Could not create cudnn handle: CUDNN_STATUS_ALLOC_FAILED的一种解决方案
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2022-06-06 08:45:53
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最近在使用tensorflow-gpu2.0的时候老是报这个错误:
Could not create cudnn handle: CUDNN_STATUS_ALLOC_FAILED
BaseCollectiveExecutor::StartAbort Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
错误和cudnn有关,排除了cuda和cudnn的版本问题,在网上查了一下,应该是GPU被占用,所以无法使用,需要在代码里面添加几行语句,设置GPU的按需分配
tf2.0下,添加以下代码:
import tensorflow as tf
physical_devices = tf.config.experimental.list_physical_devices('GPU')
assert len(physical_devices) > 0
tf.config.experimental.set_memory_growth(physical_devices[0], True)
assert tf.config.experimental.get_memory_growth(physical_devices[0]) == True
如果用的是tf1.n,则可以参考这篇博客,下面是来自这位大佬的内容:
keras(后端为tf1.n)添加以下代码:
import tensorflow as tf
from keras import backend as K
config1 = tf.ConfigProto()
config1.gpu_options.allow_growth=True
sess = tf.Session(config=config1)
K.set_session(sess)
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