Source code for api.views.runmanager_auto_rule

import json
from rest_framework.response import Response
from rest_framework.views import APIView
from master.automl.automl_rule import AutoMlRule
from django.core import serializers
import coreapi

class RunManagerAutoRule(APIView):

    coreapi_fields = (
        coreapi.Field(
            name='netconf_node',
            required=True,
            type='string',
        ),
        coreapi.Field(
            name='datasrc',
            required=True,
            type='string',
        ),
        coreapi.Field(
            name='evaldata',
            required=True,
            type='string',
        ),
        coreapi.Field(
            name='evalnode',
            required=True,
            type='string',
        ),
    )
    def post(self, request, graph_id):
        """
        Manage AutoML define information include (id, desc and etc ) \n
        Structure : AutoML - NetID - NetVer(Auto Generated by GA) - NetBatch (auto generated on every batch) \n
        (1) Define AutoML Graph definition (<- for this step) \n
        (2) Select Type of Data (<- for this step)\n
        (3) Select Type of Anal algorithm (<- for this step)\n
        (4) Select range of hyper parameters (<- for this step)\n
        (5) Run - AutoML \n
        (6) Check result of each generation with UI/UX \n
        (7) Select Best model you want use and activate it \n
        ---
        # Class Name : RunManagerAutoRule

        # Description:
            Set AutoML description, This is necessary process if you want to use automatically tune
            hyperparameters for deep learning algorithms
        """
        try:
            return_data = AutoMlRule().set_graph_type_list(graph_id, request.data)
            return Response(json.dumps(return_data))
        except Exception as e:
            return_data = {"status": "404", "result": str(e)}
            return Response(json.dumps(return_data))

    def get(self, request, graph_id):
        """
        Manage AutoML define information include (id, desc and etc ) \n
        Structure : AutoML - NetID - NetVer(Auto Generated by GA) - NetBatch (auto generated on every batch) \n
        (1) Define AutoML Graph definition (<- for this step) \n
        (2) Select Type of Data (<- for this step)\n
        (3) Select Type of Anal algorithm (<- for this step)\n
        (4) Select range of hyper parameters (<- for this step)\n
        (5) Run - AutoML \n
        (6) Check result of each generation with UI/UX \n
        (7) Select Best model you want use and activate it \n
        ---
        # Class Name : RunManagerAutoRule

        # Description:
            Get AutoML description include hyperparameters for deep learning algorithms
        """
        try:
            if graph_id.isdigit() == True :
                return_data = AutoMlRule().get_graph_type_list(graph_id)
            elif graph_id is not None :
                return_data = AutoMlRule().get_graph_info(graph_id)
            else :
                raise Exception("no vailed graph_id")
            return Response(json.dumps(return_data))
        except Exception as e:
            return_data = {"status": "404", "result": str(e)}
            return Response(json.dumps(return_data))

    def put(self, request, graph_id):
        """
        Manage AutoML define information include (id, desc and etc ) \n
        Structure : AutoML - NetID - NetVer(Auto Generated by GA) - NetBatch (auto generated on every batch) \n
        (1) Define AutoML Graph definition (<- for this step) \n
        (2) Select Type of Data (<- for this step)\n
        (3) Select Type of Anal algorithm (<- for this step)\n
        (4) Select range of hyper parameters (<- for this step)\n
        (5) Run - AutoML \n
        (6) Check result of each generation with UI/UX \n
        (7) Select Best model you want use and activate it \n
        ---
        # Class Name : RunManagerAutoRule

        # Description:
            Modify AutoML description include hyperparameters for deep learning algorithms
        """
        try:
            return_data = AutoMlRule().update_graph_type_list(graph_id, request.data)
            return Response(json.dumps(return_data))
        except Exception as e:
            return_data = {"status": "404", "result": str(e)}
            return Response(json.dumps(return_data))

    def delete(self, request, graph_id):
        """
        Manage AutoML define information include (id, desc and etc ) \n
        Structure : AutoML - NetID - NetVer(Auto Generated by GA) - NetBatch (auto generated on every batch) \n
        (1) Define AutoML Graph definition (<- for this step) \n
        (2) Select Type of Data (<- for this step)\n
        (3) Select Type of Anal algorithm (<- for this step)\n
        (4) Select range of hyper parameters (<- for this step)\n
        (5) Run - AutoML \n
        (6) Check result of each generation with UI/UX \n
        (7) Select Best model you want use and activate it \n
        ---
        # Class Name : RunManagerAutoRule

        # Description:
            Delete AutoML description include hyperparameters for deep learning algorithms
            This will remove all realted information (nn_id, ver, batch and model)
        """
        try:
            return_data = ""
            return Response(json.dumps(return_data))
        except Exception as e:
            return_data = {"status": "404", "result": str(e)}
            return Response(json.dumps(return_data))