How to download tensorflow version 1.12.0 using pip

 · I uninstalled the pre-installed version of Tensorflow on Google Colab by using!pip uninstall tensorflow -y and then!pip uninstall tensorflow-gpu -y. Then I installed the version I desired!pip install tensorflow-gpu== which seems to work and it .  · TensorFlow is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain.  · By using this, you can downgrade to almost every availale version in combination with the respective for python. For example: pip install tensorflow== (note that previous to installing Python alongside version in my case, you would get this.

TensorFlow Lite on Raspberry Pi 4 can achieve performance comparable to NVIDIA's Jetson Nano at a fraction of the cost. With the new Raspberry Pi (image credit: bltadwin.ru) shipping worldwide, you might be wondering: can this little powerhouse board be used for Machine Learning? The answer is, yes!TensorFlow Lite models running on Raspberry Pi 4 boards can achieve performance. System information OS Platform and Distribution: Linux Ubuntu TensorFlow installed from (source or binary): pip install tensorflow-gpu TensorFlow version: version Python version: how to install tensorflow version with pip. Ask Question Asked 2 years, 7 months ago. Active 5 months ago. Viewed 26k times 4 1. I need the specific tensorflow-gpu version for my application as i have cuda-9 in my system. I am able to find the whl file for tensorflow cpu, but not able to locate the same for tensorflow-gpu.

The TensorFlow pip package includes GPU support for CUDA®-enabled cards: pip install tensorflow. This guide covers GPU support and installation steps for the latest stable TensorFlow release. Older versions of TensorFlow. For releases and older, CPU and GPU packages are separate: pip install tensorflow== # CPU pip install tensorflow. I uninstalled the pre-installed version of Tensorflow on Google Colab by using!pip uninstall tensorflow -y and then!pip uninstall tensorflow-gpu -y. Then I installed the version I desired!pip install tensorflow-gpu== which seems to work and it outputs Successfully installed tensorflow-gpu The TensorFlow Docker images are already configured to run TensorFlow. A Docker container runs in a virtual environment and is the easiest way to set up GPU support. docker pull tensorflow/tensorflow:latest # Download latest stable image docker run -it -p tensorflow/tensorflow:latest-jupyter # Start Jupyter server.