Deep Learning AMI (Ubuntu) Version 8.0 - ami-e8a04697 のイメージなんですが、
Comes with latest binaries of deep learning frameworks pre-installed in separate virtual environments: MXNet, TensorFlow, Caffe, Caffe2, PyTorch, Keras, Chainer, Theano and CNTK. Fully-configured with NVidia CUDA, cuDNN and NCCL as well as Intel MKL-DNN
と書いてあるのに、それらは、どうやって使うんでしょうか?
例えば、
>python3
>>> import tensorflow
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ImportError: No module named 'tensorflow'
と言う事になります。
chainer Keras caffe 等々も同様にNo module namedとなります。
ログインした時のSignatureで
Please use one of the following commands to start the required environment with the framework of your choice:
for MXNet(+Keras1) with Python3 (CUDA 9) _____________________ source activate mxnet_p36
for MXNet(+Keras1) with Python2 (CUDA 9) _____________________ source activate mxnet_p27
for TensorFlow(+Keras2) with Python3 (CUDA 8) ________________ source activate tensorflow_p36
for TensorFlow(+Keras2) with Python2 (CUDA 8) ________________ source activate tensorflow_p27
for Theano(+Keras2) with Python3 (CUDA 8) ____________________ source activate theano_p36
for Theano(+Keras2) with Python2 (CUDA 8) ____________________ source activate theano_p27
for PyTorch with Python3 (CUDA 9) ____________________________ source activate pytorch_p36
for PyTorch with Python2 (CUDA 9) ____________________________ source activate pytorch_p27
for CNTK(+Keras2) with Python3 (CUDA 8) ______________________ source activate cntk_p36
for CNTK(+Keras2) with Python2 (CUDA 8) ______________________ source activate cntk_p27
for Caffe2 with Python2 (CUDA 9) _____________________________ source activate caffe2_p27
for Caffe with Python2 (CUDA 8) ______________________________ source activate caffe_p27
for Caffe with Python3 (CUDA 8) ______________________________ source activate caffe_p35
for Chainer with Python2 (CUDA 9) ____________________________ source activate chainer_p27
for Chainer with Python3 (CUDA 9) ____________________________ source activate chainer_p36
for base Python2 (CUDA 9) ____________________________________ source activate python2
for base Python3 (CUDA 9) ____________________________________ source activate python3
上記のような表示が出ていると思います。
もし、 TensorFlow(+Keras2) with Python3 (CUDA 8) で使いたい場合は
$ source activate tensorflow_p36
と最初に打つことで、そのセッションが
TensorFlow(+Keras2) with Python3 (CUDA 8)
の環境になります。
その時、プロンプトがどの環境を利用しているかを表すものに変わります。
(tensorflow_p36) [ec2-user@ip-xxx-xx-xx-1xx ~]$
https://docs.aws.amazon.com/ja_jp/dlami/latest/devguide/tutorial-conda.html