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chainer_test.txt
=================================== FAILURES ===================================
______________ TestUnnamedVariableToString_param_1.test_repr_cpu _______________
self = <chainer.testing.parameterized.TestUnnamedVariableToString_param_1 testMethod=test_repr_cpu>
def test_repr_cpu(self):
> self.assertEqual(repr(self.x), self.repr)
E AssertionError: Parameterized test failed.
E
E Base test method: TestUnnamedVariableToString.test_repr_cpu
E Test parameters:
E x_shape: (2, 2)
E dtype: <class 'numpy.float16'>
E repr: variable([[ 0., 1.],
E [ 2., 3.]])
E str: variable([[ 0. 1.]
E [ 2. 3.]])
E
E AssertionError: 'variable([[0., 1.],\n [2., 3.]])' != 'variable([[ 0., 1.],\n [ 2., 3.]])'
E - variable([[0., 1.],
E + variable([[ 0., 1.],
E ? + +
E - [2., 3.]])+ [ 2., 3.]])? + +
tests/chainer_tests/test_variable.py:1353: AssertionError
______________ TestUnnamedVariableToString_param_1.test_repr_gpu _______________
self = <chainer.testing.parameterized.TestUnnamedVariableToString_param_1 testMethod=test_repr_gpu>
@attr.gpu
def test_repr_gpu(self):
self.x.to_gpu()
> self.assertEqual(repr(self.x), self.repr)
E AssertionError: Parameterized test failed.
E
E Base test method: TestUnnamedVariableToString.test_repr_gpu
E Test parameters:
E x_shape: (2, 2)
E dtype: <class 'numpy.float16'>
E repr: variable([[ 0., 1.],
E [ 2., 3.]])
E str: variable([[ 0. 1.]
E [ 2. 3.]])
E
E AssertionError: 'variable([[0., 1.],\n [2., 3.]])' != 'variable([[ 0., 1.],\n [ 2., 3.]])'
E - variable([[0., 1.],
E + variable([[ 0., 1.],
E ? + +
E - [2., 3.]])+ [ 2., 3.]])? + +
tests/chainer_tests/test_variable.py:1361: AssertionError
_______________ TestUnnamedVariableToString_param_1.test_str_cpu _______________
self = <chainer.testing.parameterized.TestUnnamedVariableToString_param_1 testMethod=test_str_cpu>
def test_str_cpu(self):
> self.assertEqual(str(self.x), self.str)
E AssertionError: Parameterized test failed.
E
E Base test method: TestUnnamedVariableToString.test_str_cpu
E Test parameters:
E x_shape: (2, 2)
E dtype: <class 'numpy.float16'>
E repr: variable([[ 0., 1.],
E [ 2., 3.]])
E str: variable([[ 0. 1.]
E [ 2. 3.]])
E
E AssertionError: 'variable([[0. 1.]\n [2. 3.]])' != 'variable([[ 0. 1.]\n [ 2. 3.]])'
E - variable([[0. 1.]
E + variable([[ 0. 1.]
E ? + +
E - [2. 3.]])+ [ 2. 3.]])? + +
tests/chainer_tests/test_variable.py:1356: AssertionError
_______________ TestUnnamedVariableToString_param_1.test_str_gpu _______________
self = <chainer.testing.parameterized.TestUnnamedVariableToString_param_1 testMethod=test_str_gpu>
@attr.gpu
def test_str_gpu(self):
self.x.to_gpu()
> self.assertEqual(str(self.x), self.str)
E AssertionError: Parameterized test failed.
E
E Base test method: TestUnnamedVariableToString.test_str_gpu
E Test parameters:
E x_shape: (2, 2)
E dtype: <class 'numpy.float16'>
E repr: variable([[ 0., 1.],
E [ 2., 3.]])
E str: variable([[ 0. 1.]
E [ 2. 3.]])
E
E AssertionError: 'variable([[0. 1.]\n [2. 3.]])' != 'variable([[ 0. 1.]\n [ 2. 3.]])'
E - variable([[0. 1.]
E + variable([[ 0. 1.]
E ? + +
E - [2. 3.]])+ [ 2. 3.]])? + +
tests/chainer_tests/test_variable.py:1366: AssertionError
______________ TestUnnamedVariableToString_param_2.test_repr_cpu _______________
self = <chainer.testing.parameterized.TestUnnamedVariableToString_param_2 testMethod=test_repr_cpu>
def test_repr_cpu(self):
> self.assertEqual(repr(self.x), self.repr)
E AssertionError: Parameterized test failed.
E
E Base test method: TestUnnamedVariableToString.test_repr_cpu
E Test parameters:
E x_shape: (2, 2)
E dtype: <class 'numpy.float32'>
E repr: variable([[ 0., 1.],
E [ 2., 3.]])
E str: variable([[ 0. 1.]
E [ 2. 3.]])
E
E AssertionError: 'variable([[0., 1.],\n [2., 3.]])' != 'variable([[ 0., 1.],\n [ 2., 3.]])'
E - variable([[0., 1.],
E + variable([[ 0., 1.],
E ? + +
E - [2., 3.]])+ [ 2., 3.]])? + +
tests/chainer_tests/test_variable.py:1353: AssertionError
______________ TestUnnamedVariableToString_param_2.test_repr_gpu _______________
self = <chainer.testing.parameterized.TestUnnamedVariableToString_param_2 testMethod=test_repr_gpu>
@attr.gpu
def test_repr_gpu(self):
self.x.to_gpu()
> self.assertEqual(repr(self.x), self.repr)
E AssertionError: Parameterized test failed.
E
E Base test method: TestUnnamedVariableToString.test_repr_gpu
E Test parameters:
E x_shape: (2, 2)
E dtype: <class 'numpy.float32'>
E repr: variable([[ 0., 1.],
E [ 2., 3.]])
E str: variable([[ 0. 1.]
E [ 2. 3.]])
E
E AssertionError: 'variable([[0., 1.],\n [2., 3.]])' != 'variable([[ 0., 1.],\n [ 2., 3.]])'
E - variable([[0., 1.],
E + variable([[ 0., 1.],
E ? + +
E - [2., 3.]])+ [ 2., 3.]])? + +
tests/chainer_tests/test_variable.py:1361: AssertionError
_______________ TestUnnamedVariableToString_param_2.test_str_cpu _______________
self = <chainer.testing.parameterized.TestUnnamedVariableToString_param_2 testMethod=test_str_cpu>
def test_str_cpu(self):
> self.assertEqual(str(self.x), self.str)
E AssertionError: Parameterized test failed.
