Pylearn buildbot Fail=12 Err=28 Ran=174 Skip=0 KnownFail=0

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May 7, 2013, 7:50:31 AM5/7/13

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Summary of the output:

File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/test_cost.py", line 13, in test
ImportError: No module named common.autoname
ImportError: No module named old_dataset.dataset
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 19, in test_sgd0
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 38, in test_sgd_stepsize_variable
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 68, in test_sgd_stepsize_none
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sampling/tests/test_hmc.py", line 76, in test_hmc
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/test_cost.py", line 56, in test_gradient_fail
AssertionError: False is not true
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 76, in test_A
AssertionError:
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 108, in test_smaller
AssertionError:
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 113, in test_smaller32
AssertionError:
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 118, in test_big
AssertionError:
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/test_cost.py", line 13, in test
ImportError: No module named common.autoname
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/tests/test_stacker.py", line 29, in test_train
ImportError: No module named old_dataset.dataset
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 19, in test_sgd0
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 38, in test_sgd_stepsize_variable
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 68, in test_sgd_stepsize_none
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sampling/tests/test_hmc.py", line 76, in test_hmc
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/test_cost.py", line 56, in test_gradient_fail
AssertionError: False is not true
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 76, in test_A
AssertionError:
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 108, in test_smaller
AssertionError:
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 113, in test_smaller32
AssertionError:
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 118, in test_big
AssertionError:
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/test_cost.py", line 13, in test
ImportError: No module named common.autoname
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/dataset_ops/tests/test_cifar10.py", line 33, in test_shape_range
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/dataset_ops/tests/test_cifar10.py", line 97, in test_split_different
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/dataset_ops/tests/test_cifar10.py", line 126, in test_split_length
ImportError: No module named old_dataset.dataset
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 19, in test_sgd0
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 38, in test_sgd_stepsize_variable
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 68, in test_sgd_stepsize_none
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sampling/tests/test_mcmc.py", line 61, in test_mcmc
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/test_cost.py", line 56, in test_gradient_fail
AssertionError: False is not true
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 76, in test_A
AssertionError:

Full output:

Mon May 6 19:00:43 EDT 2013
abort: no repository found in '/part/01/Tmp/nightly_build/Theano' (.hg not found)!
parent: 1529:9737834dcb0f tip
Add the total test time in the buildbot.
branch: default
commit: (clean)
update: (current)
executing nosetests with mode=FAST_COMPILE
executing nosetests with mode=FAST_RUN
/part/01/Tmp/nightly_build/Pylearn/pylearn/sandbox/scan_inputs_groups.py:106: UserWarning: theano modules are deprecated and will be removed in release 0.7
self.M=theano.Module()
ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

EERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

...F....E/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/tests/test_mcRBM.py:131: 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, 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.
updates=trainer.cd_updates())
.......E./part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_dbd.py:17: 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, 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.
fn = theano.function([], cost, updates=ups)
.EEE.......................E.E../part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py:73: UserWarning: FunctionMaker.env is deprecated, it has been renamed 'fgraph'
env_r = f.maker.env.inputs[9]
/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py:74: UserWarning: FunctionMaker.env is deprecated, it has been renamed 'fgraph'
order = f.maker.env.toposort()
/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py:76: UserWarning: FunctionMaker.env is deprecated, it has been renamed 'fgraph'
assert str(f.maker.env.outputs[6].owner.inputs[0]) == 'r'
FFFF/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_lecun1998.py:26: UserWarning: FunctionMaker.env is deprecated, it has been renamed 'fgraph'
for i, n in enumerate(f.maker.env.toposort()):
...
======================================================================
ERROR: test (pylearn.algorithms.sandbox.test_cost.T_logfactorial)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/test_cost.py", line 13, in test
self.failUnless(numpy.all(f() - numpy.asarray([0., 0., 1.38629436, 3.29583687, 5.54517744, 8.04718956, 10.75055682, 13.62137104, 16.63553233, 19.7750212])) < 1e-5)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 586, in __call__
gof.vm.raise_with_op(self.fn.nodes[self.fn.position_of_error])
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 580, in __call__
outputs = self.fn()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')
-------------------- >> begin captured logging << --------------------
theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

--------------------- >> end captured logging << ---------------------

======================================================================
ERROR: Failure: ImportError (No module named common.autoname)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/loader.py", line 390, in loadTestsFromName
addr.filename, addr.module)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 39, in importFromPath
return self.importFromDir(dir_path, fqname)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 86, in importFromDir
mod = load_module(part_fqname, fh, filename, desc)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/tests/test_linear_regression.py", line 3, in <module>
from pylearn.algorithms.linear_regression import *
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/linear_regression.py", line 11, in <module>
from common.autoname import AutoName
ImportError: No module named common.autoname

======================================================================
ERROR: Failure: ImportError (No module named old_dataset.dataset)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/loader.py", line 390, in loadTestsFromName
addr.filename, addr.module)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 39, in importFromPath
return self.importFromDir(dir_path, fqname)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 86, in importFromDir
mod = load_module(part_fqname, fh, filename, desc)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/datasets/make_test_datasets.py", line 1, in <module>
from pylearn.old_dataset.dataset import ArrayDataSet
ImportError: No module named old_dataset.dataset

======================================================================
ERROR: test_sgd.test_sgd0
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 19, in test_sgd0
c = m.step_cost(3.0)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 586, in __call__
gof.vm.raise_with_op(self.fn.nodes[self.fn.position_of_error])
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 580, in __call__
outputs = self.fn()
NotImplementedError: input nd

======================================================================
ERROR: test_sgd.test_sgd_stepsize_variable
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 38, in test_sgd_stepsize_variable
c = m.step_cost(3.0)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 586, in __call__
gof.vm.raise_with_op(self.fn.nodes[self.fn.position_of_error])
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 580, in __call__
outputs = self.fn()
NotImplementedError: input nd

======================================================================
ERROR: test_sgd.test_sgd_stepsize_none
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 68, in test_sgd_stepsize_none
c = m.step_cost(3.0)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 586, in __call__
gof.vm.raise_with_op(self.fn.nodes[self.fn.position_of_error])
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 580, in __call__
outputs = self.fn()
NotImplementedError: input nd

======================================================================
ERROR: test_hmc.test_hmc
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sampling/tests/test_hmc.py", line 76, in test_hmc
assert abs(sampler.avg_acceptance_rate.get_value() -
UnboundLocalError: local variable 'sampler' referenced before assignment
-------------------- >> begin captured stdout << ---------------------
HMC

--------------------- >> end captured stdout << ----------------------

======================================================================
ERROR: Failure: AttributeError ('module' object has no attribute 'RandomStreams')
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/loader.py", line 390, in loadTestsFromName
addr.filename, addr.module)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 39, in importFromPath
return self.importFromDir(dir_path, fqname)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 86, in importFromDir
mod = load_module(part_fqname, fh, filename, desc)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sandbox/test_scan_inputs_groups.py", line 10, in <module>
from pylearn.sandbox.scan_inputs_groups import FillMissing
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sandbox/scan_inputs_groups.py", line 428, in <module>
scannoise=ScanNoise()
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sandbox/scan_inputs_groups.py", line 391, in __init__
self.M.rand = T.RandomStreams(seed)
AttributeError: 'module' object has no attribute 'RandomStreams'

======================================================================
FAIL: test_gradient_fail (pylearn.algorithms.sandbox.test_cost.T_nlpoisson)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/test_cost.py", line 56, in test_gradient_fail
self.failUnless(numpy.all(f() - numpy.asarray([206., 559.96605666, 558.96605666, 205., 557.96605666, 204., 30473.11077513, 459.96605666] < 1e-5)))
AssertionError: False is not true
-------------------- >> begin captured stdout << ---------------------
[array([-0., -1., -1., -0., -1., -0., -5., -1.])]

--------------------- >> end captured stdout << ----------------------

======================================================================
FAIL: test_kouh2008.test_A
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 76, in test_A
assert str(f.maker.env.outputs[6].owner.inputs[0]) == 'r'
AssertionError:
-------------------- >> begin captured logging << --------------------
pylearn.shared.layers.kouh2008: DEBUG: dtype float64
pylearn.shared.layers.kouh2008: DEBUG: output dtype float64
pylearn.shared.layers.LogisticRegression: DEBUG: allocating params w, b 10 2 float64
--------------------- >> end captured logging << ---------------------

======================================================================
FAIL: test_kouh2008.test_smaller
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 108, in test_smaller
assert rval < 6.1
AssertionError:
-------------------- >> begin captured stdout << ---------------------
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::f_0]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::f_1]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh::2008::b_0]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh::2008::b_1]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::w]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, p]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, q]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, r]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, k]
COMPILING
DONE

--------------------- >> end captured stdout << ----------------------
-------------------- >> begin captured logging << --------------------
pylearn.shared.layers.kouh2008: DEBUG: dtype float64
pylearn.shared.layers.kouh2008: DEBUG: output dtype float64
pylearn.shared.layers.LogisticRegression: DEBUG: allocating params w, b 8 2 float64
--------------------- >> end captured logging << ---------------------

======================================================================
FAIL: test_kouh2008.test_smaller32
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 113, in test_smaller32
assert rval < 6.1
AssertionError:
-------------------- >> begin captured stdout << ---------------------
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::f_0]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::f_1]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh::2008::b_0]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh::2008::b_1]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::w]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, p]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, q]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, r]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, k]
COMPILING
DONE

--------------------- >> end captured stdout << ----------------------
-------------------- >> begin captured logging << --------------------
pylearn.shared.layers.kouh2008: DEBUG: dtype float64
pylearn.shared.layers.kouh2008: DEBUG: output dtype float64
pylearn.shared.layers.LogisticRegression: DEBUG: allocating params w, b 8 2 float64
--------------------- >> end captured logging << ---------------------

======================================================================
FAIL: test_kouh2008.test_big
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 118, in test_big
assert rval < 0.1
AssertionError:
-------------------- >> begin captured stdout << ---------------------
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::f_0]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::f_1]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh::2008::b_0]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh::2008::b_1]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::w]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, p]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, q]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, r]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, k]
COMPILING
DONE

--------------------- >> end captured stdout << ----------------------
-------------------- >> begin captured logging << --------------------
pylearn.shared.layers.kouh2008: DEBUG: dtype float64
pylearn.shared.layers.kouh2008: DEBUG: output dtype float64
pylearn.shared.layers.LogisticRegression: DEBUG: allocating params w, b 100 2 float64
--------------------- >> end captured logging << ---------------------

