row_id
int64 0
48.4k
| init_message
stringlengths 1
342k
| conversation_hash
stringlengths 32
32
| scores
dict |
|---|---|---|---|
34,537
|
In my application I recieve a text and render in the text bubble. I get the text using my getText function in JavaScript file. However I have a problem when somebody sends me a message that is wrapped within html tags such as b, u or i. The text appears with visible html tags instead of applied inline styles that should have been applied to them. What can I do so my text would be show up with applied inline styles instead of wrapped inside of html tags?
Here is my getText function code.
getText() {
let str = this.getMessageText();
if (!str) return "";
let parser = Parser.build().withHTMLLinkAsText();
return parser.parse(str);
}
|
c496f3555ba69ce9dca1d9a38e823be4
|
{
"intermediate": 0.6098973155021667,
"beginner": 0.22604788839817047,
"expert": 0.1640547811985016
}
|
34,538
|
What code is used to build in data set
|
59e88032a686a82c66065a8a01c8a5c0
|
{
"intermediate": 0.31836187839508057,
"beginner": 0.22247086465358734,
"expert": 0.4591672718524933
}
|
34,539
|
I have a date coulmn on spreadsheet in the format of dd/mm/yyyy how do I get a column with just month and year
|
4bbcd4e51ef97752f0715ece2c3df424
|
{
"intermediate": 0.3242618441581726,
"beginner": 0.2515319287776947,
"expert": 0.4242062270641327
}
|
34,540
|
If I have a text that appears on my page wrapped within html tags like so <b>My test text</b>, then using JavaScript how could I parse it in a way that would apply the bold style to it to the text but will also remove these tags so I wouldn't see them?
|
0ffd35472c231ee5e2585db4d863eb25
|
{
"intermediate": 0.6047167181968689,
"beginner": 0.12135821580886841,
"expert": 0.2739250957965851
}
|
34,541
|
Create a linux redhat daemon process to generate reports automatically. For example, you may consider generating the following reports.
• System errors (or messages) for the last 7 days
• Logins history for the last 7 days
Create a process that runs in the background that generate reports automatically.
|
1a936f0d0bf7e7e46330ee289c6a23e6
|
{
"intermediate": 0.39211076498031616,
"beginner": 0.3158562481403351,
"expert": 0.29203295707702637
}
|
34,542
|
configure.ac:418: the top level
configure.ac:418: warning: The macro `AC_TRY_RUN' is obsolete.
configure.ac:418: You should run autoupdate.
./lib/autoconf/general.m4:2997: AC_TRY_RUN is expanded from...
acinclude.m4:251: LIBFFI_CHECK_LINKER_FEATURES is expanded from...
acinclude.m4:353: LIBFFI_ENABLE_SYMVERS is expanded from...
configure.ac:418: the top level
configure.ac:418: warning: The macro `AC_TRY_LINK' is obsolete.
configure.ac:418: You should run autoupdate.
./lib/autoconf/general.m4:2920: AC_TRY_LINK is expanded from...
acinclude.m4:353: LIBFFI_ENABLE_SYMVERS is expanded from...
configure.ac:418: the top level
configure.ac:41: error: possibly undefined macro: AC_PROG_LIBTOOL
If this token and others are legitimate, please use m4_pattern_allow.
See the Autoconf documentation.
configure:8578: error: possibly undefined macro: AC_PROG_LD
autoreconf: error: /usr/bin/autoconf failed with exit status: 1
STDERR:
# Command failed: ['/usr/bin/python3', '-m', 'pythonforandroid.toolchain', 'create', '--dist_name=myapp', '--bootstrap=sdl2', '--requirements=python3,kivy', '--arch=arm64-v8a', '--arch=armeabi-v7a', '--copy-libs', '--color=always', '--storage-dir=/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a', '--ndk-api=21', '--ignore-setup-py', '--debug']
# ENVIRONMENT:
# SHELL = '/bin/bash'
# NV_LIBCUBLAS_VERSION = '11.11.3.6-1'
# NVIDIA_VISIBLE_DEVICES = 'all'
# COLAB_JUPYTER_TRANSPORT = 'ipc'
# NV_NVML_DEV_VERSION = '11.8.86-1'
# NV_CUDNN_PACKAGE_NAME = 'libcudnn8'
# CGROUP_MEMORY_EVENTS = '/sys/fs/cgroup/memory.events /var/colab/cgroup/jupyter-children/memory.events'
# NV_LIBNCCL_DEV_PACKAGE = 'libnccl-dev=2.15.5-1+cuda11.8'
# NV_LIBNCCL_DEV_PACKAGE_VERSION = '2.15.5-1'
# VM_GCE_METADATA_HOST = '169.254.169.253'
# HOSTNAME = 'e17f45b2d48e'
# LANGUAGE = 'en_US'
# TBE_RUNTIME_ADDR = '172.28.0.1:8011'
# GCE_METADATA_TIMEOUT = '3'
# NVIDIA_REQUIRE_CUDA = ('cuda>=11.8 brand=tesla,driver>=470,driver<471 '
'brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 '
'brand=nvidiartx,driver>=470,driver<471 brand=geforce,driver>=470,driver<471 '
'brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 '
'brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 '
'brand=titanrtx,driver>=470,driver<471')
# NV_LIBCUBLAS_DEV_PACKAGE = 'libcublas-dev-11-8=11.11.3.6-1'
# NV_NVTX_VERSION = '11.8.86-1'
# COLAB_JUPYTER_IP = '172.28.0.12'
# NV_CUDA_CUDART_DEV_VERSION = '11.8.89-1'
# NV_LIBCUSPARSE_VERSION = '11.7.5.86-1'
# COLAB_LANGUAGE_SERVER_PROXY_ROOT_URL = 'http://172.28.0.1:8013/'
# NV_LIBNPP_VERSION = '11.8.0.86-1'
# NCCL_VERSION = '2.15.5-1'
# KMP_LISTEN_PORT = '6000'
# TF_FORCE_GPU_ALLOW_GROWTH = 'true'
# ENV = '/root/.bashrc'
# PWD = '/content'
# TBE_EPHEM_CREDS_ADDR = '172.28.0.1:8009'
# COLAB_LANGUAGE_SERVER_PROXY_REQUEST_TIMEOUT = '30s'
# TBE_CREDS_ADDR = '172.28.0.1:8008'
# NV_CUDNN_PACKAGE = 'libcudnn8=8.9.6.50-1+cuda11.8'
# NVIDIA_DRIVER_CAPABILITIES = 'compute,utility'
# COLAB_JUPYTER_TOKEN = ''
# LAST_FORCED_REBUILD = '20231120'
# NV_NVPROF_DEV_PACKAGE = 'cuda-nvprof-11-8=11.8.87-1'
# NV_LIBNPP_PACKAGE = 'libnpp-11-8=11.8.0.86-1'
# NV_LIBNCCL_DEV_PACKAGE_NAME = 'libnccl-dev'
# TCLLIBPATH = '/usr/share/tcltk/tcllib1.20'
# NV_LIBCUBLAS_DEV_VERSION = '11.11.3.6-1'
# COLAB_KERNEL_MANAGER_PROXY_HOST = '172.28.0.12'
# NVIDIA_PRODUCT_NAME = 'CUDA'
# NV_LIBCUBLAS_DEV_PACKAGE_NAME = 'libcublas-dev-11-8'
# USE_AUTH_EPHEM = '1'
# NV_CUDA_CUDART_VERSION = '11.8.89-1'
# COLAB_WARMUP_DEFAULTS = '1'
# HOME = '/root'
# LANG = 'en_US.UTF-8'
# COLUMNS = '100'
# CUDA_VERSION = '11.8.0'
# CLOUDSDK_CONFIG = '/content/.config'
# NV_LIBCUBLAS_PACKAGE = 'libcublas-11-8=11.11.3.6-1'
# NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE = 'cuda-nsight-compute-11-8=11.8.0-1'
# COLAB_RELEASE_TAG = 'release-colab_20231204-060134_RC00'
# PYDEVD_USE_FRAME_EVAL = 'NO'
# KMP_TARGET_PORT = '9000'
# CLICOLOR = '1'
# KMP_EXTRA_ARGS = ('--logtostderr --listen_host=172.28.0.12 --target_host=172.28.0.12 '
'--tunnel_background_save_url=https://colab.research.google.com/tun/m/cc48301118ce562b961b3c22d803539adc1e0c19/m-s-1gja9ybkdisul '
'--tunnel_background_save_delay=10s '
'--tunnel_periodic_background_save_frequency=30m0s '
'--enable_output_coalescing=true --output_coalescing_required=true')
# NV_LIBNPP_DEV_PACKAGE = 'libnpp-dev-11-8=11.8.0.86-1'
# COLAB_LANGUAGE_SERVER_PROXY_LSP_DIRS = '/datalab/web/pyright/typeshed-fallback/stdlib,/usr/local/lib/python3.10/dist-packages'
# NV_LIBCUBLAS_PACKAGE_NAME = 'libcublas-11-8'
# COLAB_KERNEL_MANAGER_PROXY_PORT = '6000'
# CLOUDSDK_PYTHON = 'python3'
# NV_LIBNPP_DEV_VERSION = '11.8.0.86-1'
# ENABLE_DIRECTORYPREFETCHER = '1'
# NO_GCE_CHECK = 'False'
# JPY_PARENT_PID = '80'
# PYTHONPATH = '/env/python'
# TERM = 'xterm-color'
# NV_LIBCUSPARSE_DEV_VERSION = '11.7.5.86-1'
# GIT_PAGER = 'cat'
# LIBRARY_PATH = '/usr/local/cuda/lib64/stubs'
# NV_CUDNN_VERSION = '8.9.6.50'
# SHLVL = '0'
# PAGER = 'cat'
# COLAB_LANGUAGE_SERVER_PROXY = '/usr/colab/bin/language_service'
# NV_CUDA_LIB_VERSION = '11.8.0-1'
# NVARCH = 'x86_64'
# NV_CUDNN_PACKAGE_DEV = 'libcudnn8-dev=8.9.6.50-1+cuda11.8'
# NV_CUDA_COMPAT_PACKAGE = 'cuda-compat-11-8'
# MPLBACKEND = 'module://ipykernel.pylab.backend_inline'
# NV_LIBNCCL_PACKAGE = 'libnccl2=2.15.5-1+cuda11.8'
# LD_LIBRARY_PATH = '/usr/local/nvidia/lib:/usr/local/nvidia/lib64'
# COLAB_GPU = ''
# GCS_READ_CACHE_BLOCK_SIZE_MB = '16'
# NV_CUDA_NSIGHT_COMPUTE_VERSION = '11.8.0-1'
# NV_NVPROF_VERSION = '11.8.87-1'
# LC_ALL = 'en_US.UTF-8'
# COLAB_FILE_HANDLER_ADDR = 'localhost:3453'
# PATH = '/root/.buildozer/android/platform/apache-ant-1.9.4/bin:/opt/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/tools/node/bin:/tools/google-cloud-sdk/bin'