E
E Base test method: TestUnnamedVariableToString.test_str_cpu
E Test parameters:
E x_shape: (2, 2)
E dtype: <class 'numpy.float32'>
E repr: variable([[ 0., 1.],
E [ 2., 3.]])
E str: variable([[ 0. 1.]
E [ 2. 3.]])
E
E AssertionError: 'variable([[0. 1.]\n [2. 3.]])' != 'variable([[ 0. 1.]\n [ 2. 3.]])'
E - variable([[0. 1.]
E + variable([[ 0. 1.]
E ? + +
E - [2. 3.]])+ [ 2. 3.]])? + +
tests/chainer_tests/test_variable.py:1356: AssertionError
_______________ TestUnnamedVariableToString_param_2.test_str_gpu _______________
self = <chainer.testing.parameterized.TestUnnamedVariableToString_param_2 testMethod=test_str_gpu>
@attr.gpu
def test_str_gpu(self):
self.x.to_gpu()
> self.assertEqual(str(self.x), self.str)
E AssertionError: Parameterized test failed.
E
E Base test method: TestUnnamedVariableToString.test_str_gpu
E Test parameters:
E x_shape: (2, 2)
E dtype: <class 'numpy.float32'>
E repr: variable([[ 0., 1.],
E [ 2., 3.]])
E str: variable([[ 0. 1.]
E [ 2. 3.]])
E
E AssertionError: 'variable([[0. 1.]\n [2. 3.]])' != 'variable([[ 0. 1.]\n [ 2. 3.]])'
E - variable([[0. 1.]
E + variable([[ 0. 1.]
E ? + +
E - [2. 3.]])+ [ 2. 3.]])? + +
tests/chainer_tests/test_variable.py:1366: AssertionError
______________ TestUnnamedVariableToString_param_3.test_repr_cpu _______________
self = <chainer.testing.parameterized.TestUnnamedVariableToString_param_3 testMethod=test_repr_cpu>
def test_repr_cpu(self):
> self.assertEqual(repr(self.x), self.repr)
E AssertionError: Parameterized test failed.
E
E Base test method: TestUnnamedVariableToString.test_repr_cpu
E Test parameters:
E x_shape: (2, 2)
E dtype: <class 'numpy.float64'>
E repr: variable([[ 0., 1.],
E [ 2., 3.]])
E str: variable([[ 0. 1.]
E [ 2. 3.]])
E
E AssertionError: 'variable([[0., 1.],\n [2., 3.]])' != 'variable([[ 0., 1.],\n [ 2., 3.]])'
E - variable([[0., 1.],
E + variable([[ 0., 1.],
E ? + +
E - [2., 3.]])+ [ 2., 3.]])? + +
tests/chainer_tests/test_variable.py:1353: AssertionError
______________ TestUnnamedVariableToString_param_3.test_repr_gpu _______________
self = <chainer.testing.parameterized.TestUnnamedVariableToString_param_3 testMethod=test_repr_gpu>
@attr.gpu
def test_repr_gpu(self):
self.x.to_gpu()
> self.assertEqual(repr(self.x), self.repr)
E AssertionError: Parameterized test failed.
E
E Base test method: TestUnnamedVariableToString.test_repr_gpu
E Test parameters:
E x_shape: (2, 2)
E dtype: <class 'numpy.float64'>
E repr: variable([[ 0., 1.],
E [ 2., 3.]])
E str: variable([[ 0. 1.]
E [ 2. 3.]])
E
E AssertionError: 'variable([[0., 1.],\n [2., 3.]])' != 'variable([[ 0., 1.],\n [ 2., 3.]])'
E - variable([[0., 1.],
E + variable([[ 0., 1.],
E ? + +
E - [2., 3.]])+ [ 2., 3.]])? + +
tests/chainer_tests/test_variable.py:1361: AssertionError
_______________ TestUnnamedVariableToString_param_3.test_str_cpu _______________
self = <chainer.testing.parameterized.TestUnnamedVariableToString_param_3 testMethod=test_str_cpu>
def test_str_cpu(self):
> self.assertEqual(str(self.x), self.str)
E AssertionError: Parameterized test failed.
E
E Base test method: TestUnnamedVariableToString.test_str_cpu
E Test parameters:
E x_shape: (2, 2)
E dtype: <class 'numpy.float64'>
E repr: variable([[ 0., 1.],
E [ 2., 3.]])
E str: variable([[ 0. 1.]
E [ 2. 3.]])
E
E AssertionError: 'variable([[0. 1.]\n [2. 3.]])' != 'variable([[ 0. 1.]\n [ 2. 3.]])'
E - variable([[0. 1.]
E + variable([[ 0. 1.]
E ? + +
E - [2. 3.]])+ [ 2. 3.]])? + +
tests/chainer_tests/test_variable.py:1356: AssertionError
_______________ TestUnnamedVariableToString_param_3.test_str_gpu _______________
self = <chainer.testing.parameterized.TestUnnamedVariableToString_param_3 testMethod=test_str_gpu>
@attr.gpu
def test_str_gpu(self):
self.x.to_gpu()
> self.assertEqual(str(self.x), self.str)
E AssertionError: Parameterized test failed.
E
E Base test method: TestUnnamedVariableToString.test_str_gpu
E Test parameters:
E x_shape: (2, 2)
E dtype: <class 'numpy.float64'>
E repr: variable([[ 0., 1.],
E [ 2., 3.]])
E str: variable([[ 0. 1.]
E [ 2. 3.]])
E
E AssertionError: 'variable([[0. 1.]\n [2. 3.]])' != 'variable([[ 0. 1.]\n [ 2. 3.]])'
E - variable([[0. 1.]
E + variable([[ 0. 1.]
E ? + +
E - [2. 3.]])+ [ 2. 3.]])? + +
tests/chainer_tests/test_variable.py:1366: AssertionError
______________ TestUnnamedVariableToString_param_4.test_repr_cpu _______________
self = <chainer.testing.parameterized.TestUnnamedVariableToString_param_4 testMethod=test_repr_cpu>
def test_repr_cpu(self):
> self.assertEqual(repr(self.x), self.repr)
E AssertionError: Parameterized test failed.
E
E Base test method: TestUnnamedVariableToString.test_repr_cpu
E Test parameters:
E x_shape: (3,)
E dtype: <class 'numpy.float32'>
E repr: variable([ 0., 1., 2.])
E str: variable([ 0. 1. 2.])
E
E AssertionError: 'variable([0., 1., 2.])' != 'variable([ 0., 1., 2.])'
E - variable([0., 1., 2.])
E + variable([ 0., 1., 2.])
