If I run :
# 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) #Here is the break point
I got:
test_losses = {list} <type 'list'>: [array(0.5)]
__len__ = {int} 1
0 = {ndarray} 0.5
El jueves, 28 de julio de 2016, 2:34:12 (UTC+2), Jesse Livezey escribió:
>
> 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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