2017-04-10 79 views
0

我刚刚在CUDA 8.0和Cudnn v5.1的Win10 GTX GEFORCE 850M上安装了TensorFlow-GPU 1.0.1。 当我试图弄清楚,如果安装成功,我跑了Blas SGEMM发布失败

mnist_with_summaries.py

C:\Users...\Anaconda3\Lib\site-packages\tensorflow\examples\tutorials\mnist

当我运行在Jupyter笔记本的代码,它打印

Accuracy at step 0: 0.068

Accuracy at step 10: 0.6795

Accuracy at step 10: 0.6795

Accuracy at step 20: 0.8062

Accuracy at step 30: 0.8455

Accuracy at step 40: 0.8737

Accuracy at step 50: 0.8735

Accuracy at step 60: 0.8851

Accuracy at step 70: 0.8815

Accuracy at step 80: 0.8863

Accuracy at step 90: 0.8918

而且内核刚刚在打印上面的消息后死亡。

当我尝试运行在命令提示符下的代码,则返回错误:

failed to create cublas handle

attempting to perform BLAS operation using StreamExecutor without BLAS support

Internal error: Blass SGEMM launch failed: a.shape=(10000,784),b.shape=(784,500)

而且出现这个内部错误消息三次(太多错误信息,我只是写下来的东西,我认为很有用。如果有人需要更多的信息,告诉我)。

我然后尝试运行:

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) 
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True)) 
print(sess.run(c)) 

并且输出是: [[22 28] [49. 64.]] 这一次的代码运行而不会出现错误。 但应该输出: 设备映射:

/job:localhost/replica:0/task:0/gpu:0 -> device: 0, name: GeForce GTX 850M

id: 0000:05:00.0

b: /job:localhost/replica:0/task:0/gpu:0

a: /job:localhost/replica:0/task:0/gpu:0

MatMul: /job:localhost/replica:0/task:0/gpu:0

[[22 28] [49. 64.]]

我完全丢失。有人能告诉我为什么吗?

回答