def _get_loss_object(self, loss):
"""Returns a `Loss` object.
Converts the user-supplied loss to a `Loss` object. Also allows
`SUM_OVER_BATCH_SIZE` reduction to be used for this loss.
Arguments:
loss: A string, function, or `Loss` object.
Returns:
A `Loss` object.
"""
if loss is None:
return None # Ok to have no loss for an output.
loss = losses_mod.get(loss)
if not isinstance(loss, losses_mod.Loss):
loss = losses_mod.LossFunctionWrapper(loss, name=loss.__name__)
loss._allow_sum_over_batch_size = True # pylint: disable=protected-access
return loss
def _get_loss_object(self, loss):
"""Returns a `Loss` object.
Converts the user-supplied loss to a `Loss` object. Also allows
`SUM_OVER_BATCH_SIZE` reduction to be used for this loss.
Args:
loss: A string, function, or `Loss` object.
Returns:
A `Loss` object.
"""
if loss is None:
return None # Ok to have no loss for an output.
loss = losses_mod.get(loss)
if not isinstance(loss, losses_mod.Loss):
loss_name = get_custom_object_name(loss)
if loss_name is None:
raise ValueError('Loss should be a callable, found: {}'.format(loss))
loss = losses_mod.LossFunctionWrapper(loss, name=loss_name)
loss._allow_sum_over_batch_size = True # pylint: disable=protected-access
return loss
def _get_loss_object(self, loss):
"""Returns a `Loss` object.
Converts the user-supplied loss to a `Loss` object. Also allows
`SUM_OVER_BATCH_SIZE` reduction to be used for this loss.
Arguments:
loss: A string, function, or `Loss` object.
Returns:
A `Loss` object.
"""
if loss is None:
return None # Ok to have no loss for an output.
# TODO(omalleyt): Handle special casing for crossentropy.
loss = losses_mod.get(loss)
if not isinstance(loss, losses_mod.Loss):
loss = losses_mod.LossFunctionWrapper(loss)
# Allow AUTO and SUM_OVER_BATCH_SIZE reductions.
# TODO(omalleyt): Can we reconcile CTL and built-in loss reductions?
loss._allow_sum_over_batch_size = True # pylint: disable=protected-access
return loss
