Returns a tensor whose value represents the total loss.
tf.losses.get_total_loss(
add_regularization_losses=True, name='total_loss', scope=None
)
In particular, this adds any losses you have added with tf.add_loss() to
any regularization losses that have been added by regularization parameters
on layers constructors e.g. tf.layers. Be very sure to use this if you
are constructing a loss_op manually. Otherwise regularization arguments
on tf.layers methods will not function.
Args |
|---|
add_regularization_losses
|
A boolean indicating whether or not to use the
regularization losses in the sum.
|
name
|
The name of the returned tensor.
|
scope
|
An optional scope name for filtering the losses to return. Note that
this filters the losses added with tf.add_loss() as well as the
regularization losses to that scope.
|
Returns |
|---|
A Tensor whose value represents the total loss.
|
Raises |
|---|
ValueError
|
if losses is not iterable.
|
View source on GitHub