Install Tensorflow-GPU in 5 mins - EASY!!
Why Stack Overflow recommends it
Stack Overflow users link it as the walkthrough they followed for a GPU TensorFlow setup in Anaconda, usually when asking why the resulting environment throws errors or does not use the GPU.
Recommended by 4 people across 4 different months, 2019 to 2021.
What it is
A short screen-recorded tutorial from the channel thehardwareguy showing how to install tensorflow-gpu through the Anaconda distribution on Windows 10, then use it in Jupyter notebooks. It notes that macOS follows nearly the same steps apart from one command, and links an article version.
What people said
Recommends VI11age_ID10T · 2019-08 · Stack Overflow · on “Tensorflow 2.0 beta GPU running in jupyter notebook, but not in google colab”
I am working with tensorflow 2.0 beta, and while i managed to get my GPU working on anaconda through a few youtube tutorials I am unable to get my gpu running in google colab. I know google has the option to enable a gpu from one of their servers but My GTX 1070 is much faster, and i need to run off colab and not just Jupyter exclusively. So I read the documentation [LINK] like a good boy and the only thing i think i could have done wrong is my path settings I have screenshots bellow. I followed several different youtube tutorials faithfully until the final one here [this video] gave me a way to install it to jupyter. Which is great, but I also need it to run on google colab as well. I've been tr
Recommends Falseee · 2019-09 · Stack Overflow · on “Cannot set up tensorflow gpu object detection”
I tried to follow a tutorial on how to setup tensorflow gpu ( [this video] ) but on the jupyter step i am getting this error : [LINK] (ive set in in a pastebin because its very long) I dont know what to do, ive also tried others tutorial but none of the others works, they also got errors ( but they are differents) at the jupyter step. import numpy as np import os import six.moves.urllib as urllib import sys import tarfile import tensorflow as tf import zipfile from distutils.version import StrictVersion from collections import defaultdict from io import StringIO from matplotlib import pyplot as plt from PIL import Image # This is needed since the notebook is stored in the object_detection folder.
Recommends Isara De Silva · 2020-02 · Stack Overflow · on “How to downgrade hdf5 installed with tensorflow-gpu”
recently i have tried to install tensorflow-gpu following [this video] this video But when I try to import tensorflow (or keras) my kernal dies giving following error message. C:\Users\ovin\Anaconda3\envs\GPU\lib\site-packages\h5py\__init__.py:40: UserWarning: h5py is running against HDF5 1.10.5 when it was built against 1.10.4, this may cause problems '{0}.{1}.{2}'.format(*version.hdf5_built_version_tuple) Warning! HDF5 library version mismatched error The HDF5 header files used to compile this application do not match the version used by the HDF5 library to which this application is linked. Data corruption or segmentation faults may occur if the application continues. This can happen when an ap
Recommends odd_wolf · 2021-04 · Stack Overflow · on “ImportError: No module named 'tensorflow' using anaconda + windows”
First check which environment you are using right now. If it helps open the anaconda navigator and see whether you have TensorFlow installed in the "installed" tab of that particular environment. Check the following on jupyter noteook and see what python version you're using in that environment because the environment that you are using might have a different python version after all. from platform import python_version print(python_version()) If the versions are different, try removing the TensorFlow installation and reinstalling it according to your python version. environment and recreating the same environment pip install --ignore-installed --upgrade tensorflow==' version_for_your_requir
Cites zbeedatm · 2019-08 · Stack Overflow · on “jupyter nternalError: cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version”
I installed anaconda 3.7 on windows (following this guide: [this video] ) and then tried to run a code using tensorflow ( [LINK] ) from jupyter notebook but I'm getting: InternalError: cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version When looking for my cuda version: > where cudnn* C:\Users\\Anaconda3\envs\gputest\Library\bin\cudnn64_7.dll (gputest) C:\windows\system32>pip show tensorflow Name: tensorflow Version: 1.13.1 Summary: TensorFlow is an open source machine learning framework for everyone. Home-page: [LINK] Author: Google Inc. Author-email: opensource@google.com License: Apache 2.0 Location: c:\users\...\anaconda3\envs\gputest\lib\site-packages
Cites AdeDoyle · 2020-10 · Stack Overflow · on “Why am I getting "[Errno 13] Permission denied" when trying to create a tensorflow environment in Anaconda Prompt?”
I had originally followed this tutorial to create a tensorflow-gpu enviornment using my original install of Anaconda (base environment using Python 3.7): [this video] This worked. The issues started when I tried to follow this more recent tutorial to get a newer version of tensorflow which defaults to GPU: [LINK] In this second tutorial it seems to recommend installing it in your base environment. I instead tried to create an environment for it as per the first tutorial.
Cites Dani · 2020-12 · Stack Overflow · on “How to run tensorflow-gpu”
I have one problem, my jupyter Notebook does not run on the gpu. I updated my Driver (Nvidia GTX 1660 Ti), installed CUDA 11, put the CuDNN-files into the folders and put the correct path in the environmental variables. After doing that, I added a new environment to Anaconda including a GPU-kernel and installed tensorflow-gpu (Version 2.4, because CUDA 11 needs Version >= 2.4.0), like it is explained in this video [this video] . After that I opened jupyter notebook with the new kernel. So I can run my code and until a certain step that works, but my GPU utilization in the task manager is below 1% and my RAM is at 60%-99%. So I think, my code isn't running on the GPU. I made a few tests: import te
Cites adriens63 · 2021-07 · Stack Overflow · on “tensorflow-gpu can't execute certain cells as t = tf.Variable(5), but detects my gpu”
Here are my specs : Ubuntu 20.04 tried tensorflow-gpu version 2.0 to 2.5 cuda and cudnn downloaded with conda : cuda 10.1, cudnn 7.6.5 I followed this tutorial [this video] (it lasts 5 minutes, and some comments say it works in the past month) step by step, even try the solutions in the comments : conda create -n tfgpu python=3.7 conda activate tfgpu conda install tensorflow-gpu=2.1 pip uninstall tensorflow pip uninstall tensorflow-estimator pip uninstall tensorboard pip uninstall tensorboard-plugin-wit pip install tensorflow==2.3 pip check to downgrade to many versions, I have tried all the possible combinations and versions, by rebuilding environments from scratch. In some versions, tf detects