tf-gpu.yml

name: tf-gpu
channels:
  - aaronzs
  - anaconda
  - defaults
dependencies:
  - absl-py=0.8.1=py36_0
  - astor=0.8.0=py36_0
  - blas=1.0=mkl
  - ca-certificates=2019.11.27=0
  - certifi=2019.11.28=py36_0
  - cudatoolkit=10.2.89=h74a9793_0
  - cudnn=7.6.5=cuda10.2_0
  - gast=0.3.2=py_0
  - grpcio=1.16.1=py36h351948d_1
  - icc_rt=2019.0.0=h0cc432a_1
  - intel-openmp=2019.4=245
  - libprotobuf=3.11.2=h7bd577a_0
  - markdown=3.1.1=py36_0
  - mkl=2019.4=245
  - mkl-service=2.3.0=py36hb782905_0
  - mkl_fft=1.0.15=py36h14836fe_0
  - mkl_random=1.1.0=py36h675688f_0
  - numpy=1.17.4=py36h4320e6b_0
  - numpy-base=1.17.4=py36hc3f5095_0
  - openssl=1.1.1=he774522_0
  - pip=19.3.1=py36_0
  - protobuf=3.11.2=py36h33f27b4_0
  - python=3.6.10=h9f7ef89_0
  - setuptools=44.0.0=py36_0
  - six=1.13.0=py36_0
  - sqlite=3.30.1=he774522_0
  - tensorboard=1.9.0=py36_0
  - tensorflow-gpu=1.9.0=py36_0
  - termcolor=1.1.0=py36_1
  - vc=14.1=h0510ff6_4
  - vs2015_runtime=14.16.27012=hf0eaf9b_1
  - werkzeug=0.16.0=py_0
  - wheel=0.33.6=py36_0
  - wincertstore=0.2=py36h7fe50ca_0
  - zlib=1.2.11=h62dcd97_3
  - pip:
    - cycler==0.10.0
    - joblib==0.14.1
    - kiwisolver==1.1.0
    - matplotlib==3.1.2
    - pandas==0.25.3
    - pyparsing==2.4.6
    - python-dateutil==2.8.1
    - pytz==2019.3
    - scikit-learn==0.22.1
    - scipy==1.4.1
    - sklearn==0.0
    - tfann==1.0.1
prefix: C:\Users\nickt\Anaconda3\envs\tf-gpu