理解火把预言

对于我的训练模型,此代码:

model(x[0].reshape(1,784).cuda())

返回:

tensor([[-1.9903, -4.0458, -4.1143, -4.0074, -3.5510,  7.1074]], device='cuda:0')

我的网络模型定义为:

# Hyper-parameters 
input_size = 784
hidden_size = 50
num_classes = 6
num_epochs = 5000
batch_size = 1
learning_rate = 0.0001

    criterion = nn.CrossEntropyLoss()
    optimizer = torch.optim.Adam(model.parameters(), lr=learning_rate)  

        class NeuralNet(nn.Module):
            def __init__(self, input_size, hidden_size, num_classes):
                super(NeuralNet, self).__init__()
                self.fc1 = nn.Linear(input_size, hidden_size) 
                self.relu = nn.ReLU()
                self.fc2 = nn.Linear(hidden_size, num_classes)  

            def forward(self, x):
                out = self.fc1(x)
                out = self.relu(out)
                out = self.fc2(out)
                return out

我试图理解返回值:

张量([[-1.9903,-4.0458,-4.1143,-4.0074,-3.5510,7.1074]],设备='cuda:0')

值7.1074是张量数组中最大值的可能性吗?由于7.1074位于位置5,因此此处预测输入x[0]的相关输出值是否为5?如果是这样,这背后的直觉是什么?