Name Stmts Miss Cover Missing
----------------------------------------------------------------------------
pylearn 2 1 50% 25
pylearn.algorithms 0 0 100%
pylearn.algorithms.aa 73 9 88% 29, 52, 58, 69, 72, 79, 83, 89, 110
pylearn.algorithms.exponential_mean 64 4 94% 48, 51-55
pylearn.algorithms.logistic_regression 164 128 22% 31-118, 122-124, 127-134, 153-199, 203-262, 287, 310, 323-337, 344-346, 350, 353, 356, 359, 362, 365, 368
pylearn.algorithms.mcRBM 187 84 55% 249, 362-364, 375-376, 385-388, 397-400, 407-421, 509-540, 558-560, 566-569, 578-581, 596, 607, 619-631, 660-673, 706, 711, 768-773, 808-813
pylearn.algorithms.regressor 70 9 87% 22, 49, 67, 69, 79, 82, 85, 88, 91
pylearn.algorithms.sandbox 0 0 100%
pylearn.algorithms.sandbox.cost 37 10 73% 20-21, 35-40, 44, 124
pylearn.algorithms.stacker 71 7 90% 88, 96, 101, 106-109
pylearn.dataset_ops 3 0 100%
pylearn.dataset_ops.cifar10 157 60 62% 30-35, 70-72, 74, 108, 112, 120, 146, 158, 163-165, 171, 178-185, 198-222, 229-232, 236-239, 246-262, 265-268
pylearn.dataset_ops.image_patches 68 31 54% 19-30, 38-57, 74-75, 97, 109, 116, 120-121
pylearn.dataset_ops.memo 20 1 95% 7
pylearn.dataset_ops.protocol 66 10 85% 23, 29, 41, 44, 97-100, 114-115
pylearn.dataset_ops.sandbox 0 0 100%
pylearn.datasets 1 0 100%
pylearn.datasets.config 37 8 78% 20-23, 39, 47-50
pylearn.datasets.dataset 24 3 88% 12, 44, 50
pylearn.datasets.embeddings 1 0 100%
pylearn.datasets.embeddings.parameters 5 0 100%
pylearn.datasets.embeddings.process 57 43 25% 18, 21-22, 28-49, 62-82, 90-95
pylearn.datasets.image_patches 47 36 23% 25-51, 64-69, 76-81, 102-116
pylearn.datasets.tzanetakis 74 36 51% 15-20, 25-59, 80-82, 84-87, 116, 123-124, 127
pylearn.external 0 0 100%
pylearn.formulas 0 0 100%
pylearn.gd 1 0 100%
pylearn.gd.dbd 26 0 100%
pylearn.gd.sgd 60 27 55% 19-20, 22, 28-43, 79, 85, 90, 98-101, 116-119
pylearn.io 0 0 100%
pylearn.io.amat 67 61 9% 54-137
pylearn.io.filetensor 98 15 85% 78, 86-87, 150, 157, 206-207, 212-219
pylearn.io.image_tiling 98 90 8% 9-12, 46-129, 135-137, 144-152, 155-179, 186-200
pylearn.io.seriestables 1 0 100%
pylearn.io.seriestables.series 223 38 83% 41, 43, 93, 95, 111, 114, 130-131, 134-138, 141-142, 220, 222, 225, 230, 235, 239, 242, 245, 248, 251, 255, 258, 275, 300, 332, 334, 369, 511, 515, 551, 567, 610, 660, 662
pylearn.io.wavread 33 17 48% 26, 28, 30, 32, 34-50, 53
pylearn.preprocessing 1 0 100%
pylearn.preprocessing.pca 46 13 72% 58-59, 63, 119-121, 130, 153-156, 163-164
pylearn.sampling 0 0 100%
pylearn.sampling.hmc 68 4 94% 42, 51, 152, 269
pylearn.sampling.mcmc 41 0 100%
pylearn.sandbox 0 0 100%
pylearn.sandbox.rbm 0 0 100%
pylearn.sandbox.simple_autoassociator 0 0 100%
pylearn.sandbox.sparse_random_autoassociator 0 0 100%
pylearn.shared 0 0 100%
pylearn.shared.layers 8 0 100%
pylearn.shared.layers.exponential_mean 30 16 47% 42-68, 82
pylearn.shared.layers.kording2004 69 47 32% 28, 33-34, 47-50, 61-71, 87-125
pylearn.shared.layers.kouh2008 151 53 65% 28-29, 76, 95, 113-117, 196, 199, 225-228, 247-296
pylearn.shared.layers.lecun1998 39 6 85% 38, 40, 42, 80, 84, 90
pylearn.shared.layers.logreg 31 5 84% 39-45
pylearn.shared.layers.rust2005 137 106 23% 22-23, 44-52, 71-103, 109-116, 127-172, 199-202, 237-288
pylearn.shared.layers.sandbox 0 0 100%
pylearn.shared.layers.sgd 57 45 21% 24-31, 37-59, 104-118, 122-138, 141
pylearn.shared.layers.sigmoidal_layer 22 1 95% 41
pylearn.shared.layers.squash 15 4 73% 6-7, 12-13
pylearn.shared.layers.util 25 5 80% 33-37
theano 73 7 90% 165, 172-175, 185-187
theano.compat 24 24 0% 6-46
theano.compat.python2x 228 220 4% 7-309, 312, 316, 319-322, 324, 328-341
theano.compat.six 220 219 1% 22-251, 254-392
theano.compile 13 5 62% 7, 13, 19-21, 27
theano.compile.builders 45 6 87% 45, 101-109
theano.compile.debugmode 1212 142 88% 99-100, 107, 143, 147, 159-164, 167-192, 194, 196, 198, 201-202, 205, 210, 214, 217, 220, 257-264, 276, 279-309, 313, 320-334, 353, 360, 377-378, 440, 442, 468, 470-471, 475-476, 479, 481-482, 487, 770, 831, 948, 953, 959, 966, 973, 975, 1204, 2161-2164, 2208, 2236-2248, 2317, 2326-2351, 2361, 2417, 2461-2496
theano.compile.function 35 0 100%
theano.compile.function_module 673 7 99% 23, 112, 252, 447, 450, 456, 1310
theano.compile.io 74 14 81% 105-106, 114, 126-136
theano.compile.mode 174 19 89% 4, 12, 35-52, 79, 113, 116, 120, 163, 284, 307, 363
theano.compile.module 623 74 88% 8, 12, 25, 38, 47, 56-60, 97, 107, 121-124, 127-130, 138, 146, 183-186, 268-271, 510, 512-524, 526, 528, 530, 534, 579-584, 590, 596, 614, 655, 734-737, 740, 753, 776-778, 783-784, 794, 869-871, 890-891, 1059, 1086, 1089, 1092, 1200-1202, 1212, 1219-1240
theano.compile.monitormode 14 14 0% 5-53
theano.compile.ops 82 47 43% 2-9, 22-32, 35, 38, 41-46, 49, 60-62, 68-72, 77, 80-108, 121-130, 133, 136, 139, 142-152, 158-162, 167, 178-185
theano.compile.pfunc 182 1 99% 527
theano.compile.profilemode 360 278 23% 14, 44-45, 50, 61-62, 70, 109, 121, 138-139, 142-148, 150, 156-183, 193, 221-248, 260-271, 273-292, 321-647
theano.compile.profiling 474 388 18% 32, 49-61, 67, 71, 75, 84-85, 88, 92, 101, 117-130, 154, 169-176, 186, 195-198, 200-201, 204-211, 215-216, 218-225, 227-234, 237-241, 245-265, 269-280, 283-288, 291-302, 304-324, 326-335, 343-356, 359-368, 371-376, 378-423, 432-457, 460-557, 562-700, 707-709, 713-723, 736-752, 757, 759, 763-774, 779, 786-804, 811-813, 815-1161
theano.compile.sharedvalue 62 5 92% 130-131, 138, 207, 211
theano.configdefaults 86 7 92% 9, 404-408, 429
theano.configparser 170 26 85% 13-15, 20, 27-28, 54, 59, 69, 72, 84, 127, 148-158, 248, 313-317, 337, 352, 359, 365
theano.gof 12 0 100%
theano.gof.callcache 33 26 21% 7-15, 18-25, 28-38, 41-45
theano.gof.cc 638 34 95% 16, 19, 23, 68-71, 87, 92, 329, 480, 1604-1640
theano.gof.cmodule 825 24 97% 686, 1148-1153, 1179-1181, 1197, 1225, 1251, 1263, 1278, 1650, 1660, 1666, 1679, 1691, 1703, 1712, 1821-1825, 1844-1845
theano.gof.compiledir 182 121 34% 116, 142-143, 153, 163-193, 195-337
theano.gof.compilelock 143 39 73% 15-38, 61-64, 85, 96-107, 145-146, 180-181, 194-202, 224, 236, 241-247, 260, 273, 276, 297
theano.gof.cutils 48 36 25% 6, 11, 15, 23-41, 219-295
theano.gof.destroyhandler 235 16 93% 21, 231, 603-646, 668, 760-768, 798, 818, 888
theano.gof.fg 325 58 82% 17, 34-65, 157-158, 160, 162, 178, 192, 264-265, 278-298, 415, 438, 448, 528, 531, 600-602, 607, 610-612, 615, 623, 627-628, 631-633, 635-639, 647, 652, 659-678
theano.gof.graph 401 16 96% 25-43, 118, 138, 156-158, 211, 218, 224-225, 232-235, 576, 722
theano.gof.lazylinker_c 70 33 53% 2, 7, 10, 22-23, 35, 38, 48-49, 59, 64, 74-75, 82-110
theano.gof.link 292 42 86% 9-51, 91, 101, 134, 169, 176, 180, 214, 242, 246, 284, 360-365, 367, 370, 373, 384, 395, 424, 429, 498, 519
theano.gof.null_type 18 8 56% 22, 25, 28, 31, 34, 37-40
theano.gof.op 224 51 77% 10-13, 28-31, 315-349, 395, 398, 401-404, 406-407, 410, 424-427, 435, 438, 447-448, 450, 461-467, 497, 654, 670, 675, 679-680, 682-683, 723, 725-726, 731, 734-753, 776, 779, 782, 795-802, 808, 818, 820
theano.gof.opt 928 55 94% 10, 61, 81, 182, 193, 197, 200, 245, 249, 340, 589, 805, 813, 1343, 1369, 1513, 1521-1522, 1526, 1529, 1533, 1540, 1542, 1545, 1548-1585, 1589-1593, 1596, 1602, 1725, 1740, 1743
theano.gof.optdb 147 11 93% 39, 123, 239-244, 247-248, 251, 253
theano.gof.python25 1 0 100%
theano.gof.sched 78 49 37% 3, 28, 30-31, 44, 56-69, 92-106, 136, 138, 140-154, 179-197
theano.gof.toolbox 184 27 85% 7-11, 199, 259, 263-267, 271-272, 276-277, 285, 293, 295, 298-299, 304, 307-308, 311-312, 315-316, 320, 324-325
