Pytorch 04 激活函数

ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.spines['bottom'].set_position(('data', 0))
ax.yaxis.set_ticks_position('left')
ax.spines['left'].set_position(('data', 0))
plt.ylim((0, 1))
sigmod=torch.sigmoid(x)
plt.plot(x.numpy(),sigmod.numpy())
plt.show()

 

 

ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.spines['bottom'].set_position(('data', 0))
ax.yaxis.set_ticks_position('left')
ax.spines['left'].set_position(('data', 0))
plt.ylim((-1, 1))
tanh=torch.tanh(x)
plt.plot(x.numpy(),tanh.numpy())
plt.show()

 

 

ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.spines['bottom'].set_position(('data', 0))
ax.yaxis.set_ticks_position('left')
ax.spines['left'].set_position(('data', 0))
plt.ylim((-3, 10))
relu=F.relu(x)
plt.plot(x.numpy(),relu.numpy())
plt.show()

 

为了解决relu函数z<0时的问题出现了 Leaky ReLU函数，该函数保证在z<0的时候，梯度仍然不为0。 ReLU的前半段设为αz而非0，通常α=0.01

Leaky Relu

ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.spines['bottom'].set_position(('data', 0))
ax.yaxis.set_ticks_position('left')
ax.spines['left'].set_position(('data', 0))
plt.ylim((-3, 10))
l_relu=F.leaky_relu(x,0.01)     # 0.01或比其更小的值
plt.plot(x.numpy(),l_relu.numpy())
plt.show()