我正在尝试安装依赖项以进行张量流开发。为此,我使用了yml文件tfdl_env.yml
。使用conda env create
,因此应该安装所有依赖项。
conda env create -f tfdl_env.yml
但是那里显示Solving environment: failed
和RequiredPackageNotFound
。
下面使用的yml
文件。
name: tfdeeplearning
channels:
- defaults
dependencies:
- bleach=1.5.0=py35_0
- certifi=2016.2.28=py35_0
- colorama=0.3.9=py35_0
- cycler=0.10.0=py35_0
- decorator=4.1.2=py35_0
- entrypoints=0.2.3=py35_0
- html5lib=0.9999999=py35_0
- icu=57.1=vc14_0
- ipykernel=4.6.1=py35_0
- ipython=6.1.0=py35_0
- ipython_genutils=0.2.0=py35_0
- ipywidgets=6.0.0=py35_0
- jedi=0.10.2=py35_2
- jinja2=2.9.6=py35_0
- jpeg=9b=vc14_0
- jsonschema=2.6.0=py35_0
- jupyter=1.0.0=py35_3
- jupyter_client=5.1.0=py35_0
- jupyter_console=5.2.0=py35_0
- jupyter_core=4.3.0=py35_0
- libpng=1.6.30=vc14_1
- markupsafe=1.0=py35_0
- matplotlib=2.0.2=np113py35_0
- mistune=0.7.4=py35_0
- mkl=2017.0.3=0
- nbconvert=5.2.1=py35_0
- nbformat=4.4.0=py35_0
- notebook=5.0.0=py35_0
- numpy=1.13.1=py35_0
- openssl=1.0.2l=vc14_0
- pandas=0.20.3=py35_0
- pandocfilters=1.4.2=py35_0
- path.py=10.3.1=py35_0
- pickleshare=0.7.4=py35_0
- pip=9.0.1=py35_1
- prompt_toolkit=1.0.15=py35_0
- pygments=2.2.0=py35_0
- pyparsing=2.2.0=py35_0
- pyqt=5.6.0=py35_2
- python=3.5.4=0
- python-dateutil=2.6.1=py35_0
- pytz=2017.2=py35_0
- pyzmq=16.0.2=py35_0
- qt=5.6.2=vc14_6
- qtconsole=4.3.1=py35_0
- requests=2.14.2=py35_0
- scikit-learn=0.19.0=np113py35_0
- scipy=0.19.1=np113py35_0
- setuptools=36.4.0=py35_1
- simplegeneric=0.8.1=py35_1
- sip=4.18=py35_0
- six=1.10.0=py35_1
- testpath=0.3.1=py35_0
- tk=8.5.18=vc14_0
- tornado=4.5.2=py35_0
- traitlets=4.3.2=py35_0
- vs2015_runtime=14.0.25420=0
- wcwidth=0.1.7=py35_0
- wheel=0.29.0=py35_0
- widgetsnbextension=3.0.2=py35_0
- win_unicode_console=0.5=py35_0
- wincertstore=0.2=py35_0
- zlib=1.2.11=vc14_0
- pip:
- ipython-genutils==0.2.0
- jupyter-client==5.1.0
- jupyter-console==5.2.0
- jupyter-core==4.3.0
- markdown==2.6.9
- prompt-toolkit==1.0.15
- protobuf==3.4.0
- tensorflow==1.3.0
- tensorflow-tensorboard==0.1.6
- werkzeug==0.12.2
- win-unicode-console==0.5
prefix: C:\Users\varun\Anaconda3\envs\tfdeeplearning
我正在使用Anaconda 3
,而conda
的版本是4.7.12
。我在Windows10机器上。这样做的目的是安装tensorflow及其所有依赖项。
答案 0 :(得分:4)
对我来说是同样的错误。同样在Windows 10中,带有Anaconda 3(2019.10)和Python 3.7(全部64位)。这是我的输出:
Collecting package metadata (repodata.json): done
Solving environment: failed
ResolvePackageNotFound:
- notebook==5.0.0=py35_0
- python-dateutil==2.6.1=py35_0
- wcwidth==0.1.7=py35_0
- testpath==0.3.1=py35_0
- libpng==1.6.30=vc14_1
- nbformat==4.4.0=py35_0
- tornado==4.5.2=py35_0
- numpy==1.13.1=py35_0
- setuptools==36.4.0=py35_1
- zlib==1.2.11=vc14_0
- html5lib==0.9999999=py35_0
- wheel==0.29.0=py35_0
- ipython==6.1.0=py35_0
- simplegeneric==0.8.1=py35_1
- ipykernel==4.6.1=py35_0
- colorama==0.3.9=py35_0