theano.gof.type 83 25 70% 12, 45, 97-140, 181-200, 215, 228, 257, 295, 306, 327, 356-360, 404, 409-412, 425, 446, 459, 462-465
theano.gof.unify 197 105 47% 40, 53-54, 63, 190-195, 202-203, 210-213, 220-224, 231-235, 242-243, 250, 257-264, 271-273, 280-287, 294-296, 303, 305-309, 317-321, 329-331, 342-344, 355-356, 359, 366, 370, 374, 386-395, 399, 403-405, 416-420, 427, 434-438, 446-474
theano.gof.utils 220 121 45% 1-7, 19-20, 22-35, 49-51, 53-56, 59-61, 63-64, 72, 77, 87-90, 105-107, 109-111, 113, 124, 132-133, 141-144, 146-152, 154-164, 166-168, 172, 174, 176-180, 191, 198-231, 233-239, 241, 245, 247, 259, 272-273, 276, 281-284, 311, 316, 319-324, 331, 342-346, 350, 353, 356, 361-402
theano.gof.vm 398 14 96% 33, 36-38, 53-81, 97-104, 115, 133, 147, 854
theano.gradient 615 21 97% 33-38, 60, 67, 109, 1467, 1503-1506, 1512, 1515-1516, 1519-1529, 1579, 1586, 1599, 1621
theano.ifelse 356 155 56% 88, 99-106, 131, 137, 148, 196-197, 457-462, 467-487, 492-493, 498-501, 507, 509-511, 522-536, 540-541, 548, 551-552, 554-562, 566-586, 588-592, 597-612, 615-637, 639-643, 648-697
theano.misc 0 0 100%
theano.misc.cpucount 18 15 17% 41-57
theano.misc.ordered_set 111 78 30% 1-10, 21-48, 64, 73, 79, 104-113, 115-125, 132-220
theano.misc.safe_asarray 13 2 85% 31, 48
theano.misc.strutil 34 27 21% 17-29, 32, 37-60
theano.misc.windows 20 9 55% 1-5, 11-23
theano.printing 655 183 72% 17-19, 27, 29-30, 34-37, 82, 88, 90-91, 103-104, 113-114, 117-121, 240, 242, 247, 252, 257, 287, 294, 297-299, 359, 365, 368-373, 376-398, 403-409, 415, 431, 486, 786, 789, 795-801, 811-814, 821-897, 901, 905, 908, 910, 929, 932, 936, 940-945, 948, 981, 1063, 1080-1152, 1161
theano.sandbox 0 0 100%
theano.sandbox.cuda 201 8 96% 366, 445, 447-450, 457, 459-468
theano.sandbox.cuda.basic_ops 984 96 90% 556, 841, 845, 859, 1111, 1135, 1163, 1190, 1193, 1243-1247, 1366, 1386-1387, 1407-1408, 1485, 1517, 1549, 1586, 1795, 2420, 2453, 2458, 2554, 2575, 2586, 2608, 2611, 2674, 2725, 2746, 2819, 2889, 2901, 2925, 2977-2978, 2989-2992, 3001-3004, 3013-3016, 3025-3028, 3037-3040, 3049-3053, 3061-3105
theano.sandbox.cuda.blas 285 1 99% 942
theano.sandbox.cuda.elemwise 466 170 64% 168-261, 267-408, 527, 533, 580-581, 583, 585-589, 621-624, 663-664, 715, 736, 787, 905, 1050-1054
theano.sandbox.cuda.kernel_codegen 61 34 44% 17, 20-23, 34, 64-69, 109, 115, 121, 143, 194-213, 252, 285-316
theano.sandbox.cuda.nnet 102 30 71% 30-32, 93-95, 209, 225, 228, 231, 234, 238, 241-243, 364, 367, 373, 376, 383, 534, 537, 540, 544, 547-549, 655-701
theano.sandbox.cuda.nvcc_compiler 231 3 99% 79, 91, 383
theano.sandbox.cuda.opt 787 1 99% 343
theano.sandbox.cuda.rng_curand 120 6 95% 134, 268, 277-281
theano.sandbox.cuda.type 165 1 99% 483
theano.sandbox.cuda.var 91 18 80% 51, 148, 153-167, 204-205
theano.sandbox.softsign 23 4 83% 9, 11, 19, 25
theano.scalar 2 0 100%
theano.scalar.basic 1614 22 99% 46, 85, 111, 114-118, 152, 220, 283, 414-420, 446, 449, 456, 521, 712, 718, 725, 960, 978, 2856
theano.scalar.basic_scipy 138 54 61% 19, 25, 53, 59, 65, 73, 100-101, 104, 122-124, 128, 132, 136, 150-152, 158-165, 170-173, 181-189, 197, 200, 205-274
theano.scalar.sharedvar 22 1 95% 42
theano.scan_module 8 0 100%
theano.scan_module.scan 382 32 92% 56-57, 61-65, 385-387, 426, 470-476, 488-489, 498, 600-603, 654, 658-663, 671, 680, 744, 749, 763, 1055
theano.scan_module.scan_op 1140 261 77% 154-156, 158-160, 791, 816-821, 828-830, 844, 854-861, 869-874, 878-886, 890, 894, 898-901, 909-910, 912, 917-943, 947-949, 953-954, 961-974, 980-981, 988-996, 999-1001, 1006-1007, 1009, 1022, 1767-1768, 1777-1778, 1803, 1810-2078
theano.scan_module.scan_opt 943 190 80% 449, 1207, 1213, 1217-1223, 1228, 1243, 1254-1264, 1267-1277, 1281-1296, 1305-1307, 1313-1322, 1325-1335, 1340, 1345-1362, 1368-1377, 1401-1407, 1413-1418, 1422, 1429, 1452-1693
theano.scan_module.scan_perform_ext 57 1 98% 45
theano.scan_module.scan_utils 582 52 91% 21, 28-37, 50-51, 61-63, 86, 108, 123, 136-138, 144-145, 152-155, 925, 946-1017
theano.scan_module.scan_views 18 1 94% 113
theano.sparse 16 3 81% 11-13
theano.sparse.basic 1430 11 99% 2648, 2652, 2719, 2919, 3010, 3013, 3064, 3148, 3154, 3253, 3265
theano.sparse.opt 443 140 68% 57-59, 104, 111, 135, 292-295, 302-304, 321-325, 428-436, 482, 488, 491, 504-507, 510, 518, 537-559, 758, 764-768, 908, 920-923, 1024, 1036-1039, 1127, 1130-1138, 1179, 1187-1191, 1270, 1272-1281, 1322-1329, 1337-1341, 1429, 1431-1448, 1541-1568, 1679, 1688, 1691-1697
theano.sparse.sharedvar 16 1 94% 27
theano.sparse.type 81 24 70% 5-6, 18, 22, 60, 67, 74-79, 82, 85, 87, 105, 108, 115, 118, 121, 127, 131-137, 148, 153-154
theano.sparse.utils 3 0 100%
theano.tensor 20 3 85% 26, 36, 59
theano.tensor.basic 3432 202 94% 24, 56, 58-60, 85, 101-111, 114, 7144-7145, 7149, 7280, 7286, 7288-7289, 7311-7312, 7326, 7329, 7344, 7349-7350, 7395, 7400, 7409, 7414, 7417, 7443, 7450, 7453, 7467-7474, 7478, 7498, 7509, 7513, 7529, 7534, 7556-7557, 7562, 7566-7571, 7576, 7582-7583, 7589, 7592, 7596, 7599-7602, 7607, 7631-7633, 7636, 7669, 7691, 7699-7700, 7702, 7708, 7816, 7835, 7839, 7842, 7867, 7878-7880, 7889-7891, 7899, 7909-7911, 7959, 7968-8106, 8111-8115, 8124, 8130-8156, 8163-8309
theano.tensor.blas 814 7 99% 379, 463, 474, 1939-1949
theano.tensor.blas_c 58 6 90% 267, 580, 584, 594, 607-618
theano.tensor.blas_headers 60 46 23% 6-17, 47-135, 717, 924-934, 951, 955-960, 965-967
theano.tensor.blas_scipy 38 5 87% 25-28, 32, 38
theano.tensor.deprecated 0 0 100%
theano.tensor.deprecated.rmodule 77 20 74% 7, 35-39, 53-57, 64-69, 101, 115, 124
theano.tensor.elemwise 898 69 92% 45, 54, 413-416, 422, 1897-1965, 1973-1975, 1979-2026
theano.tensor.elemwise_cgen 130 1 99% 225
theano.tensor.extra_ops 255 3 99% 388, 398, 467
theano.tensor.io 140 120 14% 6-12, 24, 27, 30, 33, 36, 43-44, 46, 52-282
theano.tensor.nnet 6 0 100%
theano.tensor.nnet.Conv3D 145 3 98% 345-348
theano.tensor.nnet.ConvGrad3D 67 0 100%
theano.tensor.nnet.ConvTransp3D 122 1 99% 34
theano.tensor.nnet.conv 598 46 92% 31-32, 129, 264, 442, 590-593, 600, 658, 667-702, 708, 721, 874, 1230, 1251-1258
theano.tensor.nnet.nnet 740 135 82% 67-71, 245, 487, 491-495, 517, 525-527, 533, 538, 544-547, 555, 566, 701, 792-794, 828-829, 833, 836, 839, 857, 944, 947, 956, 966, 969, 992, 1394-1399, 1428-1429, 1452, 1492, 1557, 1566-1567, 1571, 1587, 1589-1595, 1598, 1601, 1607, 1612-1615, 1627, 1756, 1763, 1771-1772, 1776-1779, 1781-1870, 1891
theano.tensor.nnet.sigm 309 21 93% 29, 66, 89, 108, 338, 463, 623-624, 628, 630-631, 644, 646-647, 649-654, 665
theano.tensor.opt 2097 49 98% 15, 18, 145, 351, 472, 651-655, 1334-1335, 1363, 1370-1375, 4198-4244, 4659-4666
theano.tensor.opt_uncanonicalize 42 3 93% 39, 49, 78
theano.tensor.randomstreams 66 1 98% 163
theano.tensor.raw_random 340 67 80% 55-56, 59, 62-65, 67, 70, 72-91, 134-137, 150-151, 200, 231, 246, 332, 337, 343, 381, 419-426, 505, 540, 559, 563-566, 601, 616-619, 652, 671, 675-678, 691-693, 706, 708, 716, 772-774, 778, 809-810, 823, 843, 877-889
theano.tensor.shared_randomstreams 42 5 88% 77, 79-82, 115-117
theano.tensor.sharedvar 36 4 89% 14, 86-88
theano.tensor.signal 0 0 100%
theano.tensor.signal.downsample 136 41 70% 14-16, 32, 84, 91-92, 95-96, 124, 131-151, 268-277, 284-286
theano.tensor.sort 70 1 99% 147
theano.tensor.utils 31 0 100%
theano.tensor.xlogx 41 18 56% 1, 4, 10, 13-16, 29, 31-38, 41-44, 46, 57, 59
theano.updates 46 24 48% 14, 53, 59, 61-91
theano.version 8 0 100%
----------------------------------------------------------------------------
TOTAL 36178 6003 83%
----------------------------------------------------------------------
Ran 58 tests in 224.951s

