Submission #66753998


Source Code Expand

#include <bits/stdc++.h>

// what the fuck
template<typename T, int N>
struct NDVector { using type = std::vector<typename NDVector<T, N - 1>::type>; };
template<typename T>
struct NDVector<T, 1> { using type = std::vector<T>; };

// A tensor is essentially a vector of tensors. (or multidimensional array)
template<typename T, int N>
using Tensor = typename NDVector<T, N>::type;

/**
 * Create a multidimensional vector with the given dimension sizes.
 *
 * In particular, create_vector(N) = create_tensor(N), create_matrix(N, M) = create_tensor(N, M).
 * If you have some weird multidimensional DP, you can create the DP table by doing:
 *      dp = create_tensor(5, 5, 5, 5, 5);
 *
 * Be careful, for a large number of dimensions, this uses a lot of memory and is very cache unfriendly.
 */
template<typename T>
std::vector<T> create_tensor(int N) {
    return std::vector<T>(N);
}
template <typename T, typename... ArgTypes>
Tensor<T, sizeof...(ArgTypes) + 1> create_tensor(int N, ArgTypes... args) {
    auto under = create_tensor<T>(args...);
    return std::vector(N, under);
}

/**
 * Create a matrix of the given dimensions.
 */
template<typename T>
Tensor<T, 2> create_matrix(int N, int M) {
    return create_tensor<T>(N, M);
}

/**
 * Frequently used definitions, like Vector, Matrices, pairs of ints, pairs, triples, etc.
 */
template<typename T>
using Vector = Tensor<T, 1>; // I could use std::vector<T>, but this is just too cool.
template<typename T>
using Matrix = Tensor<T, 2>;

template<typename T1, typename T2>
using Pair = std::pair<T1, T2>;
using PairII = Pair<int, int>;
using PairLL = Pair<long long, long long>;

template<typename T1, typename T2, typename T3>
using Triple = std::tuple<T1, T2, T3>;

/**
 * Read a vector from input. Set start to 1 if you want it to be 1-indexed.
 */
template<typename T>
Vector<T> read_vector(int N, int start = 0) {
    Vector<T> v(start + N);
    for (int i = start; i < (int)v.size(); i++) {
        std::cin >> v[i];
    }
    return v;
}

/**
 * Read a matrix from input. Set start_l to make lines 1-indexed. Same thing for start_c.
 */
template<typename T>
Matrix<T> read_matrix(int N, int M, int start_l = 0, int start_c = 0) {
    Matrix<T> matr = create_matrix<T>(N + start_l, M + start_c);

    for (int l = start_l; l < N + start_l; l++)
        for (int c = start_c; c < M + start_c; c++)
            std::cin >> matr[l][c];

    return matr;
}

/**
 * Print a tensor to the output stream. Prints all indices between i and j, and the elements 
 * are separated by the given separator.
 *
 * To generalize, for each dimension, you give the bounds that you want to print and the separator
 * between each order. To print a matrix, you would do:
 *
 *      print_tensor(matr, std::cout, 0, N - 1, "\n", 0, M - 1, " ");
 */
template<typename T>
void print_tensor(Tensor<T, 1>& tens, std::ostream&fout, int i, int j, const char* sep) {
    for (int t = std::max(i, 0); t <= j && t < (int)tens.size(); t++) {
        fout << tens[t];
        if (t + 1 <= j)
            fout << sep;
    }
}

template<typename T, typename... Sizes>
void print_tensor(
        Tensor<T, sizeof...(Sizes) / 3 + 1>& tens,
        std::ostream& fout, 
        int i, int j, const char* sep, Sizes... sizes) {
    for (int t = std::max(i, 0); t <= j && t < (int)tens.size(); t++) {
        print_tensor<T>(tens[t], fout, sizes...);
        if (t + 1 <= j)
            fout << sep;
    }
}

/**
 * Print a vector to the given output stream with given bounds and separator.
 */
template<typename T>
void print_vector(std::vector<T>& v, std::ostream& fout, int i = 0, int j = (1 << 30), const char* sep = " ") {
    print_tensor<T>(v, fout, i, j, sep);
}

/**
 * Read a vector of pairs. Set start to 1 if you want this to be 1-indexed.
 */
template<typename T1, typename T2>
Vector<Pair<T1, T2>> read_pairvec(int N, int start = 0) {
    Vector<Pair<T1, T2>> input = Vector<Pair<T1, T2>>(start + N);
    for (int i = start; i < start + N; i++)
        std::cin >> input[i].first >> input[i].second;
    return input;
}

/**
 * Read a vector of triples. Set start to 1 if you want this to be 1-indexed.
 *
 * If you need higher order tuples, like quadruples, you're better off using a matrix instead.
 */
template<typename T1, typename T2, typename T3>
Vector<Triple<T1, T2, T3>> read_triplevec(int N, int start = 0) {
    Vector<Triple<T1, T2, T3>> input = Vector<Triple<T1, T2, T3>>(start + N);
    for (int i = start; i < N + start; i++) {
        T1 a;
        T2 b;
        T3 c;
        std::cin >> a >> b >> c;
        input[i] = {a, b, c};
    }
    return input;
}

