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test_softmax_sums_to_one[CupyOps] and test_softmax_works_inplace[CupyOps] failing #83

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ccoulombe opened this issue Nov 13, 2018 · 1 comment
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test_softmax_sums_to_one[CupyOps] and test_softmax_works_inplace[CupyOps] failing #83

ccoulombe opened this issue Nov 13, 2018 · 1 comment

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@ccoulombe
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The test_softmax_sums_to_one[CupyOps] and test_softmax_works_inplace[CupyOps] are failing, both with:

E   TypeError: Unsupported type <class 'numpy.ndarray'>

cupy/core/elementwise.pxi:68: TypeError

in a python 3.6 virtual env. on linux. The GPU is a Tesla K80 and cuda version is 9.0.176.

(.thinc) ~ $ pip install -U --force -r requirements.txt cupy==4.5.0 thinc_gpu_ops==0.0.3 thinc==6.12.0
(.thinc) ~ $ pip list
Package        Version
-------------- -------
atomicwrites   1.2.1  
attrs          18.2.0 
cupy           4.5.0  
cymem          2.0.2  
Cython         0.29   
cytoolz        0.9.0.1
dill           0.2.8.2
fastrlock      0.4    
hypothesis     2.0.0  
mock           2.0.0  
more-itertools 4.3.0  
msgpack        0.5.6  
msgpack-numpy  0.4.3.2
msgpack-python 0.5.6  
murmurhash     1.0.1  
numpy          1.15.2 
pbr            5.1.1  
pip            18.1   
plac           0.9.6  
pluggy         0.8.0  
preshed        2.0.1  
py             1.7.0  
pytest         3.10.1 
setuptools     40.6.2 
six            1.11.0 
thinc          6.12.0 
thinc-gpu-ops  0.0.3  
toolz          0.9.0  
tqdm           4.28.1 
wheel          0.32.2 
wrapt          1.10.11
(.thinc) ~ $ pytest .thinc/lib/python3.6/site-packages/thinc
....
________________________________________________________________________________________ test_softmax_sums_to_one[CupyOps] _________________________________________________________________________________________

ops = <thinc.neural.ops.CupyOps object at 0x7f93a9da4518>

    @settings(max_examples=MAX_EXAMPLES)
>   @given(X=strategies.arrays_BI())
    def test_softmax_sums_to_one(ops, X):

.thinc/lib/python3.6/site-packages/thinc/tests/unit/test_ops.py:148: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
.thinc/lib/python3.6/site-packages/hypothesis/core.py:713: in wrapped_test
    print_example=True, is_final=True
.thinc/lib/python3.6/site-packages/hypothesis/executors/executors.py:25: in default_executor
    return function()
.thinc/lib/python3.6/site-packages/hypothesis/core.py:376: in run
    return test(*args, **kwargs)
.thinc/lib/python3.6/site-packages/thinc/tests/unit/test_ops.py:150: in test_softmax_sums_to_one
    y = ops.softmax(X)
ops.pyx:215: in thinc.neural.ops.Ops.softmax
    ???
.thinc/lib/python3.6/site-packages/cupy/core/fusion.py:871: in __call__
    return self._cupy_op(*args, **kwargs)
cupy/core/elementwise.pxi:753: in cupy.core.core.ufunc.__call__
    ???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   TypeError: Unsupported type <class 'numpy.ndarray'>

cupy/core/elementwise.pxi:68: TypeError
---------------------------------------------------------------------------------------------------- Hypothesis ----------------------------------------------------------------------------------------------------
Falsifying example: test_softmax_sums_to_one(ops=<thinc.neural.ops.CupyOps object at 0x7f93a9da4518>, X=array([[-100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100.],
       [-100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100.],
       [-100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100.],
       [-100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100.],
       [-100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100.],
       [-100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100.],
       [-100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100.]], dtype=float32))
_______________________________________________________________________________________ test_softmax_works_inplace[CupyOps] ________________________________________________________________________________________

ops = <thinc.neural.ops.CupyOps object at 0x7f93a995e390>

    @settings(max_examples=MAX_EXAMPLES)
>   @given(X=strategies.arrays_BI())
    def test_softmax_works_inplace(ops, X):

.thinc/lib/python3.6/site-packages/thinc/tests/unit/test_ops.py:167: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
.thinc/lib/python3.6/site-packages/hypothesis/core.py:713: in wrapped_test
    print_example=True, is_final=True
.thinc/lib/python3.6/site-packages/hypothesis/executors/executors.py:25: in default_executor
    return function()
.thinc/lib/python3.6/site-packages/hypothesis/core.py:376: in run
    return test(*args, **kwargs)
.thinc/lib/python3.6/site-packages/thinc/tests/unit/test_ops.py:169: in test_softmax_works_inplace
    ops.softmax(X, inplace=True)
ops.pyx:215: in thinc.neural.ops.Ops.softmax
    ???
.thinc/lib/python3.6/site-packages/cupy/core/fusion.py:871: in __call__
    return self._cupy_op(*args, **kwargs)
cupy/core/elementwise.pxi:753: in cupy.core.core.ufunc.__call__
    ???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   TypeError: Unsupported type <class 'numpy.ndarray'>

cupy/core/elementwise.pxi:68: TypeError
---------------------------------------------------------------------------------------------------- Hypothesis ----------------------------------------------------------------------------------------------------
Falsifying example: test_softmax_works_inplace(ops=<thinc.neural.ops.CupyOps object at 0x7f93a995e390>, X=array([[-100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100.],
       [-100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100.],
       [-100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100.],
       [-100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100.],
       [-100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100., -100., -100., -100., -100., -100., -100.,
        -100., -100., -100.]], dtype=float32))

Let me know if I can provide more information.

Thanks!
@honnibal
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Thanks, fixed!

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