Source code for cr.sparse._src.opt.smooth.huber

# Copyright 2021 CR-Suite Development Team
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from jax import jit, grad, lax

import jax.numpy as jnp
import cr.nimble as cnb

from .smooth import build2

[docs]def smooth_huber(tau=1.): r"""Huber penalty function and its gradient """ tau = jnp.asarray(tau) tau = cnb.promote_arg_dtypes(tau) @jit def func(x): x = jnp.asarray(x) x = cnb.promote_arg_dtypes(x) x_mag = jnp.abs(x) small = x_mag <= tau x_small = 0.5*(x_mag**2)/tau x_large = x_mag - tau/2 v = jnp.where(small, x_small, x_large) return sum(v) @jit def gradient(x): x = jnp.asarray(x) x = cnb.promote_arg_dtypes(x) g = x/jnp.maximum(tau, jnp.abs(x) ) return g return build2(func, gradient)