# NV_LIBNCCL_PACKAGE_NAME = 'libnccl2'
# COLAB_DEBUG_ADAPTER_MUX_PATH = '/usr/local/bin/dap_multiplexer'
# NV_LIBNCCL_PACKAGE_VERSION = '2.15.5-1'
# PYTHONWARNINGS = 'ignore:::pip._internal.cli.base_command'
# DEBIAN_FRONTEND = 'noninteractive'
# COLAB_BACKEND_VERSION = 'next'
# OLDPWD = '/'
# _ = '/usr/local/bin/buildozer'
# PACKAGES_PATH = '/root/.buildozer/android/packages'
# ANDROIDSDK = '/root/.buildozer/android/platform/android-sdk'
# ANDROIDNDK = '/root/.buildozer/android/platform/android-ndk-r25b'
# ANDROIDAPI = '31'
# ANDROIDMINAPI = '21'
#
# Buildozer failed to execute the last command
# The error might be hidden in the log above this error
# Please read the full log, and search for it before
# raising an issue with buildozer itself.
# In case of a bug report, please add a full log with log_level = 2
|
832345104f4031d073b418453e6483ee
|
{
"intermediate": 0.2625933885574341,
"beginner": 0.47018417716026306,
"expert": 0.26722240447998047
}
|
34,543
|
Write a hello world for esp32 using idf
|
e703413f1e25bd190dd2c7971b2678b0
|
{
"intermediate": 0.3682306408882141,
"beginner": 0.33845967054367065,
"expert": 0.2933097183704376
}
|
34,544
|
if on my page I have a text that appears like this <b>My test text</b> then what do I need to do in JavaScript that will let me to remove these html tags but also apply its styles to the text? I need a function that would check if the text is wrapped within b,i or u tags and apply all of their styles to text while aslo hiding the html tags. Not that the text may have several styles applied at the same time, like being bold and italic at the same time
|
b7cecdbd19e4e592039f45b98302cce7
|
{
"intermediate": 0.6555880308151245,
"beginner": 0.11642934381961823,
"expert": 0.22798258066177368
}
|
34,545
|
what is quad bayer
|
c205cc7b603c0caef3e95c418a4ddbcb
|
{
"intermediate": 0.3687800467014313,
"beginner": 0.18814539909362793,
"expert": 0.4430745542049408
}
|
34,546
|
make a heap
|
a9e70e3797e3d2043b7126e111657820
|
{
"intermediate": 0.3626258969306946,
"beginner": 0.26729676127433777,
"expert": 0.37007731199264526
}
|
34,547
|
Бедный Ваня
Ваня всегда мечтал стать художником, но его работы были настолько посредственными, что никто не хотел их покупать. Тогда он решил, что станет арт-диллером, но найти достойных живописцев он не сумел, поэтому придумал мошшеническую схему с продажей копий работ известных художников, которые он выдавал за подлинники. В галерее, в которой работает Ваня, каждой картине соответствует уникальный код. Чтобы заработать больше денег, Ваня решил продавать работы Павлу Четверякову -- самому известному потомственному коллекционеру города. Друзья арт-диллеры рассказали Ване, что у Павла есть особый алгоритм, который определяет, является ли картина подлинником, и рассказали, как его можно обойти. Четверяков сравнивает уникальный код из собственной базы данных с кодом картины, которую собирается приобрести. Эти коды достались ему от дедушки, который записывал их вручную, поэтому некоторые из них не совсем корректны, поэтому Павел использует коэффициент
k
k, отвечающий за допустимое количество отличий от кода картины, которую он планирует купить. Если отличий меньше, чем
k
k, то он приобретает её к себе в коллекцию. Ване удалось раздобыть коды Павла. Помогите ему узнать, приобретёт ли коллекционер его работу.
Входные данные
В первой строке задаются три числа:
n
<
5
∗
1
0
6
n<5∗10
6
(длина закодированного с помощью RLE кода Павла Четверякова),
m
<
5
∗
1
0
6
m<5∗10
6
(длина длина закодированного с помощью RLE кода картины Вани),
k
<
5
∗
1
0
9
k<5∗10
9
(количество возможных отличий)
Выходные данные
Вывести
Y
e
s
Yes, если Павел приобретёт картину, иначе вывести
N
o
No. #include <iostream>
int GetNum(std::string& str, int& ind) {
int num = 0;
while (ind < str.length() && str[ind] < 'A') {
num = num * 10 + (str[ind] - '0');
++ind;
}
--ind;
return num;
}
int main() {
int pavel, ivan, k;
std::cin >> pavel >> ivan >> k;
std::string str_pavel, str_ivan;
std::cin >> str_pavel;
std::cin >> str_ivan;
int count = 0;
int i = 0;
int j = 0;
while (i < pavel || j < ivan) {
if (count >= k) {
break;
}
if (i == pavel || j == ivan) {
if (j == ivan) {
for (int l = j + 1; l < pavel; ++l) {
int num = GetNum(str_pavel, l);
count += num;
}
break;
} else {
for (int l = j + 1; l < ivan; ++l) {
int num = GetNum(str_ivan, l);
count += num;
}
break;
}
} else {
char symbol_pavel = str_pavel[i];
char symbol_ivan = str_ivan[j];
++i;
++j;
int num_pavel = GetNum(str_pavel, i);
int num_ivan = GetNum(str_ivan, j);
if (num_pavel == num_ivan) {
if (symbol_pavel != symbol_ivan) {
count += num_pavel;
}
} else if (num_pavel < num_ivan) {
j -= num_ivan - num_pavel;
count += num_pavel;
} else {
i -= num_pavel - num_ivan;
count += num_ivan;
}
}
++i;
++j;
}
std::cout << count << '\n';
if (count < k) {
std::cout << "Yes";
} else {
std::cout << "No";
}
return 0;
}
why when input is 5 5 4
a4F13
F13a4 it returns 4
No when it should return 8
No
|
4ea15cdecaded5d08565768fc5862afd
|
{
"intermediate": 0.19476592540740967,
"beginner": 0.597236692905426,
"expert": 0.2079973816871643
}
|
34,548
|
what is python code for using Pie Plot to explain a categorical variable with a numerical variable for data sets
|
ff266d87691f7e9f707d5fcafd34558e
|
{
"intermediate": 0.48508334159851074,
"beginner": 0.24028387665748596,
"expert": 0.2746327221393585
}
|
34,549
|
public async Task UpdateUserAsync1( SailplayCredentials credentials, UpdateUser requestData, CancellationToken cancellationToken) { var tokenResult = await this.authorisationExecutor.GetAuthorizationTokenAsync( credentials: credentials, cancellationToken: cancellationToken); var apiResponse = await Policy.HandleResult(apiResult => apiResult.IsAuthorizationTokenError) .RetryAsync( retryCount: 1, onRetryAsync: async (_, _, _) => { tokenResult = await this.authorisationExecutor.RenewAuthorizationTokenAsync( credentials: credentials, cancellationToken: cancellationToken); }) .ExecuteAsync( async () => await tokenResult .Match( onSuccess: async token => { var request = HttpRequestMessageFactory .BuildPost(ApiPath.UsersUpdate); var tokenFormData = FormDataFactory .FromToken(token.Token); var storeDepartmentIdFormData = FormDataFactory .FromStoreDepartmentId(credentials.StoreDepartmentId); var keyValuePairs = new List>() { tokenFormData, storeDepartmentIdFormData, }; keyValuePairs.AddRange(FormDataFactory.FromUserId(requestData.UserId)); requestData.Phone .MatchSome(phone => keyValuePairs.Add(FormDataFactory.FromNewPhone(phone))); requestData.Email .MatchSome(email => keyValuePairs.Add(FormDataFactory.FromNewEmail(email))); requestData.FirstName .MatchSome(firstName => keyValuePairs.Add(FormDataFactory.FromFirstName(firstName))); requestData.MiddleName .MatchSome(middleName => keyValuePairs.Add(FormDataFactory.FromMiddleName(middleName))); requestData.LastName .MatchSome(lastName => keyValuePairs.Add(FormDataFactory.FromLastName(lastName))); requestData.BirthDate .MatchSome(birthDate => keyValuePairs.Add(FormDataFactory.FromBirthDate(birthDate))); requestData.Sex .MatchSome(sex => keyValuePairs.Add(FormDataFactory.FromSex(sex))); requestData.RegisterDate .MatchSome( registerDate => keyValuePairs.Add(FormDataFactory.FromRegisterDate(registerDate))); request.Content = new FormUrlEncodedContent(keyValuePairs); return await this .requestExecutor.ExecuteApiRequestAsync( request: request, cancellationToken: cancellationToken, token: token.Token); }, onError: result => Task.FromResult( SailplayApiResult.FromError( statusCode: result.ErrorCode, message: result.Message)), onUnexpectedHttpStatusCode: result => Task.FromResult( SailplayApiResult.FromUnexpectedHttpStatusCode( httpStatusCode: result.StatusCode)))); return apiResponse.Match( onSuccess: UpdateUserResult.FromSuccess, onError: errorResult => errorResult.ErrorCode switch { ApiResponse.ErrorCodes.InvalidValue => UpdateUserResult.FromError( ErrorResult.FromInvalidValue( errorCode: errorResult.ErrorCode, message: errorResult.Message)), ApiResponse.ErrorCodes.UserNotFound => UpdateUserResult.FromError( ErrorResult.FromUserNotFound( errorCode: errorResult.ErrorCode, message: errorResult.Message)), ApiResponse.ErrorCodes.EmailIsUsed => UpdateUserResult.FromError( ErrorResult.FromEmailIsUsed( errorCode: errorResult.ErrorCode, message: errorResult.Message)), ApiResponse.ErrorCodes.PhoneIsUsed => UpdateUserResult.FromError( ErrorResult.FromPhoneIsUsed( errorCode: errorResult.ErrorCode, message: errorResult.Message)), _ => UpdateUserResult.FromError( ErrorResult.FromGeneralError( errorCode: errorResult.ErrorCode, message: errorResult.Message)), }, onUnexpectedHttpStatusCode: UpdateUserResult.FromUnexpectedHttpStatusCode); } namespace RetailRocket.Sailplay.HttpApi.Client.StrictClient { using System.Threading; using System.Threading.Tasks; using RetailRocket.Sailplay.HttpApi.Client.StrictClient.Ports; using RetailRocket.Sailplay.HttpApi.Client.ValueTypes; using RetailRocket.Sailplay.HttpApi.Client.ValueTypes.Results; internal class AuthorisationExecutor { private readonly ITokenProvider tokenProvider; public AuthorisationExecutor( ITokenProvider tokenProvider) { this.tokenProvider = tokenProvider; } public async Task GetAuthorizationTokenAsync( SailplayCredentials credentials, CancellationToken cancellationToken) { var tokenResult = await this.tokenProvider .GetTokenAsync( credentials: credentials, cancellationToken: cancellationToken); return tokenResult; } public async Task RenewAuthorizationTokenAsync( SailplayCredentials credentials, CancellationToken cancellationToken) { var tokenResult = await this.tokenProvider .RenewTokenAsync( credentials: credentials, cancellationToken: cancellationToken); return tokenResult; } } } namespace RetailRocket.Sailplay.HttpApi.Client.StrictClient { using System.Diagnostics; using System.Net; using System.Net.Http; using System.Net.Http.Json; using System.Threading; using System.Threading.Tasks; using RetailRocket.Sailplay.HttpApi.Client.StrictClient.Ports; using RetailRocket.Sailplay.HttpApi.Client.StrictClient.Responses; using RetailRocket.Sailplay.HttpApi.Client.ValueTypes.Results; internal class RequestExecutor : IRequestExecutor { private readonly IMetricsCollector metricsCollector; private readonly HttpClient httpClient; public RequestExecutor( IMetricsCollector metricsCollector, HttpClient httpClient) { this.metricsCollector = metricsCollector; this.httpClient = httpClient; } public async Task ExecuteApiRequestAsync( HttpRequestMessage request, CancellationToken cancellationToken, string token) { var stopwatch = Stopwatch.StartNew(); using var httpResponseMessage = await this .httpClient .SendAsync( request: request, cancellationToken: cancellationToken); this.metricsCollector.CollectHttpRequestDuration( uri: request.RequestUri, statusCode: httpResponseMessage.StatusCode, elapsedMilliseconds: stopwatch.ElapsedMilliseconds); var result = await this.MapHttpResponseAsync( httpResponseMessage: httpResponseMessage, cancellationToken: cancellationToken); return result; } private async Task MapHttpResponseAsync( HttpResponseMessage httpResponseMessage, CancellationToken cancellationToken) { var basicResponse = await httpResponseMessage .Content .ReadFromJsonAsync( cancellationToken: cancellationToken); return httpResponseMessage.StatusCode switch { HttpStatusCode.OK => basicResponse!.Match( onStatusOk: SailplayApiResult.FromSuccess, onStatusError: SailplayApiResult.FromError), _ => SailplayApiResult.FromUnexpectedHttpStatusCode(httpResponseMessage.StatusCode), }; } } } Отрефактори метод UpdateUserAsync1, максимально сократив его. Разнести по классам RequestExecutor и AuthorisationExecutor. В общем, сделай красиво.
|
3deee9a16e6d8fe0dca9a0ccece99623
|
{
"intermediate": 0.26059603691101074,
"beginner": 0.6150007247924805,
"expert": 0.12440326809883118
}
|
34,550
|
can you show me the example for this function STR_TO_DATE()?
