tf.compat.v1.losses.get_total_loss
Returns a tensor whose value represents the total loss.
tf.compat.v1.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. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/compat/v1/losses/get_total_loss