Getting started with JupyterLab
The installation guide contains more detailed instructions
However, if you're on an older version of Raspbian, you can still install PIP. On Python 2.x: sudo apt-get install python-pip. On Python 3.x: sudo apt-get install python3-pip. With Raspbian, Python 2.x users should use pip while Python 3.x users should use pip3 when issuing PIP commands.
Pip install -upgrade pip pip list # show packages installed within the virtual environment And to exit the virtual environment later: deactivate # don't exit until you're done using TensorFlow. I want to install pip for python 2.7 on my Mac. I think this is the python located in /usr/bin/python. Unfortunately I have already installed Anaconda, which installs python 3.6.3, and changes things so that the command python xxx.py automatically runs xxx.py using python 3.6.3. Actually pip.exe in windows is an python script as others in /scripts directory, but wraped in exe to run it with default python interpreter. By opening pip.exe with 7-zip you can see main.py importing pip, sys and re modules. (And there you'll find the answer how to run it within a python shell)- pip is a regular python module. If you use pip, you can install it with: pip install jupyterlab If installing using pip install -user, you must add the user-level bin directory to your PATH environment variable in order to launch jupyter lab.
Install with conda
If you use conda
, you can install it with:
Install with pip
If you use pip
, you can install it with:
If installing using pip install --user
, you must add the user-level bin
directory to your PATH
environment variable in order to launch jupyter lab
. If you are using a Unix derivative (FreeBSD, GNU / Linux, OS X), you can achieve this by using export PATH='$HOME/.local/bin:$PATH'
command.
Run JupyterLab
Once installed, launch JupyterLab with:
Getting started with the classic Jupyter Notebook
conda
We recommend installing the classic Jupyter Notebook using the conda package manager. Either the miniconda or the miniforge conda distributions include a minimal conda installation.
Then you can install the notebook with:
Mac Python 3 Pip Install
pip
If you use pip
, you can install it with:
Congratulations, you have installed Jupyter Notebook! To run the notebook, run the following command at the Terminal (Mac/Linux) or Command Prompt (Windows):
See Running the Notebook for more details.
Getting started with Voilà
Installation
Voilà can be installed using conda
or pip
. For more detailed instructions, consult the installation guide.
conda
If you use conda
, you can install it with:
pip
If you use pip
, you can install it with:
TensorFlow 2 packages are available
tensorflow
—Latest stable release with CPU and GPU support(Ubuntu and Windows)tf-nightly
—Preview build (unstable). Ubuntu and Windows include GPU support.
Older versions of TensorFlow
For TensorFlow 1.x, CPU and GPU packages are separate:
tensorflow1.15
—Release for CPU-onlytensorflow-gpu1.15
—Release with GPU support(Ubuntu and Windows)
System requirements
- Python 3.6–3.8
- Python 3.8 support requires TensorFlow 2.2 or later.
- pip 19.0 or later (requires
manylinux2010
support) - Ubuntu 16.04 or later (64-bit)
- macOS 10.12.6 (Sierra) or later (64-bit) (no GPU support)
- Windows 7 or later (64-bit)
- Raspbian 9.0 or later
- GPU support requires a CUDA®-enabled card (Ubuntu and Windows)
pip
.Hardware requirements
- Starting with TensorFlow 1.6, binaries use AVX instructions which may not run on older CPUs.
- Read the GPU support guide to set up a CUDA®-enabled GPU card on Ubuntu or Windows.
1. Install the Python development environment on your system
Check if your Python environment is already configured:
Requires Python 3.6–3.8, pip and venv >= 19.0 If these packages are already installed, skip to the next step.
Otherwise, install Python, the pip package manager, and venv:
Ubuntu
macOS
Install using the Homebrew package manager:
Windows
Install the Microsoft Visual C++ Redistributable for Visual Studio 2015, 2017, and 2019. Starting with the TensorFlow 2.1.0 version, the msvcp140_1.dll
file is required from this package (which may not be provided from older redistributable packages). The redistributable comes with Visual Studio 2019 but can be installed separately:
- Go to the Microsoft Visual C++ downloads,
- Scroll down the page to the Visual Studio 2015, 2017 and 2019 section.
