def _forward(self,
arguments,
outputs,
device=None,
outputs_to_retain=None):
'''
Computes the values of speficied variables in ``outputs``, using values
provided in ``arguments`` that correspond to each input `Variable` of
the function whose ``is_input`` is `True`.
This function calls :func:`forward`, which is to be implemented by the
user.
Args:
arguments (tuple): Value objects of the Function's input
outputs (iterable): outputs to fetch values for.
device (:class:`~cntk.device.DeviceDescriptor`, default `None`): the device
descriptor that contains the type and id of the device on which the
computation is. If `None`, the default device is used.
Returns:
A BackPropState instance, which is used by :func:`backward`.
'''
if self.as_numpy:
arguments = tuple(
variable_value_to_seq(v, self.inputs[i])
for i, v in enumerate(arguments))
map_if_possible(outputs)
map_if_possible(outputs_to_retain)
args = arguments if len(arguments) > 1 else arguments[0]
if len(outputs) <= 1:
state, result = self.forward(args, device, outputs_to_retain)
for k in outputs:
outputs[k] = result
else:
state = self.forward(args, outputs, device, outputs_to_retain)
if state is None:
state = self._none_state
elif not isinstance(state, cntk_py.BackPropState):
state = cntk_py.UserBackPropState(self, device, state)
if self.as_numpy:
for k, v in outputs.items():
if v is None:
raise ValueError('not all outputs have been provided')
# FIXME: seq_starts
outputs[k] = sanitize_batch(k, v, None, device)
return state, outputs
def __init__(self, inputs, as_numpy=True, name=''):
super(UserFunction, self).__init__(inputs, name)
self.as_numpy = as_numpy
# Since the state will frequently not be used, we cache the None-state
# to speed up.
self._none_state = cntk_py.UserBackPropState(
self, DeviceDescriptor.cpu_device(), None)
# Memory management for user defined functions has to be controlled by
# the C++ side. For more information:
# http://www.swig.org/Doc3.0/Python.html#Python_nn35
self.__disown__()
