标签:nump fun pre data var ima info strong sof
import torch
import torch.nn.functional as F # 神经网络的模块
from torch.autograd import Variable # 神经网络的节点
import matplotlib.pyplot as plt
# fake data
x = torch.linspace(-5,5,200)
x = Variable(x)
x_np = x.data.numpy() # x.data. 转化为torch类型的
# y_rule = F.relu(x).data.numpy()
y_relu = F.relu(x).data.numpy()
# y_sigmoid = F.sigmoid(x).data.numpy()
y_sigmoid = torch.sigmoid(x).data.numpy()
y_tanh = torch.tanh(x).data.numpy()
y_softplus = F.softplus(x).data.numpy()
画图
plt.figure(1, figsize=(8, 6))
plt.subplot(221)
plt.plot(x_np, y_relu, c='red', label='relu')
plt.ylim((-1, 5))
plt.legend(loc='best')
plt.subplot(222)
plt.plot(x_np, y_sigmoid, c='red', label='sigmoid')
plt.ylim((-0.2, 1.2))
plt.legend(loc='best')
plt.subplot(223)
plt.plot(x_np, y_tanh, c='red', label='tanh')
plt.ylim((-1.2, 1.2))
plt.legend(loc='best')
plt.subplot(224)
plt.plot(x_np, y_softplus, c='red', label='softplus')
plt.ylim((-0.2, 6))
plt.legend(loc='best')
plt.show()
标签:nump fun pre data var ima info strong sof
原文地址:https://www.cnblogs.com/liu247/p/11145525.html