- Download and install the Microsoft Visual C++ Redistributable for Visual Studio 2015, 2017 and 2019 for your platform.
Make sure long paths are enabled on Windows.
Install the 64-bitPython 3 release for Windows (select pip
as an optional feature).
Raspberry Pi
Requirements for the Raspbian operating system:
Other
If
Python Pip Install Tkinter Mac
not in a virtual environment, usepython3 -m pip
for the commands below. This ensures that you upgrade and use the Python pip instead of the system pip.2. Create a virtual environment (recommended)
Python virtual environments are used to isolate package installation from the system.
Ubuntu / macOS
Create a new virtual environment by choosing a Python interpreter and making a ./venv
directory to hold it:
Activate the virtual environment using a shell-specific command:
When the virtual environment is active, your shell prompt is prefixed with (venv)
.
Install packages within a virtual environment without affecting the host system setup. Start by upgrading pip
:
And to exit the virtual environment later:
Windows
Create a new virtual environment by choosing a Python interpreter and making a .venv
directory to hold it:
Activate the virtual environment:
Install packages within a virtual environment without affecting the host system setup. Start by upgrading pip
:
And to exit the virtual environment later:
Conda
While the TensorFlow provided pip package is recommended, acommunity-supportedAnaconda packageis available. To install, read the Anaconda TensorFlow guide.
3. Install the TensorFlow pip package
Choose one of the following TensorFlow packages to install from PyPI:
tensorflow
—Latest stable release with CPU and GPU support(Ubuntu and Windows).tf-nightly
—Preview build (unstable). Ubuntu and Windows include GPU support.tensorflow1.15
—The final version of TensorFlow 1.x.
setup.py
file under REQUIRED_PACKAGES
.Virtual environment install
Verify the install:
System install
Verify the install:
Success: If a tensor is returned, you've installed TensorFlow successfully. Read the tutorials to get started.Package location
Python Install Pip Mac Brew
A few installation mechanisms require the URL of the TensorFlow Python package. The value you specify depends on your Python version.
Mac Python Pip Install
Version | URL |
---|---|
Linux | |
Python 3.6 GPU support | https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.4.0-cp36-cp36m-manylinux2010_x86_64.whl |
Python 3.6 CPU-only | https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.4.0-cp36-cp36m-manylinux2010_x86_64.whl |
Python 3.7 GPU support | https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.4.0-cp37-cp37m-manylinux2010_x86_64.whl |
Python 3.7 CPU-only | https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.4.0-cp37-cp37m-manylinux2010_x86_64.whl |
Python 3.8 GPU support | https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.4.0-cp38-cp38-manylinux2010_x86_64.whl |
Python 3.8 CPU-only | https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.4.0-cp38-cp38-manylinux2010_x86_64.whl |
macOS (CPU-only) | |
Python 3.6 | https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.4.0-cp36-cp36m-macosx_10_9_x86_64.whl |
Python 3.7 | https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.4.0-cp37-cp37m-macosx_10_9_x86_64.whl |
Python 3.8 | https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.4.0-cp38-cp38-macosx_10_14_x86_64.whl |
Windows | |
Python 3.6 GPU support | https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.4.0-cp36-cp36m-win_amd64.whl |
Python 3.6 CPU-only | https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.4.0-cp36-cp36m-win_amd64.whl |
Python 3.7 GPU support | https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.4.0-cp37-cp37m-win_amd64.whl |
Python 3.7 CPU-only | https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.4.0-cp37-cp37m-win_amd64.whl |
Python 3.8 GPU support | https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.4.0-cp38-cp38-win_amd64.whl |
Python 3.8 CPU-only | https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.4.0-cp38-cp38-win_amd64.whl |
Raspberry PI (CPU-only) | |
Python 3, Pi0 or Pi1 | https://storage.googleapis.com/tensorflow/raspberrypi/tensorflow-2.3.0rc2-cp35-none-linux_armv6l.whl |
Python 3, Pi2 or Pi3 | https://storage.googleapis.com/tensorflow/raspberrypi/tensorflow-2.3.0rc2-cp35-none-linux_armv6l.whl |