python

from sklearn.ensemble import RandomForestClassifier, HistGradientBoostingClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import roc_auc_score
from sklearn.pipeline import Pipeline
from sklearn.impute import SimpleImputer

import factory
from factory.django import DjangoModelFactory
from factory import Faker, SubFactory, post_generation
from blog.models import Post, Comment, Tag
from django.contrib.auth import get_user_model

import torch

device = 'cuda' if torch.cuda.is_available() else 'cpu'
features = torch.tensor([[1.0, 2.0], [3.0, 4.0]], requires_grad=True, device=device)
weights = torch.tensor([[0.2], [0.8]], requires_grad=True, device=device)

from django.contrib.auth import views as auth_views
from django.urls import path

app_name = 'accounts'

urlpatterns = [

from celery import shared_task
from django.core.mail import send_mail
from django.contrib.auth import get_user_model

User = get_user_model()

from django.conf import settings
from datetime import datetime


def site_settings(request):
    """Add site-wide settings to template context."""

import re

text = 'INC-102301 resolved on 2026-04-06 after payment failure for order ORD-99182.'

patterns = {
    'incident_id': r'INC-[0-9]{6}',

import torch.nn as nn
from torchvision.models import resnet50, ResNet50_Weights

model = resnet50(weights=ResNet50_Weights.IMAGENET1K_V2)

for parameter in model.parameters():

from django import forms
from .models import Event


class EventForm(forms.ModelForm):
    class Meta:

import functools
import threading
import time
from collections import OrderedDict

import numpy as np

embeddings = np.array([
    [0.9, 0.1, 0.2],
    [0.1, 0.8, 0.3],
    [0.7, 0.2, 0.4],