pytorch model container - modular construction of deep learning network

pytorch model container - modular construction of deep learning network pytorch model container summary The model containers provided by pytorch include: nn.Sequential: contains multiple network layers in order nn.ModuleList: contains multiple network layers in the form of a list nn.ModuleDict: contains multiple network layers in the fo ...

Posted on Tue, 21 Sep 2021 21:29:23 -0400 by mattcairns

PyTorch pit six data processing modules Dataloader and Dataset

Overview of data processing in deep learning Three elements of deep learning: data, computing power and algorithm In engineering practice, the importance of data has attracted more and more attention. In the data science community, there is a saying that "data determines the upper limit of the model, and algorithm determines the lower lim ...

Posted on Mon, 20 Sep 2021 21:38:27 -0400 by ven.ganeva

Summary of problems in learning pytorch framework

pytorch framework learning 1: Linear region, Logistic Regression, Softmax Classifier 1. Model inheritance and construction import torch from torch.autograd import Variable # data define(3*1) x_data = Variable(torch.Tensor([[1.0], [2.0], [3.0]])) y_data = Variable(torch.Tensor([[2.0], [4.0], [6.0]])) # model class class Model(torch.nn.Mo ...

Posted on Mon, 20 Sep 2021 10:32:12 -0400 by ozman26

Chapter three, dictionaries and collections

Dict type is not only widely used in various programs, but also the cornerstone of Python language. The dictionary can be seen in the namespace of the module, the attributes of the instance and the keyword parameters of the function. The built-in functions related to it are__ builtins__.__dict__ Module. All mapping types in the standard libra ...

Posted on Sun, 19 Sep 2021 11:50:31 -0400 by lprocks

In simple terms, it takes you to understand the principle of graph convolution neural network and the implementation of pytorch code

01 Big picture neural network After reading the graph neural network for a long time, I have learned a little from ignorance. Today, I want to express some thoughts on feature integration (aggregation) of graph neural networks such as GCN, GraghSAGE and GAT. On the one hand, it will enable more people to learn the essence of graph neural netw ...

Posted on Sat, 18 Sep 2021 02:14:35 -0400 by IndianaRogers

PyTorch: data operation

In deep learning, we usually operate on data frequently. As the basis of hands-on and in-depth learning, this section will introduce how to operate the data in memory. In PyTorch, torch.Tensor is the main tool for storing and transforming data. If you have used NumPy before, you will find that tensor and NumPy's multidimensional arrays are ...

Posted on Thu, 16 Sep 2021 20:52:34 -0400 by kf

pytorch tutorial -- building neural networks

abstract Neural networks consist of layers / modules that perform operations on data. The torch.nn namespace provides all the building blocks needed to build your own neural network. Each module in PyTorch is a subclass of nn.Module. Neural network is a module itself, which is composed of other modules (layers). This nested structure allow ...

Posted on Mon, 13 Sep 2021 14:15:15 -0400 by Fuzzylr

Hugging Face Homepage Course 3rd "Fine-tuning a pretrained model"

Fine-tuning pre-training model This text was translated from Hugging Face Home Page Under Resources course Description: Some articles translate token, Tokenizer, Tokenization into tokens, tokens, and tokenization.Although in a sense more accurate, but the author feel that it is not simple and direct enough, not enough image.Therefore, s ...

Posted on Mon, 06 Sep 2021 13:07:59 -0400 by imstupid