def add_param(self,
name,
shape=None,
dtype=numpy.float32,
initializer=None):
# type: (str, tp.Optional[types.ShapeSpec], types.DTypeSpec, tp.Optional[types.InitializerSpec]) -> None # NOQA
"""Registers a parameter to the link.
Args:
name (str): Name of the parameter. This name is also used as the
attribute name.
shape (int or tuple of ints): Shape of the parameter array. If it
is omitted, the parameter variable is left uninitialized.
dtype: Data type of the parameter array.
initializer: If it is not ``None``, the data is initialized with
the given initializer. If it is an array, the data is directly
initialized by it. If it is callable, it is used as a weight
initializer. Note that in these cases, ``dtype`` argument is
ignored.
"""
if name in self.__dict__:
raise AttributeError(
'cannot register a new parameter %s: attribute exists' % name)
if initializer is None:
initializer = initializers.NaN(dtype)
param = variable.Parameter(initializer, shape)
with self.init_scope():
setattr(self, name, param)
def test_addgrads(self):
l = chainer.Link()
with l.init_scope():
l.x = chainer.Parameter(shape=(2, 3),
initializer=initializers.NaN('d'))
l.y = chainer.Parameter(shape=2)
l.u = chainer.Parameter(shape=(2, 3))
l.v = chainer.Parameter()
l.x.grad.fill(1)
l.y.grad.fill(2)
l.u.grad.fill(3)
self.link.x.grad.fill(-1)
self.link.y.grad.fill(-2)
self.link.u.cleargrad()
self.link.addgrads(l)
gx_expect = numpy.zeros_like(l.x.grad)
gy_expect = numpy.zeros_like(l.y.grad)
gu_expect = l.u.grad
numpy.testing.assert_array_equal(self.link.x.grad, gx_expect)
numpy.testing.assert_array_equal(self.link.y.grad, gy_expect)
numpy.testing.assert_array_equal(self.link.u.grad, gu_expect)
self.assertIsNone(self.link.v.grad, None)
def add_param(self,
name,
shape=None,
dtype=numpy.float32,
initializer=None):
"""Registers a parameter to the link.
.. deprecated:: v2.0.0
Assign a :class:`~chainer.Parameter` object directly to an
attribute within :meth:`~chainer.Link.init_scope` instead.
For example, the following code
.. code-block:: python
link.add_param('W', shape=(5, 3))
can be replaced by the following assignment.
.. code-block:: python
with link.init_scope():
link.W = chainer.Parameter(None, (5, 3))
The latter is easier for IDEs to keep track of the attribute's
type.
Args:
name (str): Name of the parameter. This name is also used as the
attribute name.
shape (int or tuple of ints): Shape of the parameter array. If it
is omitted, the parameter variable is left uninitialized.
dtype: Data type of the parameter array.
initializer: If it is not ``None``, the data is initialized with
the given initializer. If it is an array, the data is directly
initialized by it. If it is callable, it is used as a weight
initializer. Note that in these cases, ``dtype`` argument is
ignored.
"""
warnings.warn(
'''\
Parameter registeration via Link.__init__ and Link.add_param are deprecated.
Assign a Parameter object directly to an attribute within a \
"with Link.init_scope():" block instead.
''', DeprecationWarning)
if name in self.__dict__:
raise AttributeError(
'cannot register a new parameter %s: attribute exists' % name)
if initializer is None:
initializer = initializers.NaN(dtype)
param = variable.Parameter(initializer, shape)
with self.init_scope():
setattr(self, name, param)
