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June 27, 2015 18:07
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Pylearn2 nosetests results
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| root@affe4bc530fd:/usr/local/src/pylearn2# nosetests | |
| /usr/local/src/pylearn2/pylearn2/packaged_dependencies/theano_linear/test_matrixmul.py:62: UserWarning: TODO: port these disabled tests to the new pylearn2 setup | |
| warnings.warn("TODO: port these disabled tests to the new pylearn2 setup") | |
| /opt/conda/lib/python2.7/site-packages/matplotlib/__init__.py:1318: UserWarning: This call to matplotlib.use() has no effect | |
| because the backend has already been chosen; | |
| matplotlib.use() must be called *before* pylab, matplotlib.pyplot, | |
| or matplotlib.backends is imported for the first time. | |
| warnings.warn(_use_error_msg) | |
| ..................../usr/local/src/pylearn2/pylearn2/training_algorithms/bgd.py:141: UserWarning: BGD is not compatible with stochastic costs and cannot determine whether the current cost is stochastic. | |
| warnings.warn("BGD is not compatible with stochastic costs " | |
| ./usr/local/src/pylearn2/pylearn2/train.py:85: UserWarning: dataset has no yaml src, model won't know what data it was trained on | |
| "data it was trained on") | |
| ./usr/local/src/pylearn2/pylearn2/monitor.py:572: UserWarning: Trained model saved without indicating yaml_src | |
| 'indicating yaml_src') | |
| ................SSSSSSSSSSSS............./usr/local/src/pylearn2/pylearn2/datasets/hdf5_deprecated.py:103: UserWarning: HDF5Dataset cannot perform test np.all(y < y_labels). Use y_labels at your own risk. | |
| "y_labels). Use y_labels at your own risk.") | |
| ..SSSSSS.SSSSSSSSSSSSSSSSSSSSSSSSSSS......../usr/local/src/pylearn2/pylearn2/datasets/preprocessing.py:1202: UserWarning: This ZCA preprocessor class is known to yield very different results on different platforms. If you plan to conduct experiments with this preprocessing on multiple machines, it is probably a good idea to do the preprocessing on a single machine and copy the preprocessed datasets to the others, rather than preprocessing the data independently in each location. | |
| warnings.warn("This ZCA preprocessor class is known to yield very " | |
| .../usr/local/src/pylearn2/pylearn2/datasets/preprocessing.py:1502: UserWarning: inv_P_ was None. Computing inverse of P_ now. This will take some time. For efficiency, it is recommended that in the future you compute the inverse in ZCA.fit() instead, by passing it store_inverse=True. | |
| warnings.warn("inv_P_ was None. Computing " | |
| ........SSSSSSS.SSSSS../usr/local/src/pylearn2/pylearn2/models/kmeans.py:21: UserWarning: Install milk ( http://packages.python.org/milk/ ) | |
| It has a better k-means implementation. Falling back to | |
| our own really slow implementation. | |
| our own really slow implementation. """) | |
| /usr/local/src/pylearn2/pylearn2/models/kmeans.py:21: UserWarning: Install milk ( http://packages.python.org/milk/ ) | |
| It has a better k-means implementation. Falling back to | |
| our own really slow implementation. | |
| our own really slow implementation. """) | |
| .ERROR (pylearn2.devtools.nan_guard): Inf detected | |
| ERROR (pylearn2.devtools.nan_guard): Big value detected | |
| ERROR (pylearn2.devtools.nan_guard): In an input | |
| ERROR (pylearn2.devtools.nan_guard): Inputs: | |