E ? + + +
tests/chainer_tests/test_variable.py:1353: AssertionError
______________ TestUnnamedVariableToString_param_4.test_repr_gpu _______________
self = <chainer.testing.parameterized.TestUnnamedVariableToString_param_4 testMethod=test_repr_gpu>
@attr.gpu
def test_repr_gpu(self):
self.x.to_gpu()
> self.assertEqual(repr(self.x), self.repr)
E AssertionError: Parameterized test failed.
E
E Base test method: TestUnnamedVariableToString.test_repr_gpu
E Test parameters:
E x_shape: (3,)
E dtype: <class 'numpy.float32'>
E repr: variable([ 0., 1., 2.])
E str: variable([ 0. 1. 2.])
E
E AssertionError: 'variable([0., 1., 2.])' != 'variable([ 0., 1., 2.])'
E - variable([0., 1., 2.])
E + variable([ 0., 1., 2.])
E ? + + +
tests/chainer_tests/test_variable.py:1361: AssertionError
_______________ TestUnnamedVariableToString_param_4.test_str_cpu _______________
self = <chainer.testing.parameterized.TestUnnamedVariableToString_param_4 testMethod=test_str_cpu>
def test_str_cpu(self):
> self.assertEqual(str(self.x), self.str)
E AssertionError: Parameterized test failed.
E
E Base test method: TestUnnamedVariableToString.test_str_cpu
E Test parameters:
E x_shape: (3,)
E dtype: <class 'numpy.float32'>
E repr: variable([ 0., 1., 2.])
E str: variable([ 0. 1. 2.])
E
E AssertionError: 'variable([0. 1. 2.])' != 'variable([ 0. 1. 2.])'
E - variable([0. 1. 2.])
E + variable([ 0. 1. 2.])
E ? + + +
tests/chainer_tests/test_variable.py:1356: AssertionError
_______________ TestUnnamedVariableToString_param_4.test_str_gpu _______________
self = <chainer.testing.parameterized.TestUnnamedVariableToString_param_4 testMethod=test_str_gpu>
@attr.gpu
def test_str_gpu(self):
self.x.to_gpu()
> self.assertEqual(str(self.x), self.str)
E AssertionError: Parameterized test failed.
E
E Base test method: TestUnnamedVariableToString.test_str_gpu
E Test parameters:
E x_shape: (3,)
E dtype: <class 'numpy.float32'>
E repr: variable([ 0., 1., 2.])
E str: variable([ 0. 1. 2.])
E
E AssertionError: 'variable([0. 1. 2.])' != 'variable([ 0. 1. 2.])'
E - variable([0. 1. 2.])
E + variable([ 0. 1. 2.])
E ? + + +
tests/chainer_tests/test_variable.py:1366: AssertionError
______________ TestNamedVariableToString_param_1.test_named_repr _______________
self = <chainer.testing.parameterized.TestNamedVariableToString_param_1 testMethod=test_named_repr>
def test_named_repr(self):
> self.assertEqual(repr(self.x), self.repr)
E AssertionError: Parameterized test failed.
E
E Base test method: TestNamedVariableToString.test_named_repr
E Test parameters:
E x_shape: (2, 2)
E dtype: <class 'numpy.float32'>
E repr: variable x([[ 0., 1.],
E [ 2., 3.]])
E str: variable x([[ 0. 1.]
E [ 2. 3.]])
E
E AssertionError: 'variable x([[0., 1.],\n [2., 3.]])' != 'variable x([[ 0., 1.],\n [ 2., 3.]])'
E - variable x([[0., 1.],
E + variable x([[ 0., 1.],
E ? + +
E - [2., 3.]])+ [ 2., 3.]])? + +
tests/chainer_tests/test_variable.py:1420: AssertionError
_______________ TestNamedVariableToString_param_1.test_named_str _______________
self = <chainer.testing.parameterized.TestNamedVariableToString_param_1 testMethod=test_named_str>
def test_named_str(self):
> self.assertEqual(str(self.x), self.str)
E AssertionError: Parameterized test failed.
E
E Base test method: TestNamedVariableToString.test_named_str
E Test parameters:
E x_shape: (2, 2)
E dtype: <class 'numpy.float32'>
E repr: variable x([[ 0., 1.],
E [ 2., 3.]])
E str: variable x([[ 0. 1.]
E [ 2. 3.]])
E
E AssertionError: 'variable x([[0. 1.]\n [2. 3.]])' != 'variable x([[ 0. 1.]\n [ 2. 3.]])'
E - variable x([[0. 1.]
E + variable x([[ 0. 1.]
E ? + +
E - [2. 3.]])+ [ 2. 3.]])? + +
tests/chainer_tests/test_variable.py:1423: AssertionError
_______________ TestNamedVariableToString_param_1.test_repr_gpu ________________
self = <chainer.testing.parameterized.TestNamedVariableToString_param_1 testMethod=test_repr_gpu>
@attr.gpu
def test_repr_gpu(self):
self.x.to_gpu()
> self.assertEqual(repr(self.x), self.repr)
E AssertionError: Parameterized test failed.
E
E Base test method: TestNamedVariableToString.test_repr_gpu
E Test parameters:
E x_shape: (2, 2)
E dtype: <class 'numpy.float32'>
E repr: variable x([[ 0., 1.],
E [ 2., 3.]])
E str: variable x([[ 0. 1.]
E [ 2. 3.]])
E
E AssertionError: 'variable x([[0., 1.],\n [2., 3.]])' != 'variable x([[ 0., 1.],\n [ 2., 3.]])'
E - variable x([[0., 1.],
E + variable x([[ 0., 1.],
E ? + +
E - [2., 3.]])+ [ 2., 3.]])? + +
tests/chainer_tests/test_variable.py:1428: AssertionError
________________ TestNamedVariableToString_param_1.test_str_gpu ________________
self = <chainer.testing.parameterized.TestNamedVariableToString_param_1 testMethod=test_str_gpu>
@attr.gpu
def test_str_gpu(self):
self.x.to_gpu()
> self.assertEqual(str(self.x), self.str)
E AssertionError: Parameterized test failed.
E
E Base test method: TestNamedVariableToString.test_str_gpu
E Test parameters:
E x_shape: (2, 2)
E dtype: <class 'numpy.float32'>
E repr: variable x([[ 0., 1.],
E [ 2., 3.]])
E str: variable x([[ 0. 1.]
E [ 2. 3.]])
E
E AssertionError: 'variable x([[0. 1.]\n [2. 3.]])' != 'variable x([[ 0. 1.]\n [ 2. 3.]])'