FAILED (errors=8, failures=5)
Closing remaining open files: /Tmp/lisa/tmpcJEgfX... done /Tmp/lisa/tmpVfUotg... done /Tmp/lisa/tmpi3Rewj... done /Tmp/lisa/tmpNzwWWi... done /Tmp/lisa/tmpjlwZHq... done /Tmp/lisa/tmpzKvX0S... done /Tmp/lisa/tmph0Q0YS... done /Tmp/lisa/tmps13oQT... done /Tmp/lisa/tmpMBjvRw... done /Tmp/lisa/tmpfB0RdU... done /Tmp/lisa/tmpEg7hDA... done
executing nosetests with mode=FAST_RUN,floatX=float32
/part/01/Tmp/nightly_build/Pylearn/pylearn/sandbox/scan_inputs_groups.py:106: UserWarning: theano modules are deprecated and will be removed in release 0.7
self.M=theano.Module()
ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

EERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

...F....E/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/tests/test_mcRBM.py:131: 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, 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.
updates=trainer.cd_updates())
..E....E./part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_dbd.py:17: 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, 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.
fn = theano.function([], cost, updates=ups)
.EEE.......................E.E../part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py:73: UserWarning: FunctionMaker.env is deprecated, it has been renamed 'fgraph'
env_r = f.maker.env.inputs[9]
/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py:74: UserWarning: FunctionMaker.env is deprecated, it has been renamed 'fgraph'
order = f.maker.env.toposort()
/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py:76: UserWarning: FunctionMaker.env is deprecated, it has been renamed 'fgraph'
assert str(f.maker.env.outputs[6].owner.inputs[0]) == 'r'
FFFF/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_lecun1998.py:26: UserWarning: FunctionMaker.env is deprecated, it has been renamed 'fgraph'
for i, n in enumerate(f.maker.env.toposort()):
...
======================================================================
ERROR: test (pylearn.algorithms.sandbox.test_cost.T_logfactorial)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/test_cost.py", line 13, in test
self.failUnless(numpy.all(f() - numpy.asarray([0., 0., 1.38629436, 3.29583687, 5.54517744, 8.04718956, 10.75055682, 13.62137104, 16.63553233, 19.7750212])) < 1e-5)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 586, in __call__
gof.vm.raise_with_op(self.fn.nodes[self.fn.position_of_error])
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 580, in __call__
outputs = self.fn()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')
-------------------- >> begin captured logging << --------------------
theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

--------------------- >> end captured logging << ---------------------

======================================================================
ERROR: Failure: ImportError (No module named common.autoname)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/loader.py", line 390, in loadTestsFromName
addr.filename, addr.module)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 39, in importFromPath
return self.importFromDir(dir_path, fqname)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 86, in importFromDir
mod = load_module(part_fqname, fh, filename, desc)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/tests/test_linear_regression.py", line 3, in <module>
from pylearn.algorithms.linear_regression import *
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/linear_regression.py", line 11, in <module>
from common.autoname import AutoName
ImportError: No module named common.autoname

======================================================================
ERROR: pylearn.algorithms.tests.test_stacker.test_train
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/tests/test_stacker.py", line 29, in test_train
cost = model.update(data, targets)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 498, in __call__
allow_downcast=s.allow_downcast)
File "/Tmp/nightly_build/Theano/theano/tensor/basic.py", line 758, in filter
raise TypeError(err_msg, data)
TypeError: ('Bad input argument to theano function at index 0(0-based)', 'TensorType(float32, matrix) cannot store a value of dtype int64 without risking loss of precision. If you do not mind this loss, you can: 1) explicitly cast your data to float32, or 2) set "allow_input_downcast=True" when calling "function".', array([[0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1,
0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1,
1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0,
0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0,
1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0],
[1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0,
1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1,
1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0,
1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0,
0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0],
[1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0,
0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0,
1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1,
1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0,
1, 0, 0, 1, 0, 0, 1, 1, 1, 0, 0, 1],
[1, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0,
1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0,
0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0,
1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 1,
0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1],
[0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1,
1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0,
1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0,
1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1,
1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1],
[1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1,
1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0,
1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0,
0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1,
1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1],
[0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 1,
0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0,
1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0,
0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1,
1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0],
[0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0,
1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1,
0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1,
1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1,
0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1],
[1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0,
1, 0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0,
1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1,
0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0,
0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0],
[0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0,
0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1,
1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1,
1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0]]))

======================================================================
ERROR: Failure: ImportError (No module named old_dataset.dataset)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/loader.py", line 390, in loadTestsFromName
addr.filename, addr.module)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 39, in importFromPath
return self.importFromDir(dir_path, fqname)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 86, in importFromDir
mod = load_module(part_fqname, fh, filename, desc)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/datasets/make_test_datasets.py", line 1, in <module>
from pylearn.old_dataset.dataset import ArrayDataSet
ImportError: No module named old_dataset.dataset

======================================================================
ERROR: test_sgd.test_sgd0
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 19, in test_sgd0
c = m.step_cost(3.0)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 586, in __call__
gof.vm.raise_with_op(self.fn.nodes[self.fn.position_of_error])
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 580, in __call__
outputs = self.fn()
NotImplementedError: input nd

======================================================================
ERROR: test_sgd.test_sgd_stepsize_variable
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 38, in test_sgd_stepsize_variable
c = m.step_cost(3.0)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 586, in __call__
gof.vm.raise_with_op(self.fn.nodes[self.fn.position_of_error])
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 580, in __call__
outputs = self.fn()
NotImplementedError: input nd

======================================================================
ERROR: test_sgd.test_sgd_stepsize_none
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 68, in test_sgd_stepsize_none
c = m.step_cost(3.0)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 586, in __call__
gof.vm.raise_with_op(self.fn.nodes[self.fn.position_of_error])
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 580, in __call__
outputs = self.fn()
NotImplementedError: input nd

======================================================================
ERROR: test_hmc.test_hmc
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sampling/tests/test_hmc.py", line 76, in test_hmc
assert abs(sampler.avg_acceptance_rate.get_value() -
UnboundLocalError: local variable 'sampler' referenced before assignment
-------------------- >> begin captured stdout << ---------------------
HMC

--------------------- >> end captured stdout << ----------------------

======================================================================
ERROR: Failure: AttributeError ('module' object has no attribute 'RandomStreams')
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/loader.py", line 390, in loadTestsFromName
addr.filename, addr.module)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 39, in importFromPath
return self.importFromDir(dir_path, fqname)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 86, in importFromDir
mod = load_module(part_fqname, fh, filename, desc)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sandbox/test_scan_inputs_groups.py", line 10, in <module>
from pylearn.sandbox.scan_inputs_groups import FillMissing
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sandbox/scan_inputs_groups.py", line 428, in <module>
scannoise=ScanNoise()
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sandbox/scan_inputs_groups.py", line 391, in __init__
self.M.rand = T.RandomStreams(seed)
AttributeError: 'module' object has no attribute 'RandomStreams'

======================================================================
FAIL: test_gradient_fail (pylearn.algorithms.sandbox.test_cost.T_nlpoisson)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/test_cost.py", line 56, in test_gradient_fail
self.failUnless(numpy.all(f() - numpy.asarray([206., 559.96605666, 558.96605666, 205., 557.96605666, 204., 30473.11077513, 459.96605666] < 1e-5)))
AssertionError: False is not true
-------------------- >> begin captured stdout << ---------------------
[array([-0., -1., -1., -0., -1., -0., -5., -1.])]

--------------------- >> end captured stdout << ----------------------

======================================================================
FAIL: test_kouh2008.test_A
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 76, in test_A
assert str(f.maker.env.outputs[6].owner.inputs[0]) == 'r'
AssertionError:
-------------------- >> begin captured logging << --------------------
pylearn.shared.layers.kouh2008: DEBUG: dtype float64
pylearn.shared.layers.kouh2008: DEBUG: output dtype float64
pylearn.shared.layers.LogisticRegression: DEBUG: allocating params w, b 10 2 float64
--------------------- >> end captured logging << ---------------------

======================================================================
FAIL: test_kouh2008.test_smaller
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 108, in test_smaller
assert rval < 6.1
AssertionError:
-------------------- >> begin captured stdout << ---------------------
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::f_0]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::f_1]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh::2008::b_0]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh::2008::b_1]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::w]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, p]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, q]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, r]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, k]
COMPILING
DONE

--------------------- >> end captured stdout << ----------------------
-------------------- >> begin captured logging << --------------------
pylearn.shared.layers.kouh2008: DEBUG: dtype float64
pylearn.shared.layers.kouh2008: DEBUG: output dtype float64
pylearn.shared.layers.LogisticRegression: DEBUG: allocating params w, b 8 2 float64
--------------------- >> end captured logging << ---------------------

======================================================================
FAIL: test_kouh2008.test_smaller32
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 113, in test_smaller32
assert rval < 6.1
AssertionError:
-------------------- >> begin captured stdout << ---------------------
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::f_0]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::f_1]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh::2008::b_0]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh::2008::b_1]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::w]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, p]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, q]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, r]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, k]
COMPILING
DONE

--------------------- >> end captured stdout << ----------------------
-------------------- >> begin captured logging << --------------------
pylearn.shared.layers.kouh2008: DEBUG: dtype float64
pylearn.shared.layers.kouh2008: DEBUG: output dtype float64
pylearn.shared.layers.LogisticRegression: DEBUG: allocating params w, b 8 2 float64
--------------------- >> end captured logging << ---------------------

======================================================================
FAIL: test_kouh2008.test_big
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 118, in test_big
assert rval < 0.1
AssertionError:
-------------------- >> begin captured stdout << ---------------------
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::f_0]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::f_1]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh::2008::b_0]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh::2008::b_1]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, Kouh2008::w]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, p]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, q]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, r]
COMPILING
DONE
PARAMS [LogisticRegression.w, LogisticRegression.b, k]
COMPILING
DONE

--------------------- >> end captured stdout << ----------------------
-------------------- >> begin captured logging << --------------------
pylearn.shared.layers.kouh2008: DEBUG: dtype float64
pylearn.shared.layers.kouh2008: DEBUG: output dtype float64
pylearn.shared.layers.LogisticRegression: DEBUG: allocating params w, b 100 2 float64
--------------------- >> end captured logging << ---------------------

----------------------------------------------------------------------
Ran 58 tests in 157.943s

FAILED (errors=9, failures=5)
Closing remaining open files: /Tmp/lisa/tmpSFn6tX... done /Tmp/lisa/tmp4OrVlz... done /Tmp/lisa/tmp8k9NuM... done /Tmp/lisa/tmpT_ZePS... done /Tmp/lisa/tmpxGjQrU... done /Tmp/lisa/tmpCV5z1S... done /Tmp/lisa/tmpPppn8v... done /Tmp/lisa/tmpuOWN1r... done /Tmp/lisa/tmpDsygOC... done /Tmp/lisa/tmps7LUS7... done /Tmp/lisa/tmpOvOENb... done
executing nosetests with mode=DEBUG_MODE with seed of the day 5763
/part/01/Tmp/nightly_build/Pylearn/pylearn/sandbox/scan_inputs_groups.py:106: UserWarning: theano modules are deprecated and will be removed in release 0.7
self.M=theano.Module()
ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

EERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

...F....E/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/tests/test_mcRBM.py:131: 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, 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.
updates=trainer.cd_updates())
...E.EEE./part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_dbd.py:17: 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, 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.
fn = theano.function([], cost, updates=ups)
.EEE........................EE../part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py:73: UserWarning: FunctionMaker.env is deprecated, it has been renamed 'fgraph'
env_r = f.maker.env.inputs[9]
/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py:74: UserWarning: FunctionMaker.env is deprecated, it has been renamed 'fgraph'
order = f.maker.env.toposort()
/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py:76: UserWarning: FunctionMaker.env is deprecated, it has been renamed 'fgraph'
assert str(f.maker.env.outputs[6].owner.inputs[0]) == 'r'
F.../part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_lecun1998.py:26: UserWarning: FunctionMaker.env is deprecated, it has been renamed 'fgraph'
for i, n in enumerate(f.maker.env.toposort()):
/Tmp/nightly_build/Theano/theano/tensor/nnet/conv.py:759: ComplexWarning: Casting complex values to real discards the imaginary part
1, val, bval, 0)
...
======================================================================
ERROR: test (pylearn.algorithms.sandbox.test_cost.T_logfactorial)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/test_cost.py", line 13, in test
self.failUnless(numpy.all(f() - numpy.asarray([0., 0., 1.38629436, 3.29583687, 5.54517744, 8.04718956, 10.75055682, 13.62137104, 16.63553233, 19.7750212])) < 1e-5)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 580, in __call__
outputs = self.fn()
File "/Tmp/nightly_build/Theano/theano/compile/debugmode.py", line 2068, in deco
return f()
File "/Tmp/nightly_build/Theano/theano/compile/debugmode.py", line 1828, in f
thunk_py()
File "/Tmp/nightly_build/Theano/theano/compile/debugmode.py", line 1663, in <lambda>
n=node: p(n, [x[0] for x in i], o))
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')
-------------------- >> begin captured logging << --------------------
theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3908, in constant_folding
required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

--------------------- >> end captured logging << ---------------------

======================================================================
ERROR: Failure: ImportError (No module named common.autoname)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/loader.py", line 390, in loadTestsFromName
addr.filename, addr.module)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 39, in importFromPath
return self.importFromDir(dir_path, fqname)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 86, in importFromDir
mod = load_module(part_fqname, fh, filename, desc)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/tests/test_linear_regression.py", line 3, in <module>
from pylearn.algorithms.linear_regression import *
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/linear_regression.py", line 11, in <module>
from common.autoname import AutoName
ImportError: No module named common.autoname

======================================================================
ERROR: Test that the image numbers come out in the right range for various dtypes
----------------------------------------------------------------------
Traceback (most recent call last):
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/dataset_ops/tests/test_cifar10.py", line 33, in test_shape_range
xval, yval = f(0)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 580, in __call__
outputs = self.fn()
File "/Tmp/nightly_build/Theano/theano/compile/debugmode.py", line 2068, in deco
return f()
File "/Tmp/nightly_build/Theano/theano/compile/debugmode.py", line 1947, in f
inputs_val=inputs_val)
BadThunkOutput: BadThunkOutput
variable : Elemwise{Composite{[Composite{[Composite{[Cast{uint8}(add(i0, i1))]}(add(i0, i1), mul(i2, i3))]}(mul(i0, i1), mul(i2, i3), i4, i5)]}}.0
Outputs Type: TensorType(uint8, vector)
Outputs Shape: (1024,)
Outputs Strides: (1,)
Inputs Type : [TensorType(float32, (True,)), TensorType(uint8, vector), TensorType(float32, (True,)), TensorType(uint8, vector), TensorType(float32, (True,)), TensorType(uint8, vector)]
Inputs Shape: [(1,), (1024,), (1,), (1024,), (1,), (1024,)]
Inputs Strides: [(4,), (1,), (4,), (1,), (4,), (1,)]
Apply : Elemwise{Composite{[Composite{[Composite{[Cast{uint8}(add(i0, i1))]}(add(i0, i1), mul(i2, i3))]}(mul(i0, i1), mul(i2, i3), i4, i5)]}}(TensorConstant{(1,) of 0.3}, Subtensor{:1024:}.0, TensorConstant{(1,) of 0.59}, Subtensor{1024:2048:}.0, TensorConstant{(1,) of 0.11}, Subtensor{2048::}.0)
thunk1 : perform
thunk2 : c_code
val1 : [ 61 44 48 ..., 188 124 99]
val2 : [ 61 44 48 ..., 188 124 99]
op : <class 'theano.tensor.elemwise.Elemwise'>
Value 1 : shape, dtype, strides, min, max, n_inf, n_nan: (1024,) uint8 (1,) 0 251 0 0
Value 2 : shape, dtype, strides, min, max, n_inf, n_nan: (1024,) uint8 (1,) 0 251 0 0
Max Abs Diff: 1
Mean Abs Diff: 0.01171875
Median Abs Diff: 0.0
Std Abs Diff: 0.107617010265
Max Rel Diff: 0
Mean Rel Diff: 0.0
Median Rel Diff: 0.0
Std Rel Diff: 0.0

======================================================================
ERROR: test_split_different (test_cifar10.TestCifar10)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/dataset_ops/tests/test_cifar10.py", line 97, in test_split_different
train_xval, train_yval = f(0)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 580, in __call__
outputs = self.fn()
File "/Tmp/nightly_build/Theano/theano/compile/debugmode.py", line 2068, in deco
return f()
File "/Tmp/nightly_build/Theano/theano/compile/debugmode.py", line 1947, in f
inputs_val=inputs_val)
BadThunkOutput: BadThunkOutput
variable : Elemwise{Composite{[Composite{[Composite{[Cast{uint8}(add(i0, i1))]}(add(i0, i1), mul(i2, i3))]}(mul(i0, i1), mul(i2, i3), i4, i5)]}}.0
Outputs Type: TensorType(uint8, vector)
Outputs Shape: (1024,)
Outputs Strides: (1,)
Inputs Type : [TensorType(float32, (True,)), TensorType(uint8, vector), TensorType(float32, (True,)), TensorType(uint8, vector), TensorType(float32, (True,)), TensorType(uint8, vector)]
Inputs Shape: [(1,), (1024,), (1,), (1024,), (1,), (1024,)]
Inputs Strides: [(4,), (1,), (4,), (1,), (4,), (1,)]
Apply : Elemwise{Composite{[Composite{[Composite{[Cast{uint8}(add(i0, i1))]}(add(i0, i1), mul(i2, i3))]}(mul(i0, i1), mul(i2, i3), i4, i5)]}}(TensorConstant{(1,) of 0.3}, Subtensor{:1024:}.0, TensorConstant{(1,) of 0.59}, Subtensor{1024:2048:}.0, TensorConstant{(1,) of 0.11}, Subtensor{2048::}.0)
thunk1 : perform
thunk2 : c_code
val1 : [ 61 44 48 ..., 188 124 99]
val2 : [ 61 44 48 ..., 188 124 99]
op : <class 'theano.tensor.elemwise.Elemwise'>
Value 1 : shape, dtype, strides, min, max, n_inf, n_nan: (1024,) uint8 (1,) 0 251 0 0
Value 2 : shape, dtype, strides, min, max, n_inf, n_nan: (1024,) uint8 (1,) 0 251 0 0
Max Abs Diff: 1
Mean Abs Diff: 0.01171875
Median Abs Diff: 0.0
Std Abs Diff: 0.107617010265
Max Rel Diff: 0
Mean Rel Diff: 0.0
Median Rel Diff: 0.0
Std Rel Diff: 0.0

======================================================================
ERROR: test that each split has the correct length
----------------------------------------------------------------------
Traceback (most recent call last):
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/dataset_ops/tests/test_cifar10.py", line 126, in test_split_length
f(i)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 580, in __call__
outputs = self.fn()
File "/Tmp/nightly_build/Theano/theano/compile/debugmode.py", line 2068, in deco
return f()
File "/Tmp/nightly_build/Theano/theano/compile/debugmode.py", line 1947, in f
inputs_val=inputs_val)
BadThunkOutput: BadThunkOutput
variable : Elemwise{Composite{[Composite{[Composite{[Cast{uint8}(add(i0, i1))]}(add(i0, i1), mul(i2, i3))]}(mul(i0, i1), mul(i2, i3), i4, i5)]}}.0
Outputs Type: TensorType(uint8, vector)
Outputs Shape: (1024,)
Outputs Strides: (1,)
Inputs Type : [TensorType(float32, (True,)), TensorType(uint8, vector), TensorType(float32, (True,)), TensorType(uint8, vector), TensorType(float32, (True,)), TensorType(uint8, vector)]
Inputs Shape: [(1,), (1024,), (1,), (1024,), (1,), (1024,)]
Inputs Strides: [(4,), (1,), (4,), (1,), (4,), (1,)]
Apply : Elemwise{Composite{[Composite{[Composite{[Cast{uint8}(add(i0, i1))]}(add(i0, i1), mul(i2, i3))]}(mul(i0, i1), mul(i2, i3), i4, i5)]}}(TensorConstant{(1,) of 0.3}, Subtensor{:1024:}.0, TensorConstant{(1,) of 0.59}, Subtensor{1024:2048:}.0, TensorConstant{(1,) of 0.11}, Subtensor{2048::}.0)
thunk1 : perform
thunk2 : c_code
val1 : [ 61 44 48 ..., 188 124 99]
val2 : [ 61 44 48 ..., 188 124 99]
op : <class 'theano.tensor.elemwise.Elemwise'>
Value 1 : shape, dtype, strides, min, max, n_inf, n_nan: (1024,) uint8 (1,) 0 251 0 0
Value 2 : shape, dtype, strides, min, max, n_inf, n_nan: (1024,) uint8 (1,) 0 251 0 0
Max Abs Diff: 1
Mean Abs Diff: 0.01171875
Median Abs Diff: 0.0
Std Abs Diff: 0.107617010265
Max Rel Diff: 0
Mean Rel Diff: 0.0
Median Rel Diff: 0.0
Std Rel Diff: 0.0

======================================================================
ERROR: Failure: ImportError (No module named old_dataset.dataset)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/loader.py", line 390, in loadTestsFromName
addr.filename, addr.module)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 39, in importFromPath
return self.importFromDir(dir_path, fqname)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 86, in importFromDir
mod = load_module(part_fqname, fh, filename, desc)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/datasets/make_test_datasets.py", line 1, in <module>
from pylearn.old_dataset.dataset import ArrayDataSet
ImportError: No module named old_dataset.dataset

======================================================================
ERROR: test_sgd.test_sgd0
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 19, in test_sgd0
c = m.step_cost(3.0)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 586, in __call__
gof.vm.raise_with_op(self.fn.nodes[self.fn.position_of_error])
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 580, in __call__
outputs = self.fn()
NotImplementedError: input nd

======================================================================
ERROR: test_sgd.test_sgd_stepsize_variable
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 38, in test_sgd_stepsize_variable
c = m.step_cost(3.0)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 586, in __call__
gof.vm.raise_with_op(self.fn.nodes[self.fn.position_of_error])
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 580, in __call__
outputs = self.fn()
NotImplementedError: input nd

======================================================================
ERROR: test_sgd.test_sgd_stepsize_none
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/gd/tests/test_sgd.py", line 68, in test_sgd_stepsize_none
c = m.step_cost(3.0)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 586, in __call__
gof.vm.raise_with_op(self.fn.nodes[self.fn.position_of_error])
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 580, in __call__
outputs = self.fn()
NotImplementedError: input nd

