Caffe2

Note

We no longer include the CNTK, Caffe, Caffe2 and Theano Conda environments in the AWS Deep Learning AMI starting with the v28 release. Previous releases of the AWS Deep Learning AMI that contain these environments will continue to be available. However, we will only provide updates to these environments if there are security fixes published by the open source community for these frameworks.

Caffe2 Tutorial

To activate the framework, follow these instructions on your Deep Learning AMI with Conda.

There is only the Python 2 with CUDA 9 with cuDNN 7 option:

$ source activate caffe2_p27
         

Start the iPython terminal.

(caffe2_p27)$ ipython

Run a quick Caffe2 program.

from caffe2.python import workspace, model_helper
import numpy as np
# Create random tensor of three dimensions
x = np.random.rand(4, 3, 2)
print(x)
print(x.shape)
workspace.FeedBlob("my_x", x)
x2 = workspace.FetchBlob("my_x")
print(x2)

You should see the initial numpy random arrays printed and then those loaded into a Caffe2 blob. Note that after loading they are the same.

More Tutorials

For more tutorials and examples refer to the framework's official Python docs, Python API for Caffe2, and the Caffe2 website.