cube-studio/myapp/models/model_nni.py

from flask_appbuilder import Model
from sqlalchemy import Column, Integer, String, ForeignKey,Float
from sqlalchemy.orm import relationship
import datetime,time,json
from sqlalchemy import (
    Boolean,
    Column,
    create_engine,
    DateTime,
    ForeignKey,
    Integer,
    MetaData,
    String,
    Table,
    Text,
    Enum,
)
from myapp.utils import core
import re
from myapp.models.base import MyappModelBase
from myapp.models.helpers import AuditMixinNullable, ImportMixin
from flask import escape, g, Markup, request
from myapp import app,db
from myapp.models.helpers import ImportMixin

from sqlalchemy import Column, Integer, String, ForeignKey ,Date,DateTime
from flask_appbuilder.models.decorators import renders
from flask import Markup
import datetime
metadata = Model.metadata
conf = app.config



class NNI(Model,AuditMixinNullable,MyappModelBase):
    __tablename__ = 'nni'
    id = Column(Integer, primary_key=True)
    job_type = Column(Enum('Job'),nullable=True,default='Job')
    project_id = Column(Integer, ForeignKey('project.id'), nullable=False)  # 定义外键
    project = relationship(
        "Project", foreign_keys=[project_id]
    )
    name = Column(String(200), unique = True, nullable=False)
    namespace = Column(String(200), nullable=True,default='automl')
    describe = Column(Text)
    parallel_trial_count = Column(Integer,default=3)
    maxExecDuration =  Column(Integer,default=3600)
    max_trial_count = Column(Integer,default=12)
    max_failed_trial_count = Column(Integer,default=3)
    objective_type = Column(Enum('maximize','minimize'),nullable=False,default='maximize')
    objective_goal = Column(Float, nullable=False,default=0.99)
    objective_metric_name = Column(String(200), nullable=False,default='accuracy')
    objective_additional_metric_names = Column(String(200),default='')   # 逗号分隔
    algorithm_name = Column(String(200),nullable=False,default='Random')
    algorithm_setting = Column(Text,default='')  # 搜索算法的配置
    parameters=Column(Text,default='{}')  # 搜索超参的配置
    job_json = Column(Text, default='{}')  # 根据不同算法和参数写入的task模板
    trial_spec=Column(Text,default='')    # 根据不同算法和参数写入的task模板
    # code_dir = Column(String(200), default='')  # 代码挂载
    job_worker_image = Column(String(200),nullable=True,default='')
    job_worker_command = Column(String(200), nullable=True, default='')
    working_dir = Column(String(200), default='')  # 挂载
    volume_mount = Column(String(100), default='kubeflow-user-workspace(pvc):/mnt,kubeflow-archives(pvc):/archives')  # 挂载
    node_selector = Column(String(100), default='cpu=true,train=true')  # 挂载
    image_pull_policy = Column(Enum('Always', 'IfNotPresent'), nullable=False, default='Always')
    resource_memory = Column(String(100), default='1G')
    resource_cpu = Column(String(100), default='1')
    resource_gpu = Column(String(100), default='0')
    experiment=Column(Text,default='')  # 构建出来的实验体
    alert_status = Column(String(100), default='Pending,Running,Succeeded,Failed,Terminated')   # 哪些状态会报警Pending,Running,Succeeded,Failed,Unknown,Waiting,Terminated



    def __repr__(self):
        return self.name

    @property
    def run(self):
        return Markup(f'<a href="/nni_modelview/run/{self.id}">运行</a>')

    @renders('parameters')
    def parameters_html(self):
        return Markup('<pre><code>' + self.parameters + '</code></pre>')


# '''
# "\"单反斜杠  %5C
# "|"      %7C
# 回车  %0D%0A
# 空格  %20
# 双引号 %22
# "&" %26
# '''

    @property
    def name_url(self):
        return Markup(f'<a target=_blank href="/experiments_modelview/list/?_flt_2_labels=%22{self.name}%22">{self.name}</a>')

    @property
    def describe_url(self):

        NNI_DOMAIN = self.project.cluster.get('NNI_DOMAIN',request.host)
        if NNI_DOMAIN:
            host = "http://"+NNI_DOMAIN
        else:
            host = request.host_url.strip('/') # 使用当前域名打开

        return Markup(f'<a target=_blank href="{host}/nni/{self.name}/">{self.describe}</a>')


    @renders('trial_spec')
    def trial_spec_html(self):
        return Markup('<pre><code>' + self.trial_spec + '</code></pre>')


    @renders('experiment')
    def experiment_html(self):
        return Markup('<pre><code>' + self.experiment + '</code></pre>')

    @property
    def log(self):
        return Markup(f'<a target=_blank href="/nni_modelview/log/{self.id}">log</a>')


    def get_node_selector(self):
        return self.get_default_node_selector(self.project.node_selector,self.resource_gpu,'train')



    def clone(self):
        return NNI(
            name=self.name.replace('_','-'),
            job_type = self.job_type,
            describe=self.describe,
            namespace=self.namespace,
            project_id=self.project_id,
            parallel_trial_count=self.parallel_trial_count,
            max_trial_count=self.max_trial_count,
            max_failed_trial_count=self.max_failed_trial_count,
            objective_type=self.objective_type,
            objective_goal=self.objective_goal,
            objective_metric_name=self.objective_metric_name,
            objective_additional_metric_names=self.objective_additional_metric_names,
            algorithm_name=self.algorithm_name,
            algorithm_setting=self.algorithm_setting,
            parameters=self.parameters,
            job_json = self.job_json,
            trial_spec=self.trial_spec,
            volume_mount=self.volume_mount,
            node_selector=self.node_selector,
            image_pull_policy=self.image_pull_policy,
            resource_memory=self.resource_memory,
            resource_cpu=self.resource_cpu,
            experiment=self.experiment,
            alert_status=self.alert_status
        )