摘要：
import torch x_data = torch.tensor([[1.0], [2.0], [3.0]]) y_data = torch.tensor([[0.], [0.], [1.]]) class LogisticRessionModel(torch.nn.Module): def _ 阅读全文
摘要：
import torch # x, y是矩阵，3行1列，也就是说总共有3个数据，每个数据只有1个特征 x_data = torch.tensor([[1.0], [2.0], [3.0]]) y_data = torch.tensor([[2.0], [4.0], [6.0]]) # design 阅读全文
摘要：
# 小试牛刀 # import torch # a = torch.tensor([1.0]) # a.requires_grad = True # 或者 a.requires_grad_() # print(a) # tensor([1.], requires_grad=True) # print 阅读全文
摘要：
import matplotlib.pylab as plt x_data = [1.0, 2.0, 3.0] y_data = [2.0, 4.0, 6.0] w = 1.0 def forward(x): return x * w def cost(xs, ys): cost = 0 for x 阅读全文
摘要：
import numpy as np import matplotlib.pyplot as plt x_data = [1.0, 2.0, 4.0] y_data = [2.0, 4.0, 8.0] def forward(x): return x * w def loss(x_val, y_va 阅读全文