forked from enviPath/enviPy
51 lines
1.2 KiB
Python
51 lines
1.2 KiB
Python
import logging
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from celery.signals import worker_process_init
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from celery import shared_task
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from epdb.models import Pathway, Node, Edge, EPModel, Setting
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from epdb.logic import SPathway
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from utilities.chem import FormatConverter
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logger = logging.getLogger(__name__)
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@shared_task(queue='background')
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def mul(a, b):
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return a * b
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@shared_task(queue='predict')
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def predict_simple(model_pk: int, smiles: str):
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mod = EPModel.objects.get(id=model_pk)
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res = mod.predict(smiles)
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return res
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@shared_task(queue='background')
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def send_registration_mail(user_pk: int):
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pass
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@shared_task(queue='model')
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def build_model(model_pk: int):
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mod = EPModel.objects.get(id=model_pk)
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X, y = mod.build_dataset()
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mod.build_model(X, y)
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@shared_task(queue='model')
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def evaluate_model(model_pk: int):
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mod = EPModel.objects.get(id=model_pk)
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mod.evaluate_model()
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@shared_task(queue='predict')
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def predict(pw_pk: int, pred_setting_pk: int):
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pw = Pathway.objects.get(id=pw_pk)
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setting = Setting.objects.get(id=pred_setting_pk)
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spw = SPathway(prediction_setting=setting, persist=pw)
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level = 0
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while not spw.done:
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spw.predict_step(from_depth=level)
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level += 1
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