The transformation from pytoch model to Tensorflow model

Recently, in the research of Query2Title model, pytorch is generally used for rapid experiments in academic circles, but most of the deployment models in the industry are still deployed with tensorflow model. Maybe I'm too lazy. Haha, pytorch has been used for a long time. Tensorflow is a little rusty. I'm lazy to use it! As a result, online ...

Posted by somenoise on Wed, 27 Apr 2022 04:20:08 +0300

# AssertionError: The `num_classes` (80) in Shared2FCBBoxHead of MMDataParallel does not matche

I think many people have encountered this problem and many have been solved. I'll improve this blog post to make it easier for you to use mmdetection. mmdetection trains its own data set to report errors ⚠️ : # AssertionError: The `num_classes` (3) in Shared2FCBBoxHead of MMDataParallel does not matches the length of `CLASSES` 80) in CocoD ...

Posted by Spartan 117 on Tue, 26 Apr 2022 17:26:39 +0300

[hands on learning pytorch notes] 36 Transformer implementation

Transformer implementation Put the contents of the previous sections together, muti head attention, positive encoding import math import pandas as pd import torch from torch import nn from d2l import torch as d2l Position based feedforward network The name is very tall. In fact, it is a single hidden layer MLP #@save class PositionWi ...

Posted by natbrazil on Mon, 25 Apr 2022 20:16:13 +0300

Detailed explanation and Python implementation of deep knowledge tracking (DKT)

The development process of knowledge tracking was summarized before. In 2015, Chris Piech and others applied deep learning to knowledge tracking for the first time, with remarkable results. Since then, a large number of improved DKT models have emerged. The deep knowledge tracking model can realize the dynamic tracking of students' knowledge st ...

Posted by skippy111 on Mon, 25 Apr 2022 06:21:26 +0300

Win10-TensorRT-Yolov5-v5.0 Demo run notes

There are too many VS environment pits. I can't remember many errors. I summarize several important points: reference material: Deploy yolov5.0 using tensorRT 0—windows_Ring__Rain blog - CSDN blog_ tensorrt yolov5 win10 uses TensorRT to deploy yolov5-v4 0(C++)_ SongpingWang blog - CSDN blog Three tensorRT acceleration methods of Yolov ...

Posted by Vizionz on Sun, 24 Apr 2022 20:30:24 +0300

Strip pooling: retreating spatial pooling for scene parsing

Article address: https://arxiv.org/pdf/2003.13328v1.pdf Source address: https://github.com/Andrew-Qibin/SPNet Problem elicitation In some cases, the target object may have a long-distance banded structure or discrete distribution (as shown in the following figure). Using a square does not solve the problem well because it inevitably merges in ...

Posted by andriy on Tue, 19 Apr 2022 00:03:22 +0300

Read the evaluation code of pysot, and watch it better compared with the code!

Evaluation code of pysot 1. Official evaluation code 2. Code reading Content to load The path of prediction results obtained in the test -- tracker_pathDataset name used for evaluation -- datasetTracker name used for evaluation -- tracker_prefix When the track result storage path and the theoretical path are changed because t ...

Posted by Swedie on Mon, 18 Apr 2022 22:55:36 +0300

[Learn pytorch notes by hand] 35. Self-attention and location coding

Self-attention mechanism and location coding theory The problem with self-Attention is that query, key and value are all themselves. y i = f ( x ...

Posted by madmega on Mon, 18 Apr 2022 20:04:42 +0300

Understanding of learning rate

definition: Back propagating the output error to the network parameters to fit the output of the sample is essentially a process of optimization, and gradually tends to the optimal solution. However, how many errors are used in updating the parameters each time needs to be determined by a parameter, which is the learning rate, also known as th ...

Posted by flyersun on Mon, 18 Apr 2022 18:08:57 +0300

Literature reading notes -- Gan -- original paper of general advantageous networkgan - group explanation

Generative Adversarial Network By Ian goodflow Time: 2014 Paper address Arxiv: https://arxiv.org/abs/1406.2661 Basic idea of GAN Generate countermeasure network GAN mainly includes two parts: generator and discriminator. The generator is mainly used to learn the distribution of real images, so as to make the images generated by itself more ...

Posted by spicey on Sun, 17 Apr 2022 02:25:53 +0300