python - 为什么我不能在 Anaconda 中安装软件包?
问题描述
我从此链接安装了 Anaconda ,当我尝试从 Anaconda Navigator 安装其他软件包时,出现以下错误:
UnsatisfiableError: The following specifications were found to be incompatible with each other:
Package _tflow_select conflicts for:
keras -> tensorflow -> _tflow_select[version='==2.1.0|==2.2.0|==2.3.0',build='mkl|gpu|eigen']
tensorflow-eigen -> _tflow_select==2.2.0=eigen
tensorflow-hub -> tensorflow[version='>=1.7.0'] -> _tflow_select[version='==2.1.0|==2.2.0|==2.3.0',build='mkl|gpu|eigen']
tensorflow-metadata -> tensorflow -> _tflow_select[version='==2.1.0|==2.2.0|==2.3.0',build='mkl|gpu|eigen']
tensorflow-gpu -> tensorflow==1.9.0 -> _tflow_select[version='==2.2.0|==2.3.0',build='mkl|eigen']
keras-gpu -> tensorflow-gpu -> tensorflow==1.9.0 -> _tflow_select[version='==2.2.0|==2.3.0',build='mkl|eigen']
tensorflow-probability -> tensorflow[version='>=1.14.0'] -> _tflow_select[version='==2.1.0|==2.2.0|==2.3.0',build='mkl|gpu|eigen']
tensorflow -> _tflow_select[version='==2.1.0|==2.2.0|==2.3.0',build='mkl|gpu|eigen']
tensorflow-datasets -> tensorflow[version='>=1.14'] -> _tflow_select[version='==2.1.0|==2.2.0|==2.3.0',build='mkl|gpu|eigen']
tensorflow-mkl -> _tflow_select==2.3.0=mkl
tensorflow-gpu -> _tflow_select==2.1.0=gpu
keras-gpu -> tensorflow-gpu -> _tflow_select==2.1.0=gpu
Package tensorflow-base conflicts for:
tensorflow-mkl -> tensorflow==1.14.0 -> tensorflow-base[version='==1.10.0|==1.11.0|==1.12.0|==1.13.1|==1.13.1|==1.14.0|==1.14.0',build='mkl_py36ha978198_0|mkl_py36hcaf7020_0|mkl_py36h81393da_0|mkl_py36h81393da_0|mkl_py36h81393da_0|mkl_py35h81393da_0|mkl_py37hcaf7020_0|mkl_py37ha978198_0']
keras -> tensorflow -> tensorflow-base[version='==1.10.0|==1.11.0|==1.11.0|==1.11.0|==1.12.0|==1.12.0|==1.12.0|==1.13.1|==1.13.1|==1.13.1|==1.13.1|==1.13.1|==1.13.1|==1.13.1|==1.13.1|==1.14.0|==1.14.0|==1.14.0|==1.14.0|==1.14.0|==1.14.0|==1.14.0|==1.14.0|==1.9.0|==1.9.0|==1.9.0|==1.9.0',build='gpu_py35h6e53903_0|eigen_py36h45df0d8_0|gpu_py37h55fc52a_0|gpu_py36h55fc52a_0|gpu_py37h871c8ca_0|gpu_py36h871c8ca_0|gpu_py36h0fff12a_0|eigen_py37hf8af7b3_0|eigen_py36hf8af7b3_0|mkl_py36h81393da_0|gpu_py36h6e53903_0|eigen_py36h45df0d8_0|mkl_py36h81393da_0|eigen_py36h45df0d8_0|gpu_py36h6e53903_0|eigen_py35h45df0d8_0|eigen_py36h45df0d8_0|gpu_py35h6e53903_0|mkl_py35h81393da_0|mkl_py36h81393da_0|gpu_py36h6e53903_0|gpu_py37h0fff12a_0|mkl_py36hcaf7020_0|mkl_py37hcaf7020_0|eigen_py36hdbc3f0e_0|eigen_py37hdbc3f0e_0|gpu_py36h9ee611f_0|gpu_py37h9ee611f_0|mkl_py36ha978198_0|mkl_py37ha978198_0|eigen_py35h45df0d8_0|gpu_py36h6e53903_0']