| ERROR (pylearn2.devtools.nan_guard): var | |
| ERROR (pylearn2.devtools.nan_guard): <TensorType(float64, matrix)> | |
| ERROR (pylearn2.devtools.nan_guard): A. <TensorType(float64, matrix)> | |
| ERROR (pylearn2.devtools.nan_guard): val | |
| ERROR (pylearn2.devtools.nan_guard): [array([[ inf, inf, inf, inf, inf], | |
| [ inf, inf, inf, inf, inf], | |
| [ inf, inf, inf, inf, inf]])] | |
| ERROR (pylearn2.devtools.nan_guard): var | |
| ERROR (pylearn2.devtools.nan_guard): <TensorType(float64, matrix)> | |
| ERROR (pylearn2.devtools.nan_guard): A. <TensorType(float64, matrix)> | |
| ERROR (pylearn2.devtools.nan_guard): val | |
| ERROR (pylearn2.devtools.nan_guard): [array([[ 0.23271284, -1.72441167, 0.10392659, 0.75127891, -2.01131259, | |
| -0.21728208, -0.58227592], | |
| [-0.8369439 , -0.20443899, -0.2864808 , 1.92397269, 1.6814356 , | |
| -0.19086308, 0.2061233 ], | |
| [ 2.15787953, 0.74631824, 0.89308301, 1.20570748, 0.01299836, | |
| -0.07539162, -0.46493743], | |
| [-0.89114511, -1.07780474, 0.55562017, -0.36061101, -0.72670668, | |
| -1.35736726, 1.09985907], | |
| [-0.14674666, 1.55485195, 0.01010881, -0.83636693, 0.873889 , | |
| -0.53304478, 0.28170689]])] | |
| ERROR (pylearn2.devtools.nan_guard): Node: | |
| ERROR (pylearn2.devtools.nan_guard): Dot22(<TensorType(float64, matrix)>, <TensorType(float64, matrix)>) | |
| ERROR (pylearn2.devtools.nan_guard): NaN detected | |
| /opt/conda/lib/python2.7/site-packages/numpy/lib/nanfunctions.py:319: RuntimeWarning: All-NaN slice encountered | |
| warnings.warn("All-NaN slice encountered", RuntimeWarning) | |
| /opt/conda/lib/python2.7/site-packages/numpy/lib/nanfunctions.py:220: RuntimeWarning: All-NaN axis encountered | |
| warnings.warn("All-NaN axis encountered", RuntimeWarning) | |
| ERROR (pylearn2.devtools.nan_guard): In an input | |
| ERROR (pylearn2.devtools.nan_guard): Inputs: | |
| ERROR (pylearn2.devtools.nan_guard): var | |
| ERROR (pylearn2.devtools.nan_guard): <TensorType(float64, matrix)> | |
| ERROR (pylearn2.devtools.nan_guard): A. <TensorType(float64, matrix)> | |
| ERROR (pylearn2.devtools.nan_guard): val | |
| ERROR (pylearn2.devtools.nan_guard): [array([[ nan, nan, nan, nan, nan], | |
| [ nan, nan, nan, nan, nan], | |
| [ nan, nan, nan, nan, nan]])] | |
| ERROR (pylearn2.devtools.nan_guard): var | |
| ERROR (pylearn2.devtools.nan_guard): <TensorType(float64, matrix)> | |
| ERROR (pylearn2.devtools.nan_guard): A. <TensorType(float64, matrix)> | |
| ERROR (pylearn2.devtools.nan_guard): val | |
| ERROR (pylearn2.devtools.nan_guard): [array([[ 0.23271284, -1.72441167, 0.10392659, 0.75127891, -2.01131259, | |
| -0.21728208, -0.58227592], | |
| [-0.8369439 , -0.20443899, -0.2864808 , 1.92397269, 1.6814356 , | |
| -0.19086308, 0.2061233 ], | |
| [ 2.15787953, 0.74631824, 0.89308301, 1.20570748, 0.01299836, | |
| -0.07539162, -0.46493743], | |
| [-0.89114511, -1.07780474, 0.55562017, -0.36061101, -0.72670668, | |
| -1.35736726, 1.09985907], | |
| [-0.14674666, 1.55485195, 0.01010881, -0.83636693, 0.873889 , | |
| -0.53304478, 0.28170689]])] | |
| ERROR (pylearn2.devtools.nan_guard): Node: | |
| ERROR (pylearn2.devtools.nan_guard): Dot22(<TensorType(float64, matrix)>, <TensorType(float64, matrix)>) | |
| ERROR (pylearn2.devtools.nan_guard): Big value detected | |
| ERROR (pylearn2.devtools.nan_guard): In an input | |
| ERROR (pylearn2.devtools.nan_guard): Inputs: | |
| ERROR (pylearn2.devtools.nan_guard): var | |