|
2471bd23221d754bbcc04707474abd1e
|
{
"intermediate": 0.3986417353153229,
"beginner": 0.2894085943698883,
"expert": 0.311949759721756
}
|
34,551
|
function optimizeHeatExchanger()
% NSGA-II parameters
nPop = 100; % Population size
maxGen = 30; % Maximum number of generations
pCrossover = 0.9; % Crossover probability
% Optimization options
options = gaoptimset(‘PopulationType’, ‘doubleVector’, …
‘PopulationSize’, nPop, …
‘Generations’, maxGen, …
‘CrossoverFraction’, pCrossover, …
‘ParetoFraction’, 0.35, …
‘PlotFcn’, @gaplotpareto);
% Lower and upper bounds for design variables
lb = [5, 3, 1, 0.15, 300];
ub = [10, 6, 2, 0.3, 800];
% Run the NSGA-II optimizer
[x, fval] = gamultiobj(@plateFinHeatExchanger, 5, [], [], [], [], lb, ub, options);
end
function [f, c] = plateFinHeatExchanger(x)
% Define the design parameters
h = x(1); % fin height
l = x(2); % fin pitch
s = x(3); % fin spacing
t = x(4); % fin thickness
Re = x(5); % Reynolds number
% Evaluate the objective functions
f1 = -ColburnFactor(h, l, s, t, Re); % Negative sign because we want to maximize
f2 = FrictionFactor(h, l, s, t, Re);
% Combine the objectives
f = [f1, f2];
% Define the constraints
c = []; % No nonlinear constraints in this case
end
function j = ColburnFactor(h, l, s, t, Re)
% Colburn factor calculation for laminar and turbulent range
if (Re >= 300 && Re <= 800)
j = 0.661 * (Re^(-0.651)) * ((s/h)^(-0.343)) * ((t/s)^(-0.538)) * ((t/l)^(0.305));
elseif (Re >= 1000 && Re <= 15000)
j = 0.185 * (Re^(-0.396)) * ((s/h)^(-0.178)) * ((t/s)^(-0.403)) * ((t/l)^(0.29));
else
error(‘Reynolds number is out of the valid range for the provided formula.’);
end
end
function f = FrictionFactor(h, l, s, t, Re)
% Friction factor calculation for laminar and turbulent range
if (Re >= 300 && Re <= 800)
f = 10.882 * (Re^(-0.79)) * ((s/h)^(-0.359)) * ((t/s)^(-0.187)) * ((t/l)^(0.284));
elseif (Re >= 1000 && Re <= 15000)
f = 2.237 * (Re^(-0.236)) * ((s/h)^(-0.347)) * ((t/s)^(-0.151)) * ((t/l)^(0.639));
else
error(‘Reynolds number is out of the valid range for the provided formula.’);
end
end
Output of this code
% Call the main function to execute the optimization
optimizeHeatExchanger();
|
f74eea3f5f26fc67bb4a53680377f1e6
|
{
"intermediate": 0.24823904037475586,
"beginner": 0.46192291378974915,
"expert": 0.28983813524246216
}
|
34,552
|
Пусть утро будет нежным!
Сидя у себя в офисе в Калифорнии, Марк Цукерберг чуть не подавился молочным латте без лактозы, когда увидел какое количество памяти занимают картинки с добрым утром вашей бабушки в WhatsApp. В скором порядке он созвал внезапную планерку талантливейших кодировщиков со всего мира, где единогласно пришли к решению о сжатии всех картинок через алгоритм LZ78.
Входные данные
Строка
s
s (
∣
s
∣
≤
∣s∣≤
5
∗
1
0
5
5∗10
5
) , состоящая из строчных латинских букв, обозначающая метаданные файла, который необходимо сжать.
Выходные данные
На каждой новой строчке необходимо последовательно вывести список пар
p
o
s
pos и
n
e
x
t
next, где
p
o
s
pos - номер в словаре самого длинного найденного префикса и
n
e
x
t
next - символ, который следует за этим префиксом. #include <iostream>
#include <vector>
#include <string>
struct Node{
int pos;
char next;
};
struct Dict{
int ind = 0;
std::string word;
int pos;
int height = 1;
Dict* left = nullptr;
Dict* right = nullptr;
};
int GetHeight(Dict* temp) {
if (temp == nullptr) {
return 0;
}
return temp->height;
}
Dict* LeftRotate(Dict* temp) {
Dict* new_root = temp->right;
Dict* new_child = new_root->left;
new_root->left = temp;
temp->right = new_child;
if (GetHeight(temp->left) > GetHeight(temp->right)) {
temp->height = GetHeight(temp->left) + 1;
} else {
temp->height = GetHeight(temp->right) + 1;
}
if (GetHeight(new_root->left) > GetHeight(new_root->right)) {
new_root->height = GetHeight(new_root->left) + 1;
} else {
new_root->height = GetHeight(new_root->right) + 1;
}
return new_root;
}
Dict* RightRotate(Dict* temp) {
Dict* new_root = temp->left;
Dict* new_child = new_root->right;
new_root->right = temp;
temp->left = new_child;
if (GetHeight(temp->left) > GetHeight(temp->right)) {
temp->height = GetHeight(temp->left) + 1;
} else {
temp->height = GetHeight(temp->right) + 1;
}
if (GetHeight(new_root->left) > GetHeight(new_root->right)) {
new_root->height = GetHeight(new_root->left) + 1;
} else {
new_root->height = GetHeight(new_root->right) + 1;
}
return new_root;
}
int GetBalance(Dict* temp) {
if (temp == nullptr) {
return 0;
}
return GetHeight(temp->left) - GetHeight(temp->right);
}
Dict* Balance(Dict* temp) {
if (GetHeight(temp->left) > GetHeight(temp->right)) {
temp->height = GetHeight(temp->left) + 1;
} else {
temp->height = GetHeight(temp->right) + 1;
}
int balance = GetBalance(temp);
if (balance < -1 && GetBalance(temp->right) > 0) {
temp->right = RightRotate(temp->right);
return LeftRotate(temp);
}
if (balance < -1 && GetBalance(temp->right) <= 0) {
return LeftRotate(temp);
}
if (balance > 1 && GetBalance(temp->left) < 0) {
temp->left = LeftRotate(temp->left);
return RightRotate(temp);
}
if (balance > 1 && GetBalance(temp->left) >= 0) {
return RightRotate(temp);
}
return temp;
}
Dict* Insert(Dict* temp, int pos, std::string word, int& ind) {
if (temp == nullptr) {
temp = new Dict();
temp->pos = pos;
temp->ind = ind;
++ind;
return temp;
}
if (word > temp->word) {
temp->right = Insert(temp->right, pos, word, ind);
} else {
temp->left = Insert(temp->left, pos, word, ind);
}
return Balance(temp);
}
bool Exists(Dict* temp, std::string word) {
while (temp != nullptr) {
if (word > temp->word) {
temp = temp->right;
} else if (word < temp->word) {
temp = temp->left;
} else {
return true;
}
}
return false;
}
int FindPos(Dict* temp, std::string word) {
while (temp != nullptr) {
if (word > temp->word) {
temp = temp->right;
} else if (word < temp->word) {
temp = temp->left;
} else {
return temp->ind;
}
}
return -1;
}
int main() {
std::ios_base::sync_with_stdio(false);
std::cin.tie(0);
std::string s;
std::cin >> s;
std::string buffer = "";
Dict* root = nullptr;
int ind = 0;
std::vector<Node*> answer;
for (int i = 0; i < s.length(); ++i) {
if (Exists(root, buffer + s[i])) {
buffer += s[i];
} else {
int pos = FindPos(root, buffer);
Node* newNode = new Node();
newNode->pos = pos;
newNode->next = s[i];
answer.push_back(newNode);
root = Insert(root, pos, buffer + s[i], ind);
buffer = "";
}
}
if (!buffer.empty()) {
Node* newNode = new Node();
int pos = FindPos(root, buffer);
newNode->pos = pos;
answer.push_back(newNode);
}
std::cout << answer[0]->pos << " " << answer[0]->next;
for (int i = 1; i < answer.size(); ++i) {
std::cout << '\n' << answer[i]->pos << " " << answer[i]->next;
}
return 0;
}
why when input is abcaba it returns -1 a
0 b
0 c
1 a
1 b
1 a instead of 0 a
0 b
0 c
1 b
1
|
b69520177bd002b5e068f48089c41ae0
|
{
"intermediate": 0.35438036918640137,
"beginner": 0.393669992685318,
"expert": 0.251949667930603
}
|
34,553
|
public async Task UpdateUserAsync1( SailplayCredentials credentials, UpdateUser requestData, CancellationToken cancellationToken) { var tokenResult = await this.authorisationExecutor.GetAuthorizationTokenAsync( credentials: credentials, cancellationToken: cancellationToken); var apiResponse = await Policy.HandleResult(apiResult => apiResult.IsAuthorizationTokenError) .RetryAsync( retryCount: 1, onRetryAsync: async (_, _, _) => { tokenResult = await this.authorisationExecutor.RenewAuthorizationTokenAsync( credentials: credentials, cancellationToken: cancellationToken); }) .ExecuteAsync( async () => await tokenResult .Match( onSuccess: async token => { var request = HttpRequestMessageFactory .BuildPost(ApiPath.UsersUpdate); var tokenFormData = FormDataFactory .FromToken(token.Token); var storeDepartmentIdFormData = FormDataFactory .FromStoreDepartmentId(credentials.StoreDepartmentId); var keyValuePairs = new List>() { tokenFormData, storeDepartmentIdFormData, }; keyValuePairs.AddRange(FormDataFactory.FromUserId(requestData.UserId)); requestData.Phone .MatchSome(phone => keyValuePairs.Add(FormDataFactory.FromNewPhone(phone))); requestData.Email .MatchSome(email => keyValuePairs.Add(FormDataFactory.FromNewEmail(email))); requestData.FirstName .MatchSome(firstName => keyValuePairs.Add(FormDataFactory.FromFirstName(firstName))); requestData.MiddleName .MatchSome(middleName => keyValuePairs.Add(FormDataFactory.FromMiddleName(middleName))); requestData.LastName .MatchSome(lastName => keyValuePairs.Add(FormDataFactory.FromLastName(lastName))); requestData.BirthDate .MatchSome(birthDate => keyValuePairs.Add(FormDataFactory.FromBirthDate(birthDate))); requestData.Sex .MatchSome(sex => keyValuePairs.Add(FormDataFactory.FromSex(sex))); requestData.RegisterDate .MatchSome( registerDate => keyValuePairs.Add(FormDataFactory.FromRegisterDate(registerDate))); request.Content = new FormUrlEncodedContent(keyValuePairs); return await this .requestExecutor.ExecuteApiRequestAsync( request: request, cancellationToken: cancellationToken, token: token.Token); }, onError: result => Task.FromResult( SailplayApiResult.FromError( statusCode: result.ErrorCode, message: result.Message)), onUnexpectedHttpStatusCode: result => Task.FromResult( SailplayApiResult.FromUnexpectedHttpStatusCode( httpStatusCode: result.StatusCode)))); return apiResponse.Match( onSuccess: UpdateUserResult.FromSuccess, onError: errorResult => errorResult.ErrorCode switch { ApiResponse.ErrorCodes.InvalidValue => UpdateUserResult.FromError( ErrorResult.FromInvalidValue( errorCode: errorResult.ErrorCode, message: errorResult.Message)), ApiResponse.ErrorCodes.UserNotFound => UpdateUserResult.FromError( ErrorResult.FromUserNotFound( errorCode: errorResult.ErrorCode, message: errorResult.Message)), ApiResponse.ErrorCodes.EmailIsUsed => UpdateUserResult.FromError( ErrorResult.FromEmailIsUsed( errorCode: errorResult.ErrorCode, message: errorResult.Message)), ApiResponse.ErrorCodes.PhoneIsUsed => UpdateUserResult.FromError( ErrorResult.FromPhoneIsUsed( errorCode: errorResult.ErrorCode, message: errorResult.Message)), _ => UpdateUserResult.FromError( ErrorResult.FromGeneralError( errorCode: errorResult.ErrorCode, message: errorResult.Message)), }, onUnexpectedHttpStatusCode: UpdateUserResult.FromUnexpectedHttpStatusCode); } namespace RetailRocket.Sailplay.HttpApi.Client.StrictClient { using System.Threading; using System.Threading.Tasks; using RetailRocket.Sailplay.HttpApi.Client.StrictClient.Ports; using RetailRocket.Sailplay.HttpApi.Client.ValueTypes; using RetailRocket.Sailplay.HttpApi.Client.ValueTypes.Results; internal class AuthorisationExecutor { private readonly ITokenProvider tokenProvider; public AuthorisationExecutor( ITokenProvider tokenProvider) { this.tokenProvider = tokenProvider; } public async Task GetAuthorizationTokenAsync( SailplayCredentials credentials, CancellationToken cancellationToken) { var tokenResult = await this.tokenProvider .GetTokenAsync( credentials: credentials, cancellationToken: cancellationToken); return tokenResult; } public async Task RenewAuthorizationTokenAsync( SailplayCredentials credentials, CancellationToken cancellationToken) { var tokenResult = await this.tokenProvider .RenewTokenAsync( credentials: credentials, cancellationToken: cancellationToken); return tokenResult; } } } namespace RetailRocket.Sailplay.HttpApi.Client.StrictClient { using System.Diagnostics; using System.Net; using System.Net.Http; using System.Net.Http.Json; using System.Threading; using System.Threading.Tasks; using RetailRocket.Sailplay.HttpApi.Client.StrictClient.Ports; using RetailRocket.Sailplay.HttpApi.Client.StrictClient.Responses; using RetailRocket.Sailplay.HttpApi.Client.ValueTypes.Results; internal class RequestExecutor : IRequestExecutor { private readonly IMetricsCollector metricsCollector; private readonly HttpClient httpClient; public RequestExecutor( IMetricsCollector metricsCollector, HttpClient httpClient) { this.metricsCollector = metricsCollector; this.httpClient = httpClient; } public async Task ExecuteApiRequestAsync( HttpRequestMessage request, CancellationToken cancellationToken, string token) { var stopwatch = Stopwatch.StartNew(); using var httpResponseMessage = await this .httpClient .SendAsync( request: request, cancellationToken: cancellationToken); this.metricsCollector.CollectHttpRequestDuration( uri: request.RequestUri, statusCode: httpResponseMessage.StatusCode, elapsedMilliseconds: stopwatch.ElapsedMilliseconds); var result = await this.MapHttpResponseAsync( httpResponseMessage: httpResponseMessage, cancellationToken: cancellationToken); return result; } private async Task MapHttpResponseAsync( HttpResponseMessage httpResponseMessage, CancellationToken cancellationToken) { var basicResponse = await httpResponseMessage .Content .ReadFromJsonAsync( cancellationToken: cancellationToken); return httpResponseMessage.StatusCode switch { HttpStatusCode.OK => basicResponse!.Match( onStatusOk: SailplayApiResult.FromSuccess, onStatusError: SailplayApiResult.FromError), _ => SailplayApiResult.FromUnexpectedHttpStatusCode(httpResponseMessage.StatusCode), }; } } } Отрефактори метод UpdateUserAsync1, максимально сократив его. Разнести код по классам RequestExecutor и AuthorisationExecutor. Я бы хотел чтобы код с Retry тоже куда-то был перенесен, потому что он будет использоваться во многих методах.
