Download Tensorflow Mac 2
To install packages like TensorFlow, you can use pip on Python 2 systems or pip3 on Python 3 systems. Package management commands.
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 3.5–3.7
- 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) (Python 3 only)
- 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 3.5–3.7 and pip >= 19.0 If these packages are already installed, skip to the next step.
Otherwise, install Python, the pip package manager, and Virtualenv:
Ubuntu
mac OS
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 not in a virtual environment, use
python3 -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 / mac OS
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 virtualenv 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 virtualenv 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 virtualenv later:
Conda
While we recommend the TensorFlow-provided pip package, a community-supportedAnaconda package is available. Create a new virtual environment by choosing a Python interpreter and making a ./venv
directory to hold it:
Activate the virtual environment:
Within the virtual environment, install the TensorFlow pip package using its complete URL: Autocad for mac os x 10.7.5.
And to exit virtualenv later:
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
.Virtualenv install
Verify the install:
System install
Verify the install:
Success: TensorFlow is now installed. Read the tutorials to get started.Package location
A few installation mechanisms require the URL of the TensorFlow Python package. The value you specify depends on your Python version.
Version | URL |
---|---|
Linux | |
Python 2.7 GPU support | https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.1.0-cp27-cp27mu-manylinux2010_x86_64.whl |
Python 2.7 CPU-only | https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.1.0-cp27-cp27mu-manylinux2010_x86_64.whl |
Python 3.5 GPU support | https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.1.0-cp35-cp35m-manylinux2010_x86_64.whl |
Python 3.5 CPU-only | https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.1.0-cp35-cp35m-manylinux2010_x86_64.whl |
Python 3.6 GPU support | https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.1.0-cp36-cp36m-manylinux2010_x86_64.whl |
Python 3.6 CPU-only | https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.1.0-cp36-cp36m-manylinux2010_x86_64.whl |
Python 3.7 GPU support | https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.1.0-cp37-cp37m-manylinux2010_x86_64.whl |
Python 3.7 CPU-only | https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.1.0-cp37-cp37m-manylinux2010_x86_64.whl |
macOS (CPU-only) | |
Python 2.7 | https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.1.0-cp27-cp27m-macosx_10_9_x86_64.whl |
Python 3.5 | https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.1.0-cp35-cp35m-macosx_10_6_intel.whl |
Python 3.6 | https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.1.0-cp36-cp36m-macosx_10_9_x86_64.whl |
Python 3.7 | https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.1.0-cp37-cp37m-macosx_10_9_x86_64.whl |
Windows | |
Python 3.5 GPU support | https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.1.0-cp35-cp35m-win_amd64.whl |
Python 3.5 CPU-only | https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.1.0-cp35-cp35m-win_amd64.whl |
Python 3.6 GPU support | https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.1.0-cp36-cp36m-win_amd64.whl |
Python 3.6 CPU-only | https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.1.0-cp36-cp36m-win_amd64.whl |
Python 3.7 GPU support | https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.1.0-cp37-cp37m-win_amd64.whl |
Python 3.7 CPU-only | https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.1.0-cp37-cp37m-win_amd64.whl |
Raspberry PI (CPU-only) | |
Python 3, Pi0 or Pi1 | https://storage.googleapis.com/tensorflow/raspberrypi/tensorflow-2.1.0-cp35-none-linux_armv6l.whl |
Python 3, Pi2 or Pi3 | https://storage.googleapis.com/tensorflow/raspberrypi/tensorflow-2.1.0-cp35-none-linux_armv7l.whl |