[GitHub] wkcn opened a new issue #9976: The assignment problem about NDArray

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

wkcn opened a new issue #9976: The assignment problem about NDArray
URL: https://github.com/apache/incubator-mxnet/issues/9976
 
 
   ## Description
   If `a` is a multi-dims array, it is not available to use `a[0] = a[1]` to assign a row.
   However, it's available to use `a[0, :] = a[1]` or `a[0]=a[1].asnumpy()`
   
   ## Environment info (Required)
   The latest pre-built MXNet has the same problem.
   ```
   ----------Python Info----------
   Version      : 3.6.4
   Compiler     : GCC 7.2.1 20171224
   Build        : ('default', 'Jan  5 2018 02:35:40')
   Arch         : ('64bit', '')
   ------------Pip Info-----------
   Version      : 9.0.1
   Directory    : /usr/lib/python3.6/site-packages/pip
   ----------MXNet Info-----------
   Version      : 1.2.0
   Directory    : /home/wkcn/proj/mxnet/python/mxnet
   Hashtag not found. Not installed from pre-built package.
   ----------System Info----------
   Platform     : Linux-4.15.5-1-ARCH-x86_64-with-arch
   system       : Linux
   node         : MiraiM
   release      : 4.15.5-1-ARCH
   version      : #1 SMP PREEMPT Thu Feb 22 22:15:20 UTC 2018
   ```
   
   Package used (Python/R/Scala/Julia):
   Python
   
   ## Build info (Required if built from source)
   
   Compiler (gcc/clang/mingw/visual studio): gcc 7.2.1
   
   MXNet commit hash:
   17a9c6ad
   
   Build config:
   `make -j4 USE_OPENCV=1 USE_BLAS=openblas `
   
   ## Minimum reproducible example
   ```python
   >>> import mxnet as mx
   >>> import numpy as np
   
   >>> a = mx.nd.array(np.arange(12).reshape((3,4)))
   >>> a
   
   [[ 0.  1.  2.  3.]
    [ 4.  5.  6.  7.]
    [ 8.  9. 10. 11.]]
   <NDArray 3x4 @cpu(0)>
   >>> a[0]=a[1]     #   HERE
   >>> a
   
   [[ 0.  1.  2.  3.]
    [ 4.  5.  6.  7.]
    [ 8.  9. 10. 11.]]
   <NDArray 3x4 @cpu(0)>
   >>> a[0]=[10,11,12,13]
   >>> a
   
   [[10. 11. 12. 13.]
    [ 4.  5.  6.  7.]
    [ 8.  9. 10. 11.]]
   <NDArray 3x4 @cpu(0)>
   >>> a[0]=a[1].asnumpy()
   >>> a
   
   [[ 4.  5.  6.  7.]
    [ 4.  5.  6.  7.]
    [ 8.  9. 10. 11.]]
   <NDArray 3x4 @cpu(0)>
   >>> a[1,:]=a[2]
   >>> a
   
   [[ 4.  5.  6.  7.]
    [ 8.  9. 10. 11.]
    [ 8.  9. 10. 11.]]
   <NDArray 3x4 @cpu(0)>
   ````

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