IsolarAB exports arxml to Matlab/Simulink to generate the model and configure the memory partition

This article uses a simple example to illustrate how to import the SWC arxml designed by Isolar into simulink to generate a model, and specify that the code generated by simulink has memory partition information. The SWC created in this article is called ECAS_Sensor_SWC. Its main function is to process sensor signals and pass them […]

Five major IO models in Linux and three IO models in Java

The five major IO models in Linux and the three IO models in Java IO model background 1. Kernel state, user state 2. The general process of the application receiving data from the network 3. Synchronous/asynchronous, blocking/non-blocking Five major Linux IO models Blocking IO Non-blocking IO Multiplexed IO Signal driven IO Asynchronous IO Three IO […]

The 2.5k ChatGPT-Java version SDK upgrade 1.1.2-beta0 supports GPT-4V, Dall-e-3 model, ToolCalls, fine-tuning Job, TTS…

1. Project Introduction Chatgpt-Java is the Java SDK of OpenAI’s official API, which can be quickly accessed for use in projects. Supports all official OpenAI interfaces. The current harvest will be 2500 + star. Open source address: https://github.com/Grt1228/chatgpt-java Official documentation: https://chatgpt-java.unfbx.com/ Latest version: 1.1.2-beta0 <dependency> <groupId>com.unfbx</groupId> <artifactId>chatgpt-java</artifactId> <version>1.1.2-beta0</version> </dependency> Currently supported features: Dall-e-3 FineTuneJob TTS […]

Oracle active/standby switchover, ogg recovery method (classic mode)

Foreword: This article mainly introduces how to recover the ogg process (classic mode) running in the main database and standby database when the Oracle database physical ADG primary and backup switches (switchover, failover). Test recovery scenario: 1 A switchover occurs between the active and standby devices, and the main database is the ogg source. 2 […]

Customization of HuggingFace model header

Recommended online tools: Three.js AI Texture Development Kit – YOLO synthetic data generator – GLTF/GLB online editing – 3D model format online conversion – Programmable 3D scene editor In this article we’ll cover how to adapt HuggingFace’s model to your task, build a custom model header in Pytorch and connect it to the body of […]

Stm32_Standard library_18_Serial port & Bluetooth module_Communication between mobile phone and Bluetooth module_Control LED light on and off

Control the LED lights on and off by inputting LED_ON and LED_OFF respectively wiring: The positive electrode of the LED is connected to positive electricity, and the negative electrode is connected to GPIOA_Pin1 Bluetooth module TXD is connected to GPIOA_Pin3, VCC is connected to positive power, and GND is connected to negative power. Note: USART2 […]

n-gram language model – text generation source code

n-gram language model – text generation source code Basic principles of n-gram model Steps of text generation 1. Preparation and word segmentation 2. Build n-gram model 3. Application of smoothing technology 4. Generate text Source code In the field of natural language processing, the n-gram language model is a basic and powerful tool. It is […]

OpenMMlab exports the yolov3 model and uses onnxruntime and tensorrt for inference

Export onnx file Use script directly import torch from mmdet.apis import init_detector, inference_detector config_file = ‘./configs/yolo/yolov3_mobilenetv2_8xb24-ms-416-300e_coco.py’ checkpoint_file = ‘yolov3_mobilenetv2_mstrain-416_300e_coco_20210718_010823-f68a07b3.pth’ model = init_detector(config_file, checkpoint_file, device=’cpu’) # or device=’cuda:0′ torch.onnx.export(model, (torch.zeros(1, 3, 416, 416),), “yolov3.onnx”, opset_version=11) The exported onnx structure is as follows: The output is the output of three different levels of detection heads. If you […]

Digital modeling experience-data processing-pandas

Digital analog experience-data processing-pandas Detailed explanation of the code: will be added next time import pandas as pd import numpy as np # # Set panda display function # pd.set_option(‘display.max_columns’, 10) # pd.set_option(‘display.max_rows’, 100) # pd.set_option(‘display.width’, 100) Series basic operations obj=pd.Series([4,7,-5,3]) obj 0 4 1 7 2-5 3 3 dtype: int64 obj.values array([ 4, 7, […]