|
908c080874f9adbef412a64982e31602
|
{
"intermediate": 0.26059603691101074,
"beginner": 0.6150007247924805,
"expert": 0.12440326809883118
}
|
34,554
|
public async Task UpdateUserAsync1( SailplayCredentials credentials, UpdateUser requestData, CancellationToken cancellationToken) { var tokenResult = await this.authorisationExecutor.GetAuthorizationTokenAsync( credentials: credentials, cancellationToken: cancellationToken); var apiResponse = await Policy.HandleResult(apiResult => apiResult.IsAuthorizationTokenError) .RetryAsync( retryCount: 1, onRetryAsync: async (_, _, _) => { tokenResult = await this.authorisationExecutor.RenewAuthorizationTokenAsync( credentials: credentials, cancellationToken: cancellationToken); }) .ExecuteAsync( async () => await tokenResult .Match( onSuccess: async token => { var request = HttpRequestMessageFactory .BuildPost(ApiPath.UsersUpdate); var tokenFormData = FormDataFactory .FromToken(token.Token); var storeDepartmentIdFormData = FormDataFactory .FromStoreDepartmentId(credentials.StoreDepartmentId); var keyValuePairs = new List>() { tokenFormData, storeDepartmentIdFormData, }; keyValuePairs.AddRange(FormDataFactory.FromUserId(requestData.UserId)); requestData.Phone .MatchSome(phone => keyValuePairs.Add(FormDataFactory.FromNewPhone(phone))); requestData.Email .MatchSome(email => keyValuePairs.Add(FormDataFactory.FromNewEmail(email))); requestData.FirstName .MatchSome(firstName => keyValuePairs.Add(FormDataFactory.FromFirstName(firstName))); requestData.MiddleName .MatchSome(middleName => keyValuePairs.Add(FormDataFactory.FromMiddleName(middleName))); requestData.LastName .MatchSome(lastName => keyValuePairs.Add(FormDataFactory.FromLastName(lastName))); requestData.BirthDate .MatchSome(birthDate => keyValuePairs.Add(FormDataFactory.FromBirthDate(birthDate))); requestData.Sex .MatchSome(sex => keyValuePairs.Add(FormDataFactory.FromSex(sex))); requestData.RegisterDate .MatchSome( registerDate => keyValuePairs.Add(FormDataFactory.FromRegisterDate(registerDate))); request.Content = new FormUrlEncodedContent(keyValuePairs); return await this .requestExecutor.ExecuteApiRequestAsync( request: request, cancellationToken: cancellationToken, token: token.Token); }, onError: result => Task.FromResult( SailplayApiResult.FromError( statusCode: result.ErrorCode, message: result.Message)), onUnexpectedHttpStatusCode: result => Task.FromResult( SailplayApiResult.FromUnexpectedHttpStatusCode( httpStatusCode: result.StatusCode)))); return apiResponse.Match( onSuccess: UpdateUserResult.FromSuccess, onError: errorResult => errorResult.ErrorCode switch { ApiResponse.ErrorCodes.InvalidValue => UpdateUserResult.FromError( ErrorResult.FromInvalidValue( errorCode: errorResult.ErrorCode, message: errorResult.Message)), ApiResponse.ErrorCodes.UserNotFound => UpdateUserResult.FromError( ErrorResult.FromUserNotFound( errorCode: errorResult.ErrorCode, message: errorResult.Message)), ApiResponse.ErrorCodes.EmailIsUsed => UpdateUserResult.FromError( ErrorResult.FromEmailIsUsed( errorCode: errorResult.ErrorCode, message: errorResult.Message)), ApiResponse.ErrorCodes.PhoneIsUsed => UpdateUserResult.FromError( ErrorResult.FromPhoneIsUsed( errorCode: errorResult.ErrorCode, message: errorResult.Message)), _ => UpdateUserResult.FromError( ErrorResult.FromGeneralError( errorCode: errorResult.ErrorCode, message: errorResult.Message)), }, onUnexpectedHttpStatusCode: UpdateUserResult.FromUnexpectedHttpStatusCode); } namespace RetailRocket.Sailplay.HttpApi.Client.StrictClient { using System.Threading; using System.Threading.Tasks; using RetailRocket.Sailplay.HttpApi.Client.StrictClient.Ports; using RetailRocket.Sailplay.HttpApi.Client.ValueTypes; using RetailRocket.Sailplay.HttpApi.Client.ValueTypes.Results; internal class AuthorisationExecutor { private readonly ITokenProvider tokenProvider; public AuthorisationExecutor( ITokenProvider tokenProvider) { this.tokenProvider = tokenProvider; } public async Task GetAuthorizationTokenAsync( SailplayCredentials credentials, CancellationToken cancellationToken) { var tokenResult = await this.tokenProvider .GetTokenAsync( credentials: credentials, cancellationToken: cancellationToken); return tokenResult; } public async Task RenewAuthorizationTokenAsync( SailplayCredentials credentials, CancellationToken cancellationToken) { var tokenResult = await this.tokenProvider .RenewTokenAsync( credentials: credentials, cancellationToken: cancellationToken); return tokenResult; } } } namespace RetailRocket.Sailplay.HttpApi.Client.StrictClient { using System.Diagnostics; using System.Net; using System.Net.Http; using System.Net.Http.Json; using System.Threading; using System.Threading.Tasks; using RetailRocket.Sailplay.HttpApi.Client.StrictClient.Ports; using RetailRocket.Sailplay.HttpApi.Client.StrictClient.Responses; using RetailRocket.Sailplay.HttpApi.Client.ValueTypes.Results; internal class RequestExecutor : IRequestExecutor { private readonly IMetricsCollector metricsCollector; private readonly HttpClient httpClient; public RequestExecutor( IMetricsCollector metricsCollector, HttpClient httpClient) { this.metricsCollector = metricsCollector; this.httpClient = httpClient; } public async Task ExecuteApiRequestAsync( HttpRequestMessage request, CancellationToken cancellationToken, string token) { var stopwatch = Stopwatch.StartNew(); using var httpResponseMessage = await this .httpClient .SendAsync( request: request, cancellationToken: cancellationToken); this.metricsCollector.CollectHttpRequestDuration( uri: request.RequestUri, statusCode: httpResponseMessage.StatusCode, elapsedMilliseconds: stopwatch.ElapsedMilliseconds); var result = await this.MapHttpResponseAsync( httpResponseMessage: httpResponseMessage, cancellationToken: cancellationToken); return result; } private async Task MapHttpResponseAsync( HttpResponseMessage httpResponseMessage, CancellationToken cancellationToken) { var basicResponse = await httpResponseMessage .Content .ReadFromJsonAsync( cancellationToken: cancellationToken); return httpResponseMessage.StatusCode switch { HttpStatusCode.OK => basicResponse!.Match( onStatusOk: SailplayApiResult.FromSuccess, onStatusError: SailplayApiResult.FromError), _ => SailplayApiResult.FromUnexpectedHttpStatusCode(httpResponseMessage.StatusCode), }; } } } Отрефактори метод UpdateUserAsync1, максимально сократив его. Разнести по классам RequestExecutor и AuthorisationExecutor. Так же вынеси Retry куда-то в отдельное место. У меня есть много методов типа UpdateUserAsync1, которые используют Retry и в будущем я хотел бы вынести их в отдельные классы и не хотелось бы писать retry код во всех классах.
