tqlong

import nltk
from nltk.corpus import treebank

# Tải dữ liệu treebank
nltk.download('treebank')
tagged_sentences = treebank.tagged_sents()

# Chia dữ liệu thành tập huấn luyện và tập kiểm tra
train_size = int(0.8 * len(tagged_sentences))
train_sents = tagged_sentences[:train_size]

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import torch
import torch.nn as nn
import torch.optim as optim
import numpy as np
import matplotlib.pyplot as plt

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import numpy as np
import matplotlib.pyplot as plt
from sklearn.decomposition import PCA
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score
from tensorflow.keras.datasets import cifar10

(x_train, y_train), (x_test, y_test) = cifar10.load_data()

print(f"Train data shape: {x_train.shape}")

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import xgboost as xgb
import pandas as pd
import numpy as np
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score

iris = load_iris()
X = iris.data 
y = iris.target

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import torch
import torch.nn as nn

class IoULoss(nn.Module):
    def __init__(self, num_classes, eps=1e-6):
        """
        IoU Loss for multi-class image segmentation.

        Args:
        - num_classes (int): Number of classes (C).

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import torch
import torch.nn as nn
import torch.optim as optim
from torch.nn.functional import relu, max_pool2d
from torch.utils.data import DataLoader
from torchvision import datasets
from torchvision import transforms as T
from tqdm import tqdm

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#include "display.h"
#include "count.h"

#include <iostream>
using namespace std;

void displayWinning()
{
    const vector<string> figures = {
        "   O \n"

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// TODO: read all numbers (int, float), separated by comma

// TODO: read a table of numbers from a text file, separated by comma

// TODO: read a table of student information from a text file, separated by comma
// (ten, tuoi, gioi tinh, diem trung binh)

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// struct_tutorial.cpp: struct examples
#include <iostream>
#include <vector>
#include <algorithm>

struct Vector {
    int x;
    int y;

    // constructor

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#include <SFML/Graphics.hpp>
#include <iostream>
#include <vector>

typedef std::vector<char> Row;
typedef std::vector<Row> GameState;
const int SIZE=3;

sf::CircleShape createShape(sf::Texture& texture, int i, int j, char player)
{