- jpeg==9b=vc14_0
- certifi==2016.2.28=py35_0
- scikit-learn==0.19.0=np113py35_0
- pip==9.0.1=py35_1
- ipython_genutils==0.2.0=py35_0
- jedi==0.10.2=py35_2
- tk==8.5.18=vc14_0
- mkl==2017.0.3=0
- icu==57.1=vc14_0
- pandas==0.20.3=py35_0
- qtconsole==4.3.1=py35_0
- widgetsnbextension==3.0.2=py35_0
- pickleshare==0.7.4=py35_0
- jupyter_console==5.2.0=py35_0
- bleach==1.5.0=py35_0
- jupyter_client==5.1.0=py35_0
- ipywidgets==6.0.0=py35_0
- openssl==1.0.2l=vc14_0
- pandocfilters==1.4.2=py35_0
- qt==5.6.2=vc14_6
- win_unicode_console==0.5=py35_0
- pytz==2017.2=py35_0
- pyzmq==16.0.2=py35_0
- pyqt==5.6.0=py35_2
- decorator==4.1.2=py35_0
- path.py==10.3.1=py35_0
- jupyter==1.0.0=py35_3
- jsonschema==2.6.0=py35_0
- markupsafe==1.0=py35_0
- requests==2.14.2=py35_0
- jupyter_core==4.3.0=py35_0
- entrypoints==0.2.3=py35_0
- six==1.10.0=py35_1
- cycler==0.10.0=py35_0
- mistune==0.7.4=py35_0
- scipy==0.19.1=np113py35_0
- traitlets==4.3.2=py35_0
- vs2015_runtime==14.0.25420=0
- wincertstore==0.2=py35_0
- matplotlib==2.0.2=np113py35_0
- nbconvert==5.2.1=py35_0
- python==3.5.4=0
- jinja2==2.9.6=py35_0
- pygments==2.2.0=py35_0
- prompt_toolkit==1.0.15=py35_0
- pyparsing==2.2.0=py35_0
- sip==4.18=py35_0
在尝试从提供的tfdl_env.yml
文件中进行几次失败的安装之后,我放弃了,只是继续自己用conda install <PACKAGE>
安装所需的软件包。然后,我还发现提供的文件中某些指定的软件包版本不是最新的,conda
无法找到此类版本。我实际上对这个Anaconda环境系统感到非常失望,因为对于创建环境的用户而言,这似乎只是一个“环境克隆工具”,但正如人们所期望的那样,它们绝对不是便携式的。
但是,也许现在我使它在Windows 10中运行了,您也可以尝试使用它。这是我从安装中创建的一个environment.yml
文件,据我所知,该文件可以正常运行(我已经在学习课程的第5部分):
name: tfdeeplearning
channels:
- defaults
dependencies:
- _tflow_select=2.2.0=eigen
- absl-py=0.9.0=py37_0
- asn1crypto=1.3.0=py37_0
- astor=0.8.0=py37_0
- attrs=19.3.0=py_0
- backcall=0.1.0=py37_0
- blas=1.0=mkl
- bleach=3.1.0=py37_0
- blinker=1.4=py37_0
- ca-certificates=2020.1.1=0
- cachetools=3.1.1=py_0
- certifi=2019.11.28=py37_0
- cffi=1.14.0=py37h7a1dbc1_0
- chardet=3.0.4=py37_1003
- click=7.0=py37_0
- colorama=0.4.3=py_0
- cryptography=2.8=py37h7a1dbc1_0
- cycler=0.10.0=py37_0
- decorator=4.4.1=py_0
- defusedxml=0.6.0=py_0
- entrypoints=0.3=py37_0
- freetype=2.9.1=ha9979f8_1
- gast=0.2.2=py37_0
- google-auth=1.11.2=py_0
- google-auth-oauthlib=0.4.1=py_2
- google-pasta=0.1.8=py_0
- grpcio=1.27.2=py37h351948d_0
- h5py=2.10.0=py37h5e291fa_0
- hdf5=1.10.4=h7ebc959_0
- icc_rt=2019.0.0=h0cc432a_1
- icu=58.2=ha66f8fd_1
- idna=2.8=py37_0
- importlib_metadata=1.5.0=py37_0
- intel-openmp=2020.0=166
- ipykernel=5.1.4=py37h39e3cac_0
- ipython=7.12.0=py37h5ca1d4c_0
- ipython_genutils=0.2.0=py37_0
- ipywidgets=7.5.1=py_0
- jedi=0.16.0=py37_0
- jinja2=2.11.1=py_0
- joblib=0.14.1=py_0
- jpeg=9b=hb83a4c4_2
- jsonschema=3.2.0=py37_0
- jupyter=1.0.0=py37_7
- jupyter_client=5.3.4=py37_0
- jupyter_console=6.1.0=py_0
- jupyter_core=4.6.1=py37_0
