from opendeep.models.container import Prototype Traceback (most recent call last): File "<stdin>", line 1, in <module> File "opendeep/__init__.py", line 29, in <module> from . import models File "opendeep/models/__init__.py", line 3, in <module> from .model import * File "opendeep/models/model.py", line 13, in <module> from theano.compat.python2x import OrderedDict # use this compatibility OrderedDict ImportError: No module named python2x how to import

When running the Quick example of the MLP on the MNIST data I am getting the following error when running on Python 3.5: Using gpu device 0: GeForce GT 650M (CNMeM is disabled, cuDNN not available) Getting data... Creating model... Training... Traceback (most recent call last): File "<ipython-input-2-360694695dce>", line 1, in <module> runfile('/Users/molinal/SkyDrive/AI/opendeep/mlp_opendeep.py', wdir='/Users/molinal/SkyDrive/AI/opendeep') File "/Users/molinal/anaconda/envs/tensorflow/lib/python3.5/site-packages/spyderlib/widgets/externalshell/sitecustomize.py", line 699, in runfile execfile(filename, namespace) File "/Users/molinal/anaconda/envs/tensorflow/lib/python3.5/site-packages/spyderlib/widgets/externalshell/sitecustomize.py", line 88, in execfile exec(compile(open(filename, 'rb').read(), filename, 'exec'), namespace) File "/Users/molinal/SkyDrive/AI/opendeep/mlp_opendeep.py", line 34, in <module> optimizer.train() File "/Users/molinal/OpenDeep/opendeep/optimization/optimizer.py", line 380, in train self.STOP = self._perform_one_epoch(f_learn, plot) File "/Users/molinal/OpenDeep/opendeep/optimization/optimizer.py", line 422, in _perform_one_epoch _outs = raise_to_list(f_learn(*batch)) File "/Users/molinal/anaconda/pkgs/theano/compile/function_module.py", line 786, in __call__ allow_downcast=s.allow_downcast) File "/Users/molinal/anaconda/pkgs/theano/tensor/type.py", line 177, in filter data.shape)) TypeError: ('Bad input argument to theano function with name "f_learn" at index 0(0-based)', 'Wrong number of dimensions: expected 2, got 4 with shape (100, 1, 28, 28).')

I trying to run the "Monitors and Live Plotting" tutorial, but when i run the code a HTTP 599 error is returned with the IOError "Cannot push session document because we failed to connect to the server (to start the server, try the 'bokeh serve' command)". The server is running and listen to localhost:5006. At the same time, the server says "INFO:tornado.general:Malformed HTTP message from 127.0.0.1: Malformed HTTP request line". Anyone have any tip to solve this?

Is there a way to plot the loss function as a function of iteration number (during training) within the Jupyter notebook?

I am new to OpenDeep, trying out the example code for monitoring channels, copy and pasted the code from the example page, but shows this error : Plot object has no attribute 'channel'. Can anyone please help. Thanks

Hi, Fantastic Library, so clear! I was just wondering, i am trying to use the library for a binary classifier experiment using the log loss function to train the model. This is for a university experiment around benchmarking different models. Would you have some time to provide an example of how to use the library to achieve the above goal. Many thanks, Best, Andrew

Dear all, I would like to know how to get the probabilities (output values of the neural network) of each class of a given trained MLP in OpenDeep ? This would play the role of a confidence. Thanks a lot !

Hi I have a question After training a model , How can I predict using sample data ?

I'm looking to evaluate OpenDeep. Any recommendations on GPU hardware (NVidia graphics cards) and what Distribution of Linux to use?

