common._cost_cod

All Samples(13) | Call(8) | Derive(0) | Import(5)

src/p/a/paddle-1.0.2/paddle/unstable/sgp_realDU.py paddle(Download)

import scipy as sp
import pylab
from common import _cost_rec, _cost_cod, _st, _replaceAtoms, _saveDict, sparsity
ra = sp.random

    E = full_out['rec_err'] + full_out['l1_pen_U'] + full_out['l1_pen_D'] + full_out['l2_pen']
    if pars['eta'] > 0:
        full_out['cod_err'] = _cost_cod(C, X, U, pars)
        E += full_out['cod_err']
    return E, full_out

            def _costC(Y):
                return _cost_cod(Y, X, U, pars)
            f = pars['eta']/(N*K)
            C, iters = _pgd(C, f*XUt.T, f*XXt, _costC, axis=1, bound=pars['Cbound'], verbose=pars['verbose'], rtol=pars['rtol'])
            timeC = time.time() - start

src/p/a/paddle-1.0.2/paddle/unstable/sgp_real.py paddle(Download)

import scipy as sp
import pylab
from common import _cost_rec, _cost_cod, _st, _replaceAtoms, _saveDict, sparsity
ra = sp.random

    E = full_out['rec_err'] + full_out['l1_pen'] + full_out['l2_pen']
    if pars['eta'] > 0:
        full_out['cod_err'] = _cost_cod(C, X, U, pars)
        E += full_out['cod_err']
    return E, full_out

            def _costC(Y):
                return _cost_cod(Y, X, U, pars)
            f = pars['eta']/(N*K)
            C, iters = _pgd(C, f*XUt.T, f*XXt, _costC, axis=1, bound=pars['Cbound'], verbose=pars['verbose'], rtol=pars['rtol'])
            timeC = time.time() - start

src/p/a/paddle-1.0.2/paddle/unstable/sgp.py paddle(Download)

import scipy as sp
import pylab
from common import _cost_rec, _cost_cod, _st, _replaceAtoms, _saveDict
ra = sp.random

    E = full_out['rec_err'] + full_out['l1_pen'] + full_out['l2_pen']
    if pars['eta'] > 0:
        full_out['cod_err'] = _cost_cod(C, X, U, pars)
        E += full_out['cod_err']
    return E, full_out

            def _costC(Y):
                return _cost_cod(Y, X, U, pars)
            f = pars['eta']/(N*K)
            C, iters = _pgd(C, f*XUt.T, f*XXt, _costC, axis=1, bound=pars['Cbound'], verbose=pars['verbose'], rtol=pars['rtol'])
            timeC = time.time() - start

src/p/a/paddle-1.0.2/paddle/dual.py paddle(Download)

import scipy as sp
import pylab
from common import _cost_rec, _cost_cod, _replaceAtoms, _saveDict
from prox import _st
ra = sp.random

    E = full_out['rec_err'] + full_out['l1_pen'] + full_out['l2_pen']
    if pars['eta'] > 0:
        full_out['cod_err'] = _cost_cod(C, X, U, pars)
        E += full_out['cod_err']
    return E, full_out

            def _costC(Y):
                return _cost_cod(Y, X, U, pars)
            f = pars['eta']/(N*K)
            C, iters = _pgd(C, f*XUt.T, f*XXt, _costC, axis=1, bound=pars['Cbound'], verbose=pars['verbose'], rtol=pars['rtol'])
            timeC = time.time() - start

src/p/a/paddle-1.0.2/paddle/unstable/dual_l1.py paddle(Download)

import scipy as sp
import pylab
from common import _cost_rec, _cost_cod, _replaceAtoms, _saveDict, sparsity
import prox
ra = sp.random