python 查tensorflow版本_python – 如何检查keras是否使用gpu版本的tensorflow？

当我运行keras脚本时，我得到以下输出：

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)

这是什么意思？我使用GPU或CPU版本的张量流？

在安装keras之前，我正在使用GPU版本的tensorflow。

另外sudo pip3列表显示tensorflow-gpu(1.1.0)，没有像tensorflow-cpu。

运行[此stackoverflow问题]中提到的命令，提供以下内容：

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