======================================================================
ERROR: test_mcmc.test_mcmc
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sampling/tests/test_mcmc.py", line 61, in test_mcmc
sampler = _sampler_on_2d_gaussian(MCMC_sampler, burnin=3000, n_samples=90000)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sampling/tests/test_mcmc.py", line 30, in _sampler_on_2d_gaussian
samples = [sampler.draw() for r in xrange(burnin)] #burn-in
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sampling/mcmc.py", line 101, in draw
self.simulate(n_steps=n_steps)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sampling/mcmc.py", line 84, in simulate
acceptance_rate = self.accept_reject_positions(self.stepsize)
File "/Tmp/nightly_build/Theano/theano/compile/function_module.py", line 580, in __call__
outputs = self.fn()
File "/Tmp/nightly_build/Theano/theano/compile/debugmode.py", line 2068, in deco
return f()
File "/Tmp/nightly_build/Theano/theano/compile/debugmode.py", line 1779, in f
"%s" % (r, storage_map[r][0])))
InvalidValueError: InvalidValueError
type(variable) = TensorType(float64, vector)
variable = <TensorType(float64, vector)>
type(value) = <type 'numpy.ndarray'>
dtype(value) = float64
shape(value) = (3,)
value = [ inf inf inf]
min(value) = inf
max(value) = inf
isfinite = False
client_node = None
hint = Graph Input '<TensorType(float64, vector)>' has invalid value [ inf inf inf]
specific_hint = none
context = ...
<TensorType(float64, vector)> [@A]

-------------------- >> begin captured stdout << ---------------------
MCMC
initial position [[-0.08738186 -3.12888464]
[-0.96973267 0.93466579]
[ 0.04386634 1.4252155 ]]
initial stepsize 0.01

--------------------- >> end captured stdout << ----------------------

======================================================================
ERROR: Failure: AttributeError ('module' object has no attribute 'RandomStreams')
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/loader.py", line 390, in loadTestsFromName
addr.filename, addr.module)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 39, in importFromPath
return self.importFromDir(dir_path, fqname)
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/importer.py", line 86, in importFromDir
mod = load_module(part_fqname, fh, filename, desc)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sandbox/test_scan_inputs_groups.py", line 10, in <module>
from pylearn.sandbox.scan_inputs_groups import FillMissing
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sandbox/scan_inputs_groups.py", line 428, in <module>
scannoise=ScanNoise()
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/sandbox/scan_inputs_groups.py", line 391, in __init__
self.M.rand = T.RandomStreams(seed)
AttributeError: 'module' object has no attribute 'RandomStreams'

======================================================================
FAIL: test_gradient_fail (pylearn.algorithms.sandbox.test_cost.T_nlpoisson)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/test_cost.py", line 56, in test_gradient_fail
self.failUnless(numpy.all(f() - numpy.asarray([206., 559.96605666, 558.96605666, 205., 557.96605666, 204., 30473.11077513, 459.96605666] < 1e-5)))
AssertionError: False is not true
-------------------- >> begin captured stdout << ---------------------
[array([-0., -1., -1., -0., -1., -0., -5., -1.])]

--------------------- >> end captured stdout << ----------------------

======================================================================
FAIL: test_kouh2008.test_A
----------------------------------------------------------------------
Traceback (most recent call last):
File "/opt/lisa/os/epd-7.1.2/lib/python2.7/site-packages/nose/case.py", line 187, in runTest
self.test(*self.arg)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/shared/layers/tests/test_kouh2008.py", line 76, in test_A
assert str(f.maker.env.outputs[6].owner.inputs[0]) == 'r'
AssertionError:
-------------------- >> begin captured logging << --------------------
pylearn.shared.layers.kouh2008: DEBUG: dtype float64
pylearn.shared.layers.kouh2008: DEBUG: output dtype float64
pylearn.shared.layers.LogisticRegression: DEBUG: allocating params w, b 10 2 float64
--------------------- >> end captured logging << ---------------------

----------------------------------------------------------------------
Ran 58 tests in 330.275s

FAILED (errors=11, failures=2)
Closing remaining open files: /Tmp/lisa/tmph4xCmQ... done /Tmp/lisa/tmpUfqZcT... done /Tmp/lisa/tmpRLJNXc... done /Tmp/lisa/tmp3Alkto... done /Tmp/lisa/tmp3yhYv8... done /Tmp/lisa/tmpPzUSlX... done /Tmp/lisa/tmppzfVnX... done /Tmp/lisa/tmp69bPqW... done /Tmp/lisa/tmpezfMLW... done /Tmp/lisa/tmpmuvYZT... done /Tmp/lisa/tmpAJ7Z22... done

Total test time: 12m 3s
Mon May 6 19:12:46 EDT 2013
686.84user 24.53system 12:03.57elapsed 98%CPU (0avgtext+0avgdata 3635304maxresident)k
495592inputs+24344outputs (668major+3921766minor)pagefaults 0swaps

li...@iro.umontreal.ca

unread,

May 8, 2013, 8:27:25 AM5/8/13

to theano-...@googlegroups.com

Tue May 7 19:00:53 EDT 2013

theano.gof.optdb 155 12 92% 39, 131, 173, 194, 239, 248, 253-254, 257, 273, 277-278

theano.gof.python25 1 0 100%
theano.gof.sched 78 49 37% 3, 28, 30-31, 44, 56-69, 92-106, 136, 138, 140-154, 179-197
theano.gof.toolbox 184 27 85% 7-11, 199, 259, 263-267, 271-272, 276-277, 285, 293, 295, 298-299, 304, 307-308, 311-312, 315-316, 320, 324-325
theano.gof.type 83 25 70% 12, 45, 97-140, 181-200, 215, 228, 257, 295, 306, 327, 356-360, 404, 409-412, 425, 446, 459, 462-465
theano.gof.unify 197 105 47% 40, 53-54, 63, 190-195, 202-203, 210-213, 220-224, 231-235, 242-243, 250, 257-264, 271-273, 280-287, 294-296, 303, 305-309, 317-321, 329-331, 342-344, 355-356, 359, 366, 370, 374, 386-395, 399, 403-405, 416-420, 427, 434-438, 446-474
theano.gof.utils 220 121 45% 1-7, 19-20, 22-35, 49-51, 53-56, 59-61, 63-64, 72, 77, 87-90, 105-107, 109-111, 113, 124, 132-133, 141-144, 146-152, 154-164, 166-168, 172, 174, 176-180, 191, 198-231, 233-239, 241, 245, 247, 259, 272-273, 276, 281-284, 311, 316, 319-324, 331, 342-346, 350, 353, 356, 361-402
theano.gof.vm 398 14 96% 33, 36-38, 53-81, 97-104, 115, 133, 147, 854
theano.gradient 615 21 97% 33-38, 60, 67, 109, 1467, 1503-1506, 1512, 1515-1516, 1519-1529, 1579, 1586, 1599, 1621
theano.ifelse 356 155 56% 88, 99-106, 131, 137, 148, 196-197, 457-462, 467-487, 492-493, 498-501, 507, 509-511, 522-536, 540-541, 548, 551-552, 554-562, 566-586, 588-592, 597-612, 615-637, 639-643, 648-697
theano.misc 0 0 100%
theano.misc.cpucount 18 15 17% 41-57
theano.misc.ordered_set 111 78 30% 1-10, 21-48, 64, 73, 79, 104-113, 115-125, 132-220
theano.misc.safe_asarray 13 2 85% 31, 48
theano.misc.strutil 34 27 21% 17-29, 32, 37-60
theano.misc.windows 20 9 55% 1-5, 11-23
theano.printing 655 183 72% 17-19, 27, 29-30, 34-37, 82, 88, 90-91, 103-104, 113-114, 117-121, 240, 242, 247, 252, 257, 287, 294, 297-299, 359, 365, 368-373, 376-398, 403-409, 415, 431, 486, 786, 789, 795-801, 811-814, 821-897, 901, 905, 908, 910, 929, 932, 936, 940-945, 948, 981, 1063, 1080-1152, 1161
theano.sandbox 0 0 100%

theano.sandbox.cuda 205 13 94% 366, 400, 404, 421, 459, 469-473, 479, 481-490

TOTAL 36190 6009 83%
----------------------------------------------------------------------
Ran 58 tests in 303.872s

FAILED (errors=8, failures=5)
Closing remaining open files: /Tmp/lisa/tmpo2RRYh... done /Tmp/lisa/tmpHUje2S... done /Tmp/lisa/tmp8iggVG... done /Tmp/lisa/tmpeRMfcd... done /Tmp/lisa/tmphZWgbR... done /Tmp/lisa/tmpg5pYSY... done /Tmp/lisa/tmplZofnc... done /Tmp/lisa/tmp8GFl_x... done /Tmp/lisa/tmpHuzvqX... done /Tmp/lisa/tmphIzkUC... done /Tmp/lisa/tmpXff3wP... done

Ran 58 tests in 160.041s

FAILED (errors=9, failures=5)
Closing remaining open files: /Tmp/lisa/tmpmOTw1F... done /Tmp/lisa/tmpKcSZsK... done /Tmp/lisa/tmpvwKwu7... done /Tmp/lisa/tmpVA6iMX... done /Tmp/lisa/tmpkJRsFR... done /Tmp/lisa/tmpgRYKt1... done /Tmp/lisa/tmpiE07aY... done /Tmp/lisa/tmpvQfxwe... done /Tmp/lisa/tmpYiB8eD... done /Tmp/lisa/tmp_hsFKp... done /Tmp/lisa/tmpXsA6cC... done
executing nosetests with mode=DEBUG_MODE with seed of the day 27317

Ran 58 tests in 333.864s

FAILED (errors=11, failures=2)
Closing remaining open files: /Tmp/lisa/tmp04U30c... done /Tmp/lisa/tmpPpKXwg... done /Tmp/lisa/tmp8Gcr3t... done /Tmp/lisa/tmpwXaKyh... done /Tmp/lisa/tmptkoDUC... done /Tmp/lisa/tmp7KbNUb... done /Tmp/lisa/tmpg0m8iK... done /Tmp/lisa/tmpEq44Ol... done /Tmp/lisa/tmpkIgCKC... done /Tmp/lisa/tmpkwl1CZ... done /Tmp/lisa/tmpua1K2d... done

Total test time: 13m 31s
Tue May 7 19:14:24 EDT 2013
693.88user 24.87system 13:30.96elapsed 88%CPU (0avgtext+0avgdata 3636240maxresident)k
548864inputs+25856outputs (289major+3960982minor)pagefaults 0swaps

li...@iro.umontreal.ca

unread,

May 10, 2013, 8:08:41 AM5/10/13

to theano-...@googlegroups.com

Thu May 9 19:00:58 EDT 2013

theano.scan_module.scan_op 1162 275 76% 154-156, 158-160, 245, 333, 790-795, 810, 835, 840-841, 847-850, 856, 873-874, 880-886, 889-891, 896-900, 905, 909-913, 917-942, 948-949, 954, 964-975, 980, 987-1001, 1004, 1016, 1028, 1041, 1767, 1806-1808, 1810-1811, 1813-2109

theano.scan_module.scan_opt 943 190 80% 449, 1207, 1213, 1217-1223, 1228, 1243, 1254-1264, 1267-1277, 1281-1296, 1305-1307, 1313-1322, 1325-1335, 1340, 1345-1362, 1368-1377, 1401-1407, 1413-1418, 1422, 1429, 1452-1693
theano.scan_module.scan_perform_ext 57 1 98% 45

theano.scan_module.scan_utils 585 53 91% 21, 28-37, 50-52, 61-62, 86, 106-123, 133, 137-138, 142, 152, 154, 936, 948-1019

