Programmer Think

1, Basic usage of optimizer Create optimizer instanceCycle: Empty gradientForward propagationCalculate LossBack propagationUpdate parameters Example: from torch import optim input = ..... optimizer = optim.SGD(params=net.parameters(), lr=1) # Optimizer instance optimizer.zero_grad() # Empty gradient output = net(input) # Forward propag ...

Requirements: There is a position size picture. Now you need to get a picture of the specified size according to the original picture, and the obtained picture should conform to the proportion of the original picture, that is, after the picture is obtained by equal scaling on the basis of the original picture, you can cut it, so as to ensure t ...

introduce Not long ago (in fact, for a long time), the CheXNet model for CT image detection of pneumonia was reproduced with Paddle A visual method CAM is mentioned in the paper, which can visualize the activation of the network. The example is shown in the figure below: [the external chain picture transfer fails. The source station may have ...

Generally, we can use many different frameworks when training models. For example, some students like to use pytoch, some students like to use tensorflow, some students like MXNet, and Caffe, which is popular at the beginning of deep learning. In this way, different training frameworks lead to different model result packages, Different dependen ...

Learning objectives: Understand the basic principles of text mining.Master the method of text classification using LSTM. Learning content: In recent years, with wechat, microblog, mayor's mailbox, sunshine hotline and other online political platforms gradually becoming an important channel for the government to understand public opinion, gat ...

Generally, in the process of model reasoning on the end side, the quantized data is used to participate in the calculation of each layer, rather than the original float data type. The usual quantized data types include UINT8/INT8/INT16, etc. due to the difference of data representation range, the accuracy loss must be involved in the quantizati ...

1, The matrix operation is used to calculate cosine similarity Cosine similarity: We know that the numerator is the multiplication of a matrix and the denominator is the product of two scalars. Denominator easy to do, the key is how to calculate the numerator? Very simply, we can deform the formula: Then we just need to normalize the mat ...

This article is the last article (TVM development code learning) add a new operator to the Relay system - Zhihu (zhihu.com) It is mainly to be familiar with the Relay operator code from six parts and deconstruct the Relay operator in TVM from the perspective of adding an operator. Reviewing the previous section, the following points are requir ...

[source code analysis] machine learning parameter server PS Lite (4) -- application node implementation 0x00 summary This is the fourth article on parameter server, which introduces kvworker and kvserver. Other articles in this series are: [ Source code analysis] machine learning parameter server PS Lite (1) -- postoffice [ Source code ...

1. Project introduction Q-learning: Q-learning was first proposed in 1989 and was initially based on tabular form. DQN: DQN (deep Q network) was proposed only in 2013. It is a Q-learning algorithm based on deep neural network, and it is also the most commonly used Q-learning algorithm at present. Objectives of the project: The DQN algorithm ...