torch.optim.SGD
时间: 2023-10-30 20:47:50 浏览: 65
SGD stands for Stochastic Gradient Descent. It is an optimization algorithm used to minimize the loss function in machine learning models. The SGD optimizer updates the model parameters in each iteration by computing the gradient of the loss function with respect to the parameters and taking a step in the opposite direction of the gradient. The "stochastic" part of the algorithm refers to the fact that the gradient is estimated using a random subset of the training data (also known as a mini-batch), rather than the entire dataset. This makes the algorithm computationally efficient and helps it avoid getting stuck in local minima. The torch.optim.SGD module in PyTorch provides an implementation of the SGD optimizer for training neural networks.