def test_dtanh_matrix():
tensor_shape = [random.randint(1, 10) for _ in range(2)]
helpers.check_gradient(lambda X: calculate.tanh(X),
lambda X: calculate.dtanh(calculate.tanh(X)),
f_arg_tensor=numpy.random.random(tensor_shape),
f_shape='lin')
def test_dtanh():
helpers.check_gradient(calculate.tanh,
lambda x: calculate.dtanh(calculate.tanh(x)),
f_shape='lin')
def test_tanh():
assert helpers.approx_equal(
calculate.tanh(numpy.array([-1.0, 0.0, 0.5, 1.0])),
[-0.761594, 0.0, 0.462117, 0.761594])
def __call__(self, input_vec):
return calculate.tanh(input_vec)