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)