E - variable x([[0. 1.]
E + variable x([[ 0. 1.]
E ? + +
E - [2. 3.]])+ [ 2. 3.]])? + +
tests/chainer_tests/test_variable.py:1433: AssertionError
______________ TestNamedVariableToString_param_2.test_named_repr _______________
self = <chainer.testing.parameterized.TestNamedVariableToString_param_2 testMethod=test_named_repr>
def test_named_repr(self):
> self.assertEqual(repr(self.x), self.repr)
E AssertionError: Parameterized test failed.
E
E Base test method: TestNamedVariableToString.test_named_repr
E Test parameters:
E x_shape: ()
E dtype: <class 'numpy.float32'>
E repr: variable x(0.0)
E str: variable x(0.0)
E
E AssertionError: 'variable x(0.)' != 'variable x(0.0)'
E - variable x(0.)
E + variable x(0.0)
E ? +
tests/chainer_tests/test_variable.py:1420: AssertionError
_______________ TestNamedVariableToString_param_2.test_named_str _______________
self = <chainer.testing.parameterized.TestNamedVariableToString_param_2 testMethod=test_named_str>
def test_named_str(self):
> self.assertEqual(str(self.x), self.str)
E AssertionError: Parameterized test failed.
E
E Base test method: TestNamedVariableToString.test_named_str
E Test parameters:
E x_shape: ()
E dtype: <class 'numpy.float32'>
E repr: variable x(0.0)
E str: variable x(0.0)
E
E AssertionError: 'variable x(0.)' != 'variable x(0.0)'
E - variable x(0.)
E + variable x(0.0)
E ? +
tests/chainer_tests/test_variable.py:1423: AssertionError
_______________ TestNamedVariableToString_param_2.test_repr_gpu ________________
self = <chainer.testing.parameterized.TestNamedVariableToString_param_2 testMethod=test_repr_gpu>
@attr.gpu
def test_repr_gpu(self):
self.x.to_gpu()
> self.assertEqual(repr(self.x), self.repr)
E AssertionError: Parameterized test failed.
E
E Base test method: TestNamedVariableToString.test_repr_gpu
E Test parameters:
E x_shape: ()
E dtype: <class 'numpy.float32'>
E repr: variable x(0.0)
E str: variable x(0.0)
E
E AssertionError: 'variable x(0.)' != 'variable x(0.0)'
E - variable x(0.)
E + variable x(0.0)
E ? +
tests/chainer_tests/test_variable.py:1428: AssertionError
________________ TestNamedVariableToString_param_2.test_str_gpu ________________
self = <chainer.testing.parameterized.TestNamedVariableToString_param_2 testMethod=test_str_gpu>
@attr.gpu
def test_str_gpu(self):
self.x.to_gpu()
> self.assertEqual(str(self.x), self.str)
E AssertionError: Parameterized test failed.
E
E Base test method: TestNamedVariableToString.test_str_gpu
E Test parameters:
E x_shape: ()
E dtype: <class 'numpy.float32'>
E repr: variable x(0.0)
E str: variable x(0.0)
E
E AssertionError: 'variable x(0.)' != 'variable x(0.0)'
E - variable x(0.)
E + variable x(0.0)
E ? +
tests/chainer_tests/test_variable.py:1433: AssertionError
_____________________ TestGoogLeNet.test_available_layers ______________________
self = <chainer_tests.links_tests.model_tests.test_vision.TestGoogLeNet testMethod=test_available_layers>
def setUp(self):
> self.link = googlenet.GoogLeNet(pretrained_model=None)
tests/chainer_tests/links_tests/model_tests/test_vision.py:263:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
chainer/links/model/vision/googlenet.py:122: in __init__
loss2_fc2=Linear(1024, 1000, **kwargs)
chainer/link.py:649: in __init__
self.add_link(name, link)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <chainer.links.model.vision.googlenet.GoogLeNet object at 0x7f8d1a678d30>
name = 'conv1'
link = <chainer.links.connection.convolution_2d.Convolution2D object at 0x7f8d1a678be0>
def add_link(self, name, link):
"""Registers a child link to this chain.
.. deprecated:: v2.0.0
Assign the child link directly to an attribute within
:meth:`~chainer.Chain.init_scope` instead.
For example, the following code
.. code-block:: python
chain.add_link('l1', L.Linear(3, 5))
can be replaced by the following line.
.. code-block:: python
with chain.init_scope():
chain.l1 = L.Linear(3, 5)
The latter is easier for IDEs to keep track of the attribute's
type.
Args:
name (str): Name of the child link. This name is also used as the
attribute name.
link (Link): The link object to be registered.
"""
warnings.warn('''\
Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
Assign a Link object directly to an attribute within a \
"with link.init_scope():" block instead.
> ''', DeprecationWarning)
E DeprecationWarning: Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
E Assign a Link object directly to an attribute within a "with link.init_scope():" block instead.
chainer/link.py:701: DeprecationWarning
_________________________ TestGoogLeNet.test_call_cpu __________________________
self = <chainer_tests.links_tests.model_tests.test_vision.TestGoogLeNet testMethod=test_call_cpu>
def setUp(self):
> self.link = googlenet.GoogLeNet(pretrained_model=None)
tests/chainer_tests/links_tests/model_tests/test_vision.py:263:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
chainer/links/model/vision/googlenet.py:122: in __init__
loss2_fc2=Linear(1024, 1000, **kwargs)
chainer/link.py:649: in __init__
self.add_link(name, link)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <chainer.links.model.vision.googlenet.GoogLeNet object at 0x7f8cee4464e0>
name = 'conv1'
link = <chainer.links.connection.convolution_2d.Convolution2D object at 0x7f8cee446320>
def add_link(self, name, link):
"""Registers a child link to this chain.
.. deprecated:: v2.0.0
Assign the child link directly to an attribute within
:meth:`~chainer.Chain.init_scope` instead.
For example, the following code
.. code-block:: python
chain.add_link('l1', L.Linear(3, 5))
can be replaced by the following line.
.. code-block:: python
with chain.init_scope():
chain.l1 = L.Linear(3, 5)
The latter is easier for IDEs to keep track of the attribute's
type.
Args:
name (str): Name of the child link. This name is also used as the
attribute name.
link (Link): The link object to be registered.
"""
warnings.warn('''\
Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
Assign a Link object directly to an attribute within a \
"with link.init_scope():" block instead.
