paper = models.Paper.objects.filter(major=student.major) grade = models.Grade.objects.filter(sid=student.id) # 计算该门考试的学生成绩 question= models.Paper.objects.filter(subject=subject1).values("pid").values('pid__i
level=models.CharField('等级',max_length=10,choices=LEVEL) score=models.IntegerField('分数',default=1) class Meta: db_table='question' verbose_name='单项选择题库' verbose_name_plural=verbose_name def __str__(self): return '<%s:%s>'%(self.subject,self.title); class Paper(models.Model)...
db_table = 'paper' verbose_name = '试卷' verbose_name_plural = verbose_name def __str__(self): return self.major; class Grade(models.Model): #foreign key 就是用来处理表与表之间关系问题 sid = models.ForeignKey(Student, on_delete=models.CASCADE, default='') # 添加外键 subject = models...
class TestPaper(models.Model): id = models.AutoField('序号',primary_key=True) title = models.CharField('题目',max_length=40,unique=True) pid = models.ManyToManyField(QuestionBank) course = models.ForeignKey(Course,on_delete=models.CASCADE,verbose_name='科目') major = models.ForeignKey(Major,...
(model_name="gemini-1.0-pro", temperature=0.8, max_output_tokens=128)template = """Describe {plant}.First, think whether {plant} exist.If they {plant} don't exist, answer "I don't have enough information about {plant}".Otherwise, give their title, a short summary and then talk ...
To answer this question, you have to recall the definition of the imaginary unit and rewrite the expression in terms of real and imaginary parts:The key observation to make is that j times j gives j2, which can be replaced with -1. This inverts the sign of one of the summands, while...
PyPaperBot是一款可以从谷歌Scholar、Crossref和SciHub下载学术论文的Python工具。PyPaperBot会尝试从谷歌...
Learn the current state-of-the-art models (such as BLIP, GIT, and BLIP2) for visual question answering with huggingface transformers library in Python.
Transfer Learning for OCRopus Model Training on Early Printed Books 全栈程序员站长 2022/07/23 7380 python .txt文件读取及数据处理总结 python机器学习编程算法jquery ##1、处理包含数据的文件 最近利用Python读取txt文件时遇到了一个小问题,就是在计算两个np.narray()类型的数组时,出现了以下错误: 全栈程序员...
The overall ‘learned index’ by this paper is a hierarchy of models (but not a tree, since two models at a certain layer can point to the same model in the next layer) As you go down the layers, the models deal with smaller and smaller subsets of the data. Unlike a B-Tree, no...