Phriction Projects Wikis Bioimaging And Optics Platform Computers & Servers at the BIOP Software TensorFlow GPU & CARE History Version 4 vs 5
Version 4 vs 5
Version 4 vs 5
Content Changes
Content Changes
Installing TensorFlow with GPU Support for Windows in order to use CARE
# Get latest [[https://www.geforce.com/drivers|NVIDIA drivers]]
# Install Anaconda from `\\svfas6.epfl.ch\biop\public\0 - BIOP Data\0-Install\CARE`
# Download `CARE-TensorFlow-GPU.yml` locally
# Open Anaconda Prompt
# Navigate to where you copied `CARE-TensorFlow-GPU.yml`
# Update Anaconda with `conda update -n base -c defaults conda`
# Create the CARE environement with `conda env create -n care -f CARE-TensorFlow-GPU.yml`
# Activate the environement with `conda activate care`
# Clone the CARE repository with `git clone https://github.com/CSBDeep/CSBDeep.git`
# Run `jupyter notebook` and see if the examples work
D:\care-oli>jupyter --paths
Installing TensorFlow with GPU Support for Windows in order to use CARE
= Prerequisites =
# Get latest [[https://www.geforce.com/drivers|NVIDIA drivers]]
# Get [[https://developer.nvidia.com/cuda-10.0-download-archive|CUDA 10.0 Toolkit]]
# Get [[https://developer.nvidia.com/rdp/cudnn-download|cuDNN for CUDA 10.0]] (Needs you to login)
# Get [[https://www.python.org/downloads/|Python 3.7]]
D:\care-oli>jupyter --paths
Installing TensorFlow with GPU Support for Windows in order to use CARE
# Get latest [[https://www.geforce.com/drivers|NVIDIA drivers]]
# Install Anaconda from `\\svfas6.epfl.ch\biop\public\0 - BIOP Data\0-Install\CARE`
# Download `CARE-TensorFlow-GPU.yml` locally
# Open Anaconda Prompt
# Navigate to where you copied `CARE-TensorFlow-GPU.yml`
# Update Anaconda with `conda update -n base -c defaults conda`= Prerequisites =
# Create the CARE environement with `conda env create -n care -f CARE-TensorFlow-GPU.yml`# Get latest [[https://www.geforce.com/drivers|NVIDIA drivers]]
# Activate the environement with `conda activate care`# Get [[https://developer.nvidia.com/cuda-10.0-download-archive|CUDA 10.0 Toolkit]]
# Clone the CARE repository with `git clone https://github.com/CSBDeep/CSBDeep.git`# Get [[https://developer.nvidia.com/rdp/cudnn-download|cuDNN for CUDA 10.0]] (Needs you to login)
# Run `jupyter notebook` and see if the examples work# Get [[https://www.python.org/downloads/|Python 3.7]]
D:\care-oli>jupyter --paths
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