Keras
Keras Tutorial
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To activate the framework, use these commands on your Using the Deep Learning AMI with Conda CLI.
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For Keras 2 with an MXNet backend on Python 3 with CUDA 9 with cuDNN 7:
$
source activate mxnet_p36 -
For Keras 2 with an MXNet backend on Python 2 with CUDA 9 with cuDNN 7:
$
source activate mxnet_p27 -
For Keras 2 with a TensorFlow backend on Python 3 with CUDA 9 with cuDNN 7:
$
source activate tensorflow_p36 -
For Keras 2 with a TensorFlow backend on Python 2 with CUDA 9 with cuDNN 7:
$
source activate tensorflow_p27
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To test importing Keras to verify which backend is activated, use these commands:
$
ipython import keras as kThe following should appear on your screen:
Using MXNet backend
If Keras is using TensorFlow, the following is displayed:
Using TensorFlow backend
Note
If you get an error, or if the wrong backend is still being used, you can update your Keras configuration manually. Edit the
~/.keras/keras.json
file and change the backend setting tomxnet
ortensorflow
.
More Tutorials
For a multi-GPU tutorial using Keras with a MXNet backend, try the Keras-MXNet Multi-GPU Training Tutorial.
You can find examples for Keras with a MXNet backend in the Deep Learning AMI with Conda
~/examples/keras-mxnet
directory.You can find examples for Keras with a TensorFlow backend in the Deep Learning AMI with Conda
~/examples/keras
directory.For additional tutorials and examples, see the Keras
website.