I resolved this issue that was due to the ImageNet subset downloaded. The
program doesn't recognize the wnid because it cannot find the folders (like
n01440764, n01443537, ...) in the training folder defined in paths.yaml.
However when I tryed the train.py it gives me these errors:
C:\deep_learning\alexnet>python train.py
Traceback (most recent call last):
File "train.py", line 180, in <module>
config = dict(list(config.items()) + list(yaml.load(f).items()))
File
"C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\yaml\__init__.py",
line 72, in load
return loader.get_single_data()
File
"C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\yaml\constructor.py",
line 35, in get_single_data
node = self.get_single_node()
File
"C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\yaml\composer.py",
line 36, in get_single_node
document = self.compose_document()
File
"C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\yaml\composer.py",
line 55, in compose_document
node = self.compose_node(None, None)
File
"C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\yaml\composer.py",
line 84, in compose_node
node = self.compose_mapping_node(anchor)
File
"C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\yaml\composer.py",
line 127, in compose_mapping_node
while not self.check_event(MappingEndEvent):
File
"C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\yaml\parser.py",
line 98, in check_event
self.current_event = self.state()
File
"C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\yaml\parser.py",
line 428, in parse_block_mapping_key
if self.check_token(KeyToken):
File
"C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\yaml\scanner.py",
line 116, in check_token
self.fetch_more_tokens()
File
"C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\yaml\scanner.py",
line 220, in fetch_more_tokens
return self.fetch_value()
File
"C:\deep_learning\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\yaml\scanner.py",
line 580, in fetch_value
self.get_mark())
yaml.scanner.ScannerError: mapping values are not allowed here
in "spec_1gpu.yaml", line 9, column 92
Please anyone could help me again?
Thanks,
Goffredo
Il giorno lunedì 20 marzo 2017 16:01:40 UTC+1, Goffredo Giordano ha scritto:
>
> 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 <giordano...@gmail.com>
>>> 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 <giordano...@gmail.com>
>>>>> 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 <
>>>>>>> giordano...@gmail.com> 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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>>>>>>>>
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>>>>>>>> send an email to theano-users...@googlegroups.com.
>>>>>>>>
>>>>>>>
>>>>>>>> For more options, visit https://groups.google.com/d/optout.
>>>>>>>>
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>>>>>>
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>>>>> --
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