Use Pytorch to perform dog and cat identification on 12,500 dog images and 12,500 cat images. Split the dataset into 20,000 images for training and 5,000 for validation. We achieved a training accuracy of 93.53% and a validation accuracy of 90.89% using a CNN algorithm.