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import json
import warnings
from typing import Any

from sammo.runners.base import BaseRunner
from sammo.base import LLMResult, Costs
from sammo.schemas import JsonSchema
from sammo.utils import serialize_json

from langchain_core.language_models.base import BaseLanguageModel

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from cgtnnlib.LearningTask import LearningTask
from cgtnnlib.nn.AugmentedReLUNetwork import AugmentedReLUNetwork
from cgtnnlib.training import train_model
from cgtnnlib.datasets import datasets

import torch.optim as optim

p = 0.5
dataset = datasets[0]
model = AugmentedReLUNetwork(

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Position;Theorem;Author;Collective;Comment;Date Lower;Date Upper;Uncertain Date
1;The Irrationality of the Square Root of 2;Pythagoras and his school;;;-500;;
2;Fundamental Theorem of Algebra;Karl Frederich Gauss;;;1799;;
3;The Denumerability of the Rational Numbers;Georg Cantor;;;1867;;
4;Pythagorean Theorem;Pythagoras and his school;;;-500;;
5;Prime Number Theorem;Jacques Hadamard;;;1896;;
5;Prime Number Theorem;Charles-Jean de la Vallee Poussin;;;1896;;
6;Godel’s Incompleteness Theorem;Kurt Godel;;;1931;;
7;Law of Quadratic Reciprocity;Karl Frederich Gauss;;;1801;;
8;The Impossibility of Trisecting the Angle and Doubling the Cube;Pierre Wantzel;;;1837;;

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#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <errno.h>

// Структура для аргументов (предположим, что она уже определена)
typedef struct {
  int s;
} arguments;

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import torch

def dabs_mean_std(
    tensor1: torch.Tensor,
    tensor2: torch.Tensor
):
    dabs: torch.Tensor = torch.abs(tensor2 - tensor1)

    mean = torch.mean(dabs)
    std = torch.std(dabs)

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---@generic A, D
---@param head A
---@param tail D
---@return fun(): A, D
local function cons(head, tail)
  return function ()
    return head, tail
  end
end

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*> \brief \b CLAQZ3
*
*  =========== DOCUMENTATION ===========
*
* Online html documentation available at
*            http://www.netlib.org/lapack/explore-html/
*
*> \htmlonly
*> Download CLAQZ3 + dependencies
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/CLAQZ3.f">

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#lang racket

(define/contract (reverse x)
  (-> exact-integer? exact-integer?)

  (cond ((= x 0) 0)
        ((< x 0) (- (reverse (- x))))
        (else (let ((reduced-x (floor (/ x 10)))
                    (digit (remainder (floor x) 10))
                    (z (expt 10 (round (log x 10)))))

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diff --git a/cgt-nn-rev6wip.ipynb b/cgt-nn-rev6wip.ipynb
index 25792be..0b03781 100644
--- a/cgt-nn-rev6wip.ipynb
+++ b/cgt-nn-rev6wip.ipynb
@@ -910,45 +910,45 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>835</th>\n",
-       "      <td>evaluate_RegularNetwork_2_p0.99_N9</td>\n",

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import curses
from curses import wrapper
from typing import Any
import torch
import torch.nn as nn
import torch.optim as optim
from cgtnnlib.datasets import breast_cancer_dataset, car_evaluation_dataset, student_performance_factors_dataset
from cgtnnlib.AugmentedReLUNetwork import AugmentedReLUNetwork
from cgtnnlib.RegularNetwork import RegularNetwork
from cgtnnlib.training import train_model