Thanks Fred! If I will fix it, I would like to keep up you.

Il giorno martedì 14 marzo 2017 15:17:16 UTC+1, nouiz ha scritto:
>
> I don't know scipy.io.matlab. Search for that error on the web. I can't 
> help with that one.
>
> Fred
>
> On Tue, Mar 14, 2017 at 9:45 AM Goffredo Giordano <[email protected] 
> <javascript:>> wrote:
>
>> Thank you Fred! I read that it was written for Python 2.7. According to 
>> you is so complex to convert it to Python 3.4? I followed your advices and 
>> the errors are these ones:
>>
>>
>> $ 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
>>
>>
>>
>> Il giorno martedì 14 marzo 2017 13:42:11 UTC+1, nouiz ha scritto:
>>
>>> The only one error you wrote about is for to different o Python version. 
>>> Not hdf5. Use Python 2.7 or do the fix Jesse wrote.
>>>
>>> Fred
>>>
>>> Le mar. 14 mars 2017 06:27, Goffredo Giordano <[email protected]> a 
>>> écrit :
>>>
>>>> Thank you Salah! Your comment was useful, however I think that more 
>>>> important are the issues from scipy.io.matlab. I have installed h5py 2.6.0 
>>>> and I think that hdf5 library is still working. But I'm not so sure and 
>>>> probably these problems are related to the hdf5 library, or matlab file 
>>>> meta_clsloc.mat. What's your idea about?
>>>>
>>>>
>>>> Il giorno lunedì 13 marzo 2017 20:44:27 UTC+1, Salah Rifai ha scritto:
>>>>
>>>>> It's weird since all the numerator and denominator are both ints. Try 
>>>>> explicitly cast it to int:
>>>>>
>>>>> for ind in range(int(labels.size / batch_size)):
>>>>>
>>>>> Best,
>>>>>
>>>> On Mon, Mar 13, 2017 at 2:51 PM, Goffredo Giordano <
>>>>> [email protected]> wrote:
>>>>>
>>>> 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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