使用conda和vs code键入m1 max mac上的张量 我在Mac上安装TensorFlow的时间最困难,并且我尝试了几种方法。 搜索Internet以寻找解决方案,导致重新创建我的Conda环境,尝试PIP,

问题描述 投票:0回答:0

{ "name": "ModuleNotFoundError", "message": "No module named 'tensorflow.keras'", "stack": "--------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[16], line 20 17 from xgboost import XGBRegressor 19 import tensorflow as tf ---> 20 from tensorflow.keras import layers, Sequential 21 from tensorflow.keras.optimizers import Adam ModuleNotFoundError: No module named 'tensorflow.keras'" }

在试图解决问题的当前迭代中,这是我的设置。

(cpsproject) ben@BenBook final % which python /Users/ben/opt/anaconda3/envs/cpsproject/bin/python (cpsproject) ben@BenBook final % python --version Python 3.11.10 (cpsproject) ben@BenBook final % conda list # packages in environment at /Users/ben/opt/anaconda3/envs/cpsproject: # # Name Version Build Channel _py-xgboost-mutex 2.0 cpu_0 absl-py 2.1.0 py311hecd8cb5_0 anyio 4.6.2 py311hecd8cb5_0 appnope 0.1.2 py311hecd8cb5_1001 argon2-cffi 21.3.0 pyhd3eb1b0_0 argon2-cffi-bindings 21.2.0 py311h6c40b1e_0 asttokens 2.0.5 pyhd3eb1b0_0 astunparse 1.6.3 py_0 async-lru 2.0.4 py311hecd8cb5_0 attrs 24.2.0 py311hecd8cb5_0 babel 2.11.0 py311hecd8cb5_0 beautifulsoup4 4.12.3 py311hecd8cb5_0 blas 1.0 openblas bleach 4.1.0 pyhd3eb1b0_0 bottleneck 1.4.2 py311h9b7fc35_0 brotli 1.0.9 h6c40b1e_8 brotli-bin 1.0.9 h6c40b1e_8 brotli-python 1.0.9 py311hcec6c5f_8 bzip2 1.0.8 h6c40b1e_6 c-ares 1.19.1 h6c40b1e_0 ca-certificates 2024.9.24 hecd8cb5_0 certifi 2024.8.30 py311hecd8cb5_0 cffi 1.17.1 py311h9205ec4_0 charset-normalizer 3.3.2 pyhd3eb1b0_0 comm 0.2.1 py311hecd8cb5_0 contourpy 1.2.0 py311ha357a0b_0 cycler 0.11.0 pyhd3eb1b0_0 cyrus-sasl 2.1.28 h3973f50_1 debugpy 1.6.7 py311hcec6c5f_0 decorator 5.1.1 pyhd3eb1b0_0 defusedxml 0.7.1 pyhd3eb1b0_0 executing 0.8.3 pyhd3eb1b0_0 flatbuffers 24.3.25 h6d0c2b6_0 fonttools 4.51.0 py311h6c40b1e_0 freetype 2.12.1 hd8bbffd_0 gast 0.5.3 pyhd3eb1b0_0 gettext 0.21.0 h4e8c18a_2 giflib 5.2.2 h46256e1_0 glib 2.78.4 hcec6c5f_0 glib-tools 2.78.4 hcec6c5f_0 google-pasta 0.2.0 pyhd3eb1b0_0 grpcio 1.62.2 py311hab2016f_0 gst-plugins-base 1.14.1 hcec6c5f_1 gstreamer 1.14.1 h6c40b1e_1 h11 0.14.0 py311hecd8cb5_0 h5py 3.12.1 py311ha611a00_0 hdf5 1.12.1 ha01d115_3 httpcore 1.0.2 py311hecd8cb5_0 httpx 0.27.0 py311hecd8cb5_0 icu 73.1 hcec6c5f_0 idna 3.7 py311hecd8cb5_0 ipykernel 6.29.5 py311hecd8cb5_0 ipython 8.27.0 py311hecd8cb5_0 ipywidgets 8.1.2 py311hecd8cb5_0 jedi 0.19.1 py311hecd8cb5_0 jinja2 3.1.4 py311hecd8cb5_1 joblib 1.4.2 py311hecd8cb5_0 jpeg 9e h46256e1_3 json5 0.9.25 py311hecd8cb5_0 jsonschema 4.23.0 py311hecd8cb5_0 jsonschema-specifications 2023.7.1 py311hecd8cb5_0 jupyter 1.0.0 py311hecd8cb5_9 jupyter-lsp 2.2.0 py311hecd8cb5_0 