kerasがgpuバージョンのテンソルフローを使用しているかどうかを確認するにはどうすればよいですか？

Question

私はkerasスクリプトを実行すると、私は次のような出力が得られます。

Using TensorFlow backend. 
2017-06-14 17:40:44.621761: W 
tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow 
library wasn't compiled to use SSE4.1 instructions, but these are 
available on your machine and could speed up CPU computations. 
2017-06-14 17:40:44.621783: W 
tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow 
library wasn't compiled to use SSE4.2 instructions, but these are 
available on your machine and could speed up CPU computations. 
2017-06-14 17:40:44.621788: W 
tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow 
library wasn't compiled to use AVX instructions, but these are 
available on your machine and could speed up CPU computations. 
2017-06-14 17:40:44.621791: W 
tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow 
library wasn't compiled to use AVX2 instructions, but these are 
available on your machine and could speed up CPU computations. 
2017-06-14 17:40:44.621795: W 
tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow 
library wasn't compiled to use FMA instructions, but these are 
available 
on your machine and could speed up CPU computations. 
2017-06-14 17:40:44.721911: I 
tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:901] successful 
NUMA node read from SysFS had negative value (-1), but there must be 
at least one NUMA node, so returning NUMA node zero 
2017-06-14 17:40:44.722288: I 
tensorflow/core/common_runtime/gpu/gpu_device.cc:887] Found device 0 
with properties: 
name: GeForce GTX 850M 
major: 5 minor: 0 memoryClockRate (GHz) 0.9015 
pciBusID 0000:0a:00.0 
Total memory: 3.95GiB 
Free memory: 3.69GiB 
2017-06-14 17:40:44.722302: I 
tensorflow/core/common_runtime/gpu/gpu_device.cc:908] DMA: 0 
2017-06-14 17:40:44.722307: I 
tensorflow/core/common_runtime/gpu/gpu_device.cc:918] 0: Y 
2017-06-14 17:40:44.722312: I 
tensorflow/core/common_runtime/gpu/gpu_device.cc:977] Creating 
TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 850M, 
pci bus id: 0000:0a:00.0) 

これは何を意味するのでしょうか？テンソルフローのGPUまたはCPUバージョンを使用していますか？

ケラスをインストールする前に、私はテンソルフローのGPU版で作業していました。

sudo pip3 listもtensorflow-gpu(1.1.0)と表示され、tensorflow-cpuのようなものはありません。 [このstackoverflowの質問]に言及したコマンドを実行

は、次のようになります：

The TensorFlow library wasn't compiled to use SSE4.1 instructions, 
but these are available on your machine and could speed up CPU 
computations. 
2017-06-14 17:53:31.424793: W 
tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow 
library wasn't compiled to use SSE4.2 instructions, but these are 
available on your machine and could speed up CPU computations. 
2017-06-14 17:53:31.424803: W 
tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow 
library wasn't compiled to use AVX instructions, but these are 
available on your machine and could speed up CPU computations. 
2017-06-14 17:53:31.424812: W 
tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow 
library wasn't compiled to use AVX2 instructions, but these are 
available on your machine and could speed up CPU computations. 
2017-06-14 17:53:31.424820: W 
tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow 
library wasn't compiled to use FMA instructions, but these are 
available on your machine and could speed up CPU computations. 
2017-06-14 17:53:31.540959: I 
tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:901] successful 
NUMA node read from SysFS had negative value (-1), but there must be 
at least one NUMA node, so returning NUMA node zero 
2017-06-14 17:53:31.541359: I 
tensorflow/core/common_runtime/gpu/gpu_device.cc:887] Found device 0 
with properties: 
name: GeForce GTX 850M 
major: 5 minor: 0 memoryClockRate (GHz) 0.9015 
pciBusID 0000:0a:00.0 
Total memory: 3.95GiB 
Free memory: 128.12MiB 
2017-06-14 17:53:31.541407: I 
tensorflow/core/common_runtime/gpu/gpu_device.cc:908] DMA: 0 
2017-06-14 17:53:31.541420: I 
tensorflow/core/common_runtime/gpu/gpu_device.cc:918] 0: Y 
2017-06-14 17:53:31.541441: I 
tensorflow/core/common_runtime/gpu/gpu_device.cc:977] Creating 
TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 850M, 
pci bus id: 0000:0a:00.0) 
2017-06-14 17:53:31.547902: E 
tensorflow/stream_executor/cuda/cuda_driver.cc:893] failed to 
allocate 128.12M (134348800 bytes) from device: 
CUDA_ERROR_OUT_OF_MEMORY 
Device mapping: 
/job:localhost/replica:0/task:0/gpu:0 -> device: 0, name: GeForce 
GTX 850M, pci bus id: 0000:0a:00.0 
2017-06-14 17:53:31.549482: I 
tensorflow/core/common_runtime/direct_session.cc:257] Device 
mapping: 
/job:localhost/replica:0/task:0/gpu:0 -> device: 0, name: GeForce 
GTX 850M, pci bus id: 0000:0a:00.0 

Answer 1

あなたはGPUのバージョンを使用しています。あなたはGPUが表示されませんtensorflowのCPUバージョンを使用する場合はCPUとGPUの両方が利用可能であり、あなたのケースでは

from tensorflow.python.client import device_lib 
print(device_lib.list_local_devices()) 

：あなたは（もthis質問をご確認ください）で利用可能なtensorflowデバイスを一覧表示することができます。あなたの場合、テンソルフローデバイス（with tf.device("..")）を設定しないと、テンソルフローが自動的にgpuを選択します！

また、sudo pip3 listは、あなたがtensorflow-gpuを使用していることを明確に示しています。 tensoflowのCPUバージョンをお持ちの場合は、名前はtensorflow(1.1.0)のようになります。

警告については、thisの問題を確認してください。