renorm¶

paddle. renorm ( x, p, axis, max_norm ) [source]

renorm

This operator is used to calculate the p-norm along the axis, suppose the input-shape on axis dimension has the value of T, then the tensor is split into T parts, the p-norm should be calculated for each part, if the p-norm for part i is larger than max-norm, then each element in part i should be re-normalized at the same scale so that part-i’ p-norm equals max-norm exactly, otherwise part-i stays unchanged.

Parameters

x (Tensor) – The input Tensor
p (float) – The power of the norm operation.
axis (int) – the dimension to slice the tensor.
max-norm (float) – the maximal norm limit.

Returns

the renorm Tensor.

Return type

Tensor

Examples

           >>> import paddle
>>> input = [[[2.0, 2, -2], [3, 0.3, 3]],
...          [[2, -8, 2],   [3.1, 3.7, 3]]]
>>> x = paddle.to_tensor(input,dtype='float32')
>>> y = paddle.renorm(x, 1.0, 2, 2.05)
>>> print(y)
Tensor(shape=[2, 2, 3], dtype=float32, place=Place(cpu), stop_gradient=True,
[[[ 0.40594056,  0.29285714, -0.41000000],
  [ 0.60891086,  0.04392857,  0.61500001]],
 [[ 0.40594056, -1.17142856,  0.41000000],
  [ 0.62920785,  0.54178572,  0.61500001]]])

          