| ERROR (pylearn2.devtools.nan_guard): <TensorType(float64, matrix)> | |
| ERROR (pylearn2.devtools.nan_guard): A. <TensorType(float64, matrix)> | |
| ERROR (pylearn2.devtools.nan_guard): val | |
| ERROR (pylearn2.devtools.nan_guard): [array([[ 1.00000000e+20, 1.00000000e+20, 1.00000000e+20, | |
| 1.00000000e+20, 1.00000000e+20], | |
| [ 1.00000000e+20, 1.00000000e+20, 1.00000000e+20, | |
| 1.00000000e+20, 1.00000000e+20], | |
| [ 1.00000000e+20, 1.00000000e+20, 1.00000000e+20, | |
| 1.00000000e+20, 1.00000000e+20]])] | |
| ERROR (pylearn2.devtools.nan_guard): var | |
| ERROR (pylearn2.devtools.nan_guard): <TensorType(float64, matrix)> | |
| ERROR (pylearn2.devtools.nan_guard): A. <TensorType(float64, matrix)> | |
| ERROR (pylearn2.devtools.nan_guard): val | |
| ERROR (pylearn2.devtools.nan_guard): [array([[ 0.23271284, -1.72441167, 0.10392659, 0.75127891, -2.01131259, | |
| -0.21728208, -0.58227592], | |
| [-0.8369439 , -0.20443899, -0.2864808 , 1.92397269, 1.6814356 , | |
| -0.19086308, 0.2061233 ], | |
| [ 2.15787953, 0.74631824, 0.89308301, 1.20570748, 0.01299836, | |
| -0.07539162, -0.46493743], | |
| [-0.89114511, -1.07780474, 0.55562017, -0.36061101, -0.72670668, | |
| -1.35736726, 1.09985907], | |
| [-0.14674666, 1.55485195, 0.01010881, -0.83636693, 0.873889 , | |
| -0.53304478, 0.28170689]])] | |
| ERROR (pylearn2.devtools.nan_guard): Node: | |
| ERROR (pylearn2.devtools.nan_guard): Dot22(<TensorType(float64, matrix)>, <TensorType(float64, matrix)>) | |
| .................../usr/local/src/pylearn2/pylearn2/expr/tests/test_normalize.py:73: UserWarning: TODO: add test for the CudaConvnet version. | |
| warnings.warn("TODO: add test for the CudaConvnet version.") | |
| ........../usr/local/src/pylearn2/pylearn2/expr/tests/test_probabilistic_max_pooling.py:256: UserWarning: TODO: make sampling tests run on c01b format of pooling. | |
| warnings.warn("TODO: make sampling tests run on c01b format of pooling.") | |
| .............................................................SSSSSSSSSSSS............./usr/local/src/pylearn2/pylearn2/datasets/dense_design_matrix.py:1478: UserWarning: It looks like DefaultViewConverter.axes has been changed directly, please use the set_axes() method instead. | |
| "instead." % self.__class__.__name__) | |
| ......./usr/local/src/pylearn2/pylearn2/models/dbm/layer.py:2051: UserWarning: GaussianVisLayer math very faith based, need to finish working through gaussian.lyx | |
| warnings.warn("GaussianVisLayer math very faith based, need to finish working through gaussian.lyx") | |
| .............../usr/local/src/pylearn2/pylearn2/models/tests/test_dropout.py:17: UserWarning: | |
| TODO: add test that dropout_fprop with all include probabilities and scales set | |
| to 1 is equivalent to fprop. | |
| TODO: add a test file to the corresponding cost module and make sure that the | |
| dropout cost with everything set to 1 is equivalent to the Default cost | |
| """) | |
| ...S.S..............................S........../usr/local/src/pylearn2/pylearn2/models/rbm.py:591: UserWarning: The parameter 'updates' of theano.function() expects an OrderedDict, got <type 'dict'>. Using a standard dictionary here results in non-deterministic behavior. You should use an OrderedDict if you are using Python 2.7 (theano.compat.OrderedDict for older python), or use a list of (shared, update) pairs. Do not just convert your dictionary to this type before the call as the conversion will still be non-deterministic. | |
