python for循环之外的程序被放进循环里执行了？

一开始我只print那个名为loss_axis的list结果发现它先print出来许多空[]（我对loss_axis的定义就是空list），最后才print出来了完整的loss_axis。为什么会这样

附上完整的代码

import torch
from torch.utils.data import Dataset, DataLoader
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation

filepath = 'c:\\Users\\dell\\Desktop\\code\\diabetes.csv'
epoch_len = 5
count = 0
loss_axis = []

class DiabetesDataset(Dataset):
    def __init__(self, filepath):
        xy = np.loadtxt(filepath, delimiter = ',', dtype = np.float32)
        self.len = xy.shape[0]
        self.x_data = torch.from_numpy(xy[:, :-1])
        self.y_data = torch.from_numpy(xy[:, [-1]])

    def __getitem__(self, index):
        return self.x_data[index], self.y_data[index]

    def __len__(self):
        return self.len

dataset = DiabetesDataset('diabetes.csv')
train_loader = DataLoader(dataset = dataset, batch_size = 32, shuffle = True, num_workers = 2)

class Model(torch.nn.Module):
    def __init__(self):
        super(Model ,self).__init__()
        self.linear1 = torch.nn.Linear(8, 6)
        self.linear2 = torch.nn.Linear(6, 4)
        self.linear3 = torch.nn.Linear(4, 1)
        self.sigmoid = torch.nn.Sigmoid()

    def forward(self, x):
        x = self.sigmoid(self.linear1(x))
        x = self.sigmoid(self.linear2(x))
        x = self.sigmoid(self.linear3(x))
        return x

model = Model()

criterion = torch.nn.BCELoss(reduction = 'mean')
optimizer = torch.optim.SGD(model.parameters(), lr = 0.01)

if __name__ == '__main__':
    for epoch in range(epoch_len):
        for i, data in enumerate(train_loader, 0):
            count = count + 1
            #prepare data
            inputs, labels = data
            #forward
            y_pred = model(inputs)
            loss = criterion(y_pred, labels)
            loss_axis.append(loss.item())
            #print(epoch, i, loss.item())
            #backward
            optimizer.zero_grad()
            loss.backward()
            #update
            optimizer.step()


print(loss_axis)
print("1")
# epoch_axis = np.linspace(1, epoch_len, count)
# plt.figure(num = 'loss', figsize = (8, 5))
# plt.plot(epoch_axis, loss_axis, color = 'red')
# plt.xlim((0, epoch_len))
# # plt.ylim((0, loss_axis[0]))
# plt.xlabel('epoch')
# plt.ylabel('loss')
# plt.grid()
# plt.show()

lose.item()本身就是列表吧，所以你打印的是列表

看不出来问题在哪。不过看着程序，好像不连贯啊。能把完整程序发出来么。

。