[In-depth understanding of pytorch] PyTorch training and evaluation model

PyTorch training and evaluating models

In the field of machine learning and deep learning, PyTorch is a very popular deep learning framework. It provides flexible and powerful tools that make training and evaluating models easier. This article describes how to use PyTorch to prepare datasets, define training loops, choose optimization algorithms, and show how to evaluate model performance.

Prepare dataset

Before starting to train the model, we first need to prepare the dataset. PyTorch provides torch.utils.datamodules that help us load and process data. Usually, we need to customize a dataset class to load our data and preprocess the data.

import torch
from torch.utils.data import Dataset