Thank you, but it doesn't modify nothing. The errors are the same.


Il giorno lunedì 13 marzo 2017 17:12:06 UTC+1, Jesse Livezey ha scritto:
>
> You can probably modify line 27 in make_labels.py to be
> for ind in range(labels.size // batch_size):
>
> This code was probably written with python 2 where division worked 
> differently.
>
> On Monday, March 13, 2017 at 8:45:39 AM UTC-7, Goffredo Giordano wrote:
>>
>> Hi,
>> I'm a new user and I'm trying to study the ample world of machine 
>> learning. I would like to run the theano_alexnet training from 
>> https://github.com/uoguelph-mlrg/theano_alexnet.
>> My computer is a Windows 10 native-machine 64 bit Intel core i7. I use 
>> WinPython-64bit-3.4.4.4QT5 from WinPython 3.4.4.3, Visual Studio 2015 
>> Community Edition Update 3, CUDA 8.0.44 (64-bit), cuDNN v5.1 (August 10, 
>> 2016) for CUDA 8.0, Git source control based on MinGW compiler and OpenBLAS 
>> 0.2.14. 
>> As fundamental python libraries Theano is 0.9.0beta1 version, Scipy is 
>> 0.19.0, Keras 1.2.2, Lasagne 0.2.dev1, Numpy 1.11.1, hickle 2.0.4, h5py 
>> 2.6.0, pycuda, pylearn2, zeromq.
>> I have downloaded the training images, the validation images and I have 
>> unzipped the development kit from Imagenet dataset. I have configured the 
>> paths.yaml with my folders but I do not know where I could find the val.txt 
>> and train.txt files. I used the meta_clsloc.mat file and 
>> ILSVRC2012_validation_ground_truth.txt file from the development kit from 
>> Imagenet dataset. With the Git bash control i try to run the 
>> generate_toy_data.sh and I can find the train_labels.npy, val_labels.npy, 
>> img_mean.npy, shuffled_train_filenames.npy with the validation alex net 
>> *.hkl files, but nothing in the training folder. Probably I forgot some 
>> important features, so I would apologize previously. Thank you so much!
>>
>>
>> Goffredo_Giordano@Goffredo MINGW64 /c/deep_learning/alexnet/preprocessing
>> $ sh generate_toy_data.sh
>> ciao
>> generating toy dataset ...
>>                                                       make_hkl.py:72: 
>> VisibleDeprecationWarning: using a non-integer number instead of an integer 
>> will result in an error in the future
>>   hkl.dump(img_batch[:, :, :, :half_size],
>> make_hkl.py:76: VisibleDeprecationWarning: using a non-integer number 
>> instead of an integer will result in an error in the future
>>   hkl.dump(img_batch[:, :, :, half_size:],
>> Traceback (most recent call last):
>>   File "make_train_val_txt.py", line 26, in <module>
>>     synsets = scipy.io.loadmat(meta_clsloc_mat)['synsets'][0]
>>   File 
>> "C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\scipy\io\matlab\mio.py",
>>  
>> line 136, in loadmat
>>     matfile_dict = MR.get_variables(variable_names)
>>   File 
>> "C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\scipy\io\matlab\mio5.py",
>>  
>> line 272, in get_variables
>>     hdr, next_position = self.read_var_header()
>>   File 
>> "C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\scipy\io\matlab\mio5.py",
>>  
>> line 226, in read_var_header
>>     mdtype, byte_count = self._matrix_reader.read_full_tag()
>>   File "scipy\io\matlab\mio5_utils.pyx", line 546, in 
>> scipy.io.matlab.mio5_utils.VarReader5.read_full_tag 
>> (scipy\io\matlab\mio5_utils.c:5330)
>>   File "scipy\io\matlab\mio5_utils.pyx", line 554, in 
>> scipy.io.matlab.mio5_utils.VarReader5.cread_full_tag 
>> (scipy\io\matlab\mio5_utils.c:5400)
>>   File "scipy\io\matlab\streams.pyx", line 164, in 
>> scipy.io.matlab.streams.ZlibInputStream.read_into 
>> (scipy\io\matlab\streams.c:3052)
>>   File "scipy\io\matlab\streams.pyx", line 151, in 
>> scipy.io.matlab.streams.ZlibInputStream._fill_buffer 
>> (scipy\io\matlab\streams.c:2913)
>> zlib.error: Error -3 while decompressing data: invalid distance too far 
>> back
>> make_labels.py:17: VisibleDeprecationWarning: using a non-integer number 
>> instead of an integer will result in an error in the future
>>   labels = labels[:labels.size / orig_batch_size * orig_batch_size]
>> make_labels.py:23: VisibleDeprecationWarning: using a non-integer number 
>> instead of an integer will result in an error in the future
>>   labels_0 = labels.reshape((-1, batch_size))[::num_div].reshape(-1)
>> make_labels.py:24: VisibleDeprecationWarning: using a non-integer number 
>> instead of an integer will result in an error in the future
>>   labels_1 = labels.reshape((-1, batch_size))[1::num_div].reshape(-1)
>> Traceback (most recent call last):
>>   File "make_labels.py", line 125, in <module>
>>     div_labels(train_label_name, orig_batch_size, num_div)
>>   File "make_labels.py", line 27, in div_labels
>>     for ind in range(labels.size / batch_size):
>> TypeError: 'float' object cannot be interpreted as an integer
>>
>>

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