KERAS
Keras is a minimalist, highly modular neural networks library written in Python and capable of running on top of either TensorFlow or Theano.
Sample scripts for Keras use are available in directory /opt/packages/examples/keras on Bridges.
Documentation
Usage
To use Keras, you must load the appropriate Keras module, then activate the virtual environment and launch python. Once python is launched, you can import keras or other specific software.
Find and load the appropriate Keras module
To see what versions of Keras are available type
module avail keras
Note that the names of the keras modules reflect the software it has been built with. For example, the module keras/2.2.0_tf1.7_py2_gpu establishes an environment
- using Keras 2.2.0, TensorFlow 1.7, and Python2
- for use on GPUs
To see what other modules are needed, what commands are available and how to get additional help type
module help keras
Use a command like this in your batch script or interactive session to load the keras module. This command loads the default keras module. Be sure to load the specific module you need by using its full name.
module load keras
Loading the keras module will also load other necessary modules for you. You can list those with the module list command. Check to see if there are others you need to load manually by typing the module help keras command.
Activate the virtual environment, launch python, import needed software
Use the source activate command to load the virtual environment
source activate
Start python.
python
Add any necessary software with the import command.
import keras
Example
Here is an example of using Keras on Bridges. In this example, an interactive session has been started in one of Bridges’ GPU partitions. To read more about Bridges’ partitions and how to use interactive sessions, see the Running Jobs section of the Bridges User Guide.
[joeuser@gpu045 keras]$ module available keras ---------- /opt/modulefiles ------------ keras/1.1.2 keras/2.0.4 keras/2.0.6_anaconda keras/2.0.6_anaconda_nogpu keras/2.2.0_tf1.7_py2_gpu keras/2.2.0_tf1.7_py3_gpu [joeuser@gpu045 keras]$ module load keras/2.2.0_tf1.7_py3_gpu [joeuser@gpu045 keras]$ module list Currently Loaded Modulefiles: 1) psc_path/1.1 4) cuda/9.0 7) python/3.6.4_gcc5_np1.14.5 2) slurm/default 5) mpi/gcc_openmpi 8) tensorflow/1.7_py3_gpu 3) gcc/5.3.0 6) phdf5/1.10.2_gnu_openmpi 9) keras/2.2.0_tf1.7_py3_gpu [joeuser@gpu045 keras]$ source activate (tf1.7_py3_gpu) [joeuser@gpu045 keras]$ python Python 3.6.4 (default, Jun 28 2018, 13:20:07) [GCC 5.3.0] on linux Type "help", "copyright", "credits" or "license" for more information. >>> import keras Using TensorFlow backend. >>> print(keras.__version__) 2.2.0 >>> import pandas >>> print(pandas.__version__) 0.23.1 >>> (tf1.7_py3_gpu) [joeuser@gpu045 keras]$ deactivate