1.1 PySocks 1.7.1 python-dateutil 2.8.2 pytorch-pretrained-bert 0.6.2 pytz 2024.1 pyu2f 0.1.5 PyYAML 6.0.1 regex 2023.12.25 requests 2.31.0 requests-oauthlib 1.3.1 rsa 4.9 s3transfer 0.10.1 safetensors 0.4.2 scikit-learn 1.3.2 scipy 1.10.1 sentence-transformers 2.4.0 setuptools 69.1.1 six 1.16.0 sympy 1.12 tensorboard 2.11.2 tensorboard-data-server 0.6.1 tensorboard-plugin-wit 1.8.1 tensorflow 2.13.1 tensorflow-estimator 2.11.0 tensorflow-io-gcs-filesystem 0.34.0 termcolor 2.4.0 threadpoolctl 3.3.0 tokenizers 0.15.2 torch 2.2.1 tqdm 4.66.2 transformers 4.38.1 triton 2.2.0 typing_extensions 4.10.0 tzdata 2024.1 urllib3 1.26.18 wcwidth 0.2.13 Werkzeug 3.0.1 wheel 0.42.0 wrapt 1.16.0 yarl 1.9.4 zipp 3.17.0 参考下这些包

[dkgee]

其他什么都正常，就是这个requirements.txt里面依赖和python3.6环境不兼容，各种报错啊 mkl-fft>=1.2.0 # 版本不对 python3.8却能正常安装 mkl-random==1.2.0 # 版本不对 mkl-service==2.3.0 # 找不到 sklearn==0.0 # 报错

absl-py 2.1.0 aiohttp 3.9.3 aiosignal 1.3.1 astunparse 1.6.3 async-timeout 4.0.3 attrs 23.2.0 blessed 1.20.0 blinker 1.7.0 boto3 1.34.72 botocore 1.34.72 Brotli 1.1.0 cached-property 1.5.2 cachetools 5.3.3 certifi 2024.2.2 cffi 1.16.0 charset-normalizer 3.3.2 click 8.1.7 contourpy 1.1.1 cryptography 42.0.5 cycler 0.12.1 easydict 1.12 filelock 3.13.1 flatbuffers 23.5.26 fonttools 4.49.0 frozenlist 1.4.1 fsspec 2024.2.0 gast 0.4.0 google-auth 2.28.1 google-auth-oauthlib 0.4.6 google-pasta 0.2.0 gpustat 1.1.1 grpcio 1.54.3 h5py 3.10.0 huggingface-hub 0.21.2 idna 3.6 importlib-metadata 7.0.1 importlib_resources 6.1.2 Jinja2 3.1.3 jmespath 1.0.1 joblib 1.3.2 keras 2.11.0 kiwisolver 1.4.5 libclang 16.0.6 Markdown 3.5.2 MarkupSafe 2.1.5 matplotlib 3.7.5 mpmath 1.3.0 multidict 6.0.5 networkx 3.1 nltk 3.8.1 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 8.9.2.26 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-ml-py 12.535.133 nvidia-nccl-cu12 2.19.3 nvidia-nvjitlink-cu12 12.3.101 nvidia-nvtx-cu12 12.1.105 oauthlib 3.2.2 opt-einsum 3.3.0 packaging 23.2 pandas 2.0.3 pillow 10.2.0 pip 24.0 protobuf 3.19.6 psutil 5.9.8 pyasn1 0.5.1 pyasn1-modules 0.3.0 pycparser 2.21 PyJWT 2.8.0 pyOpenSSL 24.0.0 pyparsing 3.1.1 PySocks 1.7.1 python-dateutil 2.8.2 pytorch-pretrained-bert 0.6.2 pytz 2024.1 pyu2f 0.1.5 PyYAML 6.0.1 regex 2023.12.25 requests 2.31.0 requests-oauthlib 1.3.1 rsa 4.9 s3transfer 0.10.1 safetensors 0.4.2 scikit-learn 1.3.2 scipy 1.10.1 sentence-transformers 2.4.0 setuptools 69.1.1 six 1.16.0 sympy 1.12 tensorboard 2.11.2 tensorboard-data-server 0.6.1 tensorboard-plugin-wit 1.8.1 tensorflow 2.13.1 tensorflow-estimator 2.11.0 tensorflow-io-gcs-filesystem 0.34.0 termcolor 2.4.0 threadpoolctl 3.3.0 tokenizers 0.15.2 torch 2.2.1 tqdm 4.66.2 transformers 4.38.1 triton 2.2.0 typing_extensions 4.10.0 tzdata 2024.1 urllib3 1.26.18 wcwidth 0.2.13 Werkzeug 3.0.1 wheel 0.42.0 wrapt 1.16.0 yarl 1.9.4 zipp 3.17.0 参考下这些包

谢谢，解决了，我这边环境为： （1）环境为 python 3.8 pip 24.0 （2）2个依赖包得更新版本 mkl-random==1.2.2 mkl-service==2.4.0 （3）运行环境得能访问hunggingface，其中open_intent_detection/backbones/base.py 第38行，自动会去hugging face下载 bert-base-uncased 模型了，虽然我提前把模型离线下载到本地，但貌似没用，还好这模型小，不用等太久。 （4）open_intent_detection/run.py 第49行，训练时数据保存目录得修改；第52行，模型输出目录得重新配置