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(