Python3.10 报错 UnboundLocalError: local variablereferenced before assignment,原因和解决办法

原来 的环境 是 python 3.7  torch1.13.1 环境 下面跑通的代码  

    到 python 3.10 和torch 2.3.1报错

原因:

  1. 在函数内部更改全局变量就会出现此错误。
  2. 函数内部没有初始化
  3. 函数内部的循环内部没有初始化 (3.10)

报错UnboundLocalError: local variablereferenced before assignment

如果在函数内部的 一开始的地方初始化变量还是会报错的

解决   gradient_penalty = 0  要在循环的内部,初始化

改成

def train(iterations, batch_size):
    num_steps = 0
    # 每多少次 生成一个批评家(鉴别器)
    critic_iterations = 10
    # 每多少次 输出下 损失数值
    print_every = 30
    with tqdm(total=iterations * batch_size, desc='Training', ncols=70) as pbar:
        dlosses = []  # 存储判别器损失
        glosses = []  # 存储生成器损失
        for iteration in range(iterations):
            for _ in range(batch_size):
                # 增加步数计数
                num_steps += 1

                # 初始化 gradient_penalty
                # python 3.10
                gradient_penalty = 0

                # 2. 训练生成器
                # 生成新的假数据
                # 每 critic_iterations 次迭代更新一次生成器
                if num_steps % critic_iterations == 1:
                    noise = torch.randn(batch_size, input_dim, device=device)
                    fake_data = generator(noise)
                    if gradient_penalty != 0 :
                        # 生成器的损失
                        g_loss = gradient_penalty.data.item()
                        glosses.append(g_loss.item())
                        # 重置判别器优化器的梯度
                        optimizer_G.zero_grad()
                        g_loss.backward()
                        optimizer_G.step()

其他

===================================================

摘录自 https://blog.youkuaiyun.com/weixin_48419914/article/details/122008139 ================================================

例一(不会报错):
a= 3
def temp():
    print(a)
temp() #输出的结果为3
在上面一段代码中,函数temp的操作是打印a的值,但函数内部并没有对a进行定义,此时系统会在外部寻找a的值,而我们在函数外部给a赋值为3,这种在函数外部赋值的变量被称为全局变量(global variable),这种情况下运行函数temp不会出错,

例二(会报错):
a= 3
def temp():
    print(a)
    a+=1
temp() #会报错, UnboundLocalError: local variable 'a' referenced before assignment
原因是我们定义的函数temp内部第一次打印a是调用的全局变量,而打印后却令a=a+1,在函数内部试图更改全局变量a导致错误。

例三(改正例二):
如果我们确实希望通过函数temp打印全局变量a,并且将a的值加1,那么就要在函数内部声明全局变量。

a= 3
def temp():
    global a #声明我们在函数内部使用的是在函数外部定义的全局变量a
    print(a)
    a+=1
temp() 
调用temp函数,不会再报错了。此时就会发现a的值确实变成4

 
 

Traceback (most recent call last): File "/app/visualize.py", line 759, in run_visualization analysisfile = pd.read_csv( File "/usr/local/lib/python3.10/dist-packages/pandas/util/_decorators.py", line 311, in wrapper return func(*args, **kwargs) File "/usr/local/lib/python3.10/dist-packages/pandas/io/parsers/readers.py", line 680, in read_csv return _read(filepath_or_buffer, kwds) File "/usr/local/lib/python3.10/dist-packages/pandas/io/parsers/readers.py", line 575, in _read parser = TextFileReader(filepath_or_buffer, **kwds) File "/usr/local/lib/python3.10/dist-packages/pandas/io/parsers/readers.py", line 933, in __init__ self._engine = self._make_engine(f, self.engine) File "/usr/local/lib/python3.10/dist-packages/pandas/io/parsers/readers.py", line 1217, in _make_engine self.handles = get_handle( # type: ignore[call-overload] File "/usr/local/lib/python3.10/dist-packages/pandas/io/common.py", line 789, in get_handle handle = open( FileNotFoundError: [Errno 2] No such file or directory: &#39;/log_data/1.3.26-2132/stats_without_nalimov_outlier_1.3.26-2132.csv&#39; 2025-03-21 15:34:37,123:INFO:cumulative plot 2025-03-21 15:34:37,123:ERROR:cant generate histogram plots (no analysisfile due to no db entry or not enough data) Traceback (most recent call last): File "/app/visualize.py", line 835, in run_visualization return cumulative_plot(analysis_folder, image_folder, analysisfile) UnboundLocalError: local variable &#39;analysisfile&#39; referenced before assignment 2025-03-21 15:34:37,123:INFO:performed cyclic generation of outlier and statistic plots for 1.3.26-2132 Finished outlier calculation! 2025-03-21 15:34:37,123:INFO:Outlier calculation for 1.4.8-480.10.320+ETD 2025-03-21 15:34:37,123:INFO:Starting Cyclic Data Generation for 1.4.8-480.10.320+ETD Generating Outlier for 1.4.8-480.10.320+ETD 2025-03-21 15:34:37,123:INFO:fetching database entries.. 2025-03-21 15:34:37,124:INFO:Finding outliers and create log overview for all floors 2025-03-21 15:34:37,125:INFO:Analysis folder /log_data/1.4.8-480.10.320+ETD/filtered_logs/analyzed 2025-03-21 15:34:37,127:ERROR:Could not generate outlier for 1.4.8-480.10.320+ETD Traceback (most recent call last): File "/app/docker_outlier.py", line 63, in <module> generate_outlier_and_visualization(firmware) File "/app/docker_outlier.py", line 28, in generate_outlier_and_visualization outlier.outliergenerator(current_firmware) File "/app/outlier.py", line 840, in outliergenerator out.generate_outlier() File "/app/outlier.py", line 459, in generate_outlier self.allruns_printout(self.list_of_logs) # write csv of all runs File "/app/outlier.py", line 753, in allruns_printout alllogs_overview.to_csv(os.path.join( File "/usr/local/lib/python3.10/dist-packages/pandas/core/generic.py", line 3551, in to_csv return DataFrameRenderer(formatter).to_csv( File "/usr/local/lib/python3.10/dist-packages/pandas/io/formats/format.py", line 1180, in to_csv csv_formatter.save() File "/usr/local/lib/python3.10/dist-packages/pandas/io/formats/csvs.py", line 241, in save with get_handle( File "/usr/local/lib/python3.10/dist-packages/pandas/io/common.py", line 697, in get_handle check_parent_directory(str(handle)) File "/usr/local/lib/python3.10/dist-packages/pandas/io/common.py", line 571, in check_parent_directory raise OSError(rf"Cannot save file into a non-existent directory: &#39;{parent}&#39;") OSError: Cannot save file into a non-existent directory: &#39;/log_data/1.4.8-480.10.320+ETD&#39;
最新发布
03-22
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