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python中一个文件（A.py）怎么调用另一个文件（B.py）中定义的类AA详解和示例

news 2025/8/7 19:38:49

本文主要讲解python文件中怎么调用另外一个py文件中定义的类，将通过代码和示例解读，帮助大家理解和使用。

代码

B.py

如在文件B.py,定义了类别Bottleneck，其包含卷积层、正则化和激活函数层，主要对输入图像进行处理。但没有读取图像等代码。


from torch import nndef autopad(k, p=None, d=1):  # kernel, padding, dilation# Pad to 'same' shape outputsif d > 1:k = d * (k - 1) + 1 if isinstance(k, int) else [d * (x - 1) + 1 for x in k]  # actual kernel-sizeif p is None:p = k // 2 if isinstance(k, int) else [x // 2 for x in k]  # auto-padreturn pclass Conv(nn.Module):# Standard convolution with args(ch_in, ch_out, kernel, stride, padding, groups, dilation, activation)default_act = nn.SiLU()  # default activationdef __init__(self, c1, c2, k=3, s=2, p=None, g=1, d=1, act=True):super().__init__()self.conv = nn.Conv2d(c1, c2, k, s, autopad(k, p, d), groups=g, dilation=d, bias=False)self.bn = nn.BatchNorm2d(c2)self.act = self.default_act if act is True else act if isinstance(act, nn.Module) else nn.Identity()def forward(self, x):return self.act(self.bn(self.conv(x)))def forward_fuse(self, x):return self.act(self.conv(x))class Bottleneck(nn.Module):# Standard bottleneckdef __init__(self, c1, c2, shortcut=True, g=1, e=0.5):  # ch_in, ch_out, shortcut, groups, expansionsuper().__init__()c_ = int(c2 * e)  # hidden channelsself.cv1 = Conv(c1, c_, 1, 1)self.cv2 = Conv(c_, c2, 3, 2, g=g)self.add = shortcut and c1 == c2def forward(self, x):return x + self.cv2(self.cv1(x)) if self.add else self.cv2(self.cv1(x))

A.py

文件A.py，在此部分，加载一幅图像并对其进行卷积处理。在代码中，没有卷积等层的定义，通过调用B.py中定义的类进行。

import B
from PIL import Image
from torchvision import transforms
import math
if __name__ == '__main__':image = Image.open("../11111.jpg")transform = transforms.Compose([transforms.ToTensor()])# 对图像应用转换操作input_image = transform(image)input_image = input_image.unsqueeze(0)CBR=B.Bottleneck(3,64)x=CBR(input_image )print(x.shape)