def test_erf() -> None:
try:
from scipy.special import erf as scipy_erf
except:
pytest.skip("scipy not installed skipping test for erf")
x = np.array([-1000, -100, -10] + np.linspace(-5, 5, 1001).tolist() +
[10, 100, 1000])
y_scipy = scipy_erf(x)
# Test mx.nd
y_mxnet = util.erf(mx.nd, mx.nd.array(x)).asnumpy()
assert np.allclose(y_mxnet, y_scipy, rtol=1e-3)
# Test mx.sym
X = mx.symbol.Variable("x")
func = util.erf(mx.sym, X)
func_exec = func.bind(ctx=mx.cpu(), args={"x": mx.nd.array(x)})
func_exec.forward()
y_mxnet_sym = func_exec.outputs[0].asnumpy()
assert np.allclose(y_mxnet_sym, y_scipy, rtol=1e-3)
# Text np
y_np = util.erf(np, x)
assert np.allclose(y_np, y_scipy, atol=1e-7)
def test_erf() -> None:
try:
from scipy.special import erf as scipy_erf
except:
pytest.skip("scipy not installed skipping test for erf")
x = np.array([-1000, -100, -10] + np.linspace(-5, 5, 1001).tolist() +
[10, 100, 1000])
y_mxnet = util.erf(mx.nd, mx.nd.array(x)).asnumpy()
y_scipy = scipy_erf(x)
assert np.allclose(y_mxnet, y_scipy)
def test_erf() -> None:
try:
from scipy.special import erf as scipy_erf
except:
pytest.skip("scipy not installed skipping test for erf")
x = np.array([-1000, -100, -10] + np.linspace(-5, 5, 1001).tolist() +
[10, 100, 1000])
y_scipy = scipy_erf(x)
# Text np
y_np = erf(x)
assert np.allclose(y_np, y_scipy, atol=1e-7)
def standard_gaussian_cdf(x: np.array) -> np.array:
u = x / (np.sqrt(2.0))
return (erf(u) + 1.0) / 2.0
def cdf(self, x):
F = self.F
u = self.F.broadcast_div(self.F.broadcast_minus(x, self.mu),
self.sigma * math.sqrt(2.0))
return (erf(F, u) + 1.0) / 2.0
