check_floatX, upcast_int8_nfunc,
_good_broadcast_unary_normal_no_complex)
class T_sigmoid(unittest.TestCase):
def setUp(self):
utt.seed_rng()
def test_elemwise(self):
utt.verify_grad(sigmoid, [numpy.random.rand(3, 4)])
SigmoidTester = makeBroadcastTester(
op=sigmoid,
expected=upcast_int8_nfunc(lambda inputs: check_floatX(
inputs, 1 / (1 + numpy.exp(-inputs)))),
good=_good_broadcast_unary_normal_no_complex,
# grad=_grad_broadcast_unary_normal,
name='SigmoidTester',
)
UltraFastSigmoidTester = makeBroadcastTester(
op=ultra_fast_sigmoid,
expected=upcast_int8_nfunc(lambda inputs: check_floatX(
inputs, 1 / (1 + numpy.exp(-inputs)))),
good=_good_broadcast_unary_normal_no_complex,
# grad=_grad_broadcast_unary_normal,
name='UltraFastSigmoidTester',
# This is an approx of the sigmoid. That is why we raise eps
eps=5e-2)
HardSigmoidTester = makeBroadcastTester(
_good_broadcast_unary_normal_no_complex)
class T_sigmoid(unittest.TestCase):
def setUp(self):
utt.seed_rng()
def test_elemwise(self):
utt.verify_grad(sigmoid, [np.random.rand(3, 4)])
SigmoidTester = makeBroadcastTester(
op=sigmoid,
expected=upcast_int8_nfunc(lambda inputs: check_floatX(
inputs, 1 / (1 + np.exp(-inputs)))),
good=copymod(_good_broadcast_unary_normal_no_complex,
without=['uint16']), # The reason that 'uint16' is excluted is that
# theano works well but numpy overflows resulting
# in an assertion error.
# grad=_grad_broadcast_unary_normal,
name='SigmoidTester',
)
UltraFastSigmoidTester = makeBroadcastTester(
op=ultra_fast_sigmoid,
expected=upcast_int8_nfunc(lambda inputs: check_floatX(
inputs, 1 / (1 + np.exp(-inputs)))),
good=copymod(_good_broadcast_unary_normal_no_complex,
without=['uint16']), # numpy fucnting overflows with uint16.
# grad=_grad_broadcast_unary_normal,
name='UltraFastSigmoidTester',
# This is an approx of the sigmoid. That is why we raise eps
from theano.tensor.tests.test_basic import (
expected_chi2sf, _good_broadcast_unary_chi2sf,
makeBroadcastTester, mode_no_scipy, skip_scipy)
from theano_lgpl.elemwise_c import cchi2sf
CChi2SFTester = makeBroadcastTester(
op=cchi2sf,
expected=expected_chi2sf,
good=_good_broadcast_unary_chi2sf,
eps=2e-10,
mode=mode_no_scipy,
skip=skip_scipy,
name='CChi2SFTester',
check_name=False)
_good_broadcast_unary_normal_no_complex,
)
class T_sigmoid(unittest.TestCase):
def setUp(self):
utt.seed_rng()
def test_elemwise(self):
utt.verify_grad(sigmoid, [numpy.random.rand(3, 4)])
SigmoidTester = makeBroadcastTester(
op=sigmoid,
expected=lambda inputs: check_floatX(inputs, 1 / (1 + numpy.exp(-inputs))),
good=_good_broadcast_unary_normal_no_complex,
# grad=_grad_broadcast_unary_normal,
name="SigmoidTester",
)
UltraFastSigmoidTester = makeBroadcastTester(
op=ultra_fast_sigmoid,
expected=lambda inputs: check_floatX(inputs, 1 / (1 + numpy.exp(-inputs))),
good=_good_broadcast_unary_normal_no_complex,
# grad=_grad_broadcast_unary_normal,
name="UltraFastSigmoidTester",
# This is an approx of the sigmoid. That is why we raise eps
eps=5e-2,
)
HardSigmoidTester = makeBroadcastTester(
makeBroadcastTester, rand, check_floatX, upcast_int8_nfunc,
_good_broadcast_unary_normal_no_complex)
class T_sigmoid(unittest.TestCase):
def setUp(self):
utt.seed_rng()
def test_elemwise(self):
utt.verify_grad(sigmoid, [numpy.random.rand(3, 4)])
SigmoidTester = makeBroadcastTester(
op=sigmoid,
expected=upcast_int8_nfunc(
lambda inputs: check_floatX(inputs, 1 / (1 + numpy.exp(-inputs)))),
good=_good_broadcast_unary_normal_no_complex,
# grad=_grad_broadcast_unary_normal,
name='SigmoidTester',
)
UltraFastSigmoidTester = makeBroadcastTester(
op=ultra_fast_sigmoid,
expected=upcast_int8_nfunc(
lambda inputs: check_floatX(inputs, 1 / (1 + numpy.exp(-inputs)))),
good=_good_broadcast_unary_normal_no_complex,
# grad=_grad_broadcast_unary_normal,
name='UltraFastSigmoidTester',
# This is an approx of the sigmoid. That is why we raise eps
eps=5e-2)
HardSigmoidTester = makeBroadcastTester(