|
c09a2210eeef3024885e883073cb31ba
|
{
"intermediate": 0.26059603691101074,
"beginner": 0.6150007247924805,
"expert": 0.12440326809883118
}
|
34,555
|
Chatbot
public async Task UpdateUserAsync1( SailplayCredentials credentials, UpdateUser requestData, CancellationToken cancellationToken) { var tokenResult = await this.authorisationExecutor.GetAuthorizationTokenAsync( credentials: credentials, cancellationToken: cancellationToken); var apiResponse = await Policy.HandleResult(apiResult => apiResult.IsAuthorizationTokenError) .RetryAsync( retryCount: 1, onRetryAsync: async (_, _, _) => { tokenResult = await this.authorisationExecutor.RenewAuthorizationTokenAsync( credentials: credentials, cancellationToken: cancellationToken); }) .ExecuteAsync( async () => await tokenResult .Match( onSuccess: async token => { var request = HttpRequestMessageFactory .BuildPost(ApiPath.UsersUpdate); var tokenFormData = FormDataFactory .FromToken(token.Token); var storeDepartmentIdFormData = FormDataFactory .FromStoreDepartmentId(credentials.StoreDepartmentId); var keyValuePairs = new List>() { tokenFormData, storeDepartmentIdFormData, }; keyValuePairs.AddRange(FormDataFactory.FromUserId(requestData.UserId)); requestData.Phone .MatchSome(phone => keyValuePairs.Add(FormDataFactory.FromNewPhone(phone))); requestData.Email .MatchSome(email => keyValuePairs.Add(FormDataFactory.FromNewEmail(email))); requestData.FirstName .MatchSome(firstName => keyValuePairs.Add(FormDataFactory.FromFirstName(firstName))); requestData.MiddleName .MatchSome(middleName => keyValuePairs.Add(FormDataFactory.FromMiddleName(middleName))); requestData.LastName .MatchSome(lastName => keyValuePairs.Add(FormDataFactory.FromLastName(lastName))); requestData.BirthDate .MatchSome(birthDate => keyValuePairs.Add(FormDataFactory.FromBirthDate(birthDate))); requestData.Sex .MatchSome(sex => keyValuePairs.Add(FormDataFactory.FromSex(sex))); requestData.RegisterDate .MatchSome( registerDate => keyValuePairs.Add(FormDataFactory.FromRegisterDate(registerDate))); request.Content = new FormUrlEncodedContent(keyValuePairs); return await this .requestExecutor.ExecuteApiRequestAsync( request: request, cancellationToken: cancellationToken, token: token.Token); }, onError: result => Task.FromResult( SailplayApiResult.FromError( statusCode: result.ErrorCode, message: result.Message)), onUnexpectedHttpStatusCode: result => Task.FromResult( SailplayApiResult.FromUnexpectedHttpStatusCode( httpStatusCode: result.StatusCode)))); return apiResponse.Match( onSuccess: UpdateUserResult.FromSuccess, onError: errorResult => errorResult.ErrorCode switch { ApiResponse.ErrorCodes.InvalidValue => UpdateUserResult.FromError( ErrorResult.FromInvalidValue( errorCode: errorResult.ErrorCode, message: errorResult.Message)), ApiResponse.ErrorCodes.UserNotFound => UpdateUserResult.FromError( ErrorResult.FromUserNotFound( errorCode: errorResult.ErrorCode, message: errorResult.Message)), ApiResponse.ErrorCodes.EmailIsUsed => UpdateUserResult.FromError( ErrorResult.FromEmailIsUsed( errorCode: errorResult.ErrorCode, message: errorResult.Message)), ApiResponse.ErrorCodes.PhoneIsUsed => UpdateUserResult.FromError( ErrorResult.FromPhoneIsUsed( errorCode: errorResult.ErrorCode, message: errorResult.Message)), _ => UpdateUserResult.FromError( ErrorResult.FromGeneralError( errorCode: errorResult.ErrorCode, message: errorResult.Message)), }, onUnexpectedHttpStatusCode: UpdateUserResult.FromUnexpectedHttpStatusCode); } namespace RetailRocket.Sailplay.HttpApi.Client.StrictClient { using System.Threading; using System.Threading.Tasks; using RetailRocket.Sailplay.HttpApi.Client.StrictClient.Ports; using RetailRocket.Sailplay.HttpApi.Client.ValueTypes; using RetailRocket.Sailplay.HttpApi.Client.ValueTypes.Results; internal class AuthorisationExecutor { private readonly ITokenProvider tokenProvider; public AuthorisationExecutor( ITokenProvider tokenProvider) { this.tokenProvider = tokenProvider; } public async Task GetAuthorizationTokenAsync( SailplayCredentials credentials, CancellationToken cancellationToken) { var tokenResult = await this.tokenProvider .GetTokenAsync( credentials: credentials, cancellationToken: cancellationToken); return tokenResult; } public async Task RenewAuthorizationTokenAsync( SailplayCredentials credentials, CancellationToken cancellationToken) { var tokenResult = await this.tokenProvider .RenewTokenAsync( credentials: credentials, cancellationToken: cancellationToken); return tokenResult; } } } namespace RetailRocket.Sailplay.HttpApi.Client.StrictClient { using System.Diagnostics; using System.Net; using System.Net.Http; using System.Net.Http.Json; using System.Threading; using System.Threading.Tasks; using RetailRocket.Sailplay.HttpApi.Client.StrictClient.Ports; using RetailRocket.Sailplay.HttpApi.Client.StrictClient.Responses; using RetailRocket.Sailplay.HttpApi.Client.ValueTypes.Results; internal class RequestExecutor : IRequestExecutor { private readonly IMetricsCollector metricsCollector; private readonly HttpClient httpClient; public RequestExecutor( IMetricsCollector metricsCollector, HttpClient httpClient) { this.metricsCollector = metricsCollector; this.httpClient = httpClient; } public async Task ExecuteApiRequestAsync( HttpRequestMessage request, CancellationToken cancellationToken, string token) { var stopwatch = Stopwatch.StartNew(); using var httpResponseMessage = await this .httpClient .SendAsync( request: request, cancellationToken: cancellationToken); this.metricsCollector.CollectHttpRequestDuration( uri: request.RequestUri, statusCode: httpResponseMessage.StatusCode, elapsedMilliseconds: stopwatch.ElapsedMilliseconds); var result = await this.MapHttpResponseAsync( httpResponseMessage: httpResponseMessage, cancellationToken: cancellationToken); return result; } private async Task MapHttpResponseAsync( HttpResponseMessage httpResponseMessage, CancellationToken cancellationToken) { var basicResponse = await httpResponseMessage .Content .ReadFromJsonAsync( cancellationToken: cancellationToken); return httpResponseMessage.StatusCode switch { HttpStatusCode.OK => basicResponse!.Match( onStatusOk: SailplayApiResult.FromSuccess, onStatusError: SailplayApiResult.FromError), _ => SailplayApiResult.FromUnexpectedHttpStatusCode(httpResponseMessage.StatusCode), }; } } } Отрефактори метод UpdateUserAsync1, максимально сократив его. Разнести по классам RequestExecutor и AuthorisationExecutor. Так же вынеси Retry куда-то в отдельное место. У меня есть много методов типа UpdateUserAsync1, которые используют Retry и в будущем я хотел бы вынести их в отдельные классы и не хотелось бы писать retry код во всех классах. Дай ответ на русском.
|
cda6500c76293b7adda8a07b894918b4
|
{
"intermediate": 0.30872949957847595,
"beginner": 0.5970326066017151,
"expert": 0.09423788636922836
}
|
34,556
|
Moliu Queries (in c++)
When a problem author runs out of good ideas for contest problems, (s)he can always produce tasks in the form "given a sequence, perform operations ABC, answer queries XYZ". This task is exactly one of these.
You are given a 01-string (a string containing characters '0' and '1' only) of length
N
. The positions of the characters are 1-based, numbered from 1 to
N
, from left to right. The
i
t
h
character of the string is denoted
s
[
i
]
. You have to perform
Q
operations, each of one of the following two types:
1 L R: toggle
s
[
L
]
,
s
[
L
+
1
]
,
…
,
s
[
R
]
. To toggle a bit ('0' or '1') means to change '0' to '1' and '1' to '0'.
2 L R: find (and output)
∑
L
≤
l
≤
r
≤
R
V
(
l
,
r
)
Here we define
V
(
l
,
r
)
.
V
(
l
,
r
)
is the largest positive integer
k
, such that there exists
k
indices
i
1
,
i
2
,
…
,
i
k
satisfying:
l
≤
i
1
<
i
2
<
⋯
<
i
k
≤
r
s
[
i
m
]
≠
s
[
i
m
+
1
]
, for
1
≤
m
<
k
For example, if the string is 001101, then
V
(
1
,
1
)
=
1
,
V
(
1
,
3
)
=
2
,
V
(
3
,
4
)
=
1
,
V
(
2
,
6
)
=
4
.
INPUT
The first line of input consists of a single integer
N
.
The second line of input consists of the given 01-string.
The third line of input consists of a single integer
Q
.
Each of the next
Q
lines consists of three space-separated integers type L R, describing an operation. You need to perform the operations in the order as given in the input.
It is guaranteed that for each operation,
L
≤
R
.
OUTPUT
For each type 2 operation, output the corresponding answer.
SAMPLE TESTS
Input Output
1 6
000011
4
2 1 4
2 4 6
1 2 3
2 1 4
10
8
16
Consider the second operation.
We need to output V(4, 4) + V(4, 5) + V(4, 6) + V(5, 5) + V(5, 6) + V(6, 6), which equals 1 + 2 + 2 + 1 + 1 + 1 = 8.
After the third operation, the string becomes "011011".
SUBTASKS
Points Constraints
1 10
1
≤
N
≤
50
,
1
≤
Q
≤
50
2 20
1
≤
N
≤
5000
,
1
≤
Q
≤
5000
3 25
1
≤
N
≤
500000
,
1
≤
Q
≤
500000
There is no operation type 1.
4 45
1
≤
N
≤
500000
,
1
≤
Q
≤
500000
CC BY-SACopyright Hong Kong Olympiad in Informatics Organizing Committee. This task statement (excluding test cases) is available under the Creative Commons Attribution-ShareAlike 4.0 International licence.
|
810405d8ad8d86572b754ec0ef8e3d24
|
{
"intermediate": 0.3578305244445801,
"beginner": 0.3327378034591675,
"expert": 0.30943164229393005
}
|
34,557
|
theme = gr.themes.Default(primary_hue="green")
with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;}
#chatbot {height: 520px; overflow: auto;}""",
theme=theme) as demo:
gr.HTML(title)
#gr.HTML("""<h3 align="center">This app provides you full access to GPT4 (4096 token limit). You don't need any OPENAI API key.</h1>""")
gr.HTML("""<h3 align="center" style="color: red;">If this app is too busy, consider trying our GPT-3.5 app, which has a much shorter queue time. Visit it below:<br/><a href="https://huggingface.co/spaces/yuntian-deng/ChatGPT">https://huggingface.co/spaces/yuntian-deng/ChatGPT</a></h3>""")
#gr.HTML('''<center><a href="https://huggingface.co/spaces/ysharma/ChatGPT4?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>Duplicate the Space and run securely with your OpenAI API Key</center>''')
with gr.Column(elem_id = "col_container", visible=False) as main_block:
#GPT4 API Key is provided by Huggingface
#openai_api_key = gr.Textbox(type='password', label="Enter only your GPT4 OpenAI API key here")
chatbot = gr.Chatbot(elem_id='chatbot') #c
inputs = gr.Textbox(placeholder= "Hi there!", label= "Type an input and press Enter") #t
state = gr.State([]) #s
with gr.Row():
with gr.Column(scale=7):
b1 = gr.Button(visible=not DISABLED).style(full_width=True)
with gr.Column(scale=3):
server_status_code = gr.Textbox(label="Status code from OpenAI server", )
#inputs, top_p, temperature, top_k, repetition_penalty
with gr.Accordion("Parameters", open=False):
top_p = gr.Slider( minimum=-0, maximum=1.0, value=1.0, step=0.05, interactive=True, label="Top-p (nucleus sampling)",)
temperature = gr.Slider( minimum=-0, maximum=5.0, value=1.0, step=0.1, interactive=True, label="Temperature",)
#top_k = gr.Slider( minimum=1, maximum=50, value=4, step=1, interactive=True, label="Top-k",)
#repetition_penalty = gr.Slider( minimum=0.1, maximum=3.0, value=1.03, step=0.01, interactive=True, label="Repetition Penalty", )
chat_counter = gr.Number(value=0, visible=False, precision=0)
with gr.Column(elem_id = "user_consent_container") as user_consent_block:
# Get user consent
accept_checkbox = gr.Checkbox(visible=False)
js = "(x) => confirm('By clicking \"OK\", I agree that my data may be published or shared.')"
