如何解决创建conda环境时解决PackageNotFound错误
我试图使用 conda env create -n clam -f docs/clam.yaml
我得到以下结果:
Collecting package Metadata (repodata.json): done
Solving environment: Failed
ResolvePackageNotFound:
- mkl-service==2.3.0=py37he904b0f_0
- libedit==3.1.20181209=hc058e9b_0
- cffi==1.14.0=py37h2e261b9_0
- ld_impl_linux-64==2.33.1=h53a641e_7
- zlib==1.2.11=h7b6447c_3
- python-spams==2.6.1=py37h55324e4_1204
- tensorflow-base==1.14.0=mkl_py37h7ce6ba3_0
- matplotlib==3.1.1=py37h5429711_0
- gmp==6.1.2=h6c8ec71_1
- xorg-libice==1.0.10=h516909a_0
- pyzmq==18.1.1=py37he6710b0_0
- grpcio==1.27.2=py37hf8bcb03_0
- xorg-kbproto==1.0.7=h14c3975_1002
- libprotobuf==3.11.4=hd408876_0
- ninja==1.9.0=py37hfd86e86_0
- xorg-libxext==1.3.4=h516909a_0
- expat==2.2.6=he6710b0_0
- gobject-introspection==1.56.1=py37hbc4ca2d_2
- freetype==2.9.1=h8a8886c_1
- libtiff==4.1.0=h2733197_0
- fontconfig==2.13.1=he4413a7_1000
- xz==5.2.4=h14c3975_4
- pixman==0.38.0=h7b6447c_0
- numpy==1.18.1=py37h4f9e942_0
- numpy-base==1.18.1=py37hde5b4d6_1
- pytorch==1.3.1=py3.7_cuda10.1.243_cudnn7.6.3_0
- ncurses==6.2=he6710b0_0
- c-ares==1.15.0=h7b6447c_1001
- gstreamer==1.14.0=hb453b48_1
- harfbuzz==2.4.0=h37c48d4_1
- zstd==1.3.7=h0b5b093_0
- tk==8.6.8=hbc83047_0
- xorg-libsm==1.2.3=h84519dc_1000
- libcroco==0.6.13=h8d621e5_0
- libstdcxx-ng==9.1.0=hdf63c60_0
- pango==1.42.4=h7062337_3
- h5py==2.10.0=nompi_py37h513d04c_102
- xorg-libx11==1.6.9=h516909a_0
- mkl_random==1.1.0=py37hd6b4f25_0
- mkl_fft==1.0.15=py37ha843d7b_0
- dbus==1.13.12=h746ee38_0
- python==3.7.7=hcf32534_0_cpython
- tensorflow==1.14.0=mkl_py37h45c423b_0
- intel-openmp==2019.4=243
...
总共有 80 多行。
我该如何处理。我见过有人使用 pip,但在这种情况下,包太多了,我不确定它是否会起作用。有没有更好的办法?
yaml 文件是这样的
name: deep_learning
channels:
- pytorch
- conda-forge
- defaults
dependencies:
- _libgcc_mutex=0.1=main
- _tflow_select=2.3.0=mkl
- absl-py=0.9.0=py37_0
- astor=0.8.0=py37_0
- attrs=19.3.0=py_0
- backcall=0.1.0=py37_0
- blas=1.0=mkl
- c-ares=1.15.0=h7b6447c_1001
- ca-certificates=2020.1.1=0
- cairo=1.16.0=h18b612c_1001
- certifi=2019.11.28=py37_1
- cffi=1.14.0=py37h2e261b9_0
- cudatoolkit=10.1.243=h6bb024c_0
- cycler=0.10.0=py37_0
- cython=0.29.15=py37he6710b0_0
- dbus=1.13.12=h746ee38_0
- decorator=4.4.2=py_0
- defusedxml=0.6.0=py_0
- entrypoints=0.3=py37_0
- expat=2.2.6=he6710b0_0
- fontconfig=2.13.1=he4413a7_1000
- freetype=2.9.1=h8a8886c_1
- fribidi=1.0.9=h516909a_0
- gast=0.3.3=py_0
- gdk-pixbuf=2.36.9=1
- glib=2.63.1=h5a9c865_0
- gmp=6.1.2=h6c8ec71_1
- gobject-introspection=1.56.1=py37hbc4ca2d_2
- google-pasta=0.2.0=py_0
