<gh_stars>10-100

from Utils import eval_numerical_gradient

x = np.linspace(-1,1,10*32).reshape([10,32])
l = ReLU()
grads = l.backward(x,np.ones([10,32])/(32*10))
numeric_grads = eval_numerical_gradient(lambda x: l.forward(x).mean(), x=x)
assert np.allclose(grads, numeric_grads, rtol=1e-3, atol=0),\
    "error"