> ''', DeprecationWarning)
E DeprecationWarning: Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
E Assign a Link object directly to an attribute within a "with link.init_scope():" block instead.
chainer/link.py:701: DeprecationWarning
_________________________ TestGoogLeNet.test_call_gpu __________________________
self = <chainer_tests.links_tests.model_tests.test_vision.TestGoogLeNet testMethod=test_call_gpu>
def setUp(self):
> self.link = googlenet.GoogLeNet(pretrained_model=None)
tests/chainer_tests/links_tests/model_tests/test_vision.py:263:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
chainer/links/model/vision/googlenet.py:122: in __init__
loss2_fc2=Linear(1024, 1000, **kwargs)
chainer/link.py:649: in __init__
self.add_link(name, link)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <chainer.links.model.vision.googlenet.GoogLeNet object at 0x7f8d1a5aac88>
name = 'conv1'
link = <chainer.links.connection.convolution_2d.Convolution2D object at 0x7f8d1a5aac50>
def add_link(self, name, link):
"""Registers a child link to this chain.
.. deprecated:: v2.0.0
Assign the child link directly to an attribute within
:meth:`~chainer.Chain.init_scope` instead.
For example, the following code
.. code-block:: python
chain.add_link('l1', L.Linear(3, 5))
can be replaced by the following line.
.. code-block:: python
with chain.init_scope():
chain.l1 = L.Linear(3, 5)
The latter is easier for IDEs to keep track of the attribute's
type.
Args:
name (str): Name of the child link. This name is also used as the
attribute name.
link (Link): The link object to be registered.
"""
warnings.warn('''\
Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
Assign a Link object directly to an attribute within a \
"with link.init_scope():" block instead.
> ''', DeprecationWarning)
E DeprecationWarning: Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
E Assign a Link object directly to an attribute within a "with link.init_scope():" block instead.
chainer/link.py:701: DeprecationWarning
_________________________ TestGoogLeNet.test_copy_cpu __________________________
self = <chainer_tests.links_tests.model_tests.test_vision.TestGoogLeNet testMethod=test_copy_cpu>
def setUp(self):
> self.link = googlenet.GoogLeNet(pretrained_model=None)
tests/chainer_tests/links_tests/model_tests/test_vision.py:263:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
chainer/links/model/vision/googlenet.py:122: in __init__
loss2_fc2=Linear(1024, 1000, **kwargs)
chainer/link.py:649: in __init__
self.add_link(name, link)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <chainer.links.model.vision.googlenet.GoogLeNet object at 0x7f8d1847ae80>
name = 'conv1'
link = <chainer.links.connection.convolution_2d.Convolution2D object at 0x7f8d1847ab38>
def add_link(self, name, link):
"""Registers a child link to this chain.
.. deprecated:: v2.0.0
Assign the child link directly to an attribute within
:meth:`~chainer.Chain.init_scope` instead.
For example, the following code
.. code-block:: python
chain.add_link('l1', L.Linear(3, 5))
can be replaced by the following line.
.. code-block:: python
with chain.init_scope():
chain.l1 = L.Linear(3, 5)
The latter is easier for IDEs to keep track of the attribute's
type.
Args:
name (str): Name of the child link. This name is also used as the
attribute name.
link (Link): The link object to be registered.
"""
warnings.warn('''\
Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
Assign a Link object directly to an attribute within a \
"with link.init_scope():" block instead.
> ''', DeprecationWarning)
E DeprecationWarning: Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
E Assign a Link object directly to an attribute within a "with link.init_scope():" block instead.
chainer/link.py:701: DeprecationWarning
_________________________ TestGoogLeNet.test_copy_gpu __________________________
self = <chainer_tests.links_tests.model_tests.test_vision.TestGoogLeNet testMethod=test_copy_gpu>
def setUp(self):
> self.link = googlenet.GoogLeNet(pretrained_model=None)
tests/chainer_tests/links_tests/model_tests/test_vision.py:263:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
chainer/links/model/vision/googlenet.py:122: in __init__
loss2_fc2=Linear(1024, 1000, **kwargs)
chainer/link.py:649: in __init__
self.add_link(name, link)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <chainer.links.model.vision.googlenet.GoogLeNet object at 0x7f8ca10bdef0>
name = 'conv1'
link = <chainer.links.connection.convolution_2d.Convolution2D object at 0x7f8ca10bdf60>
def add_link(self, name, link):
"""Registers a child link to this chain.
.. deprecated:: v2.0.0
Assign the child link directly to an attribute within
:meth:`~chainer.Chain.init_scope` instead.
For example, the following code
.. code-block:: python
chain.add_link('l1', L.Linear(3, 5))
can be replaced by the following line.
.. code-block:: python
with chain.init_scope():
chain.l1 = L.Linear(3, 5)
The latter is easier for IDEs to keep track of the attribute's
type.
Args:
name (str): Name of the child link. This name is also used as the
attribute name.
link (Link): The link object to be registered.
"""
warnings.warn('''\
Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
Assign a Link object directly to an attribute within a \
"with link.init_scope():" block instead.
> ''', DeprecationWarning)
E DeprecationWarning: Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
E Assign a Link object directly to an attribute within a "with link.init_scope():" block instead.
chainer/link.py:701: DeprecationWarning
________________________ TestGoogLeNet.test_extract_cpu ________________________
self = <chainer_tests.links_tests.model_tests.test_vision.TestGoogLeNet testMethod=test_extract_cpu>
def setUp(self):
> self.link = googlenet.GoogLeNet(pretrained_model=None)
tests/chainer_tests/links_tests/model_tests/test_vision.py:263:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
chainer/links/model/vision/googlenet.py:122: in __init__
loss2_fc2=Linear(1024, 1000, **kwargs)
chainer/link.py:649: in __init__
self.add_link(name, link)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <chainer.links.model.vision.googlenet.GoogLeNet object at 0x7f8c93a42160>
name = 'conv1'
link = <chainer.links.connection.convolution_2d.Convolution2D object at 0x7f8c93a42208>
def add_link(self, name, link):
"""Registers a child link to this chain.
.. deprecated:: v2.0.0
Assign the child link directly to an attribute within
:meth:`~chainer.Chain.init_scope` instead.
For example, the following code
.. code-block:: python
chain.add_link('l1', L.Linear(3, 5))
can be replaced by the following line.
.. code-block:: python
with chain.init_scope():
chain.l1 = L.Linear(3, 5)
The latter is easier for IDEs to keep track of the attribute's
type.
Args:
name (str): Name of the child link. This name is also used as the
attribute name.
link (Link): The link object to be registered.
"""
warnings.warn('''\
Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
Assign a Link object directly to an attribute within a \
"with link.init_scope():" block instead.
