1.CSS transition Introduction Usually when a CSS property value changes, the browser will immediately update the corresponding style. A transition function has been added to CSS3, through which we can smoothly transition elements from one style to another within a specified time, similar to a simple animation, but without resorting to flash or JavaScript. In […]
Tag: transform
[Transfer] Very simple and easy to understand FFT (Fast Fourier Transform)
FFT Preface Fast Fourier transform is the collective name for efficient and fast calculation methods that use computers to calculate the Discrete Fourier Transform (DFT), referred to as FFT. Fast Fourier transform was proposed by J.W. Cooley and T.W. Tukey in 1965. Using this algorithm can greatly reduce the number of multiplications required by the […]
OpenGL space coordinate transformation
First, you need to understand matrices. Matrices are often used for coordinate transformation in programs. Common matrices are: 1. Scaling matrix 2. Displacement matrix More one-dimensional coordinates: Homogeneous Coordinates use: 1. Allows us to displace on a 3D vector (we cannot displace the vector without the w component) 2. Divide the x, y and z […]
OpenGL_Learn07 (Transform)
1. Vector Vectors have a direction and a magnitude. If a vector has 2 dimensions, it represents the direction of a plane (imagine a 2D image), and when it has 3 dimensions, it can represent the direction of a 3D world. You can think of these 2D vectors as 3D vectors with z coordinate 0. […]
Three-dimensional transformation matrix practice – rotation, scaling, mirroring, cross-cutting, translation, and orthogonal projection of three-dimensional point clouds
1. Rotation matrix (right-handed coordinate system) Rotate around the x-axis Rotation matrix: The matrix on the right is the original coordinates of the point cloud, and the matrix on the left is the rotation matrix Visualization: Rotate 90 degrees around the x-axis Code: import vtk import numpy as np import math def pointPolydataCreate(pointCloud): points = […]
2.5 CSS element transformation
2D transformation: transform 1.1 displacement: translate translate: One value represents the horizontal direction, two values represent: horizontal and vertical directions. translateX: To set the horizontal displacement, you need to specify the length value; if you specify a percentage, it is the percentage of the reference to its own width. translateY: To set the vertical displacement, […]
Transformer-based decode target detection framework (modify DETR source code)
Tip: Transformer structure target detection decoder, including loss calculation, with source code attached Article directory Preface 1. Interpretation of main function code 1. Understanding the overall structure 2. Main function code interpretation 3. Source code link 2. Interpretation of decode module code 1. Interpretation of decoded TransformerDec module code 2. Interpretation of decoded TransformerDecoder module […]
Chapter 2, Dynamic Programming Algorithm (2.3.1-2.3.2.6)——Conversion (editing, transformation) issues
Table of Contents 2.3 Dynamic programming algorithm implementation——conversion (editing, transformation) problem 2.3.1 String conversion problem 2.3.1.1Problems 2.3.1.2 Determine dynamic rules (DP, state transition equation) and initial value (1) Insertion operation realizes state transfer (2) Delete operation to achieve state transfer (3) Replacement operation realizes state transfer (4)Initial value (5) Dynamic rules (DP, state transition equation) […]
[RNN+Encrypted Traffic A] ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for…
Article directory Introduction to the paper Summary Problems Paper contribution 1.ET-BERT 2. Experiment Summarize Paper content data set Readable citations Reference connection Introduction to the paper Original title: ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic Classification Chinese title: ET-BERT: A datagram contextual representation method based on pre-trained transformers for encrypted traffic […]
transformers-Generation with LLMs
https://huggingface.co/docs/transformers/main/en/llm_tutorialhttps://huggingface.co/docs/transformers /main/en/llm_tutorialThe stopping condition is determined by the model, and the model should be able to learn when to output an end-of-sequence (EOS) flag. If this is not the case, generation stops when some predefined maximum length is reached. from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained( “mistralai/Mistral-7B-v0.1″, device_map=”auto”, load_in_4bit=True ) from transformers import AutoTokenizer tokenizer […]