MXNetLearning/ActivationFunctions.py at master · yauyimsing/MXNetLearning · GitHub

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import d2lzh as d2l
from mxnet import autograd, nd


def xyplot(x_vals, y_vals, name):
    d2l.set_figsize(figsize=(5, 2.5))
    d2l.plt.plot(x_vals.asnumpy(), y_vals.asnumpy())
    d2l.plt.xlabel('x')
    d2l.plt.ylabel(name+'(x)')


def ReLuMethod():
    x = nd.arange(-8.0, 8.0, 0.1)
    x.attach_grad()
    with autograd.record():
        y = x.relu()
    xyplot(x, y, 'relu')
    y.backward()
    xyplot(x, x.grad, 'grad of relu')

def SigmoidMethod():
    x = nd.arange(-8.0, 8.0, 0.1)
    x.attach_grad()
    with autograd.record():
        y = x.sigmoid()
    xyplot(x, y, 'sigmoid')
    y.backward()
    xyplot(x, x.grad, 'grad of sigmoid')


def TanhMethod():
    x = nd.arange(-8.0, 8.0, 0.1)
    x.attach_grad()
    with autograd.record():
        y = x.tanh()
    xyplot(x, y, 'tanh')
    y.backward()
    xyplot(x, x.grad, 'grad of tanh')


def main():
    #ReLuMethod()
    #SigmoidMethod()
    TanhMethod()

if __name__ == '__main__':
    main()