> ''', DeprecationWarning)
E DeprecationWarning: Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
E Assign a Link object directly to an attribute within a "with link.init_scope():" block instead.
chainer/link.py:701: DeprecationWarning
________________________ TestGoogLeNet.test_extract_gpu ________________________
self = <chainer_tests.links_tests.model_tests.test_vision.TestGoogLeNet testMethod=test_extract_gpu>
def setUp(self):
> self.link = googlenet.GoogLeNet(pretrained_model=None)
tests/chainer_tests/links_tests/model_tests/test_vision.py:263:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
chainer/links/model/vision/googlenet.py:122: in __init__
loss2_fc2=Linear(1024, 1000, **kwargs)
chainer/link.py:649: in __init__
self.add_link(name, link)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <chainer.links.model.vision.googlenet.GoogLeNet object at 0x7f8c93a7a4e0>
name = 'conv1'
link = <chainer.links.connection.convolution_2d.Convolution2D object at 0x7f8c93a7a550>
def add_link(self, name, link):
"""Registers a child link to this chain.
.. deprecated:: v2.0.0
Assign the child link directly to an attribute within
:meth:`~chainer.Chain.init_scope` instead.
For example, the following code
.. code-block:: python
chain.add_link('l1', L.Linear(3, 5))
can be replaced by the following line.
.. code-block:: python
with chain.init_scope():
chain.l1 = L.Linear(3, 5)
The latter is easier for IDEs to keep track of the attribute's
type.
Args:
name (str): Name of the child link. This name is also used as the
attribute name.
link (Link): The link object to be registered.
"""
warnings.warn('''\
Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
Assign a Link object directly to an attribute within a \
"with link.init_scope():" block instead.
> ''', DeprecationWarning)
E DeprecationWarning: Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
E Assign a Link object directly to an attribute within a "with link.init_scope():" block instead.
chainer/link.py:701: DeprecationWarning
________________________ TestGoogLeNet.test_predict_cpu ________________________
self = <chainer_tests.links_tests.model_tests.test_vision.TestGoogLeNet testMethod=test_predict_cpu>
def setUp(self):
> self.link = googlenet.GoogLeNet(pretrained_model=None)
tests/chainer_tests/links_tests/model_tests/test_vision.py:263:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
chainer/links/model/vision/googlenet.py:122: in __init__
loss2_fc2=Linear(1024, 1000, **kwargs)
chainer/link.py:649: in __init__
self.add_link(name, link)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <chainer.links.model.vision.googlenet.GoogLeNet object at 0x7f8ca107b390>
name = 'conv1'
link = <chainer.links.connection.convolution_2d.Convolution2D object at 0x7f8ca107b438>
def add_link(self, name, link):
"""Registers a child link to this chain.
.. deprecated:: v2.0.0
Assign the child link directly to an attribute within
:meth:`~chainer.Chain.init_scope` instead.
For example, the following code
.. code-block:: python
chain.add_link('l1', L.Linear(3, 5))
can be replaced by the following line.
.. code-block:: python
with chain.init_scope():
chain.l1 = L.Linear(3, 5)
The latter is easier for IDEs to keep track of the attribute's
type.
Args:
name (str): Name of the child link. This name is also used as the
attribute name.
link (Link): The link object to be registered.
"""
warnings.warn('''\
Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
Assign a Link object directly to an attribute within a \
"with link.init_scope():" block instead.
> ''', DeprecationWarning)
E DeprecationWarning: Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
E Assign a Link object directly to an attribute within a "with link.init_scope():" block instead.
chainer/link.py:701: DeprecationWarning
________________________ TestGoogLeNet.test_predict_gpu ________________________
self = <chainer_tests.links_tests.model_tests.test_vision.TestGoogLeNet testMethod=test_predict_gpu>
def setUp(self):
> self.link = googlenet.GoogLeNet(pretrained_model=None)
tests/chainer_tests/links_tests/model_tests/test_vision.py:263:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
chainer/links/model/vision/googlenet.py:122: in __init__
loss2_fc2=Linear(1024, 1000, **kwargs)
chainer/link.py:649: in __init__
self.add_link(name, link)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <chainer.links.model.vision.googlenet.GoogLeNet object at 0x7f8c8ba68a90>
name = 'conv1'
link = <chainer.links.connection.convolution_2d.Convolution2D object at 0x7f8c8ba68b00>
def add_link(self, name, link):
"""Registers a child link to this chain.
.. deprecated:: v2.0.0
Assign the child link directly to an attribute within
:meth:`~chainer.Chain.init_scope` instead.
For example, the following code
.. code-block:: python
chain.add_link('l1', L.Linear(3, 5))
can be replaced by the following line.
.. code-block:: python
with chain.init_scope():
chain.l1 = L.Linear(3, 5)
The latter is easier for IDEs to keep track of the attribute's
type.
Args:
name (str): Name of the child link. This name is also used as the
attribute name.
link (Link): The link object to be registered.
"""
warnings.warn('''\
Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
Assign a Link object directly to an attribute within a \
"with link.init_scope():" block instead.
> ''', DeprecationWarning)
E DeprecationWarning: Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
E Assign a Link object directly to an attribute within a "with link.init_scope():" block instead.
chainer/link.py:701: DeprecationWarning
__________________________ TestGoogLeNet.test_prepare __________________________
self = <chainer_tests.links_tests.model_tests.test_vision.TestGoogLeNet testMethod=test_prepare>
def setUp(self):
> self.link = googlenet.GoogLeNet(pretrained_model=None)
tests/chainer_tests/links_tests/model_tests/test_vision.py:263:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
chainer/links/model/vision/googlenet.py:122: in __init__
loss2_fc2=Linear(1024, 1000, **kwargs)
chainer/link.py:649: in __init__
self.add_link(name, link)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <chainer.links.model.vision.googlenet.GoogLeNet object at 0x7f8ca108dd68>
name = 'conv1'
link = <chainer.links.connection.convolution_2d.Convolution2D object at 0x7f8ca108ddd8>
def add_link(self, name, link):
"""Registers a child link to this chain.
.. deprecated:: v2.0.0
Assign the child link directly to an attribute within
:meth:`~chainer.Chain.init_scope` instead.
For example, the following code
.. code-block:: python
chain.add_link('l1', L.Linear(3, 5))
can be replaced by the following line.
.. code-block:: python
with chain.init_scope():
chain.l1 = L.Linear(3, 5)
The latter is easier for IDEs to keep track of the attribute's
type.
Args:
name (str): Name of the child link. This name is also used as the
attribute name.
link (Link): The link object to be registered.
"""
warnings.warn('''\
Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
Assign a Link object directly to an attribute within a \
"with link.init_scope():" block instead.
