tf.losses.get_total_loss

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Returns a tensor whose value represents the total loss.

Aliases:

• tf.compat.v1.losses.get_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.