| self.learn_func = theano.function([minibatch], updates=updates) | |
| ..../opt/conda/lib/python2.7/site-packages/Theano-0.7.0-py2.7.egg/theano/gof/cmodule.py:293: RuntimeWarning: numpy.ndarray size changed, may indicate binary incompatibility | |
| rval = __import__(module_name, {}, {}, [module_name]) | |
| ..........S.................................................................................................................S............................................SSSSSSSSSSSS...SSSSS/usr/local/src/pylearn2/pylearn2/training_algorithms/sgd.py:590: UserWarning: The channel that has been chosen for monitoring is: objective. | |
| 'monitoring is: ' + str(self.channel_name) + '.') | |
| ..SS./usr/local/src/pylearn2/pylearn2/train.py:66: UserWarning: save_path specified but save_freq is 0 (never save). Is this intentional? | |
| warnings.warn('save_path specified but save_freq is 0 ' | |
| ......S...........................E...............................................................................................................S................/usr/local/src/pylearn2/pylearn2/tests/test_monitor.py:298: UserWarning: TODO: add unit test that iterators uneven property is set correctly. | |
| warnings.warn("TODO: add unit test that iterators uneven property is set correctly.") | |
| /usr/local/src/pylearn2/pylearn2/tests/test_monitor.py:333: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future. | |
| assert None not in batches | |
| ..............S.. | |
| ====================================================================== | |
| ERROR: Failure: ImportError (Import of Cython module failed. Please make sure you have run 'python setup.py develop' in the pylearn2 directory | |
| Original exception: | |
| ImportError: No module named _window_flip) | |
| ---------------------------------------------------------------------- | |
| Traceback (most recent call last): | |
| File "/opt/conda/lib/python2.7/site-packages/nose/loader.py", line 414, in loadTestsFromName | |
| addr.filename, addr.module) | |
| File "/opt/conda/lib/python2.7/site-packages/nose/importer.py", line 47, in importFromPath | |
| return self.importFromDir(dir_path, fqname) | |
| File "/opt/conda/lib/python2.7/site-packages/nose/importer.py", line 94, in importFromDir | |
| mod = load_module(part_fqname, fh, filename, desc) | |
| File "/usr/local/src/pylearn2/pylearn2/train_extensions/tests/test_window_flip.py", line 5, in <module> | |
| from pylearn2.train_extensions.window_flip import WindowAndFlip | |
| File "/usr/local/src/pylearn2/pylearn2/train_extensions/window_flip.py", line 16, in <module> | |
| reraise_as(ImportError("Import of Cython module failed. Please make sure " | |
| File "/usr/local/src/pylearn2/pylearn2/utils/exc.py", line 90, in reraise_as | |
| six.reraise(type(new_exc), new_exc, orig_exc_traceback) | |
| File "/usr/local/src/pylearn2/pylearn2/train_extensions/window_flip.py", line 13, in <module> | |
| from ..utils._window_flip import random_window_and_flip_c01b | |
| ImportError: Import of Cython module failed. Please make sure you have run 'python setup.py develop' in the pylearn2 directory | |
| Original exception: | |
| ImportError: No module named _window_flip | |
| ---------------------------------------------------------------------- | |
| Ran 696 tests in 1761.151s | |
| FAILED (SKIP=96, errors=1) |
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