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### `tf.clip_by_norm(t, clip_norm, name=None)` {#clip_by_norm}
Clips tensor values to a maximum L2-norm.
Given a tensor `t`, and a maximum clip value `clip_norm`, this operation
normalizes `t` so that its L2-norm is less than or equal to `clip_norm`.
Specifically, if the L2-norm is already less than or equal to `clip_norm`,
then `t` is not modified. If the 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(t)`
In this case, the L2-norm of the output tensor is `clip_norm`.
This operation is typically used to clip gradients before applying them with
an optimizer.
##### Args:
* <b>`t`</b>: A `Tensor`.
* <b>`clip_norm`</b>: A 0-D (scalar) `Tensor` > 0. A maximum clipping value.
* <b>`name`</b>: A name for the operation (optional).
##### Returns:
A clipped `Tensor`.
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