jupyter_client 8.6.0 py311hecd8cb5_0 jupyter_console 6.6.3 py311hecd8cb5_0 jupyter_core 5.7.2 py311hecd8cb5_0 jupyter_events 0.10.0 py311hecd8cb5_0 jupyter_server 2.14.1 py311hecd8cb5_0 jupyter_server_terminals 0.4.4 py311hecd8cb5_1 jupyterlab 4.2.5 py311hecd8cb5_0 jupyterlab_pygments 0.1.2 py_0 jupyterlab_server 2.27.3 py311hecd8cb5_0 jupyterlab_widgets 3.0.10 py311hecd8cb5_0 keras 3.4.1 py311hecd8cb5_0 kiwisolver 1.4.4 py311hcec6c5f_0 krb5 1.20.1 h428f121_1 lcms2 2.12 hf1fd2bf_0 lerc 3.0 he9d5cce_0 libabseil 20240116.2 cxx17_h548131f_0 libbrotlicommon 1.0.9 h6c40b1e_8 libbrotlidec 1.0.9 h6c40b1e_8 libbrotlienc 1.0.9 h6c40b1e_8 libclang 14.0.6 default_hd95374b_1 libclang13 14.0.6 default_habbcc1a_1 libcurl 8.9.1 h3a17b82_0 libcxx 14.0.6 h9765a3e_0 libdeflate 1.17 hb664fd8_1 libedit 3.1.20230828 h6c40b1e_0 libev 4.33 h9ed2024_1 libffi 3.4.4 hecd8cb5_1 libgfortran 5.0.0 11_3_0_hecd8cb5_28 libgfortran5 11.3.0 h9dfd629_28 libglib 2.78.4 h19e1a8f_0 libgrpc 1.62.2 hf2926fd_0 libiconv 1.16 h6c40b1e_3 libllvm14 14.0.6 h26321d7_4 libnghttp2 1.57.0 h9beae6a_0 libopenblas 0.3.21 h54e7dc3_0 libpng 1.6.39 h6c40b1e_0 libpq 17.0 h184c1cd_0 libprotobuf 4.25.3 h34eed0b_0 libsodium 1.0.18 h1de35cc_0 libssh2 1.11.0 hf20ceda_0 libtiff 4.5.1 hcec6c5f_0 libwebp-base 1.3.2 h46256e1_1 libxgboost 2.1.1 hab2016f_0 libxml2 2.13.1 h6070cd6_2 llvm-openmp 14.0.6 h0dcd299_0 lz4-c 1.9.4 hcec6c5f_1 markdown 3.4.1 py311hecd8cb5_0 markdown-it-py 2.2.0 py311hecd8cb5_1 markupsafe 2.1.3 py311h6c40b1e_0 matplotlib 3.9.2 py311hecd8cb5_0 matplotlib-base 3.9.2 py311hc25a08b_0 matplotlib-inline 0.1.6 py311hecd8cb5_0 mdurl 0.1.0 py311hecd8cb5_0 mistune 2.0.4 py311hecd8cb5_0 ml_dtypes 0.4.0 py311he327ffe_0 mysql 8.4.0 hbfece55_1 namex 0.0.7 py311hecd8cb5_0 nbclient 0.8.0 py311hecd8cb5_0 nbconvert 7.16.4 py311hecd8cb5_0 nbformat 5.10.4 py311hecd8cb5_0 ncurses 6.4 hcec6c5f_0 nest-asyncio 1.6.0 py311hecd8cb5_0 notebook 7.2.2 py311hecd8cb5_1 notebook-shim 0.2.3 py311hecd8cb5_0 numexpr 2.10.1 py311hc59c7be_0 numpy 1.26.4 py311h91b6869_0 numpy-base 1.26.4 py311hb3ec012_0 openjpeg 2.5.2 hbf2204d_0 openldap 2.6.4 h6e6fb41_0 openssl 3.0.15 h46256e1_0 opt_einsum 3.3.0 pyhd3eb1b0_1 optree 0.12.1 py311h1962661_0 overrides 7.4.0 py311hecd8cb5_0 packaging 24.1 py311hecd8cb5_0 pandas 2.2.2 py311he327ffe_0 pandocfilters 1.5.0 pyhd3eb1b0_0 parso 0.8.3 pyhd3eb1b0_0 pcre2 10.42 h9b97e30_1 pexpect 4.8.0 pyhd3eb1b0_3 pillow 11.0.0 py311h9c91434_0 pip 24.2 py311hecd8cb5_0 platformdirs 3.10.0 py311hecd8cb5_0 ply 3.11 py311hecd8cb5_0 prometheus_client 0.21.0 py311hecd8cb5_0 prompt-toolkit 3.0.43 py311hecd8cb5_0 prompt_toolkit 3.0.43 hd3eb1b0_0 protobuf 4.25.3 py311h43dadc6_0 psutil 5.9.0 py311h6c40b1e_0 ptyprocess 0.7.0 