INFO:opendeep.optimization.optimizer:Train monitors: {'crossentropy/train': 0.45665097, 'error/train': 0.17261043} Traceback (most recent call last): File "/home/elliotnam/workspace2/facerecognition/rnnrbm_mnist.py", line 95, in <module> run_sequence(1) File "/home/elliotnam/workspace2/facerecognition/rnnrbm_mnist.py", line 54, in run_sequence optimizer.train(plot=plot) File "/usr/local/lib/python2.7/dist-packages/opendeep-0.0.9a0-py2.7.egg/opendeep/optimization/optimizer.py", line 391, in train self.STOP = self._perform_one_epoch(train_function, plot) File "/usr/local/lib/python2.7/dist-packages/opendeep-0.0.9a0-py2.7.egg/opendeep/optimization/optimizer.py", line 464, in _perform_one_epoch plot.update_plots(epoch=self.epoch_counter, monitors=current_mean_monitors) File "/usr/local/lib/python2.7/dist-packages/opendeep-0.0.9a0-py2.7.egg/opendeep/monitor/plot.py", line 213, in update_plots line_color=self.colors[color_idx % len(self.colors)]) File "/home/elliotnam/.local/lib/python2.7/site-packages/bokeh/_glyph_functions.py", line 37, in func glyph = _make_glyph(glyphclass, kwargs, glyph_ca) File "/home/elliotnam/.local/lib/python2.7/site-packages/bokeh/plotting_helpers.py", line 144, in _make_glyph return glyphclass(**kws) File "/home/elliotnam/.local/lib/python2.7/site-packages/bokeh/plot_object.py", line 90, in __init__ super(PlotObject, self).__init__(**kwargs) File "/home/elliotnam/.local/lib/python2.7/site-packages/bokeh/properties.py", line 357, in __init__ setattr(self, name, value) File "/home/elliotnam/.local/lib/python2.7/site-packages/bokeh/properties.py", line 371, in __setattr__ (name, self.__class__.__name__, text, nice_join(matches))) AttributeError: unexpected attribute 'y_axis_label' to Line, possible attributes are line_alpha, line_cap, line_color, line_dash, line_dash_offset, line_join, line_width, name, session, tags, visible, x or y

hi do you have any CNN example code for example, CNN for mnist something like that thx

Hello. I'm writing a network that predicts the probabilities of each symbol(character) from the previous context. I've written codes for training, and it seems work well. I want to save the total network settings(including trained weights) then reload and use them later. In other words, I want to separate the training from the part that applies actual data to the trained network. Can I do? If so, what should I do? Thank you for maintaining such a nice project, anyway!

Trying to run the Your First Model tutorial, but I get the error that follows below. I've had to install the most recent stable version of Theano (0.7.0) instead of the bleeding edge one indicated in the install instructions due to some compatibility issues with Python 3.2, in case that could somehow be the root of the problem. Unlike this fellow (http://www.opendeep.org/v0.0.8/discuss/55b3b090a96deb1900990d7e) I haven't figured out the cause, though I'll let you know if I work it out. Running Kali Linux, Python 3.2, Pillow 2.7.0, numpy 1.9.2, and scipy 0.16.0 in addition to the aforementioned theano 0.7.0. Incidentally, thanks for putting this package together. A lot of work goes into something like this. Traceback (most recent call last): File "/home/usrname/PycharmProjects/599/OpenDeepTut.py", line 3, in <module> from opendeep.models.model import Model File "/home/usrname/Downloads/opendeep/opendeep/opendeep/__init__.py", line 26, in <module> from . import data File "/home/usrname/Downloads/opendeep/opendeep/opendeep/data/__init__.py", line 8, in <module> from .standard_datasets import * File "/home/usrname/Downloads/opendeep/opendeep/opendeep/data/standard_datasets/__init__.py", line 4, in <module> from .midi import * File "/home/usrname/Downloads/opendeep/opendeep/opendeep/data/standard_datasets/midi/__init__.py", line 3, in <module> from .jsb_chorales import JSBChorales File "/home/usrname/Downloads/opendeep/opendeep/opendeep/data/standard_datasets/midi/jsb_chorales.py", line 14, in <module> from opendeep.utils.midi import midiread File "/home/usrname/Downloads/opendeep/opendeep/opendeep/utils/midi/__init__.py", line 15, in <module> from MidiOutFile import MidiOutFile ImportError: No module named MidiOutFile

when I run your rbmminst sample I got this error Traceback (most recent call last): File "E:\project\python\test\test\opendeep_rbm.py", line 72, in <module> tile_shape=closest_to_square_factors(rbm.hidden_size), AttributeError: 'RBM' object has no attribute 'hidden_size'

I got this error, I can't find getSubSet() on the source, Did you change it ? File "E:\project_luna\cuda\open_deep\test\opendeeptest2.py", line 36, in <module> test_xs, _ = mnist.getSubset(datasets.Dataset.test_inputs) AttributeError: 'MNIST' object has no attribute 'getSubset'

