我正在尝试运行Tensorflow-gpu。
我安装了 Cuda-9.0 和 cuDNN v7.0.3。我测试了两者（如他们的指南中所述）并且它们工作正常。
然后我使用 pip3（我使用 python3）安装了 Tensorflow-gpu，它在导入时给了我这个错误：
Traceback (most recent call last):
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in <module>
from tensorflow.python.pywrap_tensorflow_internal import *
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>
_pywrap_tensorflow_internal = swig_import_helper()
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "/usr/lib/python3.5/imp.py", line 242, in load_module
return load_dynamic(name, filename, file)
File "/usr/lib/python3.5/imp.py", line 342, in load_dynamic
return _load(spec)
ImportError: libcublas.so.8.0: cannot open shared object file: No such file or directory
During handling …numba.jit在python中使用。
我可以将普通函数转换为jit类型并运行：
from numba import jit
def sum(a, b):
return a+b
func = jit(sum)
print(func(1, 2))
如何做到这一点的方法？这样的事情（这不起作用，我知道为什么）。
from numba import jit
class some_class:
def __init__(self, something = 0):
self.number = something
def get_num(self):
return self.number
my_object = some_class(5)
func = jit(my_object.get_num)
print(my_object.func())
PS我也尝试过装饰器，它可以工作，但是我不能将其用于导入的类（我自己没有定义的类），所以我正在研究这个。
我想tensorflow在我的GPU上运行代码，但无法正常工作。我安装了Cuda和cuDNN，并具有兼容的GPU。
我从GPU的官方网站教程中获取了此示例，此处为GPU的Tensorflow教程
# 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))
这是我的输出：
Device mapping: no known devices.
2017-10-31 16:15:40.298845: I tensorflow/core/common_runtime/direct_session.cc:300] Device mapping:
MatMul: (MatMul): /job:localhost/replica:0/task:0/cpu:0
2017-10-31 16:15:56.895802: I tensorflow/core/common_runtime/simple_placer.cc:872] MatMul: (MatMul)/job:localhost/replica:0/task:0/cpu:0
b: (Const): /job:localhost/replica:0/task:0/cpu:0
2017-10-31 16:15:56.895910: I tensorflow/core/common_runtime/simple_placer.cc:872] …