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The data used in this example is three categories of English data. torchtext is used to process the data, build an iterator and build textcnn. The data is trained with textcnn to get the training results. In this example, the validation set is not used to evaluate the model. 1, Development environment and data set 1. Development envir ...

Source GitHub address The torchvision module in PyTorch framework includes: torchvision datasets,torchvision.models,torchvision. The three sub packages of transforms. For details, please refer to the official website: http://pytorch.org/docs/master/torchvision/index.html. Refer to github for specific code: https://github.com/pytorch/vision/tr ...

catalogue abstract Import libraries used by the project Set global parameters Image preprocessing Read data Set model Set up training and validation test Complete code abstract I have written a lot about the actual combat of models in the previous article. This is the last one of the actual combat. I didn't add visualization or deco ...

This blog post will be released in Nuggets community first! preface Don't say anything. Let's see the renderings first Originally, I was going to get the model trained on the experimental platform yesterday. As a result, when I got up in the morning, I found that I didn't know why. Maybe there were many people using it. My cloud device ...

For an input picture, the picture is a grid image, that is, the picture is divided into one grid, and each grid represents one pixel. For patch (picture block), we traverse the picture from top to bottom and from left to right according to the size of the block, and then convolute each image block. How to convolute: (1) For the convolution of ...

In the article Introduction to PyTorch deep learning practice notes 9-SoftMax classifier Mr. Liu gave an after-school exercise and downloaded kaggle's Otto dataset Do more classification. 0 Overview Let's take a look at the background of the official website. The Otto Group is one of the world's biggest e-commerce companies, with subsidiar ...

Pytorch learning notes (6): a simple LeNet network model using GPU It also mentioned how to realize the operation on GPU. Although it is not detailed, it is also enough. Summary: (if you are familiar with the summary knowledge, the following detailed explanation can be omitted) Default CPU for calculation.Variables or models on CPU cann ...

catalogue preface 1, Data loading 1. Load package 2. Read data II. Text processing 1. Remove useless characters 2. Text segmentation 3. Remove stop words 4. Remove low-frequency words 5. Divide training set and test set 3, Convert text into vector form 1. Convert text into TF IDF vector 2. Convert text into word2vec vector 3. Conv ...

(I've just started to study in depth and try to record all the exercises of the class. I'll give you a dish and chicken. If there is any mistake or lack of understanding, please give me advice.) 2. Preparatory knowledge 2.1 data operation First question Run the code in this section. Change the conditional statement X == Y in this sectio ...

Tensor data operation 1. Tensor creation # Import some common libraries import torch from IPython import display from matplotlib import pyplot as plt import numpy as np import random import torch.nn as nn import torch.optim as optim # torch.optim module provides many common optimization algorithms, such as SGD, Adam and RMSProp. from torc ...