TOTAL 36215 6024 83%
----------------------------------------------------------------------
Ran 58 tests in 323.564s

FAILED (errors=8, failures=5)
Closing remaining open files: /Tmp/lisa/tmpxEBTmG... done /Tmp/lisa/tmpBgS5qd... done /Tmp/lisa/tmpSyoAx4... done /Tmp/lisa/tmpbaS0qY... done /Tmp/lisa/tmpefa_cu... done /Tmp/lisa/tmplzD9ET... done /Tmp/lisa/tmpkk1KAD... done /Tmp/lisa/tmp02Irqo... done /Tmp/lisa/tmp9IS8hk... done /Tmp/lisa/tmp4Z1uxD... done /Tmp/lisa/tmpC2zniR... done

Ran 58 tests in 180.533s

FAILED (errors=9, failures=5)
Closing remaining open files: /Tmp/lisa/tmpf67qxI... done /Tmp/lisa/tmp4XpH6K... done /Tmp/lisa/tmp91eKiq... done /Tmp/lisa/tmpvuRT1G... done /Tmp/lisa/tmpLLnyAb... done /Tmp/lisa/tmp2Bvmsw... done /Tmp/lisa/tmptevIkK... done /Tmp/lisa/tmprpyu_v... done /Tmp/lisa/tmpZpkfND... done /Tmp/lisa/tmpxFQxHu... done /Tmp/lisa/tmp0eAma4... done
executing nosetests with mode=DEBUG_MODE with seed of the day 28080

Ran 58 tests in 349.591s

FAILED (errors=11, failures=2)
Closing remaining open files: /Tmp/lisa/tmpmWJqST... done /Tmp/lisa/tmp9z5o0C... done /Tmp/lisa/tmpKfpV7M... done /Tmp/lisa/tmpH2PT8J... done /Tmp/lisa/tmpuPOlBj... done /Tmp/lisa/tmpn16BHW... done /Tmp/lisa/tmpCYE2Ej... done /Tmp/lisa/tmpguQHQK... done /Tmp/lisa/tmpsIN6yo... done /Tmp/lisa/tmpnjnCPA... done /Tmp/lisa/tmpnaBvCD... done

Total test time: 14m 29s
Thu May 9 19:15:27 EDT 2013
682.81user 25.95system 14:29.22elapsed 81%CPU (0avgtext+0avgdata 3573520maxresident)k
534328inputs+17464outputs (251major+4065295minor)pagefaults 0swaps

li...@iro.umontreal.ca

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May 11, 2013, 7:40:26 AM5/11/13

to theano-...@googlegroups.com

Fri May 10 19:00:45 EDT 2013

Ran 58 tests in 244.250s

FAILED (errors=8, failures=5)
Closing remaining open files: /Tmp/lisa/tmpv5Rbu1... done /Tmp/lisa/tmpAVEm0k... done /Tmp/lisa/tmpPjyZ8n... done /Tmp/lisa/tmpwQamya... done /Tmp/lisa/tmp2fdjh4... done /Tmp/lisa/tmprCwVji... done /Tmp/lisa/tmptrgO1D... done /Tmp/lisa/tmptRGO7S... done /Tmp/lisa/tmpLXqjJH... done /Tmp/lisa/tmpTTAx56... done /Tmp/lisa/tmpWltZdN... done

Ran 58 tests in 159.518s

FAILED (errors=9, failures=5)
Closing remaining open files: /Tmp/lisa/tmpNduaOt... done /Tmp/lisa/tmplESQ4f... done /Tmp/lisa/tmp5mHB49... done /Tmp/lisa/tmpXj6Id0... done /Tmp/lisa/tmpIbvuE5... done /Tmp/lisa/tmpDv9XiR... done /Tmp/lisa/tmpStOBFc... done /Tmp/lisa/tmph_bvg6... done /Tmp/lisa/tmp8eieuJ... done /Tmp/lisa/tmp5bUKME... done /Tmp/lisa/tmpzXenAa... done
executing nosetests with mode=DEBUG_MODE with seed of the day 23499

Ran 58 tests in 336.372s

FAILED (errors=11, failures=2)
Closing remaining open files: /Tmp/lisa/tmpNTMZCT... done /Tmp/lisa/tmpZxjPnz... done /Tmp/lisa/tmp0XWBK9... done /Tmp/lisa/tmpdgwkrZ... done /Tmp/lisa/tmpieZofy... done /Tmp/lisa/tmpEVXyk7... done /Tmp/lisa/tmpNYDmCS... done /Tmp/lisa/tmpPMZH03... done /Tmp/lisa/tmp0HtRsA... done /Tmp/lisa/tmpjBxxCP... done /Tmp/lisa/tmp5VX6uZ... done

Total test time: 12m 31s
Fri May 10 19:13:16 EDT 2013
690.84user 27.02system 12:30.18elapsed 95%CPU (0avgtext+0avgdata 3573284maxresident)k
162888inputs+17480outputs (339major+4061218minor)pagefaults 0swaps

li...@iro.umontreal.ca

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May 12, 2013, 7:31:51 AM5/12/13

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Sat May 11 19:00:38 EDT 2013

Ran 58 tests in 228.213s

FAILED (errors=8, failures=5)
Closing remaining open files: /Tmp/lisa/tmpC2KPqQ... done /Tmp/lisa/tmps8lp5h... done /Tmp/lisa/tmpfd28m2... done /Tmp/lisa/tmpkx8P1b... done /Tmp/lisa/tmpzjeFKP... done /Tmp/lisa/tmpFyZPSJ... done /Tmp/lisa/tmpoHA_md... done /Tmp/lisa/tmptAP8St... done /Tmp/lisa/tmpXzxPcT... done /Tmp/lisa/tmpwGLKfH... done /Tmp/lisa/tmpZZyh3q... done

Ran 58 tests in 156.035s

FAILED (errors=9, failures=5)
Closing remaining open files: /Tmp/lisa/tmpDrFowh... done /Tmp/lisa/tmpi9AwF8... done /Tmp/lisa/tmpMQw8r6... done /Tmp/lisa/tmpvftJ9D... done /Tmp/lisa/tmp65OHIg... done /Tmp/lisa/tmpAF6ahm... done /Tmp/lisa/tmpNR1Cb9... done /Tmp/lisa/tmpCZlK0r... done /Tmp/lisa/tmpTbefFs... done /Tmp/lisa/tmplp13Oz... done /Tmp/lisa/tmpM7Qpyn... done
executing nosetests with mode=DEBUG_MODE with seed of the day 22450

Ran 58 tests in 330.681s

FAILED (errors=11, failures=2)
Closing remaining open files: /Tmp/lisa/tmpqQqpNf... done /Tmp/lisa/tmpHOtdj2... done /Tmp/lisa/tmpM9bRgS... done /Tmp/lisa/tmpzJlJ3n... done /Tmp/lisa/tmpegE6jR... done /Tmp/lisa/tmpDNn90j... done /Tmp/lisa/tmpDPAmto... done /Tmp/lisa/tmpTgjbPx... done /Tmp/lisa/tmpZIzLBf... done /Tmp/lisa/tmp0KFXyO... done /Tmp/lisa/tmpynBajq... done

Total test time: 12m 5s
Sat May 11 19:12:43 EDT 2013
681.26user 25.81system 12:04.94elapsed 97%CPU (0avgtext+0avgdata 3571760maxresident)k
100888inputs+17480outputs (443major+4105095minor)pagefaults 0swaps

li...@iro.umontreal.ca

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May 14, 2013, 8:26:34 AM5/14/13

to theano-...@googlegroups.com

Mon May 13 19:00:48 EDT 2013

Ran 58 tests in 308.421s

FAILED (errors=8, failures=5)
Closing remaining open files: /Tmp/lisa/tmpsTs9DV... done /Tmp/lisa/tmpBZbdxh... done /Tmp/lisa/tmpbtLdR5... done /Tmp/lisa/tmpuDaP_4... done /Tmp/lisa/tmpqi6Nht... done /Tmp/lisa/tmpvxk8QD... done /Tmp/lisa/tmpwKjXlr... done /Tmp/lisa/tmpyEJz8X... done /Tmp/lisa/tmpFKsqAT... done /Tmp/lisa/tmp3k61pB... done /Tmp/lisa/tmpyDHNaw... done

Ran 58 tests in 156.682s

FAILED (errors=9, failures=5)
Closing remaining open files: /Tmp/lisa/tmpwXxtMv... done /Tmp/lisa/tmpfOoL9k... done /Tmp/lisa/tmpxk8EBF... done /Tmp/lisa/tmpANQvmn... done /Tmp/lisa/tmpgFVGV6... done /Tmp/lisa/tmprSqFQR... done /Tmp/lisa/tmpeOUAky... done /Tmp/lisa/tmpwHDdeO... done /Tmp/lisa/tmprdL5LT... done /Tmp/lisa/tmpANHC6m... done /Tmp/lisa/tmpZxB5Uv... done
executing nosetests with mode=DEBUG_MODE with seed of the day 29742

Ran 58 tests in 328.630s

FAILED (errors=11, failures=2)
Closing remaining open files: /Tmp/lisa/tmpWJggmz... done /Tmp/lisa/tmpFAIZsQ... done /Tmp/lisa/tmpYfJmsG... done /Tmp/lisa/tmpOdW8u8... done /Tmp/lisa/tmpy7WxlK... done /Tmp/lisa/tmpOrnVBM... done /Tmp/lisa/tmpnhzbm7... done /Tmp/lisa/tmpitKt2A... done /Tmp/lisa/tmp6VQldf... done /Tmp/lisa/tmp2Paeyq... done /Tmp/lisa/tmpXN36gi... done

Total test time: 13m 27s
Mon May 13 19:14:16 EDT 2013
679.94user 24.01system 13:28.12elapsed 87%CPU (0avgtext+0avgdata 3636136maxresident)k
535568inputs+24304outputs (253major+3894291minor)pagefaults 0swaps

li...@iro.umontreal.ca

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May 15, 2013, 8:02:45 AM5/15/13

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Tue May 14 19:00:45 EDT 2013

Ran 58 tests in 254.870s

FAILED (errors=8, failures=5)
Closing remaining open files: /Tmp/lisa/tmpOS_d5l... done /Tmp/lisa/tmpuHUr_i... done /Tmp/lisa/tmpXl3QT5... done /Tmp/lisa/tmplyAw47... done /Tmp/lisa/tmpz87SMO... done /Tmp/lisa/tmp8EfJCz... done /Tmp/lisa/tmpt4hBMl... done /Tmp/lisa/tmp3FouIQ... done /Tmp/lisa/tmpO62ZP5... done /Tmp/lisa/tmpyWMlh6... done /Tmp/lisa/tmpHWEpfl... done

