I think you just want to do
for i in range(n_test_batches):
test_losses = [test_model(i)]
y_pred_test = salidas_capa3(i)
print y_pred_test
The salidas_capa3 function expects a minibatch index as an argument.
On Wednesday, July 27, 2016 at 11:27:08 PM UTC-7, Beatriz G. wrote:
>
> I am not able of extract the value of that function at that point, I have
> debugged and I I have gotten the results of test_model in the attached pic.
>
> Thank you for your help.
>
>
>
> What is the value of test_model(i) at that point? I think it should be an
>> array of indices.
>>
>> On Wednesday, July 27, 2016 at 1:52:27 AM UTC-7, Beatriz G. wrote:
>>>
>>> Hi Jesse, thank you for your reply.
>>>
>>> I have tried to use it when I test:
>>>
>>> #Aqui se tiene que cargar la red
>>>
>>> layer0.W.set_value(w0_test)
>>> layer0.b.set_value(b0_test)
>>>
>>> layer1.W.set_value(w1_test)
>>> layer1.b.set_value(b1_test)
>>>
>>> layer2.W.set_value(w2_test)
>>> layer2.b.set_value(b2_test)
>>>
>>> # test it on the test set
>>> for i in range(n_test_batches):
>>> test_losses = [test_model(i)]
>>> y_pred_test = salidas_capa3[test_model(i)]
>>> print y_pred_test
>>> test_score = numpy.mean(test_losses)
>>>
>>> print((' test error of best model %f %%') % (test_score * 100.))
>>>
>>>
>>>
>>> but I get the following error:
>>>
>>>
>>> Traceback (most recent call last):
>>> File "/home/beaa/Escritorio/Theano/Separando_Lenet.py", line 414, in
>>> <module>
>>> evaluate_lenet5()
>>> File "/home/beaa/Escritorio/Theano/Separando_Lenet.py", line 390, in
>>> evaluate_lenet5
>>> y_pred_test = salidas_capa3[test_model(i)]
>>> File
>>> "/home/beaa/.local/lib/python2.7/site-packages/theano/compile/function_module.py",
>>> line 545, in __getitem__
>>> return self.value[item]
>>> File
>>> "/home/beaa/.local/lib/python2.7/site-packages/theano/compile/function_module.py",
>>> line 480, in __getitem__
>>> s = finder[item]
>>> TypeError: unhashable type: 'numpy.ndarray'
>>>
>>>
>>>
>>> and I do not know what produces it.
>>>
>>>
>>> Regards
>>>
>>>
>>> El miércoles, 27 de julio de 2016, 2:29:24 (UTC+2), Jesse Livezey
>>> escribió:
>>>>
>>>> You should be able to use this function to output y_pred
>>>>
>>>> salidas_capa3 = theano.function(
>>>> [index],
>>>> layer3.y_pred,
>>>> givens={
>>>> x: test_set_x[index * batch_size: (index + 1) * batch_size],
>>>> }
>>>> )
>>>>
>>>>
>>>> On Monday, July 25, 2016 at 3:09:09 AM UTC-7, Beatriz G. wrote:
>>>>>
>>>>> Hi, anyone knows how to get the test labels that the classifier has
>>>>> given to the data?
>>>>>
>>>>> I would like to extrat the data that has not been well classified.
>>>>>
>>>>> Regards.
>>>>>
>>>>
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