tf.clip_by_average_norm(t, clip_norm, name=None)

tf.clip_by_average_norm(t, clip_norm, name=None)

See the guide: Training > Gradient Clipping

Clips tensor values to a maximum average L2-norm.

Given a tensor t, and a maximum clip value clip_norm, this operation normalizes t so that its average L2-norm is less than or equal to clip_norm. Specifically, if the average L2-norm is already less than or equal to clip_norm, then t is not modified. If the average L2-norm is greater than clip_norm, then this operation returns a tensor of the same type and shape as t with its values set to:

t * clip_norm / l2norm_avg(t)

In this case, the average L2-norm of the output tensor is clip_norm.

This operation is typically used to clip gradients before applying them with an optimizer.

Args:

• t: A Tensor.
• clip_norm: A 0-D (scalar) Tensor > 0. A maximum clipping value.
• name: A name for the operation (optional).

Returns:

A clipped Tensor.

Defined in tensorflow/python/ops/clip_ops.py.