I don't undertand, what Theano don't support? We support advanced indexing.

Fred

On Wed, Jan 25, 2017 at 2:53 PM, Feras Almasri <[email protected]> wrote:

> thanks for mentioning this but theano function itself doesn't accept this
> implementation. how can I implement it ?
>
> On Wednesday, January 25, 2017 at 8:14:25 PM UTC+1, nouiz wrote:
>>
>> That way of working will be super slow. Try to make your code
>> "vectorized" by using advanced indexing when possible:
>>
>> https://docs.scipy.org/doc/numpy/reference/arrays.indexing.
>> html#advanced-indexing
>>
>> On Tue, Jan 24, 2017 at 4:17 PM, Feras Almasri <[email protected]> wrote:
>>
>>> layer_Fmaps of size (1,69,236,236) sitwches of size (1,69,708,708)
>>>
>>> in each 3 by 3 matrix in layer_Fmaps there is only cell having a value 1
>>> which should be replace by the opposite value of sitwches
>>>
>>> I can't find a way to solve the problem by assigning a direct value into
>>> a certain location using a loop
>>>
>>> def switchs(layer_Fmaps, step=2, switches):
>>>         for idx in range(96):
>>>             for i in range(0, 708, step):
>>>                 for j in range(0, 708, step):
>>>                     val = layer_Fmaps[0][idx][i/2,j/2]
>>>                     switches = T.set_subtensor(switches[0][idx][i:i + step, 
>>> j:j + step],val)
>>>         return  switches
>>>
>>> knowing that switchs and layer_Fmaps are tensor4
>>>
>>> img = np.zeros((1,96,236,236))
>>> sswitchs =  np.zeros((1,96,708,708))
>>>
>>> inp = T.tensor4('img')
>>> SW = T.tensor4('SW')
>>>
>>> tester = switchs(img,3,sswitchs)
>>>
>>> f = theano.function([inp, SW], tester)
>>>
>>> d = f(img,sswitchs)
>>>
>>> Any suggestion would be appreciated.
>>>
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>>
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