I want you to train three different deep learning models using MLP, 1-D and 2-D convolution, respectively

I want you to train three different deep learning models using MLP, 1-D and 2-D convolution, respectively. I will give you the data. Something like these: https://colab.research.google.com/github/maticvl/dataHacker/blob/master/pyTorch/008_ArtificialNeuralNetworkPerceptron.ipynb#scrollTo=dIj4OrwYE7Hn https://github.com/rasbt/stat453-deep-learning-ss21/blob/main/L09/code/mlp-pytorch_softmax-crossentr.ipynb At the end I want to see that kind of results: Epoch number 1 - Training dataset. Got 128 out of 752 images correctly (17.021%). Epoch loss: 2.263 - Testing dataset. Got 43 out of 238 images correctly (18.067%). Epoch number 2 - Training dataset. Got 178 out of 752 images correctly (23.670%). Epoch loss: 2.240 - Testing dataset. Got 64 out of 238 images correctly (26.891%). Epoch number 3 - Training dataset. Got 154 out of 752 images correctly (20.479%). Epoch loss: 2.166 - Testing dataset. Got 64 out of 238 images correctly (26.891%). My data is larger than 20 mb.