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Aurelius84
shingstone-lu
zhwesky2010
paddle的版本是2.1.0 win10操作系统 程序如下： import numpy as np import paddle
程序段1
x=np.random.uniform(high=20,size=(2,1,500,500)) x = paddle.to_tensor(x,dtype='int32') result1 = paddle.max(x) print(result1)
程序段2
x=np.random.uniform(high=20,size=(2,1,500,500)) x = paddle.to_tensor(x,dtype='int64') result1 = paddle.max(x) print(result1)
程序段1可以正常执行，但是将程序段1改为程序段2('int32'->'int64')就会出现下面的错误： Traceback (most recent call last): File "e:/luqinghua/ICNet/测试代码.py", line 281, in
print(result1)
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python37\lib\site-packages\paddle\fluid\dygraph\varbase_patch_methods.py", line 464, in str
return to_string(self)
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python37\lib\site-packages\paddle\tensor\to_string.py", line 205, in to_string
np_var = var.numpy()
OSError: (External) Cuda error(700), an illegal memory access was encountered.
[Advise: Please search for the error code(700) on website( https://docs.nvidia.com/cuda/archive/10.0/cuda-runtime-api/group__CUDART__TYPES.html#group__CUDART__TYPES_1g3f51e3575c2178246db0a94a430e0038 ) to get Nvidia's official solution about CUDA Error.] (at C:\home\workspace\Paddle_release\paddle\fluid\platform\gpu_info.cc:394)
感觉有点内存不够用了。 后续的程序中我需要用到paddle.nn.functional.cross_entropy计算predict和label的交叉熵， predict的形状为[N,2,504,504]，label的形状为[N,1,504,504] 如果label使用int64，就会出现上面的错误；如果使用int32就可以避免上面的错误，但是cross_entropy在use_softmax=True和soft_label=False的情况下要求输入的label为int64。