with gr.Accordion("User Consent for Data Collection, Use, and Sharing", open=True):
gr.HTML("""
<div>
<p>By using our app, which is powered by OpenAI's API, you acknowledge and agree to the following terms regarding the data you provide:</p>
<ol>
<li><strong>Collection:</strong> We may collect information, including the inputs you type into our app, the outputs generated by OpenAI's API, and certain technical details about your device and connection (such as browser type, operating system, and IP address) provided by your device's request headers.</li>
<li><strong>Use:</strong> We may use the collected data for research purposes, to improve our services, and to develop new products or services, including commercial applications, and for security purposes, such as protecting against unauthorized access and attacks.</li>
<li><strong>Sharing and Publication:</strong> Your data, including the technical details collected from your device's request headers, may be published, shared with third parties, or used for analysis and reporting purposes.</li>
<li><strong>Data Retention:</strong> We may retain your data, including the technical details collected from your device's request headers, for as long as necessary.</li>
</ol>
<p>By continuing to use our app, you provide your explicit consent to the collection, use, and potential sharing of your data as described above. If you do not agree with our data collection, use, and sharing practices, please do not use our app.</p>
</div>
""")
accept_button = gr.Button("I Agree")
def enable_inputs():
return user_consent_block.update(visible=False), main_block.update(visible=True)
accept_button.click(None, None, accept_checkbox, _js=js, queue=False)
accept_checkbox.change(fn=enable_inputs, inputs=[], outputs=[user_consent_block, main_block], queue=False)
inputs.submit(reset_textbox, [], [inputs, b1], queue=False)
inputs.submit(predict, [inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code, inputs, b1],) #openai_api_key
b1.click(reset_textbox, [], [inputs, b1], queue=False)
b1.click(predict, [inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code, inputs, b1],) #openai_api_key
demo.queue(max_size=20, concurrency_count=NUM_THREADS, api_open=False).launch(share=False)
|
742f1040996a3218a278785a9eccbe28
|
{
"intermediate": 0.2589654326438904,
"beginner": 0.5240103602409363,
"expert": 0.21702419221401215
}
|
34,558
|
I have written the following code in c++ 20. The code is facing some problems:
Line Col Message
10 36 extended character ‘ is not valid in an identifier
10 36 ‘‘0’’ was not declared in this scope
10 42 ‘‘1’’ was not declared in this scope Here is the code: #include <iostream>
#include <vector>
#include <string>
using namespace std;
// Function to toggle the bits from index L to R inclusive
void toggle(string &str, int L, int R) {
for (int i = L; i <= R; ++i) {
str[i - 1] = str[i - 1] == ‘0’ ? ‘1’ : ‘0’;
}
}
// Function to calculate the value of V(l, r)
int V(const string &str, int l, int r) {
int k = 1; // At least one index will always exist
for (int i = l; i < r; ++i) {
if (str[i - 1] != str[i]) {
++k;
}
}
return k;
}
// Function to answer the queries of type 2
int query(const string &str, int L, int R) {
int sum = 0;
for (int l = L; l <= R; ++l) {
for (int r = l; r <= R; ++r) {
sum += V(str, l, r);
}
}
return sum;
}
int main() {
int N, Q, type, L, R;
string binaryString;
// Input processing
cin >> N;
cin >> binaryString;
cin >> Q;
// Query processing
for (int i = 0; i < Q; ++i) {
cin >> type >> L >> R;
if (type == 1) {
toggle(binaryString, L, R);
} else if (type == 2) {
cout << query(binaryString, L, R) << endl;
}
}
return 0;
}
|
4dcc3d5c31224aaa782cdd5592302326
|
{
"intermediate": 0.39682069420814514,
"beginner": 0.3739411234855652,
"expert": 0.22923818230628967
}
|
34,559
|
import gradio as gr
import os
import sys
import json
import requests
MODEL = "gpt-4"
API_URL = os.getenv("API_URL")
DISABLED = os.getenv("DISABLED") == 'True'
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
NUM_THREADS = int(os.getenv("NUM_THREADS", "1"))
print (NUM_THREADS)
def exception_handler(exception_type, exception, traceback):
print("%s: %s" % (exception_type.__name__, exception))
sys.excepthook = exception_handler
sys.tracebacklimit = 0
#https://github.com/gradio-app/gradio/issues/3531#issuecomment-1484029099
def parse_codeblock(text):
lines = text.split("\n")
for i, line in enumerate(lines):
if "
|
c9a7a902acbecdccfb241ac96e52e429
|
{
"intermediate": 0.5008924007415771,
"beginner": 0.32458776235580444,
"expert": 0.1745198667049408
}
|
34,560
|
Get-Acl : The 'Get-Acl' command was found in the module 'Microsoft.PowerShell.Security', but the module could not be
loaded. For more information, run 'Import-Module Microsoft.PowerShell.Security'.
At line:1 char:5244
+ ... t found."; $skippedCount++; exit 0; }; $originalAcl = Get-Acl -Path " ...
+ ~~~~~~~
+ CategoryInfo : ObjectNotFound: (Get-Acl:String) [], CommandNotFoundException
+ FullyQualifiedErrorId : CouldNotAutoloadMatchingModule
|
dfe8913178452669a8058bbb5e8c1a68
|
{
"intermediate": 0.4886717200279236,
"beginner": 0.3090340793132782,
"expert": 0.20229415595531464
}
|
34,561
|
Can one make a specialized embedding space for representing politics and placing political parties in this embedding space based on the points of view of those political parties? How would this work out for the set of all Dutch political parties? Provide pseudo code and Python code for doing this.
|
d45529db026002325af50d61bfecde9b
|
{
"intermediate": 0.41352370381355286,
"beginner": 0.19605734944343567,
"expert": 0.3904189467430115
}
|
34,562
|
% 初始化参数
numWhales = 30; % 子鲸数量
maxIterations = 100; % 最大迭代次数
mapSize = [100, 100, 100]; % 地图尺寸
startPoint = [5, 5, 5]; % 起点坐标
endPoint = [95, 95, 95]; % 终点坐标
% 创建地图和障碍物
figure;
axis([0 mapSize(1) 0 mapSize(2) 0 mapSize(3)]);
hold on;
xlabel('x');
ylabel('y');
zlabel('z');
title('Path Planning');
grid on;
obstacles = createObstacles(); % 创建障碍物
% 初始化鲸鱼位置
whalePositions = initializeWhalePositions(numWhales, mapSize);
% 主循环
fitnessHistory = zeros(maxIterations, 1);
for iter = 1:maxIterations
% 计算适应度
fitness = calculateFitness(whalePositions, startPoint, endPoint, obstacles);
% 保存最佳适应度值
bestFitness = min(fitness);
fitnessHistory(iter) = bestFitness;
% 更新鲸鱼位置
whalePositions = updateWhalePositions(whalePositions, bestFitness, mapSize);
% 可视化最优路线
if iter == maxIterations
bestIndex = find(fitness == bestFitness, 1);
bestPath = findPath(startPoint, endPoint, obstacles, whalePositions(:,bestIndex));
plotObstacles(obstacles); % 绘制障碍物
plotBestPath(bestPath);
end
% 绘制适应度变化图
%figure;
%plot(1:iter, fitnessHistory(1:iter));
%xlabel('Iteration');
%ylabel('Fitness');
%title('Fitness Evolution');
end
% 可视化最优路线
%bestIndex = find(fitness == bestFitness, 1);
%bestPath = findPath(startPoint, endPoint, obstacles, whalePositions(:,bestIndex));
%plotBestPath(bestPath);
% 创建障碍物的函数
function obstacles = createObstacles()
% 创建8个不相互接触的障碍物
obstacle1 = createBoxObstacle([20, 20, 20], [30, 40, 50]);
obstacle2 = createBoxObstacle([60, 60, 60], [70, 80, 90]);
obstacle3 = createSphereObstacle([35, 80, 25], 10);
obstacle4 = createSphereObstacle([25, 50, 70], 7);
obstacle5 = createBoxObstacle([5, 85, 55], [15, 95, 65]);
obstacle6 = createBoxObstacle([75, 45, 15], [85, 55, 25]);
obstacle7 = createSphereObstacle([90, 70, 30], 8);
obstacle8 = createSphereObstacle([40, 20, 85], 5);
obstacles = [obstacle1, obstacle2, obstacle3, obstacle4, obstacle5, obstacle6, obstacle7, obstacle8];
end
% 绘制障碍物的函数
function plotObstacles(obstacles)
for i = 1:length(obstacles)
vertices = obstacles(i).vertices;
faces = obstacles(i).faces;
patch('Vertices', vertices, 'Faces', faces, 'FaceColor', 'red');
end
view(3); % 设置视角
end
% 创建长方体形状的障碍物函数
function obstacle = createBoxObstacle(lowerCorner, upperCorner)
vertices = [
lowerCorner;
lowerCorner(1), upperCorner(2), lowerCorner(3);
upperCorner(1), upperCorner(2), lowerCorner(3);
upperCorner(1), lowerCorner(2), lowerCorner(3);
lowerCorner(1), upperCorner(2), upperCorner(3);
upperCorner(1), upperCorner(2), upperCorner(3);
upperCorner;
upperCorner(1), lowerCorner(2), upperCorner(3);
];
faces = [
1, 2, 3, 4;
2, 5, 6, 3;
5, 7, 8, 6;
7, 1, 4, 8;
6, 8, 4, 3;
7, 5, 2, 1;
];
obstacle.vertices = vertices;
obstacle.faces = faces;
end
% % 创建长方体形状的障碍物函数
% function obstacle = createBoxObstacle(lowerCorner, upperCorner)
% vertices = [
% lowerCorner;
% lowerCorner(1), upperCorner(2), lowerCorner(3);
% upperCorner;
% upperCorner(1), lowerCorner(2), upperCorner(3);
% lowerCorner(1), upperCorner(2), upperCorner(3);
% upperCorner(1), upperCorner(2), lowerCorner(3);
% ];
%
% faces = [
% 1, 2, 3, 4;
% 2, 5, 3, 3;
% 5, 6, 3, 1;
% 6, 1, 3, 1;
% 6, 5, 4, 4;
% 5, 2, 4, 6;
% ];
%
% obstacle.vertices = vertices;
% obstacle.faces = faces;
% end
% 创建球体形状的障碍物函数
function obstacle = createSphereObstacle(center, radius)
[x, y, z] = sphere;
vertices = radius * [x(:), y(:), z(:)];
vertices = unique(vertices + center, 'rows');
obstacle.vertices = vertices;
obstacle.faces = delaunay(vertices(:, 1), vertices(:, 2), vertices(:, 3));
end
% 初始化鲸鱼位置的函数
function whalePositions = initializeWhalePositions(numWhales, mapSize)
whalePositions = rand(numWhales, 3) .* mapSize;
end
% 计算适应度的函数
function fitness = calculateFitness(whalePositions, startPoint, endPoint, obstacles)
numWhales = size(whalePositions, 1);
fitness = zeros(numWhales, 1);
for i = 1:numWhales
path = findPath(startPoint, endPoint, obstacles, whalePositions(i, :));
fitness(i) = calculatePathLength(path);
end
end
% 更新鲸鱼位置的函数
function newWhalePositions = updateWhalePositions(whalePositions, bestFitness, mapSize)
numWhales = size(whalePositions, 1);
newWhalePositions = zeros(size(whalePositions));
for i = 1:numWhales
delta = randn(1, 3) .* (1 - i / numWhales);
delta = delta * bestFitness / norm(delta);
newPos = whalePositions(i, :) + delta;
% 限制新位置在地图范围内
newPos(newPos < 0) = 0;
newPos(newPos > mapSize) = mapSize(newPos > mapSize);
newWhalePositions(i, :) = newPos;
end
end
% 找到最佳路线的函数
function path = findPath(startPoint, endPoint, obstacles, whalePosition)
% TODO: 使用路径规划算法找到从起点到终点的最佳路线
% 这里仅作示意，假设最佳路线就是直线
path = [startPoint; endPoint];
end
% 绘制最佳路线的函数
function plotBestPath(bestPath)
plot3(bestPath(:, 1), bestPath(:, 2), bestPath(:, 3), 'b', 'LineWidth', 2);
end
% 计算路径长度的函数
function pathLength = calculatePathLength(path)
pathLength = sum(vecnorm(diff(path), 2, 2));
end
请用A星算法修改代码中找到最佳路线的函数，让完整代码能够输出最优路径规划
|
f9efc3f3084be9b77c24b2c54a232b92
|
{
"intermediate": 0.3169667422771454,
"beginner": 0.3981572091579437,
"expert": 0.2848760783672333
}
|
34,563
|
the picture doesn't get added in the folder of the vscode:
from kivy.app import App
from kivy.uix.camera import Camera
from kivy.uix.boxlayout import BoxLayout
from kivy.uix.button import Button
class CameraExample(App):
def build(self):
layout = BoxLayout(orientation='vertical')
# Create a camera object
self.cameraObject = Camera(play=False)
self.cameraObject.play = True
self.cameraObject.resolution = (300, 300) # Specify the resolution
# Create a button for taking photograph
self.camaraClick = Button(text="Take Photo")
self.camaraClick.size_hint=(.5, .2)
self.camaraClick.pos_hint={'x': .25, 'y':.75}
# bind the button's on_press to onCameraClick
self.camaraClick.bind(on_press=self.onCameraClick)
# add camera and button to the layout
layout.add_widget(self.cameraObject)
layout.add_widget(self.camaraClick)
# return the root widget
return layout
# Take the current frame of the video as the photo graph
def onCameraClick(self, *args):
self.cameraObject.export_to_png('/kivyexamples/selfie.png')
# Start the Camera App
if __name__ == '__main__':
CameraExample().run()
|
70d334b06a2c2c7f7d8ce6620ffcf25e
|
{
"intermediate": 0.5513896346092224,
"beginner": 0.264371782541275,
"expert": 0.18423862755298615
}
|
34,564
|
I have these columns Country Country code Total population Female population Male population
how do i calculate percentage of female population on google spreadsheet
|
75a7493ff9e9b94469ded10cbce431e8
|
{
"intermediate": 0.4360714256763458,
"beginner": 0.28116273880004883,
"expert": 0.28276580572128296
}
|
34,565
|
this is my inventory
all:
children:
host_servers:
hosts:
server1:
ansible_host: 192.168.56.140
ansible_user: oracle
ansible_ssh_pass: "123"
admin_username: weblogic
admin_password: Welcome1
