我已经花了相当多的时间挖掘周围的堆栈溢出和其他寻找答案，但无法找到任何东西

大家好，
我正在运行Tensorflow，Keras在上面。我90%确定我安装了Tensorflow GPU，有没有办法检查我安装的是哪一个？
我试图从Jupyter笔记本上运行一些CNN模型，我注意到Keras正在CPU上运行模型（检查任务管理器，CPU为100%）。
我试着从tensorflow网站运行这段代码：

# Creates a graph.
a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')
b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')
c = tf.matmul(a, b)
# Creates a session with log_device_placement set to True.
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
# Runs the op.
print(sess.run(c))

这就是我得到的

MatMul: (MatMul): /job:localhost/replica:0/task:0/cpu:0
2017-06-29 17:09:38.783183: I c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\common_runtime\simple_placer.cc:847] MatMul: (MatMul)/job:localhost/replica:0/task:0/cpu:0
b: (Const): /job:localhost/replica:0/task:0/cpu:0
2017-06-29 17:09:38.784779: I c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\common_runtime\simple_placer.cc:847] b: (Const)/job:localhost/replica:0/task:0/cpu:0
a: (Const): /job:localhost/replica:0/task:0/cpu:0
2017-06-29 17:09:38.786128: I c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\common_runtime\simple_placer.cc:847] a: (Const)/job:localhost/replica:0/task:0/cpu:0
[[ 22.  28.]
 [ 49.  64.]]

对我来说，这表明我正在运行我的CPU，出于某种原因。
我有一个GTX1050（驱动程序版本382. 53），我安装了CUDA，和Cudnn，并安装了tensorflow没有任何问题。我也安装了Visual Studio 2015，因为它被列为兼容版本。
我记得CUDA提到了一个不兼容的驱动程序正在安装，但如果我没记错的话，CUDA应该安装了自己的驱动程序。

**编辑：**我运行这些命令来列出可用设备

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

这就是我得到的

[name: "/cpu:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 14922788031522107450
]

还有很多这样的警告

2017-06-29 17:32:45.401429: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE instructions, but these are available on your machine and could speed up CPU computations.

编辑2

试着逃跑

pip3 install --upgrade tensorflow-gpu

我得到了

Requirement already up-to-date: tensorflow-gpu in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages
Requirement already up-to-date: markdown==2.2.0 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu)
Requirement already up-to-date: html5lib==0.9999999 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu)
Requirement already up-to-date: werkzeug>=0.11.10 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu)
Requirement already up-to-date: wheel>=0.26 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu)
Requirement already up-to-date: bleach==1.5.0 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu)
Requirement already up-to-date: six>=1.10.0 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu)
Requirement already up-to-date: protobuf>=3.2.0 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu)
Requirement already up-to-date: backports.weakref==1.0rc1 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu)
Requirement already up-to-date: numpy>=1.11.0 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu)
Requirement already up-to-date: setuptools in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from protobuf>=3.2.0->tensorflow-gpu)

**已解决：**查看评论解决方案。感谢所有帮助过我的人！

我是新来的，所以任何帮助都非常感谢！谢谢你。