التعليمي

import torch.nn as nn import torch.nn.functional as F from dataclasses import dataclass torch.manual_seed(0) @dataclass class Cfg: d_model: int = 192…

print(“\n[5/10] Creating a synthetic multimodal report…”) monthly_data = pd.DataFrame( { “Month”: [“Jan”, “Feb”, “Mar”, “Apr”, “May”, “Jun”], “Query Volume”: [1200,…

def _purge(*prefixes): for name in [m for m in list(sys.modules) if any(m == p or m.startswith(p + “.”) for p…

def extract_function_source(full_text, function_name): text = full_text.replace(“\r\n”, “\n”) fence = re.search(r”“`(?:python)?\n(.*?)“`”, text, flags=re.S | re.I) if fence: text = fence.group(1) pattern…

print(“\n” + “=” * 90) print(“[5] cuTile kernels are defined only if cuda.tile imports successfully”) print(“=” * 90) if cutile_import_ok:…

print(“\n########## 5. ANALYSIS ##########”) import numpy as np, pandas as pd def find_latest_report(): cands = [] for base in [os.path.expanduser(“~/.local/share/garak/garak_runs”),…

mock_server_code = r”’ from fastapi import FastAPI, Request import time app = FastAPI() STATE = {“calls”: 0} @app.post(“/v1/chat/completions”) async def…