- graphite2=1.3.13=h23475e2_0
- grpcio=1.27.2=py37hf8bcb03_0
- gst-plugins-base=1.14.0=hbbd80ab_1
- gstreamer=1.14.0=hb453b48_1
- h5py=2.10.0=nompi_py37h513d04c_102
- harfbuzz=2.4.0=h37c48d4_1
- hdf5=1.10.5=nompi_h3c11f04_1104
- icu=58.2=h9c2bf20_1
- importlib_Metadata=1.5.0=py37_0
- intel-openmp=2019.4=243
- ipykernel=5.1.4=py37h39e3cac_0
- ipython=7.13.0=py37h5ca1d4c_0
- ipython_genutils=0.2.0=py37_0
- jedi=0.16.0=py37_1
- jinja2=2.11.1=py_0
- jpeg=9b=h024ee3a_2
- jupyter_client=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=py37he6710b0_0
- ld_impl_linux-64=2.33.1=h53a641e_7
- libblas=3.8.0=14_mkl
- libcroco=0.6.13=h8d621e5_0
- libedit=3.1.20181209=hc058e9b_0
- libffi=3.2.1=hd88cf55_4
- libgcc=7.2.0=h69d50b8_2
- libgcc-ng=9.1.0=hdf63c60_0
- libgfortran-ng=7.3.0=hdf63c60_0
- libiconv=1.15=h516909a_1006
- liblapack=3.8.0=14_mkl
- libpng=1.6.37=hbc83047_0
- libprotobuf=3.11.4=hd408876_0
- librsvg=2.46.2=h33a7fed_1
- libsodium=1.0.16=h1bed415_0
- libstdcxx-ng=9.1.0=hdf63c60_0
- libtiff=4.1.0=h2733197_0
- libuuid=2.32.1=h14c3975_1000
- libxcb=1.13=h1bed415_1
- libxml2=2.9.9=hea5a465_1
- markdown=3.1.1=py37_0
- markupsafe=1.1.1=py37h7b6447c_0
- matplotlib=3.1.1=py37h5429711_0
- mistune=0.8.4=py37h7b6447c_0
- mkl=2019.4=243
- mkl-service=2.3.0=py37he904b0f_0
- mkl_fft=1.0.15=py37ha843d7b_0
- mkl_random=1.1.0=py37hd6b4f25_0
- nbconvert=5.6.1=py37_0
- nbformat=5.0.4=py_0
- ncurses=6.2=he6710b0_0
- ninja=1.9.0=py37hfd86e86_0
- notebook=6.0.1=py37_0
- numpy=1.18.1=py37h4f9e942_0
- numpy-base=1.18.1=py37hde5b4d6_1
- olefile=0.46=py37_0
- openssl=1.1.1e=h7b6447c_0
- pandoc=2.2.3.2=0
- pandocfilters=1.4.2=py37_1
- pango=1.42.4=h7062337_3
- parso=0.6.2=py_0
- pcre=8.43=he6710b0_0
- pexpect=4.8.0=py37_0
- pickleshare=0.7.5=py37_0
- pillow=7.0.0=py37hb39fc2d_0
- pip=20.0.2=py37_1
- pixman=0.38.0=h7b6447c_0
- prometheus_client=0.7.1=py_0
- prompt-toolkit=3.0.4=py_0
- prompt_toolkit=3.0.4=0
- ptyprocess=0.6.0=py37_0
- pycparser=2.20=py_0
- pygments=2.6.1=py_0
- pyparsing=2.4.6=py_0
- pyqt=5.9.2=py37h05f1152_2
- pyrsistent=0.15.7=py37h7b6447c_0
- python=3.7.7=hcf32534_0_cpython
- python-dateutil=2.8.1=py_0
- python-spams=2.6.1=py37h55324e4_1204
- pytorch=1.3.1=py3.7_cuda10.1.243_cudnn7.6.3_0
- pytz=2019.3=py_0
- pyzmq=18.1.1=py37he6710b0_0
- qt=5.9.7=h5867ecd_1
- readline=8.0=h7b6447c_0
- scipy=1.4.1=py37h0b6359f_0
- send2trash=1.5.0=py37_0
- setuptools=45.3.0=py37_0
- sip=4.19.8=py37hf484d3e_0
- six=1.14.0=py37_0
- sqlite=3.31.1=h7b6447c_0
- tensorboard=1.14.0=py37hf484d3e_0