- keras-applications=1.0.8=py_0
- keras-preprocessing=1.1.0=py_1
- kiwisolver=1.1.0=py37ha925a31_0
- libpng=1.6.37=h2a8f88b_0
- libprotobuf=3.11.4=h7bd577a_0
- libsodium=1.0.16=h9d3ae62_0
- m2w64-gcc-libgfortran=5.3.0=6
- m2w64-gcc-libs=5.3.0=7
- m2w64-gcc-libs-core=5.3.0=7
- m2w64-gmp=6.1.0=2
- m2w64-libwinpthread-git=5.0.0.4634.697f757=2
- markdown=3.1.1=py37_0
- markupsafe=1.1.1=py37he774522_0
- matplotlib=3.1.3=py37_0
- matplotlib-base=3.1.3=py37h64f37c6_0
- mistune=0.8.4=py37he774522_0
- mkl=2020.0=166
- mkl-service=2.3.0=py37hb782905_0
- mkl_fft=1.0.15=py37h14836fe_0
- mkl_random=1.1.0=py37h675688f_0
- msys2-conda-epoch=20160418=1
- nbconvert=5.6.1=py37_0
- nbformat=5.0.4=py_0
- notebook=6.0.3=py37_0
- numpy=1.18.1=py37h93ca92e_0
- numpy-base=1.18.1=py37hc3f5095_1
- oauthlib=3.1.0=py_0
- openssl=1.1.1d=he774522_4
- opt_einsum=3.1.0=py_0
- pandas=1.0.1=py37h47e9c7a_0
- pandoc=2.2.3.2=0
- pandocfilters=1.4.2=py37_1
- parso=0.6.1=py_0
- pip=20.0.2=py37_1
- prometheus_client=0.7.1=py_0
- prompt_toolkit=3.0.3=py_0
- protobuf=3.11.4=py37h33f27b4_0
- pyasn1=0.4.8=py_0
- pyasn1-modules=0.2.7=py_0
- pycparser=2.19=py37_0
- pygments=2.5.2=py_0
- pyjwt=1.7.1=py37_0
- pyopenssl=19.1.0=py37_0
- pyparsing=2.4.6=py_0
- pyqt=5.9.2=py37h6538335_2
- pyreadline=2.1=py37_1
- pyrsistent=0.15.7=py37he774522_0
- pysocks=1.7.1=py37_0
- python=3.7.6=h60c2a47_2
- python-dateutil=2.8.1=py_0
- pytz=2019.3=py_0
- pywinpty=0.5.7=py37_0
- pyzmq=18.1.1=py37ha925a31_0
- qt=5.9.7=vc14h73c81de_0
- qtconsole=4.6.0=py_1
- requests=2.22.0=py37_1
- requests-oauthlib=1.3.0=py_0
- rsa=4.0=py_0
- scikit-learn=0.22.1=py37h6288b17_0
- scipy=1.4.1=py37h9439919_0
- send2trash=1.5.0=py37_0
- setuptools=45.2.0=py37_0
- sip=4.19.8=py37h6538335_0
- six=1.14.0=py37_0
- sqlite=3.31.1=he774522_0
- tensorboard=2.1.0=py3_0
- tensorflow=1.15.0=eigen_py37h9f89a44_0
- tensorflow-base=1.15.0=eigen_py37h07d2309_0
- tensorflow-estimator=1.15.1=pyh2649769_0
- termcolor=1.1.0=py37_1
- terminado=0.8.3=py37_0
- testpath=0.4.4=py_0
- tornado=6.0.3=py37he774522_3
- traitlets=4.3.3=py37_0
- urllib3=1.25.8=py37_0
- vc=14.1=h0510ff6_4
- vs2015_runtime=14.16.27012=hf0eaf9b_1
- wcwidth=0.1.8=py_0
- webencodings=0.5.1=py37_1
- werkzeug=0.16.1=py_0
- wheel=0.34.2=py37_0
- widgetsnbextension=3.5.1=py37_0
- win_inet_pton=1.1.0=py37_0
- wincertstore=0.2=py37_0
- winpty=0.4.3=4
- wrapt=1.11.2=py37he774522_0
- zeromq=4.3.1=h33f27b4_3
- zipp=2.2.0=py_0
- zlib=1.2.11=h62dcd97_3
- pip:
- ipython-genutils==0.2.0
- jupyter-client==6.0.0
- jupyter-core==4.6.3
- pickleshare==0.7.5
- pywin32==227
prefix: C:\Users\jose_\Anaconda3\envs\tfdeeplearning
只需将内容复制到框中的environment.yml
文件中,然后执行conda env create -f environment.yml
。
此外,签出最后一行prefix
,您必须在其中修改路径以匹配您的路径(可能只是替换jose_
)。正如我之前说过的那样,此Conda环境工具似乎不适合创建可分发到不同机器的便携式环境。
祝你好运。