Here is the Microsoft Edge copilot explanation of the code (think it as chartGPT front end). 看看楼上谁真懂了这程序。
>> You
please explain the code in the image
>> ')
save_path = '/home/demo/output.jpeg'
th = Thread(target=ModelInference, args=(prompt, save_path))
th.start()
try:
time.sleep(6)
except KeyboardInterrupt:
running = False
traceback.print_exc()
th.join()
AI-generated code. Review and use carefully. More info on FAQ.
if __name__ == '__main__': This line checks if the script is being run as the main program. If it is, the code within this block will execute.
prompt = input('>>> ') This line takes user input from the console and assigns it to a variable named prompt.
save_path = '/home/demo/output.jpeg' This line defines a file path where the output will be saved.
th = Thread(target=ModelInference, args=(prompt, save_path)) This line creates a new thread to run a function called ModelInference with prompt and save_path as arguments.
th.start() This line starts the execution of the thread.
The try-except block is used to handle exceptions. In this case, it’s used to catch a KeyboardInterrupt exception, which is typically raised when the user hits Ctrl+C while the script is running.
time.sleep(6) This line makes the script pause for 6 seconds.
running = False If there’s a keyboard interruption, it sets a running variable to False.
traceback.print_exc() This line prints the traceback of the exception.
th.join() This line makes the main program wait for the thread to complete execution before proceeding.
This script appears to be part of a larger program for running some kind of model inference. The model inference is run in a separate thread, and the main program waits for a short period of time (6 seconds) for potential keyboard interruption. If there’s a keyboard interruption, it stops the execution and prints the traceback of the exception. Finally, it waits for the thread to complete execution before proceeding. The results of the model inference are presumably saved to the specified path. Please note that the actual behavior might depend on the implementation of the ModelInference function, which is not shown in the image.
Here is the Microsoft Edge copilot explanation of the code (think it as chartGPT front end). 看看楼上谁真懂了这程序。
================
repost due to format issue
================
You
please explain the code in the image
(above code image copied to copilot and its interpretation below).
Copilot
Analyzing the image: Privacy blur hides faces from Copilot
Sure, I’d be happy to explain the code in the image. Here’s a breakdown:
Python
if __name__ == '__main__':
prompt = input('>>> ')
save_path = '/home/demo/output.jpeg'
th = Thread(target=ModelInference, args=(prompt, save_path))
th.start()
try:
time.sleep(6)
except KeyboardInterrupt:
running = False
traceback.print_exc()
th.join()
AI-generated code. Review and use carefully. More info on FAQ.
if __name__ == '__main__': This line checks if the script is being run as the main program. If it is, the code within this block will execute.
prompt = input('>>> ') This line takes user input from the console and assigns it to a variable named prompt.
save_path = '/home/demo/output.jpeg' This line defines a file path where the output will be saved.
th = Thread(target=ModelInference, args=(prompt, save_path)) This line creates a new thread to run a function called ModelInference with prompt and save_path as arguments.
th.start() This line starts the execution of the thread.
The try-except block is used to handle exceptions. In this case, it’s used to catch a KeyboardInterrupt exception, which is typically raised when the user hits Ctrl+C while the script is running.
time.sleep(6) This line makes the script pause for 6 seconds.
running = False If there’s a keyboard interruption, it sets a running variable to False.
traceback.print_exc() This line prints the traceback of the exception.
th.join() This line makes the main program wait for the thread to complete execution before proceeding.
This script appears to be part of a larger program for running some kind of model inference. The model inference is run in a separate thread, and the main program waits for a short period of time (6 seconds) for potential keyboard interruption. If there’s a keyboard interruption, it stops the execution and prints the traceback of the exception. Finally, it waits for the thread to complete execution before proceeding. The results of the model inference are presumably saved to the specified path. Please note that the actual behavior might depend on the implementation of the ModelInference function, which is not shown in the image.
5月16日，针对网传华为大模型文生图现场展示疑似人工操控的消息，华为昇腾社区回应称：并非调取预置图片，本次展示的均为真实代码，也将在昇腾社区上开放。
事情的起因是，6天前在鲲鹏昇腾开发者大会的一场面向开发者的技术讨论会上，华为演示了mxRAG SDK功能，即如何通过十几行代码即可完成RAG应用开发。
据网传视频及聊天截图，华为在演示文生图功能时，按下Crtl-C中断，显示对应代码为time.sleep（6），有网友解释代码的意思是：暂停6秒，然后读取本地的一张图片展示出来。
因此，华为被质疑大模型能力演示造假。
昇腾社区回应称，现场图片为实时生成，调用的是开源大模型。代码中有time.sleep（6）等表述，是命令等待读取外部开源大模型实时生成的图片，并非调取预置图片。本次展示的均为真实代码，也将在昇腾社区上开放，欢迎开发者使用并提出宝贵建议。
“具体什么情况很难说，但演示场景还是可以理解的。”一位AI相关开发者告诉《AI光年》，因为目前企业很难接受真实演示场景出故障，所以“大家做demo多少都有一些作假的成分”，他猜测，华为这次演示可能存在“赶工”抢发布热点的情况。
《AI光年》发现，华为此次展示的mxRAG SDK功能，目前还未在开发者资源下载中心上线，资源最新更新时间为4月22日。
据《AI光年》了解，mxRAG的功能为检索增强生成——检索（Retrieval）、增强（Augmentation）和生成（Generation）。这一能力是目前开发大语言模型（LLM）所需的重要能力之一。
据一篇香港理工大学、百度、新加坡国立大学等研究机构发表的一篇论文，LLM+RAG被应用于多个领域，包括但不限于：问答系统、聊天机器人、事实验证、金融领域的决策支持、科学领域的分子发现等。未来还可以提高模型的可信度，开发多语言和多模态的RA-LLMs等。
由于昇腾社区暂未公布源代码，开发者目前仅能通过网传代码截图进行经验判断和讨论，《AI光年》发现，大部分开发者认为文生图过程理论上“完全没必要sleep（6）”。但具体情况如何？华为mxRAG SDK功能如何？还需资源开放后再做验证。