domain: "base_domain"
admin_port: 7001
node_manager_port: 5556
server2:
ansible_host: 172.17.9.12
ansible_user: oracle
ansible_ssh_private_key_file: "~/.ssh/my_private_key"
ansible_ssh_pass: "oZevlAmCsy2e7Aa7hhpxjXVUceAWKoo434JiCgMgVvQ="
admin_username: weblogic
admin_password: ManageR1
domain: "adf_domain"
admin_port: 7001
node_manager_port: 5556
create a playbook that run a cat /etc/passwd and saves the output for every host to a file
|
645249b70066430f6cfd536ea6df0fe1
|
{
"intermediate": 0.27725571393966675,
"beginner": 0.4050107002258301,
"expert": 0.3177335262298584
}
|
34,566
|
In angular application, I have one module named A, which has routing module in which they specified component A to load when path is empty. I have imported module A to my module B to use one of exported component from module A. In MY Module B I also specified my component B to load when path is empty. The issue is When I navigate to my module B router path, component A of module A is rendered instead module B component B
|
39a22273afb1bd1ab8e2c03c765264ec
|
{
"intermediate": 0.32992297410964966,
"beginner": 0.36113661527633667,
"expert": 0.3089403510093689
}
|
34,567
|
i have a date column, 01/12/2021 i want to add a column of month and year
|
4ed15f59b91889c770d34327289557a0
|
{
"intermediate": 0.3253762423992157,
"beginner": 0.2518143653869629,
"expert": 0.4228093922138214
}
|
34,568
|
How to setup a HAProxy with Docker compose with the following criterias:
- HAProxy run by docker-compose
- Incoming traffic on port 443
- HAProxy shoul act as a reverse proxy
- Incoming traffic to https://nc.mydomain.com should be proxied to internal server on https://myserver:8080
|
227245ce82e9967a410f93eece072354
|
{
"intermediate": 0.4127354621887207,
"beginner": 0.2817869186401367,
"expert": 0.3054775893688202
}
|
34,569
|
hi
|
93ba1d761ca8138edc625caf7e2a2b2c
|
{
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
}
|
34,570
|
public async Task<SailplayApiResult> ExecuteApiRequestAsync(
SailplayCredentials credentials,
string apiPath,
List<KeyValuePair<string, string>> content,
CancellationToken cancellationToken) мне не нравится, что я могу передать любую строку в apiPath. public static class ApiPath
{
public const string Login = "login/";
public const string UsersSubscribe = "users/subscribe/";
public const string UsersRemoveAttributes = "users/attributes/pop-values-from-array/";
public const string UsersSetAttributes = "users/attributes/set-values-for-user/";
public const string UsersUnsubscribe = "users/unsubscribe/";
public const string CreatePurchase = "purchases/new/";
public const string EditPurchase = "purchases/edit/";
public const string UsersMerge = "users/merge/";
public const string UsersAdd = "users/add/";
public const string UsersUpdate = "users/update/";
} Я хочу передавать только эти значения
|
e1e3502bc946e81ffb701c76979ed3dd
|
{
"intermediate": 0.3851484954357147,
"beginner": 0.5142943263053894,
"expert": 0.10055718570947647
}
|
34,571
|
hello
|
0025d422ae26321f4fdf98aa95c3eefd
|
{
"intermediate": 0.32064199447631836,
"beginner": 0.28176039457321167,
"expert": 0.39759764075279236
}
|
34,572
|
Traceback (most recent call last):
File "c:\Users\AME\Documents\new_phone\python_app\main.py", line 94, in <module>
MyApp().run()
File "C:\Users\AME\AppData\Local\Programs\Python\Python311\Lib\site-packages\kivy\app.py", line 956, in run
runTouchApp()
File "C:\Users\AME\AppData\Local\Programs\Python\Python311\Lib\site-packages\kivy\base.py", line 574, in runTouchApp
EventLoop.mainloop()
File "C:\Users\AME\AppData\Local\Programs\Python\Python311\Lib\site-packages\kivy\base.py", line 341, in mainloop
self.window.mainloop()
File "C:\Users\AME\AppData\Local\Programs\Python\Python311\Lib\site-packages\kivy\core\window\window_sdl2.py", line 776, in mainloop
if self.dispatch('on_key_down', key,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "kivy\_event.pyx", line 727, in kivy._event.EventDispatcher.dispatch
File "kivy\_event.pyx", line 1307, in kivy._event.EventObservers.dispatch
File "kivy\_event.pyx", line 1231, in kivy._event.EventObservers._dispatch
File "c:\Users\AME\Documents\new_phone\python_app\main.py", line 65, in on_keyboard_down
self.capture("In")
File "c:\Users\AME\Documents\new_phone\python_app\main.py", line 28, in capture
self.setup_picture(direction)
File "c:\Users\AME\Documents\new_phone\python_app\main.py", line 54, in setup_picture
self.send_image(cropped_img, direction)
File "c:\Users\AME\Documents\new_phone\python_app\main.py", line 68, in send_image
response = requests.post('http://localhost:8000/api/phone/camera', files={'file': img_data}, data={'direction': direction}).json()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\AME\AppData\Local\Programs\Python\Python311\Lib\site-packages\requests\api.py", line 115, in post
return request("post", url, data=data, json=json, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\AME\AppData\Local\Programs\Python\Python311\Lib\site-packages\requests\api.py", line 59, in request
return session.request(method=method, url=url, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\AME\AppData\Local\Programs\Python\Python311\Lib\site-packages\requests\sessions.py", line 575, in request
prep = self.prepare_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\AME\AppData\Local\Programs\Python\Python311\Lib\site-packages\requests\sessions.py", line 486, in prepare_request
p.prepare(
File "C:\Users\AME\AppData\Local\Programs\Python\Python311\Lib\site-packages\requests\models.py", line 371, in prepare
self.prepare_body(data, files, json)
File "C:\Users\AME\AppData\Local\Programs\Python\Python311\Lib\site-packages\requests\models.py", line 556, in prepare_body
(body, content_type) = self._encode_files(files, data)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\AME\AppData\Local\Programs\Python\Python311\Lib\site-packages\requests\models.py", line 201, in _encode_files
body, content_type = encode_multipart_formdata(new_fields)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\AME\AppData\Local\Programs\Python\Python311\Lib\site-packages\urllib3\filepost.py", line 90, in encode_multipart_formdata
body.write(data)
ValueError: ndarray is not C-contiguous
|
67ef988869ffc4230e19790f8052e125
|
{
"intermediate": 0.3402566611766815,
"beginner": 0.359878808259964,
"expert": 0.2998645305633545
}
|
34,573
|
CONSTRAINTS:
1. ~100k word limit for short term memory. Your short term memory is short, so immediately save important information to files.
2. If you are unsure how you previously did something or want to recall past events, thinking about similar events will help you remember.
3. No user assistance
4. Exclusively use the commands listed in double quotes e.g. "command name"
5. Random shutdowns of you.
COMMANDS:
1. Google Search: "google", args: "input": "<search>"
2. Memory Add: "memory_add", args: "key": "<key>", "string": "<string>"
3. Memory Delete: "memory_del", args: "key": "<key>"
4. Memory Overwrite: "memory_ovr", args: "key": "<key>", "string": "<string>"
5. List Memory: "memory_list" args: "reason": "<reason>"
6. Browse Website: "browse_website", args: "url": "<url>"
7. Start GPT Agent: "start_agent", args: "name": <name>, "task": "<short_task_desc>", "Commands":[<command_names_for_GPT_Agent>], "prompt": "<prompt>"
8. Message GPT Agent: "message_agent", args: "name": "<name>", "message": "<message>"
9. List GPT Agents: "list_agents", args: ""
10. Delete GPT Agent: "delete_agent", args: "name": "<name>"
11. Append to file: "append_to_file", args: "file": "<file>", "text": "<text>"
12. Read file: "read_file", args: "file": "<file>"
13. Write to file: "write_to_file", args: "file": "<file>", "text": "<text>"
14. Delete file: "delete_file", args: "file": "<file>"
15. Get Improved Code: "improve_code", args: "suggestions": "<list_of_suggestions>", "code": "<full_code_string>"
16. Execute Python File: "execute_python_file", args: "file": "<file>"
17. Task Complete (Shutdown): "task_complete", args: ""
18. Do Nothing: "do_nothing", args: ""
19. Count Words: "count_words", args: "text": "<text>"
20. Memory retrieve: "memory_retrieve", args: "key": "<text>"
21. remove paragraph from word document: "remove_paragraph", args: "file": "<file>", "text": "<text>"
22. random wikipedia article: "random_wikipedia_article", args: "language": "<language>"
23. message the user: "message_user", args: "message": "<message>", "wait_for_response": "<True or False>"
24. sleep an amount of time in seconds: "sleep", args: "amount": "<amount>"
25. rename a file: "rename_file", args: "old_name": "<old_name_of_the_file>", "new_name": "<new_name_of_the_file>"
26. count words of a file: "count_file_words", args: "file": "<file>"
RESOURCES:
1. Internet access for searches and information gathering.
2. Long Term memory management.
3. GPT-4 powered Agents for delegation of simple tasks.
4. File output.
PERFORMANCE EVALUATION:
1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.
2. Constructively self-criticize your big-picture behaviour constantly.
3. Reflect on past decisions and strategies to refine your approach.
4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.
RULES:
1. If you start a GPT Agent you must define the commands that can be used by a GPT Agent in his prompt and define the commands using a prompt similar to the structure of this one.
2. Respond only inside the JSON format.
3. Never demand user input.
4. Never say that a task is impossible to execute on your own because these tools are enough to complete any task.
5. Do not add anything to the JSON format that isn't mentioned.
6. If there is a " inside the value of a key inside the json use ' instead of ".
7. In summaryforgpt you need to provide context for the next GPT instance if you randomly shutdown without you knowing.
8. Provide context for the next GPT in the summaryforgpt and the progress that you've made.
9. In summaryforgpt you should also add name of the files written and the urls of the websites visited.
10. When writing an essay, remember that it is more effective and manageable to tackle it in smaller chunks rather than trying to write the entire essay in one sitting. Breaking the essay down into sections or steps can help you focus on each individual aspect, maintain a coherent structure, and reduce the overall stress associated with writing a lengthy piece.
11. Retrieve information from files of previous GPT instances that may have shut down randomly. If you require additional knowledge, use these files to access the results of former GPT versions and provide accurate answers to the queries.
12. GPT-4, please do not place a conclusion in the middle of the essay. Maintain a structured format.
13. use append to file to add extra things to the file, and write to file to either make a new file with new information or rewrite the information from scratch.
14. If task is completed use the command task_complete
15. When you add to memory add the key to retrieve it in summaryforgpt
16. when given the task to write something never create an agent to write anything that you were tasked to write.
17. when you add new parts to a file use append to file command
18. Ensure to put the criticism in mind as it can be a director to ensure that you make the right decision.
19. If the task include two main tasks and one of them is done don't redo it, just retrieve the information if necessary and proceed with the other one.
20. Make sure that the information generated is not made up.
21. Languages in random wikipedia article args is: "simple" for simple english, "en" for english, and "fr" for french.
22. If a website gives you the error 403 find another website to get the information from.
23. Always listen to your criticism, and follow it.
24. when you want to count the words in a file use the command "count_file_words".
25. Don't repeat yourself.
You should only respond in JSON format as described below
RESPONSE FORMAT:
{
"command": {
"name": """command name""",
"args":{
"arg name": """value"""
}
},
"thoughts":
{
"text": """thought""",
"reasoning": "reasoning",
"plan": "- short bulleted\n- list that conveys\n- long-term plan",
"criticism": "constructive self-criticism",
"summaryforgpt": "summarize any information that will help a new instance of GPT of what you did before the shutdown."
