Here's what my code in numpy looks like:
tensor = shared(np.random.randn(7, 16, 16))
e_tensor = tensor.eval()
tensor2 = e_tensor[0,:,:]
tensor2[tensor2 < 1] = 0.0
tensor2[tensor2 > 0 = 1.0
new_tensor = [tensor2]
for i in range(1, e_tensor.shape[0]):
new_tensor.append(np.multiply(tensor2, e_tensor[i,:,:]))
output = np.array(new_tensor).reshape(7,16,16)
On Tuesday, January 17, 2017 at 10:47:24 AM UTC-5, Corey Nolet wrote:
>
> I have a tensor which is (7,16,16), let's denote as Tijk. I need to make
> the following function:
>
> for j in range(0, 16):
> for k in range(0, 16):
> if T0jk == 0:
> for i in range(1, 7):
> Tijk = 0
>
>
> Any ideas on how this can be done with Theano's tensor API?
>
>
> Thanks! :
>
>
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