PyTorch编写代码遇到的问题

时间：2025-03-30 07:35:01

PyTorch编写代码遇到的问题

flyfish

错误提示：no module named xxx

xxx为自定义文件夹的名字
因为搜索不到，所以将当前路径加入到包的搜索目录
解决方法：

import sys
sys.path.append('..') #将上层目录加入到搜索路径中
sys.path.append('/home/xxx') # 绝对路径
import os
sys.path.append(os.getcwd()) #		#将当前工作路径加入到搜索路径中

还可以在当前终端的命令行设置

export PYTHONPATH=$PYTHONPATH:./
错误提示：AttributeError: ‘NoneType’ object has no attribute ‘shape’

height, width, channel =

在Linux系统下报错AttributeError: ‘NoneType’ object has no attribute ‘shape’
img=()，读取一张图片时，是包含三个量的元组，分别是：
[0]：图像的高度
[1]：图像的宽度
[2]：图像的通道数
解决方法：读的文件出错 或者查看文件路径是否正确

错误提示 ：TypeError: slice indices must be integers or None or have an index method

cropped_im = img[ny1 : ny2, nx1 : nx2, :]
解决方法：需要将ny1 : ny2, nx1 : nx2转换成int类型

错误提示 ：Input type () and weight type () should be the same

以下三小段分别是Data type CPU tensor GPU tensor
32-bit floating point
64-bit floating point

出错在类型转换

更改为np.float32

import torchvision.transforms as transforms
import numpy as np

transform = transforms.ToTensor()

def convert_image_to_tensor(image):
    """convert an image to pytorch tensor
        image: numpy array , h * w * c
        image_tensor: , c * h * w
        """
    image = image.astype(np.float32)  

    return transform(image)
错误提示：RuntimeError: zero-dimensional tensor (at position 0) cannot be concatenated

版本问题 旧式写法

import torch
x = torch.tensor(0.1)
y = torch.tensor(0.2)
z = torch.cat((x, y))

改成新式写法

x = torch.tensor([0.1])
y = torch.tensor([0.2])
z = torch.cat((x, y))
print(z)

结果

tensor([0.1000, 0.2000])
错误提示：TypeError: ‘float’ object is not subscriptable

多了下标 a = ()[0]
去除下标 a = ()

错误提示：argument ‘input’ (position 1) must be Tensor, not list

需要将list转换成tensor
假设a是list
(a)

GPU模型和CPU模型之间的转换

假设原来保存的是GPU模型，要转换为CPU模型

torch.save(model, os.path.join( "./"))
cpu_model = torch.load("./", map_location=lambda storage, loc: storage)
dummy_input = torch.randn(1, 3, 224, 224)

假设原来保存的是CPU模型，要转换为GPU模型

device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
torch.save(model, os.path.join( "./"))
gpu_model = torch.load("./", map_location=lambda storage, loc: storage.cuda)
dummy_input = torch.randn(1, 3, 224, 224)
dummy_input = dummy_input.to(device)
错误提示 RuntimeError: Subtraction, the - operator, with a bool tensor is not supported. If you are trying to invert a mask, use the ~ or logical_not() operator instead.

原代码

# Store only unsuppressed boxes for this class
image_boxes.append(class_decoded_locs[1 - suppress])
image_labels.append(torch.LongTensor((1 - suppress).sum().item() * [c]).to(device))
image_scores.append(class_scores[1 - suppress])

更改为

image_boxes.append(class_decoded_locs[~suppress])
image_labels.append(torch.LongTensor((~ suppress).sum().item() * [c]).to(device))
image_scores.append(class_scores[~suppress])
错误提示 RuntimeError: Expected object of scalar type Byte but got scalar type Bool for argument #2 ‘other’ in call to _th_max

原代码

   suppress = torch.zeros((n_above_min_score), dtype=torch.uint8).to(device)

更改为

   suppress = torch.zeros((n_above_min_score), dtype=torch.bool).to(device)
UserWarning: volatile was removed and now has no effect. Use with torch.no_grad(): instead.
#之前旧版本
...
x = Variable(torch.randn(1), volatile=True)
return x

#新版
with torch.no_grad():
    ...
    x = torch.randn(1)
return x
错误提示

RuntimeError: Attempting to deserialize object on CUDA device 1 but .device_count() is 1. Please use with map_location to map your storages to an existing device.
或者是 RuntimeError: expected device cuda:0 but got device cuda:1

错误原因之一
使用了CUDA 1显卡训练保存的模型文件,使用CUDA 0验证
代码中写了
device = (“cuda” if .is_available() else “cpu”)

可以在命令行设置让哪些GPU可见
export CUDA_VISIBLE_DEVICES=1 #GPU编号
export CUDA_VISIBLE_DEVICES=0,1,2,3#4张显卡可见
也可以在代码里改成
checkpoint = (checkpoint,map_location=‘cuda:0’)

错误提示

raise ConnectionError(e, request=request)
requests.exceptions.ConnectionError: HTTPConnectionPool(host='localhost', port=8097): Max retries exceeded with url: /update (Caused by NewConnectionError('< object at 0x7f3111915e80>: Failed to establish a new connection: [Errno 111] Connection refused',))
Exception in user code:

解决方案
因为没有启动visdom可视化程序，所有报错
在终端执行命令 visdom之后就能看到如下信息

Checking for scripts.
It's Alive!
INFO:root:Application Started
You can navigate to http://localhost:8097

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