def test_sigmoid():
'''
Test using a numerically stable reference sigmoid implementation
'''
def ref_sigmoid(x):
if x >= 0:
return 1 / (1 + np.exp(-x))
else:
z = np.exp(x)
return z / (1 + z)
sigmoid = np.vectorize(ref_sigmoid)
x = K.placeholder(ndim=2)
f = K.function([x], [activations.sigmoid(x)])
test_values = get_standard_values()
result = f([test_values])[0]
expected = sigmoid(test_values)
assert_allclose(result, expected, rtol=1e-05)
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