pyhd3eb1b0_2 pure_eval 0.2.2 pyhd3eb1b0_0 py-xgboost 2.1.1 py311hecd8cb5_0 pycparser 2.21 pyhd3eb1b0_0 pygments 2.15.1 py311hecd8cb5_1 pyparsing 3.2.0 py311hecd8cb5_0 pyqt 5.15.10 py311hcec6c5f_0 pyqt5-sip 12.13.0 py311h6c40b1e_0 pysocks 1.7.1 py311hecd8cb5_0 python 3.11.10 h4d6d9e5_0 python-dateutil 2.9.0post0 py311hecd8cb5_2 python-fastjsonschema 2.20.0 py311hecd8cb5_0 python-flatbuffers 24.3.25 py311hecd8cb5_0 python-json-logger 2.0.7 py311hecd8cb5_0 python-tzdata 2023.3 pyhd3eb1b0_0 pytz 2024.1 py311hecd8cb5_0 pyyaml 6.0.2 py311h46256e1_0 pyzmq 25.1.2 py311hcec6c5f_0 qt-main 5.15.2 hf83fbd5_11 qtconsole 5.6.0 py311hecd8cb5_0 qtpy 2.4.1 py311hecd8cb5_0 re2 2022.04.01 he9d5cce_0 readline 8.2 hca72f7f_0 referencing 0.30.2 py311hecd8cb5_0 requests 2.32.3 py311hecd8cb5_1 rfc3339-validator 0.1.4 py311hecd8cb5_0 rfc3986-validator 0.1.1 py311hecd8cb5_0 rich 13.7.1 py311hecd8cb5_0 rpds-py 0.10.6 py311hf2ad997_0 scikit-learn 1.5.1 py311he327ffe_0 scipy 1.14.1 py311hedc7b93_0 seaborn 0.13.2 py311hecd8cb5_0 send2trash 1.8.2 py311hecd8cb5_0 setuptools 75.1.0 py311hecd8cb5_0 sip 6.7.12 py311hcec6c5f_0 six 1.16.0 pyhd3eb1b0_1 snappy 1.2.1 h6d0c2b6_0 sniffio 1.3.0 py311hecd8cb5_0 soupsieve 2.5 py311hecd8cb5_0 sqlite 3.45.3 h6c40b1e_0 stack_data 0.2.0 pyhd3eb1b0_0 tensorboard 2.17.0 py311hecd8cb5_0 tensorboard-data-server 0.7.0 py311hf1618be_1 tensorflow 2.17.0 cpu_py311hb3d9b59_0 tensorflow-base 2.17.0 cpu_py311h0426836_0 tensorflow-estimator 2.17.0 cpu_py311h7aa49ff_0 termcolor 2.1.0 py311hecd8cb5_0 terminado 0.17.1 py311hecd8cb5_0 threadpoolctl 3.5.0 py311h85bffb1_0 tinycss2 1.2.1 py311hecd8cb5_0 tk 8.6.14 h4d00af3_0 tornado 6.4.1 py311h46256e1_0 traitlets 5.14.3 py311hecd8cb5_0 typing-extensions 4.11.0 py311hecd8cb5_0 typing_extensions 4.11.0 py311hecd8cb5_0 tzdata 2024b h04d1e81_0 unicodedata2 15.1.0 py311h6c40b1e_0 urllib3 2.2.3 py311hecd8cb5_0 wcwidth 0.2.5 pyhd3eb1b0_0 webencodings 0.5.1 py311hecd8cb5_1 websocket-client 1.8.0 py311hecd8cb5_0 werkzeug 3.0.6 py311hecd8cb5_0 wheel 0.44.0 py311hecd8cb5_0 widgetsnbextension 4.0.10 py311hecd8cb5_0 wrapt 1.14.1 py311h6c40b1e_0 xgboost 2.1.1 py311hecd8cb5_0 xz 5.4.6 h6c40b1e_1 yaml 0.2.5 haf1e3a3_0 zeromq 4.3.5 hcec6c5f_0 zlib 1.2.13 h4b97444_1 zstd 1.5.6 h138b38a_0
任何想法?
我尝试了更新和降级TensorFlow和Keras。 最初,我正在使用Python 3.12.x,但我了解到这是一个禁忌。 将Python降级到3.11.10也没有起作用,但是TensorFlow文档表明它与3.11兼容。 环境

cpsproject

是我对虚拟环境的第三次迭代,这是我首先安装TensorFlow首先要开始的第二次迭代,希望Conda将与随后的软件包添加一起使用任何冲突。 那也不起作用,这是我现在最新的状态。
	

评论您指示的上下文,在计算机上安装了Python,TF,Keras。但是,困难在于Vscode接口,您必须为“ Python环境”执行(右上角)选择内核。更多vscode

详细信息 我使用默认环境对您的代码行进行了测试,然后一个具有正确环境的环境进行了测试,这无问题。在Conda上安装Jupyter笔记本时,没有发生此问题。
看以下图像:
环境错误:

环境成功
    

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