I got this error, Now I am using phthon 2.7 INFO:opendeep.optimization.optimizer:Initializing optimizer <class 'opendeep.optimization.adadelta.AdaDelta'> INFO:opendeep.optimization.optimizer:Optimizer config args: {'grad_clip': None, 'save_freq': 1000000, 'min_batch_size': 1, 'stop_threshold': inf, 'decay': 0.95, 'hard_clip': False, 'learning_rate': 1e-06, 'batch_size': 100, 'stop_patience': 1, 'epochs': 10, 'lr_decay': None, 'model': <opendeep.data.standard_datasets.image.mnist.MNIST object at 0x00000000143F7630>, 'dataset': <opendeep.models.single_layer.autoencoder.DenoisingAutoencoder object at 0x00000000233BDA58>, 'lr_decay_factor': None} Traceback (most recent call last): File "E:\project_luna\cuda\open_deep\test\opendeeptest2.py", line 29, in <module> optimizer = AdaDelta(dae, mnist) File "F:\python27\python-2.7.9.amd64\lib\site-packages\opendeep-0.0.9a0-py2.7.egg\opendeep\optimization\adadelta.py", line 72, in __init__ super(AdaDelta, self).__init__(**initial_parameters) File "F:\python27\python-2.7.9.amd64\lib\site-packages\opendeep-0.0.9a0-py2.7.egg\opendeep\optimization\optimizer.py", line 123, in __init__ "Found %s" % str(type(model)) AssertionError: Optimizer input model needs to be a Model class! Found <class 'opendeep.data.standard_datasets.image.mnist.MNIST'>

I just git latest one and I got this error please check 2015-07-28 23:08:34,829 - opendeep.optimization.optimizer - INFO - Compiling f_learn 1/1 function for model <class '__main__.DenoisingAutoencoder'>... Traceback (most recent call last): File "E:\project\python\test\test\opendeeptest.py", line 83, in <module> optimizer.train() File "E:\program\python34\python-3.4.3.amd64\lib\site-packages\opendeep\optimization\optimizer.py", line 330, in train outputs=[train_cost] + self.train_monitors_dict.values(), TypeError: can only concatenate list (not "dict_values") to list

http://www.opendeep.org/docs/monitors-and-live-plotting on the sample, from opendeep.models.single_layer.basic import BasicLayer, SoftmaxLayer there is no basic (packge) and can't find BasicLayer , Which one I have to use ?

http://www.opendeep.org/docs/tutorial-first-steps On Example Code # grab 100 test examples test_xs, _ = mnist.getSubset(datasets.TEST) --> change like this mnist.getSubset(datasets.Dataset.test_inputs) is test_inputs is right attribute ?

hi thanks again your quick response I got latest one and I still got these error Please check 1) print () issues test_cifar10.py, example) print len(self.cifar.train_inputs) --> print (len(self.cifar.train_inputs)) 2) raise () issues MidFileParser.py,EventDispatcher.py example) raise TypeError, "It is not a valid midi file!" -> raise (TypeError, "It is not a valid midi file!") 3) packaage Path issues midi.py, MidiOutFile.py,RawOutstreamFile,MidiInFile,RawInstreamFile,MidiFileParser, EventDispatcher example) from MidiOutFile import MidiOutFile --> from opendeep.utils.midi.MidiOutFile import MidiOutFile 4) unused packages in python 3 issues RawOutstreamFile.py, RawInstreamFile, MIdiFileParser from types import StringType from cStringIO import StringIO 5) MidiOutFile,EventDispatcher from constants import * --> from . import constants 6) rnn_gsn,rnn_rbm cPickle is not used in python 3.4 import cPickle as pickle --> import pickle 7) Optimizer.py not used I commented from itertools import izip 8) mnist I got this error File "E:\project_luna\cuda\open_deep\test\opendeeptest.py", line 23, in <module> mnist = MNIST() File "F:\python34\python-3.4.3.amd64\lib\site-packages\opendeep-0.0.9a0-py3.4.egg\opendeep\data\standard_datasets\image\mnist.py", line 68, in __init__ gzip.open(self.path, 'rb') UnicodeDecodeError: 'ascii' codec can't decode byte 0x90 in position 614: ordinal not in range(128) so I changed the code like this gzip.open(self.path, 'rb'),encoding='iso-8859-1' 9) I still get this error from test import opendeeptest File "E:\project_luna\cuda\open_deep\test\opendeeptest.py", line 39, in <module> dae = DenoisingAutoencoder(**config) File "F:\python34\python-3.4.3.amd64\lib\site-packages\opendeep-0.0.9a0-py3.4.egg\opendeep\models\single_layer\autoencoder.py", line 152, in __init__ **{arg: val for (arg, val) in locals().iteritems() if arg is not 'self'} AttributeError: 'dict' object has no attribute 'iteritems'