conflict with matplotlib.pyplot

Riproduci l’esempio fornito in Python 3.6 con matplotlib.pyplot, ArrayFire, l’operazione aritmetica e data.join. Ispeziona arrayfire/data.py in join, arrayfire/util.py in safe_call e il percorso segnalato src/backend/cuda/jit.cpp per determinare perché l’ordine di importazione cambia il fallimento del JIT; il lavoro è concluso quando il riproduttore non genera più errori senza richiedere una soluzione alternativa basata sull’ordine di importazione.

These codes will trigger an error in just in time compiler

import matplotlib; matplotlib.use('Agg')
import matplotlib.pyplot as plt
import arrayfire as af

a = af.data.range( 640, 1280, dim=0 )
b = af.data.range( 640, 1280, dim=0 ) - 1

af.data.join(0,a,b,)

and the error output is

Traceback (most recent call last):
  File "test.py", line 8, in <module>
    af.data.join(0,a,b,)
  File "/home/herbert/anaconda3/lib/python3.6/site-packages/arrayfire/data.py", line 320, in join
    safe_call(backend.get().af_join(c_pointer(out.arr), dim, first.arr, second.arr))
  File "/home/herbert/anaconda3/lib/python3.6/site-packages/arrayfire/util.py", line 79, in safe_call
    raise RuntimeError(to_str(err_str))
RuntimeError: In function std::vector<char> cuda::compileToPTX(const char*, std::string)
In file src/backend/cuda/jit.cpp:

However, without any major change, the following two will not,

# change the import order between pyplot and arrayfire

import matplotlib; matplotlib.use('Agg')
import arrayfire as af
import matplotlib.pyplot as plt

a = af.data.range( 640, 1280, dim=0 )
b = af.data.range( 640, 1280, dim=0 ) - 1

af.data.join(0,a,b,)

or

# do not perform the arithmetic operation on one of the array  

import matplotlib; matplotlib.use('Agg')
import matplotlib.pyplot as plt
import arrayfire as af

a = af.data.range( 640, 1280, dim=0 )
b = af.data.range( 640, 1280, dim=0 )

af.data.join(0,a,b,)

Here is my python environment obtained by running python in a terminal.

Python 3.6.8 |Anaconda, Inc.| (default, Dec 30 2018, 01:22:34) 
[GCC 7.3.0] on linux
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