def __init__(self, shape=None, dtype=None, needs_gradient=False, is_sparse=False,
dynamic_axes=[cntk_py.Axis.default_dynamic_axis(), cntk_py.Axis.default_batch_axis()], name=''):
shape = utils.sanitize_shape(shape)
if dtype is None:
dtype = np.float32
dtype = utils.sanitize_dtype_cntk(dtype)
super(Variable, self).__init__(shape, is_sparse, dtype, needs_gradient, name,
dynamic_axes)
def __init__(self, value=None, shape=None, dtype=None, device=None, name=''):
if dtype is None:
if isinstance(value, np.ndarray):
dtype = value.dtype
else:
dtype = np.float32
if np.isscalar(value):
super(Constant, self).__init__(utils.sanitize_shape(shape), sanitize_dtype_cntk(dtype), value)
else:
ndav = sanitize_value(shape, value, dtype, device)
super(Constant, self).__init__(ndav, name)
def __init__(self, shape=None, init=None, data_type=None, device=None, name=""):
if data_type is None:
if not isinstance(init, np.ndarray):
data_type = FLOAT_32
else:
data_type = str(init.dtype)
if init is None:
init = 0
if isinstance(init, (np.ndarray, list, float, int)):
ndav = _sanitize_value(shape, init, data_type, device)
super(Parameter, self).__init__(ndav, name)
else:
shape = utils.sanitize_shape(shape)
data_type = utils.sanitize_dtype_cntk(data_type)
super(Parameter, self).__init__(shape, data_type, init, device, name)
def _sanitize_value(shape, value, dtype, device):
np_dtype = utils.sanitize_dtype_numpy(dtype)
cntk_dtype = utils.sanitize_dtype_cntk(dtype)
if value is None:
if shape is None:
raise ValueError("you need to specify at least shape or value")
shape = utils.sanitize_shape(shape)
ndav = utils.create_NDArrayView(shape, cntk_dtype, device)
else:
if not isinstance(value, np.ndarray) or value.dtype != np_dtype:
if np.isscalar(value) and shape:
value = np.full(shape, value, dtype=np_dtype)
else:
value = np.asarray(value, dtype=np_dtype)
ndav = utils.create_NDArrayView_from_NumPy(value, device)
return ndav
def __init__(self, shape=None, init=None, dtype=None,
device=None, name=''):
if dtype is None:
if isinstance(init, np.ndarray):
dtype = init.dtype
else:
dtype = np.float32
if init is None:
init = 0
if isinstance(init, (np.ndarray, list, float, int)):
ndav = sanitize_value(shape, init, dtype, device)
super(Parameter, self).__init__(ndav, name)
else:
shape = utils.sanitize_shape(shape)
cntk_dtype = utils.sanitize_dtype_cntk(dtype)
super(Parameter, self).__init__(shape, cntk_dtype, init,
device, name)
def __init__(self,
shape=None,
init=None,
data_type=None,
device=None,
name=''):
if data_type is None:
if not isinstance(init, np.ndarray):
data_type = FLOAT_32
else:
data_type = str(init.dtype)
if init is None:
init = 0
if isinstance(init, (np.ndarray, list, float, int)):
ndav = _sanitize_value(shape, init, data_type, device)
super(Parameter, self).__init__(ndav, name)
else:
shape = utils.sanitize_shape(shape)
data_type = utils.sanitize_dtype_cntk(data_type)
super(Parameter, self).__init__(shape, data_type, init, device,
name)
