로지스틱회귀_클래스로파이토치

import torch import torch.nn as nn import torch.nn.functional as F import torch.optim as optim torch.manual_seed(1) x_data = [[1, 2], [2, 3], [3, 1], [4, 3], [5, 3], [6, 2]] y_data = [[0], [0], [0], [1], [1], [1]] x_train = torch.FloatTensor(x_data) y_train = torch.FloatTensor(y_data) class BinaryClassifier(nn.Module): def __init__(self): super().__init__() self.linear = nn.Linear(2, 1) self.sigmoid = nn.Sigmoid() def forward(self, x): return self.sigmoid(self.linear(x)) model = BinaryClassifier...