echoger.blogg.se - Pip3 upgrade

run ( a + b )) 42 > Run a TensorFlow demo modelĪll TensorFlow packages, including the demo models, are installed in the Python library. run ( hello )) Hello, TensorFlow ! > a = tf. constant ( 'Hello, TensorFlow!' ) > sess = tf. NOTE: If you are upgrading from a previous installation of TensorFlow > import tensorflow as tf com / tensorflow / mac / tensorflow - 0.8. $ sudo pip3 install - upgrade https :// storage. com / tensorflow / linux / gpu / tensorflow - 0.8. com / tensorflow / linux / cpu / tensorflow - 0.8. whlįor python3: # Ubuntu/Linux 64-bit, CPU only: $ sudo pip install - upgrade https :// storage. For # other versions, see "Install from sources" below. Install TensorFlow: # Ubuntu/Linux 64-bit, CPU only: $ sudo apt - get install python - pip python - dev

Install pip (or pip3 for python3) if it is not already installed: # Ubuntu/Linux 64-bit The packages that will be installed or upgraded during the pip install are listed in the REQUIRED_PACKAGES section of setup.py Pip is a package management system used to install and manage software packages written in Python. If you encounter installation errors, see common problems for some solutions. The names of the pip and Docker images are listed in the corresponding installation sections. If you are familiar with Pip, Virtualenv, Anaconda, or Docker, please feel free to adapt the instructions to your particular needs.

Docker install: Run TensorFlow in a Docker container isolated from all other programs on your machine.

Does not impact existing Python programs on your machine.

Anaconda install: Install TensorFlow in its own environment for those running the Anaconda Python distribution.

Virtualenv install: Install TensorFlow in its own directory, not impacting any existing Python programs on your machine.

May impact existing Python programs on your machine.

Pip install: Install TensorFlow on your machine, possibly upgrading previously installed Python packages.

We support different ways to install TensorFlow: Please see Cuda installation for details. other versions are supported (Cuda toolkit >= 7.0 and cuDNN 6.5(v2), 7.0(v3), v5) only when installing from sources. The GPU version (Linux only) works best with Cuda Toolkit 7.5 and cuDNN v4. The TensorFlow Python API supports Python 2.7 and Python 3.3+. You can install TensorFlow either from our provided binary packages or from the github source.