Ran 58 tests in 159.314s

FAILED (errors=9, failures=5)
Closing remaining open files: /Tmp/lisa/tmp7rOy0R... done /Tmp/lisa/tmpsjw5We... done /Tmp/lisa/tmpCeyzNA... done /Tmp/lisa/tmpQN7RmQ... done /Tmp/lisa/tmpgDSYei... done /Tmp/lisa/tmpP8LvvT... done /Tmp/lisa/tmp0a6Ek5... done /Tmp/lisa/tmpjIBf8J... done /Tmp/lisa/tmp2d5mqt... done /Tmp/lisa/tmpz7ZB9G... done /Tmp/lisa/tmpVJZc5N... done
executing nosetests with mode=DEBUG_MODE with seed of the day 22637

Ran 58 tests in 337.143s

FAILED (errors=11, failures=2)
Closing remaining open files: /Tmp/lisa/tmpDrpqUG... done /Tmp/lisa/tmpfBemnB... done /Tmp/lisa/tmpgHNBUU... done /Tmp/lisa/tmppRnRO9... done /Tmp/lisa/tmpx7puur... done /Tmp/lisa/tmpXL8niK... done /Tmp/lisa/tmpdNOxiY... done /Tmp/lisa/tmpMzl7ib... done /Tmp/lisa/tmpj1HjVA... done /Tmp/lisa/tmpxyyED0... done /Tmp/lisa/tmpnez8qV... done

Total test time: 12m 42s
Tue May 14 19:13:27 EDT 2013
694.77user 25.16system 12:41.71elapsed 94%CPU (0avgtext+0avgdata 3635992maxresident)k
166632inputs+17480outputs (376major+3928365minor)pagefaults 0swaps

li...@iro.umontreal.ca

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May 16, 2013, 7:44:27 AM5/16/13

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Wed May 15 19:00:55 EDT 2013

abort: no repository found in '/part/01/Tmp/nightly_build/Theano' (.hg not found)!
parent: 1529:9737834dcb0f tip
Add the total test time in the buildbot.
branch: default
commit: (clean)
update: (current)
executing nosetests with mode=FAST_COMPILE
executing nosetests with mode=FAST_RUN
/part/01/Tmp/nightly_build/Pylearn/pylearn/sandbox/scan_inputs_groups.py:106: UserWarning: theano modules are deprecated and will be removed in release 0.7
self.M=theano.Module()
ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)

File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3934, in constant_folding

required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)

File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3934, in constant_folding

required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

ERROR (theano.gof.opt): Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)

File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3934, in constant_folding

required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

EERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)

File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3934, in constant_folding

required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)

File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3934, in constant_folding

required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)

File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3934, in constant_folding

required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(2,)]')

ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)

File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3934, in constant_folding

required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)

File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3934, in constant_folding

required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: <theano.gof.opt.LocalOptGroup instance>['constant_folding']
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 747, in transform
repl = opt.transform(node)

File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3934, in constant_folding

required = thunk()
File "/Tmp/nightly_build/Theano/theano/gof/op.py", line 615, in rval
r = p(n, [x[0] for x in i], o)
File "/Tmp/nightly_build/Theano/theano/tensor/elemwise.py", line 879, in perform
variables = ufunc(*ufunc_args)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 42, in impl
return LogFactorial.st_impl(x)
File "/part/01/Tmp/nightly_build/Pylearn/pylearn/algorithms/sandbox/cost.py", line 34, in st_impl
raise TypeError('type(x) = %s, must be int or long' % type(x))
TypeError: ("type(x) = <type 'float'>, must be int or long", 'While computing [logfactorial.0]: Failed calling ufunc for op scalar_logfactoral for params of shape [(10,)]')

theano.gof.opt: ERROR: Optimization failure due to: constant_folding
theano.gof.opt: ERROR: TRACEBACK:
theano.gof.opt: ERROR: Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)

File "/Tmp/nightly_build/Theano/theano/tensor/opt.py", line 3934, in constant_folding

theano.gof.cc 638 32 95% 16, 19, 23, 68-71, 87, 92, 329, 480, 1606-1639

theano.gof.cmodule 825 24 97% 686, 1148-1153, 1179-1181, 1197, 1225, 1251, 1263, 1278, 1650, 1660, 1666, 1679, 1691, 1703, 1712, 1821-1825, 1844-1845
theano.gof.compiledir 182 121 34% 116, 142-143, 153, 163-193, 195-337
theano.gof.compilelock 143 39 73% 15-38, 61-64, 85, 96-107, 145-146, 180-181, 194-202, 224, 236, 241-247, 260, 273, 276, 297
theano.gof.cutils 48 36 25% 6, 11, 15, 23-41, 219-295
theano.gof.destroyhandler 235 16 93% 21, 231, 603-646, 668, 760-768, 798, 818, 888
theano.gof.fg 325 58 82% 17, 34-65, 157-158, 160, 162, 178, 192, 264-265, 278-298, 415, 438, 448, 528, 531, 600-602, 607, 610-612, 615, 623, 627-628, 631-633, 635-639, 647, 652, 659-678
theano.gof.graph 401 16 96% 25-43, 118, 138, 156-158, 211, 218, 224-225, 232-235, 576, 722
theano.gof.lazylinker_c 70 33 53% 2, 7, 10, 22-23, 35, 38, 48-49, 59, 64, 74-75, 82-110

theano.gof.link 295 35 88% 5, 18-34, 50-51, 102, 107, 135, 201, 242, 284, 360-361, 367, 370, 394, 424, 429-431, 521-540, 650, 658

theano.tensor.basic 3432 209 94% 24, 56, 58-60, 85, 101-111, 114, 6806, 7102, 7144-7146, 7152, 7176, 7256, 7272, 7289, 7311, 7329, 7339, 7344, 7349-7350, 7399-7400, 7404, 7409, 7427, 7443, 7465-7467, 7474, 7479, 7498-7499, 7508, 7513, 7518, 7525, 7529, 7551-7553, 7568-7573, 7578, 7583, 7600-7602, 7607, 7613, 7617, 7639, 7641, 7650, 7674, 7700, 7702, 7708, 7711, 7714-7715, 7724, 7794, 7822, 7864, 7867, 7878-7886, 7891, 7911, 7917, 7924-7926, 7931, 7969, 7971, 7980-8114, 8119-8124, 8128-8152, 8161-8168, 8175-8321
theano.tensor.blas 815 9 99% 466, 474, 482, 501, 518, 1950-1960

theano.tensor.blas_c 58 6 90% 267, 580, 584, 594, 607-618
theano.tensor.blas_headers 60 46 23% 6-17, 47-135, 717, 924-934, 951, 955-960, 965-967
theano.tensor.blas_scipy 38 5 87% 25-28, 32, 38
theano.tensor.deprecated 0 0 100%
theano.tensor.deprecated.rmodule 77 20 74% 7, 35-39, 53-57, 64-69, 101, 115, 124
theano.tensor.elemwise 898 69 92% 45, 54, 413-416, 422, 1897-1965, 1973-1975, 1979-2026
theano.tensor.elemwise_cgen 130 1 99% 225
theano.tensor.extra_ops 255 3 99% 388, 398, 467
theano.tensor.io 140 120 14% 6-12, 24, 27, 30, 33, 36, 43-44, 46, 52-282
theano.tensor.nnet 6 0 100%
theano.tensor.nnet.Conv3D 145 3 98% 345-348
theano.tensor.nnet.ConvGrad3D 67 0 100%
theano.tensor.nnet.ConvTransp3D 122 1 99% 34
theano.tensor.nnet.conv 598 46 92% 31-32, 129, 264, 442, 590-593, 600, 658, 667-702, 708, 721, 874, 1230, 1251-1258
theano.tensor.nnet.nnet 740 135 82% 67-71, 245, 487, 491-495, 517, 525-527, 533, 538, 544-547, 555, 566, 701, 792-794, 828-829, 833, 836, 839, 857, 944, 947, 956, 966, 969, 992, 1394-1399, 1428-1429, 1452, 1492, 1557, 1566-1567, 1571, 1587, 1589-1595, 1598, 1601, 1607, 1612-1615, 1627, 1756, 1763, 1771-1772, 1776-1779, 1781-1870, 1891
theano.tensor.nnet.sigm 309 21 93% 29, 66, 89, 108, 338, 463, 623-624, 628, 630-631, 644, 646-647, 649-654, 665

theano.tensor.opt 2110 84 96% 15, 18, 145, 351, 472, 638-639, 642, 651-674, 677-681, 1334-1335, 1338, 1343-1344, 1373-1377, 4198-4230, 4232-4265, 4267, 4270, 4622, 4661, 4665, 4682-4692

theano.tensor.opt_uncanonicalize 42 3 93% 39, 49, 78
theano.tensor.randomstreams 66 1 98% 163
theano.tensor.raw_random 340 67 80% 55-56, 59, 62-65, 67, 70, 72-91, 134-137, 150-151, 200, 231, 246, 332, 337, 343, 381, 419-426, 505, 540, 559, 563-566, 601, 616-619, 652, 671, 675-678, 691-693, 706, 708, 716, 772-774, 778, 809-810, 823, 843, 877-889
theano.tensor.shared_randomstreams 42 5 88% 77, 79-82, 115-117
theano.tensor.sharedvar 36 4 89% 14, 86-88
theano.tensor.signal 0 0 100%
theano.tensor.signal.downsample 136 41 70% 14-16, 32, 84, 91-92, 95-96, 124, 131-151, 268-277, 284-286
theano.tensor.sort 70 1 99% 147
theano.tensor.utils 31 0 100%
theano.tensor.xlogx 41 18 56% 1, 4, 10, 13-16, 29, 31-38, 41-44, 46, 57, 59
theano.updates 46 24 48% 14, 53, 59, 61-91
theano.version 8 0 100%
----------------------------------------------------------------------------

TOTAL 36232 6059 83%
----------------------------------------------------------------------
Ran 58 tests in 270.129s

FAILED (errors=8, failures=5)
Closing remaining open files: /Tmp/lisa/tmp2SmTrW... done /Tmp/lisa/tmpfjzF3A... done /Tmp/lisa/tmpcOmIsx... done /Tmp/lisa/tmpPhcQdH... done /Tmp/lisa/tmpZMXhBi... done /Tmp/lisa/tmpIR4nmX... done /Tmp/lisa/tmpgLBrk5... done /Tmp/lisa/tmpO6pCw9... done /Tmp/lisa/tmpl6Zr0Y... done /Tmp/lisa/tmphv9D7A... done /Tmp/lisa/tmp8cBvE3... done

executing nosetests with mode=FAST_RUN,floatX=float32
/part/01/Tmp/nightly_build/Pylearn/pylearn/sandbox/scan_inputs_groups.py:106: UserWarning: theano modules are deprecated and will be removed in release 0.7
self.M=theano.Module()
ERROR (theano.gof.opt): Optimization failure due to: constant_folding
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/Tmp/nightly_build/Theano/theano/gof/opt.py", line 1213, in process_node
replacements = lopt.transform(node)