/**
 * Removes duplicates from vector. Assumes it is sorted.
 */
template<typename T>
void deduplicate(Vector<T>& v) {
    v.resize(std::unique(v.begin(), v.end()) - v.begin());    
}

/**
 * Solve a testcase of the problem. You will code your solution here instead of main.
 */
void solve_test();

/**
 * Call this function if you have a problem with multiple testcases.
 */
void multitest_problem() {
    int T;
    std::cin >> T;

    while (T--) solve_test();
}

int main() {
    std::cin.tie(NULL);
    std::iostream::sync_with_stdio(false);

    // Choose one of the following functions, depending on the problem type.
    solve_test();
    //multitest_problem();

    return 0;
}

void solve_test() {
    int N, Q;
    std::cin >> N >> Q;

    auto X = read_vector<int>(Q, 0);
    auto cap = Vector<int>(1 + N);

    for (int i = 0; i < Q; i++) {
        if (X[i] >= 1) {
            cap[X[i]]++;
            std::cout << X[i] << " ";
        } else {
            int best = 1;
            for (int i = 1; i <= N; i++)
                if (cap[i] < cap[best])
                    best = i;
            cap[best]++;
            std::cout << best << " ";
        }
    }
}


Submission Info

Submission Time
Task B - Reverse Proxy
User Tinca_Matei
Language C++ 23 (gcc 12.2)
Score 200
Code Size 6001 Byte
Status AC
Exec Time 1 ms
Memory 3616 KiB

Judge Result

Set Name Sample All
Score / Max Score 0 / 0 200 / 200
Status
AC × 3
AC × 42
Set Name Test Cases
Sample sample_01.txt, sample_02.txt, sample_03.txt
All sample_01.txt, sample_02.txt, sample_03.txt, test_01.txt, test_02.txt, test_03.txt, test_04.txt, test_05.txt, test_06.txt, test_07.txt, test_08.txt, test_09.txt, test_10.txt, test_11.txt, test_12.txt, test_13.txt, test_14.txt, test_15.txt, test_16.txt, test_17.txt, test_18.txt, test_19.txt, test_20.txt, test_21.txt, test_22.txt, test_23.txt, test_24.txt, test_25.txt, test_26.txt, test_27.txt, test_28.txt, test_29.txt, test_30.txt, test_31.txt, test_32.txt, test_33.txt, test_34.txt, test_35.txt, test_36.txt, test_37.txt, test_38.txt, test_39.txt
Case Name Status Exec Time Memory
sample_01.txt AC 1 ms 3408 KiB
sample_02.txt AC 1 ms 3460 KiB
sample_03.txt AC 1 ms 3472 KiB
test_01.txt AC 1 ms 3400 KiB
test_02.txt AC 1 ms 3480 KiB
test_03.txt AC 1 ms 3484 KiB
test_04.txt AC 1 ms 3552 KiB
test_05.txt AC 1 ms 3404 KiB
test_06.txt AC 1 ms 3412 KiB
test_07.txt AC 1 ms 3484 KiB
test_08.txt AC 1 ms 3492 KiB
test_09.txt AC 1 ms 3476 KiB
test_10.txt AC 1 ms 3340 KiB
test_11.txt AC 1 ms 3420 KiB
test_12.txt AC 1 ms 3428 KiB
test_13.txt AC 1 ms 3476 KiB
test_14.txt AC 1 ms 3484 KiB
test_15.txt AC 1 ms 3612 KiB
test_16.txt AC 1 ms 3404 KiB
test_17.txt AC 1 ms 3456 KiB
test_18.txt AC 1 ms 3484 KiB
test_19.txt AC 1 ms 3344 KiB
test_20.txt AC 1 ms 3432 KiB
test_21.txt AC 1 ms 3424 KiB
test_22.txt AC 1 ms 3476 KiB
test_23.txt AC 1 ms 3348 KiB
test_24.txt AC 1 ms 3424 KiB
test_25.txt AC 1 ms 3616 KiB
test_26.txt AC 1 ms 3552 KiB
test_27.txt AC 1 ms 3608 KiB
test_28.txt AC 1 ms 3548 KiB
test_29.txt AC 1 ms 3468 KiB
test_30.txt AC 1 ms 3432 KiB
test_31.txt AC 1 ms 3484 KiB
test_32.txt AC 1 ms 3424 KiB
test_33.txt AC 1 ms 3404 KiB
test_34.txt AC 1 ms 3556 KiB
test_35.txt AC 1 ms 3560 KiB
test_36.txt AC 1 ms 3484 KiB
test_37.txt AC 1 ms 3488 KiB
test_38.txt AC 1 ms 3404 KiB
test_39.txt AC 1 ms 3476 KiB