tensorflow-estimator -> tensorflow-base[version='>=1.14.0,<1.15.0a0']
tensorflow -> tensorflow-base[version='==1.10.0|==1.11.0|==1.11.0|==1.11.0|==1.12.0|==1.12.0|==1.12.0|==1.13.1|==1.13.1|==1.13.1|==1.13.1|==1.13.1|==1.13.1|==1.13.1|==1.13.1|==1.14.0|==1.14.0|==1.14.0|==1.14.0|==1.14.0|==1.14.0|==1.14.0|==1.14.0|==1.9.0|==1.9.0|==1.9.0|==1.9.0',build='gpu_py35h6e53903_0|eigen_py36h45df0d8_0|gpu_py37h55fc52a_0|gpu_py36h55fc52a_0|gpu_py37h871c8ca_0|gpu_py36h871c8ca_0|gpu_py36h0fff12a_0|eigen_py37hf8af7b3_0|eigen_py36hf8af7b3_0|mkl_py36h81393da_0|gpu_py36h6e53903_0|eigen_py36h45df0d8_0|mkl_py36h81393da_0|eigen_py36h45df0d8_0|gpu_py36h6e53903_0|eigen_py35h45df0d8_0|eigen_py36h45df0d8_0|gpu_py35h6e53903_0|mkl_py35h81393da_0|mkl_py36h81393da_0|gpu_py36h6e53903_0|gpu_py37h0fff12a_0|mkl_py36hcaf7020_0|mkl_py37hcaf7020_0|eigen_py36hdbc3f0e_0|eigen_py37hdbc3f0e_0|gpu_py36h9ee611f_0|gpu_py37h9ee611f_0|mkl_py36ha978198_0|mkl_py37ha978198_0|eigen_py35h45df0d8_0|gpu_py36h6e53903_0']
keras-gpu -> tensorflow-gpu -> tensorflow==1.9.0 -> tensorflow-base==1.14.0=gpu_py37h9ee611f_0 -> tensorflow-base[version='>=1.14.0,<1.15.0a0']
tensorflow-eigen -> tensorflow==1.9.0 -> tensorflow-base==1.13.1=eigen_py37hf8af7b3_0 -> tensorflow-base[version='>=1.14.0,<1.15.0a0']
tensorflow-datasets -> tensorflow[version='>=1.14'] -> tensorflow-estimator[version='>=1.14.0,<1.15.0'] -> tensorflow-base[version='>=1.14.0,<1.15.0a0']
tensorflow-mkl -> tensorflow==1.14.0 -> tensorflow-base==1.14.0=mkl_py37ha978198_0 -> tensorflow-base[version='>=1.14.0,<1.15.0a0']
tensorflow -> tensorflow-estimator[version='>=1.14.0,<1.15.0'] -> tensorflow-base[version='>=1.14.0,<1.15.0a0']
tensorflow-base
...
我提到我只有根环境。有谁知道这些冲突意味着什么以及如何解决这个问题?
解决方案
您必须安装到新环境而不是 conda 根环境中。
推荐阅读
- php - 在codeigniter中每3个数据添加新的div和end div
- javascript - 如何在 ExtJS 上使用一种以上的 gridfilter 类型?
- c# - 如何添加由脚本创建的每个按钮单击侦听器事件?
- angularjs - 在角度中使用 ng-if 来显示或隐藏图像
- reactjs - React Hooks 和 TypeScript Fetching API:对象可能为“空”
- c# - 分段上传文件中的 Amazon S3 加载问题
- javascript - 在两个页面之间共享对象数组
- python - 在机器/深度学习上运行代码时出错
- javascript - jQuery :hover 选择器在 Edge 和 Firefox 中无法正常工作
- informix - 通过 Powershell 安装 Informix ODBC 驱动程序