[GitHub] sxjscience commented on issue #10173: Unpredictable nan in Array

[GitBox <gi...@apache.org>]

sxjscience commented on issue #10173: Unpredictable nan in Array
URL: https://github.com/apache/incubator-mxnet/issues/10173#issuecomment-375398324
 
 
   @CXMA479 Thanks for reporting this!. It seems to be a bug. I've revised the code to repeat the process multiple times:
   ```python
   import mxnet as mx
   import numpy as np
   def bench_mark(D_slice, P_slice):
       n= D_slice.shape[0]
       e3 = mx.nd.empty((n*n,2))
       for i in range(n):
           e3[n*i:n*(i+1)]  = (e3[n*i:n*(i+1)]*0+1)*( P_slice[i] - D_slice[i])
       return e3
   
   for i in range(100):
       x = mx.nd.random.uniform(shape=(2,5,2))
       y = mx.nd.random.uniform(shape=(2,5,2))
       e3_bm = bench_mark(x[0], y[0])
       print(x[0].asnumpy())
       print(y[0].asnumpy())
       print('-'*20)
       # print((e3_bm).asnumpy())
       e3_bm_npy = e3_bm.asnumpy()
       assert(np.isnan(e3_bm_npy).any() == False), str(e3_bm_npy)
   ```
   
   Result:
   
   ```log
        17     # print((e3_bm).asnumpy())
        18     e3_bm_npy = e3_bm.asnumpy()
   ---> 19     assert(np.isnan(e3_bm_npy).any() == False), str(e3_bm_npy)
        20
   
   AssertionError: [[ 0.5124911   0.45078474]
    [ 0.5124911   0.45078474]
    [ 0.5124911   0.45078474]
    [ 0.5124911   0.45078474]
    [ 0.5124911   0.45078474]
    [        nan         nan]
    [-0.57626355  0.13732177]
    [-0.57626355  0.13732177]
    [-0.57626355  0.13732177]
    [-0.57626355  0.13732177]
    [ 0.2129727  -0.06519118]
    [ 0.2129727  -0.06519118]
    [ 0.2129727  -0.06519118]
    [ 0.2129727  -0.06519118]
    [ 0.2129727  -0.06519118]
    [ 0.17914966 -0.17914736]
    [ 0.17914966 -0.17914736]
    [ 0.17914966 -0.17914736]
    [ 0.17914966 -0.17914736]
    [ 0.17914966 -0.17914736]
    [-0.6420211   0.68399173]
    [-0.6420211   0.68399173]
    [-0.6420211   0.68399173]
    [-0.6420211   0.68399173]
    [-0.6420211   0.68399173]]
   
   ```

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