Hi guys, I would thank you because I resolved the previous errors: the
errors related to scipy probably were attributable to the meta_clsloc.mat
file. I have downloaded another file from
https://github.com/heuritech/convnets-keras/blob/a06ebbbca392a7eedc8a2e71ddcc8796e086c35a/convnetskeras/data/meta_clsloc.mat
and it fixed them. However I found another error, and I don't know if it is
related to the Python 3.4 version. Anyone could help me again?
$ sh generate_toy_data.sh
generating toy dataset ...
Traceback (most recent call last):
File "make_train_val_txt.py", line 61, in <module>
str(dict_orig_id_to_sorted_id[int(val_labels[ind])]) + '\n'
KeyError: 490
Goffredo
Il giorno martedì 14 marzo 2017 15:42:05 UTC+1, Goffredo Giordano ha
scritto:
>
> 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]>
>> 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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