> ''', DeprecationWarning)
E DeprecationWarning: Child link registeration via Chain.__init__ and Chain.add_link are deprecated.
E Assign a Link object directly to an attribute within a "with link.init_scope():" block instead.
chainer/link.py:701: DeprecationWarning
=============================== warnings summary ===============================
tests/chainer_tests/links_tests/model_tests/test_vision.py::TestResNetLayers_param_0::test_predict_cpu
/home/kenichi/Development/chainer/chainer/functions/normalization/batch_normalization.py:469: RuntimeWarning: overflow encountered in multiply
x_mu *= inv_std
/home/kenichi/.pyenv/versions/local-3.6.3/lib/python3.6/site-packages/numpy/core/_methods.py:26: RuntimeWarning: invalid value encountered in reduce
return umr_maximum(a, axis, None, out, keepdims)
tests/chainer_tests/links_tests/model_tests/test_vision.py::TestResNetLayers_param_1::test_predict_cpu
/home/kenichi/Development/chainer/chainer/functions/normalization/batch_normalization.py:469: RuntimeWarning: overflow encountered in multiply
x_mu *= inv_std
/home/kenichi/.pyenv/versions/local-3.6.3/lib/python3.6/site-packages/numpy/core/_methods.py:26: RuntimeWarning: invalid value encountered in reduce
return umr_maximum(a, axis, None, out, keepdims)
tests/chainer_tests/links_tests/model_tests/test_vision.py::TestResNetLayers_param_2::test_predict_cpu
/home/kenichi/Development/chainer/chainer/functions/normalization/batch_normalization.py:469: RuntimeWarning: overflow encountered in multiply
x_mu *= inv_std
/home/kenichi/.pyenv/versions/local-3.6.3/lib/python3.6/site-packages/numpy/core/_methods.py:26: RuntimeWarning: invalid value encountered in reduce
return umr_maximum(a, axis, None, out, keepdims)
tests/chainer_tests/training_tests/extensions_tests/test_parameter_statistics.py::TestParameterStatistics_param_0::test_report_key_pattern
/home/kenichi/.pyenv/versions/local-3.6.3/lib/python3.6/site-packages/numpy/lib/function_base.py:4291: RuntimeWarning: Invalid value encountered in percentile
interpolation=interpolation)
tests/chainer_tests/training_tests/extensions_tests/test_parameter_statistics.py::TestParameterStatistics_param_1::test_report_key_pattern
/home/kenichi/.pyenv/versions/local-3.6.3/lib/python3.6/site-packages/numpy/lib/function_base.py:4291: RuntimeWarning: Invalid value encountered in percentile
interpolation=interpolation)
tests/chainer_tests/training_tests/extensions_tests/test_parameter_statistics.py::TestParameterStatistics_param_2::test_report
/home/kenichi/.pyenv/versions/local-3.6.3/lib/python3.6/site-packages/numpy/lib/function_base.py:4291: RuntimeWarning: Invalid value encountered in percentile
interpolation=interpolation)
tests/chainer_tests/training_tests/extensions_tests/test_parameter_statistics.py::TestParameterStatistics_param_2::test_report_key_pattern
/home/kenichi/.pyenv/versions/local-3.6.3/lib/python3.6/site-packages/numpy/lib/function_base.py:4291: RuntimeWarning: Invalid value encountered in percentile
interpolation=interpolation)
tests/chainer_tests/training_tests/extensions_tests/test_parameter_statistics.py::TestParameterStatistics_param_2::test_report_late_register
/home/kenichi/.pyenv/versions/local-3.6.3/lib/python3.6/site-packages/numpy/lib/function_base.py:4291: RuntimeWarning: Invalid value encountered in percentile
interpolation=interpolation)
tests/chainer_tests/training_tests/extensions_tests/test_parameter_statistics.py::TestParameterStatistics_param_3::test_report_key_pattern
/home/kenichi/.pyenv/versions/local-3.6.3/lib/python3.6/site-packages/numpy/lib/function_base.py:4291: RuntimeWarning: Invalid value encountered in percentile
interpolation=interpolation)
tests/chainer_tests/training_tests/extensions_tests/test_parameter_statistics.py::TestParameterStatisticsArguments_param_0::test_report_key_prefix
/home/kenichi/.pyenv/versions/local-3.6.3/lib/python3.6/site-packages/numpy/lib/function_base.py:4291: RuntimeWarning: Invalid value encountered in percentile
interpolation=interpolation)
tests/chainer_tests/training_tests/extensions_tests/test_parameter_statistics.py::TestParameterStatisticsArguments_param_0::test_skip_params
/home/kenichi/.pyenv/versions/local-3.6.3/lib/python3.6/site-packages/numpy/lib/function_base.py:4291: RuntimeWarning: Invalid value encountered in percentile
interpolation=interpolation)
tests/chainer_tests/training_tests/triggers_tests/test_interval_trigger.py::TestIntervalTrigger_param_0::test_resumed_trigger_backward_compat
/home/kenichi/Development/chainer/chainer/training/triggers/interval_trigger.py:89: UserWarning: The previous value of iteration is not saved. IntervalTrigger guesses it using current iteration. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of iteration is not saved. '
/home/kenichi/Development/chainer/chainer/training/triggers/interval_trigger.py:101: UserWarning: The previous value of epoch_detail is not saved. IntervalTrigger uses the value of trainer.updater.previous_epoch_detail. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of epoch_detail is not saved. '
tests/chainer_tests/training_tests/triggers_tests/test_interval_trigger.py::TestIntervalTrigger_param_1::test_resumed_trigger_backward_compat
/home/kenichi/Development/chainer/chainer/training/triggers/interval_trigger.py:89: UserWarning: The previous value of iteration is not saved. IntervalTrigger guesses it using current iteration. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of iteration is not saved. '
/home/kenichi/Development/chainer/chainer/training/triggers/interval_trigger.py:101: UserWarning: The previous value of epoch_detail is not saved. IntervalTrigger uses the value of trainer.updater.previous_epoch_detail. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of epoch_detail is not saved. '
tests/chainer_tests/training_tests/triggers_tests/test_interval_trigger.py::TestIntervalTrigger_param_2::test_resumed_trigger_backward_compat
/home/kenichi/Development/chainer/chainer/training/triggers/interval_trigger.py:89: UserWarning: The previous value of iteration is not saved. IntervalTrigger guesses it using current iteration. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of iteration is not saved. '
/home/kenichi/Development/chainer/chainer/training/triggers/interval_trigger.py:101: UserWarning: The previous value of epoch_detail is not saved. IntervalTrigger uses the value of trainer.updater.previous_epoch_detail. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of epoch_detail is not saved. '
tests/chainer_tests/training_tests/triggers_tests/test_interval_trigger.py::TestIntervalTrigger_param_3::test_resumed_trigger_backward_compat
/home/kenichi/Development/chainer/chainer/training/triggers/interval_trigger.py:89: UserWarning: The previous value of iteration is not saved. IntervalTrigger guesses it using current iteration. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of iteration is not saved. '
/home/kenichi/Development/chainer/chainer/training/triggers/interval_trigger.py:101: UserWarning: The previous value of epoch_detail is not saved. IntervalTrigger uses the value of trainer.updater.previous_epoch_detail. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of epoch_detail is not saved. '
tests/chainer_tests/training_tests/triggers_tests/test_interval_trigger.py::TestIntervalTrigger_param_4::test_resumed_trigger_backward_compat
