def test_lincg_fletcher(): rval = lincg.linear_cg_fletcher_reeves(lambda x: [T.dot(symb['L'], x)], [symb['g']], rtol=1e-20, damp=0., maxiter=10000, floatX=floatX, profile=0) f = theano.function([symb['L'], symb['g']], rval[0]) t1 = time.time() Linv_g = f(vals['L'], vals['g']) print 'test_lincg runtime (s):', time.time() - t1 numpy.testing.assert_almost_equal(Linv_g, vals['Linv_g'], decimal=3)
def test_lincg_fletcher(): rval = lincg.linear_cg_fletcher_reeves( lambda x: [T.dot(symb['L'], x)], [symb['g']], rtol=1e-20, damp = 0., maxiter = 10000, floatX = floatX, profile=0) f = theano.function([symb['L'], symb['g']], rval[0]) t1 = time.time() Linv_g = f(vals['L'], vals['g']) print 'test_lincg runtime (s):', time.time() - t1 numpy.testing.assert_almost_equal(Linv_g, vals['Linv_g'], decimal=3)
def test_lincg_fletcher_xinit(): symb['xinit'] = T.vector('xinit') vals['xinit'] = rng.rand(nparams).astype(floatX) rval = lincg.linear_cg_fletcher_reeves(lambda x: [T.dot(symb['L'], x)], [symb['g']], rtol=1e-20, damp=0., maxiter=10000, floatX=floatX, xinit=[symb['xinit']], profile=0) f = theano.function([symb['L'], symb['g'], symb['xinit']], rval[0]) t1 = time.time() Linv_g = f(vals['L'], vals['g'], vals['xinit']) print 'test_lincg runtime (s):', time.time() - t1 numpy.testing.assert_almost_equal(Linv_g, vals['Linv_g'], decimal=3)
def test_lincg_fletcher_xinit(): symb['xinit'] = T.vector('xinit') vals['xinit'] = rng.rand(nparams).astype(floatX) rval = lincg.linear_cg_fletcher_reeves( lambda x: [T.dot(symb['L'], x)], [symb['g']], rtol=1e-20, damp = 0., maxiter = 10000, floatX = floatX, xinit = [symb['xinit']], profile=0) f = theano.function([symb['L'], symb['g'], symb['xinit']], rval[0]) t1 = time.time() Linv_g = f(vals['L'], vals['g'], vals['xinit']) print 'test_lincg runtime (s):', time.time() - t1 numpy.testing.assert_almost_equal(Linv_g, vals['Linv_g'], decimal=3)