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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