- tensorflow=1.14.0=mkl_py37h45c423b_0
- tensorflow-base=1.14.0=mkl_py37h7ce6ba3_0
- tensorflow-estimator=1.14.0=py_0
- termcolor=1.1.0=py37_1
- terminado=0.8.3=py37_0
- testpath=0.4.4=py_0
- tk=8.6.8=hbc83047_0
- tornado=6.0.4=py37h7b6447c_1
- traitlets=4.3.3=py37_0
- wcwidth=0.1.8=py_0
- werkzeug=1.0.0=py_0
- wheel=0.34.2=py37_0
- wrapt=1.12.1=py37h7b6447c_1
- xorg-kbproto=1.0.7=h14c3975_1002
- xorg-libice=1.0.10=h516909a_0
- xorg-libsm=1.2.3=h84519dc_1000
- xorg-libx11=1.6.9=h516909a_0
- xorg-libxext=1.3.4=h516909a_0
- xorg-libxrender=0.9.10=h516909a_1002
- xorg-renderproto=0.11.1=h14c3975_1002
- xorg-xextproto=7.3.0=h14c3975_1002
- xorg-xproto=7.0.31=h14c3975_1007
- xz=5.2.4=h14c3975_4
- zeromq=4.3.1=he6710b0_3
- zipp=2.2.0=py_0
- zlib=1.2.11=h7b6447c_3
- zstd=1.3.7=h0b5b093_0
- pip:
- 2to3==1.0
- asciitree==0.3.3
- asgiref==2.3.2
- asn1crypto==1.2.0
- async-timeout==3.0.1
- atomicwrites==1.3.0
- autobahn==19.5.1
- automat==0.8.0
- bleach==3.1.0
- channels==2.1.7
- chardet==3.0.4
- click==7.0
- codacy-coverage==1.3.11
- constantly==15.1.0
- coverage==4.5.4
- cryptography==2.3.1
- daphne==2.2.5
- django==2.2.7
- djangorestframework==3.9.4
- fasteners==0.15
- filelock==3.0.12
- flask==1.0.2
- future==0.18.2
- hyperlink==19.0.0
- idna==2.8
- imagecodecs==2020.2.18
- imageio==2.6.1
- incremental==17.5.0
- intervaltree==3.0.2
- itsdangerous==1.1.0
- joblib==0.14.0
- jsonfield2==3.0.3
- jsonschema==2.6.0
- lmdb==0.98
- lxml==4.2.1
- lz4==2.2.1
- monotonic==1.5
- mypy-extensions==0.4.3
- ndg-httpsclient==0.5.0
- networkx==2.4
- numcodecs==0.6.4
- opencv-python==4.1.1.26
- openslide-python==1.1.1
- openslides==3.0
- packaging==19.2
- pandas==0.25.3
- pkgconfig==1.5.1
- pluggy==0.13.1
- progressbar2==3.43.1
- protobuf==3.10.0
- py==1.8.0
- pyasn1==0.4.3
- pyflann==1.6.14
- pyhamcrest==1.9.0
- pyopenssl==18.0.0
- PyPDF2==1.26.0
- pytest==4.6.2
- pytest-cov==2.7.1
- python-utils==2.3.0
- pywavelets==1.1.1
- pyyaml==3.13
- requests==2.22.0
- requests-mock==1.5.2
- roman==3.1
- scikit-image==0.16.2
- scikit-learn==0.22.1
- seaborn==0.9.0
- sklearn==0.0
- sortedcontainers==2.1.0
- sqlparse==0.3.0
- tensorboardx==1.9
- tifffile==2020.2.16
- toml==0.10.0
- torchsummary==1.5.1
- torchvision==0.1.8
- tox==3.13.2
- tqdm==4.37.0
- twisted==19.7.0
- txaio==18.8.1
- typing-extensions==3.7.4.1
- urllib3==1.25.7
- virtualenv==16.7.7
- webencodings==0.5.1
- websockets==8.1
- zarr==2.3.2
- zope-interface==4.6.0
prefix: /home/fedshyvana/anaconda3/envs/deep_learning
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