test_nn_conv2d.py

import torch
import torchvision
from torch import nn
from torch.nn import Conv2d
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter

dataset = torchvision.datasets.CIFAR10("torchvision_dataset", train=False,
                                       transform=torchvision.transforms.ToTensor(),
                                       download=True)

dataloader = DataLoader(dataset, batch_size=64)

class Tudui(nn.Module):
    def __init__(self):
        super(Tudui, self).__init__()
        self.conv1 = Conv2d(in_channels=3, out_channels=6, kernel_size=3, stride=1, padding=0)

    def forward(self, x):
        x = self.conv1(x)
        return x

tudui_nn = Tudui()
print(tudui_nn)

writer = SummaryWriter("logsForTestNNConv2d")
step = 0

for data in dataloader:
    imgs, targets = data
    output = tudui_nn(imgs)
    print(imgs.shape)
    #torch.Size([64, 3, 32, 32])
    print(output.shape)
    #torch.Size([64, 6, 30, 30])
    writer.add_images("input", imgs, step)

    output = torch.reshape(output, (-1, 3, 30, 30))
    writer.add_images("output",output, step)
    step = step + 1

writer.close()