/home/kenichi/Development/chainer/chainer/training/triggers/interval_trigger.py:89: UserWarning: The previous value of iteration is not saved. IntervalTrigger guesses it using current iteration. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of iteration is not saved. '
/home/kenichi/Development/chainer/chainer/training/triggers/interval_trigger.py:101: UserWarning: The previous value of epoch_detail is not saved. IntervalTrigger uses the value of trainer.updater.previous_epoch_detail. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of epoch_detail is not saved. '
tests/chainer_tests/training_tests/triggers_tests/test_manual_schedule_trigger.py::TestTrigger_param_0::test_resumed_trigger_backward_compat
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:83: UserWarning: The previous value of iteration is not saved. ManualScheduleTrigger guesses it using current iteration. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of iteration is not saved. '
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:95: UserWarning: The previous value of epoch_detail is not saved. ManualScheduleTrigger uses the value of trainer.updater.previous_epoch_detail. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of epoch_detail is not saved. '
tests/chainer_tests/training_tests/triggers_tests/test_manual_schedule_trigger.py::TestTrigger_param_1::test_resumed_trigger_backward_compat
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:83: UserWarning: The previous value of iteration is not saved. ManualScheduleTrigger guesses it using current iteration. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of iteration is not saved. '
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:95: UserWarning: The previous value of epoch_detail is not saved. ManualScheduleTrigger uses the value of trainer.updater.previous_epoch_detail. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of epoch_detail is not saved. '
tests/chainer_tests/training_tests/triggers_tests/test_manual_schedule_trigger.py::TestTrigger_param_2::test_resumed_trigger_backward_compat
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:83: UserWarning: The previous value of iteration is not saved. ManualScheduleTrigger guesses it using current iteration. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of iteration is not saved. '
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:95: UserWarning: The previous value of epoch_detail is not saved. ManualScheduleTrigger uses the value of trainer.updater.previous_epoch_detail. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of epoch_detail is not saved. '
tests/chainer_tests/training_tests/triggers_tests/test_manual_schedule_trigger.py::TestTrigger_param_3::test_resumed_trigger_backward_compat
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:83: UserWarning: The previous value of iteration is not saved. ManualScheduleTrigger guesses it using current iteration. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of iteration is not saved. '
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:95: UserWarning: The previous value of epoch_detail is not saved. ManualScheduleTrigger uses the value of trainer.updater.previous_epoch_detail. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of epoch_detail is not saved. '
tests/chainer_tests/training_tests/triggers_tests/test_manual_schedule_trigger.py::TestTrigger_param_4::test_resumed_trigger_backward_compat
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:83: UserWarning: The previous value of iteration is not saved. ManualScheduleTrigger guesses it using current iteration. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of iteration is not saved. '
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:95: UserWarning: The previous value of epoch_detail is not saved. ManualScheduleTrigger uses the value of trainer.updater.previous_epoch_detail. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of epoch_detail is not saved. '
tests/chainer_tests/training_tests/triggers_tests/test_manual_schedule_trigger.py::TestTrigger_param_5::test_resumed_trigger_backward_compat
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:83: UserWarning: The previous value of iteration is not saved. ManualScheduleTrigger guesses it using current iteration. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of iteration is not saved. '
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:95: UserWarning: The previous value of epoch_detail is not saved. ManualScheduleTrigger uses the value of trainer.updater.previous_epoch_detail. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of epoch_detail is not saved. '
tests/chainer_tests/training_tests/triggers_tests/test_manual_schedule_trigger.py::TestTrigger_param_6::test_resumed_trigger_backward_compat
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:83: UserWarning: The previous value of iteration is not saved. ManualScheduleTrigger guesses it using current iteration. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of iteration is not saved. '
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:95: UserWarning: The previous value of epoch_detail is not saved. ManualScheduleTrigger uses the value of trainer.updater.previous_epoch_detail. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of epoch_detail is not saved. '
tests/chainer_tests/training_tests/triggers_tests/test_manual_schedule_trigger.py::TestTrigger_param_7::test_resumed_trigger_backward_compat
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:83: UserWarning: The previous value of iteration is not saved. ManualScheduleTrigger guesses it using current iteration. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of iteration is not saved. '
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:95: UserWarning: The previous value of epoch_detail is not saved. ManualScheduleTrigger uses the value of trainer.updater.previous_epoch_detail. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of epoch_detail is not saved. '
tests/chainer_tests/training_tests/triggers_tests/test_manual_schedule_trigger.py::TestTrigger_param_8::test_resumed_trigger_backward_compat
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:83: UserWarning: The previous value of iteration is not saved. ManualScheduleTrigger guesses it using current iteration. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of iteration is not saved. '
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:95: UserWarning: The previous value of epoch_detail is not saved. ManualScheduleTrigger uses the value of trainer.updater.previous_epoch_detail. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of epoch_detail is not saved. '
tests/chainer_tests/training_tests/triggers_tests/test_manual_schedule_trigger.py::TestTrigger_param_9::test_resumed_trigger_backward_compat
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:83: UserWarning: The previous value of iteration is not saved. ManualScheduleTrigger guesses it using current iteration. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of iteration is not saved. '
/home/kenichi/Development/chainer/chainer/training/triggers/manual_schedule_trigger.py:95: UserWarning: The previous value of epoch_detail is not saved. ManualScheduleTrigger uses the value of trainer.updater.previous_epoch_detail. If this trigger is not called at every iteration, it may not work correctly.
'The previous value of epoch_detail is not saved. '
-- Docs: http://doc.pytest.org/en/latest/warnings.html
===== 34 failed, 39313 passed, 28 skipped, 44 warnings in 6125.11 seconds ======
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