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/prepr >>> ocessing >>> $ 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.am >>> d64\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.am >>> d64\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.am >>> d64\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 >>> >>> -- > > --- > You received this message because you are subscribed to the Google Groups > "theano-users" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. > For more options, visit https://groups.google.com/d/optout. > -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. 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