impelement dpnp.norm

[vtavana]

In this PR, dpnp.norm is updated using existing functions in dpnp.

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• Have you added a test, reproducer or referred to issue with a reproducer?
• Have you tested your changes locally for CPU and GPU devices?
• Have you made sure that new changes do not introduce compiler warnings?
• Have you checked performance impact of proposed changes?
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[github-actions]

View rendered docs @ https://intelpython.github.io/dpnp/pull//index.html

[vtavana]

timing case 1: output is scalar
Poor performance on cpu for floating point data types is known and related to dpnp.dot function.

import dpctl,dpctl.tensor as dpt, numpy, dpnp
import numpy.random as default_rng
npoints = 10**8
dims = 3
x = default_rng.random((npoints, dims))
dtype = "i4"
x = numpy.array(x, dtype=dtype)
device="gpu"
x_dp = dpnp.array(x, device=device)

%timeit numpy.linalg.norm(x)

%timeit dpnp.linalg.norm(x_dp)

device="cpu"
x_dp = dpnp.array(x, device=device)
%timeit dpnp.linalg.norm(x_dp)

[vtavana]

timing case 2: output is a vector

import dpctl,dpctl.tensor as dpt, numpy, dpnp
import numpy.random as default_rng
npoints = 10**8
dims = 3
x = default_rng.random((npoints, dims))
dtype = "i4"
x = numpy.array(x, dtype=dtype)
device="gpu"
x_dp = dpnp.array(x, device=device)

%timeit numpy.linalg.norm(x, axis=1)

%timeit dpnp.linalg.norm(x_dp, axis=1)

device="cpu"
x_dp = dpnp.array(x, device=device)
%timeit dpnp.linalg.norm(x_dp, axis=1)

[antonwolfy]

Thank you @vtavana