import torch
import torchvision.datasets
from mmcv import DataLoader
from mmcv.cnn import Linear
from torch import nn

dataset = torchvision.datasets.CIFAR10(r"C:\Users\123\Desktop\python4.7\test03\data", train=False, transform=torchvision.transforms.ToTensor(),
                                       download=True)
dataloader = DataLoader(dataset, batch_size=64)

class LR(nn.Module):
    def __init__(self):
        super(LR, self).__init__()
        self.linear1 = Linear(196608, 10)

    def forward(self, input):
        output = self.linear1(input)
        return output

lrp = LR()



for data in dataloader:
    imgs, targets = data
    print(imgs.shape)
    output = torch.reshape(imgs, (1, 1, 1, -1))
    # output = torch.flatten(imgs)
    print(output.shape)
    output = lrp(output)
    print(output.shape)