Setting_up_TensorFlow_Conda_Environment/Install TensorFlow under Conda Env on Linux.md

In John-R-Wallace-NOAA/FishNIRS: NIRS on fish structures.

# In a bash shell under Linux

# Install Miniconda
bash Miniconda3-latest-Linux-x86_64.sh

# If you'd prefer that conda's base environment not be activated on startup, 
#   set the auto_activate_base parameter to false:

conda config --set auto_activate_base false


# In the first two sections of code below, the only real difference is that for the CPU version "tensorflow" is installed, 
#    and for the gpu version "tensorflow-gpu" is installed.


# ---------- Tensorflow CPU only, no GPU nor TensorRT. (Using the conda-forge package manager.) --------------

conda create -y -p tf_cpu_only python=3.8

conda env list

# If there is no name given using 'conda env list' use the full path, 
#     e.g.: conda activate /more_home/h_jwallace/Python/tf_cpu_only
conda activate tf_cpu_only

python --version

conda install -y -c conda-forge cudatoolkit=11.2 cudnn=8.1.0

# If versions and builds are not listed below, something went wrong
conda list cudatoolkit

conda list cudnn

# Check CUDA installation 
nvcc --version # If nvcc is installed
conda list cuda

# conda install tensorflow -c conda-forge    
conda install -y -c conda-forge tensorflow=2.10.1

# Find version number of tensorflow
conda list tensorflow

# Verfiy TensorFlow using an interactive approach
python
>>> 
import tensorflow as tf
print(tf.__version__)
print(tf)

tf.config.list_physical_devices('CPU')
tf.config.list_physical_devices('GPU')

a = tf.constant(7)
b = tf.constant(10)
print(tf.add(a,b))

print(tf.reduce_sum(tf.random.normal([1000, 1000])))

quit()
>>>

conda deactivate

John-R-Wallace-NOAA/FishNIRS documentation built on April 12, 2025, 12:59 a.m.