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Tim Lorsbach
2025-10-29 19:46:20 +01:00
parent 13ed86a780
commit 138846d84d
35 changed files with 477 additions and 108 deletions
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24
epdb/management/commands/create_ml_models.py
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@ -2,7 +2,9 @@ from django.conf import settings as s
from django.core.management.base import BaseCommand
from django.db import transaction
from epdb.models import MLRelativeReasoning, EnviFormer, Package
from epdb.models import EnviFormer, MLRelativeReasoning
Package = s.GET_PACKAGE_MODEL()
class Command(BaseCommand):
@ -75,11 +77,13 @@ class Command(BaseCommand):
return packages
# Iteratively create models in options["model_names"]
print(f"Creating models: {options['model_names']}\n"
f"Data packages: {options['data_packages']}\n"
f"Rule Packages (only for MLRR): {options['rule_packages']}\n"
f"Eval Packages: {options['eval_packages']}\n"
f"Threshold: {options['threshold']:.2f}")
print(
f"Creating models: {options['model_names']}\n"
f"Data packages: {options['data_packages']}\n"
f"Rule Packages (only for MLRR): {options['rule_packages']}\n"
f"Eval Packages: {options['eval_packages']}\n"
f"Threshold: {options['threshold']:.2f}"
)
data_packages = decode_packages(options["data_packages"])
eval_packages = decode_packages(options["eval_packages"])
rule_packages = decode_packages(options["rule_packages"])
@ -90,10 +94,10 @@ class Command(BaseCommand):
pack,
data_packages=data_packages,
eval_packages=eval_packages,
threshold=options['threshold'],
threshold=options["threshold"],
name=f"EnviFormer - {', '.join(options['data_packages'])} - T{options['threshold']:.2f}",
description=f"EnviFormer transformer trained on {options['data_packages']} "
f"evaluated on {options['eval_packages']}.",
f"evaluated on {options['eval_packages']}.",
)
elif model_name == "mlrr":
model = MLRelativeReasoning.create(
@ -101,10 +105,10 @@ class Command(BaseCommand):
rule_packages=rule_packages,
data_packages=data_packages,
eval_packages=eval_packages,
threshold=options['threshold'],
threshold=options["threshold"],
name=f"ECC - {', '.join(options['data_packages'])} - T{options['threshold']:.2f}",
description=f"ML Relative Reasoning trained on {options['data_packages']} with rules from "
f"{options['rule_packages']} and evaluated on {options['eval_packages']}.",
f"{options['rule_packages']} and evaluated on {options['eval_packages']}.",
)
else:
raise ValueError(f"Cannot create model of type {model_name}, unknown model type")