def init_weight(weights, initializer, scale=1.0):
"""Helper function for initialization of the weight tensor.
This function accepts several types of initializer, prepares
the appropriate ``~chainer.Initializer`` if necessary,
and does the initialization.
Args:
weights (numpy.ndarray or cupy.ndarray):
Weight tensor to be initialized.
initializer: The value used to initialize the data.
May be ``None`` (in which case
:class:`~chainer.initializers.HeNormal`
is used as an initializer), a scalar to set all values to,
an ``numpy.ndarray`` to be assigned,
or a callable that takes :class:`numpy.ndarray`
or :class:`cupy.ndarray` and edits its value.
scale (scalar): A constant to multiply initializer by.
"""
if initializer is None:
initializer = HeNormal(1 / numpy.sqrt(2))
elif numpy.isscalar(initializer):
initializer = Constant(initializer)
elif isinstance(initializer, numpy.ndarray):
initializer = Constant(initializer)
assert callable(initializer)
initializer(weights)
weights *= scale
def init_weight(weights, initializer, scale=1.0):
"""Helper function for initialization of the weight tensor.
This function accepts several types of initializer, prepares
the appropriate ``~chainer.Initializer`` if necessary,
and does the initialization.
Args:
weights (numpy.ndarray or cupy.ndarray):
Weight tensor to be initialized.
initializer: The value used to initialize the data.
May be ``None`` (in which case
:class:`~chainer.initializers.HeNormal`
is used as an initializer), a scalar to set all values to,
an ``numpy.ndarray`` to be assigned,
or a callable that takes :class:`numpy.ndarray`
or :class:`cupy.ndarray` and edits its value.
scale (scalar): A constant to multiply initializer by.
"""
if initializer is None:
initializer = HeNormal(1 / numpy.sqrt(2))
elif numpy.isscalar(initializer):
initializer = Constant(initializer)
elif isinstance(initializer, numpy.ndarray):
initializer = Constant(initializer)
assert callable(initializer)
initializer(weights)
weights *= scale
def generate_array(initializer, shape, xp):
"""Return initialized array.
The algorithms used to make the new values depend on the
concrete derived classes. The dtype of a generated array depends on
``initializer.dtype``.
Args:
initializer: A callable object that takes :class:`numpy.ndarray`
or :class:`cupy.ndarray` and edits its value.
shape (tuple): Shape of a return array.
xp (module): :mod:`cupy` or :mod:`numpy`.
Returns:
numpy.ndarray or cupy.ndarray: An initialized array.
"""
dtype = numpy.float32
if hasattr(initializer, 'dtype') and initializer.dtype is not None:
dtype = initializer.dtype
array = xp.empty(shape, dtype=dtype)
initializer(array)
return array
def generate_array(initializer, shape, xp):
"""Return initialized array.
The algorithms used to make the new values depend on the
concrete derived classes. The dtype of a generated array depends on
``initializer.dtype``.
Args:
initializer: A callable object that takes :class:`numpy.ndarray`
or :class:`cupy.ndarray` and edits its value.
shape (tuple): Shape of a return array.
xp (module): :mod:`cupy` or :mod:`numpy`.
Returns:
numpy.ndarray or cupy.ndarray: An initialized array.
"""
dtype = numpy.float32
if hasattr(initializer, 'dtype') and initializer.dtype is not None:
dtype = initializer.dtype
array = xp.empty(shape, dtype=dtype)
initializer(array)
return array