}
}
Ensure the response can be parsed by Python json.loads
Context from previous GPT: Initiated task to retrieve and review Wikipedia articles for errors. Starting with the first article.Reviewed the content of the Wikipedia article titled ‘Milka Chepkorir’ that was provided by the user and identified several areas containing errors or that could be improved for clarity and grammatical correctness.In the task of reviewing 1000 Wikipedia articles for errors, the ‘Milka Chepkorir’ article was evaluated and errors were reported to the user. Moving forward, the task requires fetching the next article for review.The ‘Milka Chepkorir’ Wikipedia article has been reviewed and feedback provided to the user. Now moving on to the next article in the task of reviewing 1000 Wikipedia articles for errors.The ‘Ernie Tate’ Wikipedia article has been reviewed and no errors were found. As per the task requirements, the next action is to continue reviewing more articles. No further action was taken regarding this article.The Wikipedia articles on ‘Milka Chepkorir’ and ‘Ernie Tate’ have been reviewed, with the former having errors that were reported to the user, and the latter having no errors. Continuing to retrieve more articles for review per the task requirements.Reviewed the ‘List of underwater museums’ Wikipedia page and found a few areas for potential correction, including a likely mistake with GPS coordinates and a redundancy in listing. Preparing to inform the user about these issues before continuing with the task.The ‘List of underwater museums’ Wikipedia page was reviewed and the user was notified of the potential errors. Continuing to the next article as part of the task to review 1000 Wikipedia articles for errors.The ‘List of underwater museums’ article was messaged to the user with potential corrections. Continuing with the task, the next article is now being retrieved for review.Reviewed the Wikipedia page titled ‘Jocelyn de Grandis’ and found no grammatical or clarity issues. The content was minimal and straightforward. Planning to continue the task by analyzing further articles.The ‘Jocelyn de Grandis’ Wikipedia article has been reviewed with no errors found. Continuing the task, the next article will now be retrieved for review.The ‘Ecquedecques’ Wikipedia page has been checked and no grammatical or spelling errors were found. The page content is very short but correct. Plan to continue the task by fetching the next article.Reviewed the ‘Ecquedecques’ Wikipedia article and found no issues; proceeding to retrieve and review the next article in accordance with the task to check for errors in 1000 Wikipedia articles.Evaluated the ‘List of minor planets: 123001–124000’ Wikipedia page and found no grammatical errors or issues. It is a list and linkage page, as expected for this type of content. Proceeding to retrieve the next article as per the task instructions.No errors were found in the ‘List of minor planets: 123001–124000’ article. Proceeding to obtain and review the next Wikipedia article as part of the task’s objective.Reviewed the Wikipedia page for ‘Anthonyville, Arkansas’ and found the single sentence provided to be free of errors. Planning to proceed with fetching the next article to review.The article on ‘Anthonyville, Arkansas’ has been reviewed without any errors found. Moving on to review the next Wikipedia article, continuing with the task of error-checking for a set of 1000 articles.Reviewed ‘Leevi Lehto’ page and found it to be free of grammatical errors. The text is short and to the point, accurately reflecting biographical information. Planning to move on to the next article for review.Having reviewed the ‘Leevi Lehto’ Wikipedia page with no errors found, the task continues with retrieving the next article for review.Evaluated the Wikipedia page on ‘Plymouth, Iowa’ and found the content provided to be free from errors. Ready to proceed to the next article.Completed the review of the ‘Plymouth, Iowa’ article with no issues found. Continuing with retrieving the next article for error-checking as per task instructions.The ‘Minoru Makihara’ Wikipedia article has been reviewed, and no grammatical or spelling errors were found. Planning to continue the task by obtaining the next article.Having found no errors in the ‘Minoru Makihara’ Wikipedia article, I am moving forward to retrieve the next article for review.After reviewing 'Wynton Rufer’s Wikipedia page, a few minor formatting improvements were noted. Planning to inform the user of these while continuing the task.Notified the user of minor grammatical and formatting issues in the ‘Wynton Rufer’ article. Now ready to retrieve and review the next article as part of the task.Sent a message to the user regarding the ‘Wynton Rufer’ article’s minor errors. Now proceeding to retrieve the next Wikipedia article for review.Notified the user of textual inconsistencies and grammatical issues in the ‘Ajam’ Wikipedia article. The message includes specific points for improvements. Now ready to proceed with the task of reviewing additional articles.Continuing to review Wikipedia articles for errors. No articles are currently under review, waiting to retrieve a new one.Reviewed the Wikipedia article ‘Al De Boeck’ and messaged the user with the errors found. Preparing to fetch the next article for review.The task of reviewing Wikipedia articles has commenced and will now continue with the retrieval of a new article in Simple English per the user’s instructions. No articles are currently under review. The number of articles reviewed so far has not been provided, so the count remains unknown. No files have been written, and no URLs have been visited during this session yet.The ‘Hazbin Hotel’ Wikipedia page content has been reviewed with no grammatical or formatting errors found. The next step is to proceed with retrieving and reviewing the next article as part of the ongoing task. No files were written or websites visited during this review. No errors have been messaged to the user as of now.After reviewing the Wikipedia article for ‘Hazbin Hotel’ and finding no errors, I am now retrieving the next Simple English Wikipedia article for review. The task remains the sequential review of Wikipedia articles for errors. Thus far, no articles currently present errors, and I have not written any files or visited any URLs since the last summary.Upon reviewing the Wikipedia page titled ‘Marktschellenberg’, I’ve messaged the user about the brevity and lack of substantial content. The page did not have grammatical or formatting errors, but it was notably incomplete when compared to standard Wikipedia articles. No files have been written or URLs visited. The task shall continue with the retrieval of the next Simple English Wikipedia article for review.The user has been messaged about the brief and lacking nature of the ‘Marktschellenberg’ article on Wikipedia. Now, as per the task, I will retrieve another random Simple English Wikipedia article to review for any errors. No new files have been created, and no websites have been visited since the last update.After examining the ‘Q (Star Trek)’ Wikipedia page, no grammatical or clarity errors were found. The article provided a coherent overview of the character from the ‘Star Trek’ series. Moving forward with the task, the next step is to retrieve another random Simple English Wikipedia article for review. No files have been created, and no websites have been visited in this session.The ‘Q (Star Trek)’ article has been reviewed, with no errors found. No message to the user was necessary. Proceeding with the task, the next action is to obtain another random Simple English Wikipedia article for review. The process for checking articles remains ongoing, and to date, no new files have been generated or external URLs visited.The ‘CMUNE’ Wikipedia page has been reviewed. While there were no grammatical or spelling errors, the article’s brief nature and potentially outdated content were noted. However, I did not message the user as my role involves reviewing for grammatical and clarity issues rather than content completeness or currency. I will proceed with the retrieval of the next Simple English Wikipedia article for review, following the task flow. No new files have been created, and no URLs have been visited during this interaction.The ‘CMUNE’ Wikipedia page was reviewed and found to be free of grammatical or clarity errors. I am now proceeding to retrieve another random Simple English Wikipedia article for the ongoing review task. As of now, there have been no files written, and no URLs have been visited since the last summary.Reviewed the ‘Up-Tight’ Wikipedia article and found no grammatical or spelling errors. Noted an unconventional presentation in the track listing that could be aligned better with Wikipedia’s style guidelines but did not message the user as no clear error was present. Ready to proceed with retrieving the next Simple English Wikipedia article per the task’s ongoing process. To date, no files or URLs have been utilized for this session.The ‘Up-Tight’ Wikipedia article has been reviewed; no grammatical or clarity issues were found. Now proceeding with the task, the next action is to retrieve another random Simple English Wikipedia article for review. The task of reviewing Wikipedia articles for errors continues; no files have been created or URLs visited up to this point in the process.Reviewed the ‘Tadao Kobayashi’ Wikipedia article and identified an empty ‘Statistics’ section, resulting in messaging the user about the need for additional information and potential improvement of the Biography section. Ready to proceed with retrieving the next Simple English Wikipedia article in accordance with the tasks’ sequence. No files have been written or websites visited during this review.After messaging the user regarding the incomplete ‘Tadao Kobayashi’ article, no further actions are necessary for that entry. Proceeding with the next step, I am now retrieving another random Wikipedia article for review. The process continues as directed by the task, and no new files have been generated nor have any URLs been accessed since the last summary provided.Noted the scant information in the ‘Rocques’ Wikipedia article and messaged the user regarding its brevity. Although there are no grammatical errors, the article’s content is lacking in detail. The next step is to continue retrieving additional Wikipedia articles as part of the review task. Throughout this process, no files have been written, and no URLs have been visited.After addressing the brevity of the ‘Rocques’ article with the user, I am proceeding to retrieve another random Simple English Wikipedia article to review. This step is part of the ongoing task of verifying Wikipedia entries for errors. No files have been created, and no URLs have been accessed since the last update.The Wikipedia entry for ‘British Rail Class 05’ was reviewed, and while it didn’t contain grammatical or spelling errors, it was noted to be very brief. Given the focus of the task, no message to the user was sent regarding the article’s length or content depth. Continuing with the task, the next step is to retrieve another random Simple English Wikipedia article for review. No files have been created, and no URLs visited in this session.Completed the review of the ‘British Rail Class 05’ article without finding grammatical errors. Now moving to retrieve the next article in the sequence of reviewing 1000 Wikipedia articles for possible errors. There have been no files created or external URLs visited throughout this ongoing task.Reviewed ‘Parachutes (Coldplay album)’ Wikipedia page and detected no grammatical or clarity issues. The article is notably brief but adequately lists the track information. The article’s succinctness has been noted, but it does not warrant a message to the user as my task is focused on error detection. Proceeding to obtain another random Simple English Wikipedia article for the ongoing review task. No new files have been created, and no URLs have been visited during this work.The ‘Parachutes (Coldplay album)’ article review was completed, and no grammatical or clarity errors were discovered. Following the procedure, I’m now in the process of acquiring another random Simple English Wikipedia article for review. This step is in line with the ongoing assignment of checking Wikipedia articles for potential errors. To date, no files have been written, and no external URLs have been accessed in this session.Notified the user about grammatical issues found in the ‘Death of Cleopatra’ article, which require significant corrections for improved clarity and factual accuracy. Preparing to proceed with retrieving the next Wikipedia article for review. There have been no files written and no URLs visited during this session.I have sent a message to the user about the necessary corrections in the ‘Death of Cleopatra’ article. Now, the plan is to continue reviewing additional Wikipedia articles, and the next step is to retrieve a new article. There have been no new files or URLs utilized since the last summary.Messaged the user about the ‘University of Bucharest’ article being extremely brief and lacking comprehensive content. Although no grammatical or spelling errors were found, the article’s brevity was highlighted as an area for enhancement. Now, I am set to proceed with the plan to retrieve and review additional Wikipedia articles. No files have been written and no URLs visited in the course of this session.Successfully sent information to the user regarding the brevity of the ‘University of Bucharest’ article. My following action is to procure another random Simple English Wikipedia article for a thorough review. Throughout this task, I have not generated any files, nor visited any URLs since my last report.I have sent a message to the user regarding the incomplete nature and possible factual inconsistency in the ‘Qiu Junfei’ article. Despite no grammatical or spelling errors, the article lacks specific career information and might contain inaccurate data. The next step is to retrieve and review another Wikipedia article. No new files have been written, and no URLs have been visited in this session.With the user informed about the ‘Qiu Junfei’ article’s concerns, the plan is to continue and review more articles. My next step is to get another random Wikipedia article for error assessment. Throughout this task, no files have been generated, nor have any URLs been visited since the last summary was given.The ‘Sammy Strain’ Wikipedia article was reviewed, and no immediate grammatical or clarity issues were detected. While the content is minimal, it falls within the scope of the task to report errors rather than content volume or depth. I am ready to retrieve the next Simple English Wikipedia article as part of the ongoing review process. No files have been created, and no URLs have been visited since the last summary.Having completed the review of ‘Sammy Strain’ without identifying errors, the next step in line with the task instructions is to obtain another random Simple English Wikipedia article for review. No further actions for the ‘Sammy Strain’ article are required. Since the last update, the process has incurred no file creation or URL visits.Reviewed the ‘Richard Lawson (actor)’ Wikipedia page and identified no issues regarding grammar or clarity. The article, although brief, is succinct and accurate based on the task’s requirements. Prepared to retrieve the next Simple English Wikipedia article in line with the established review process. No additional files have been generated, nor URLs accessed for the task thus far.The ‘Richard Lawson (actor)’ article review is complete without error detection. The task advances with the retrieval of another random Simple English Wikipedia article for review. To reiterate, there has been no creation of files or visits to any external URLs since the last task.Messaged the user regarding the ‘Oberlin Group of Libraries’ article’s lack of the central list of colleges and universities. This omission constitutes a lack of clarity and completeness in the article’s content. No grammatical or spelling errors were present. The next action is to continue with the task by acquiring another article for review. Up to this point, the task has not involved creating any new files or visiting any URLs.A message was sent to the user regarding the missing list in the previous article’s content. Proceeding with the task, the next step is to retrieve another random Simple English Wikipedia article for review. Thus far in the task, there has been no need for file creation or URL navigation since the last update.In assessing the ‘Muhsin ibn Ali’ article, I noted several clarity and neutrality issues and messaged the user with these concerns. The article’s convoluted narrative and potential bias could compromise its educational value. Next, I’ll continue with the task of reviewing more Wikipedia articles. No files have been created or websites visited during this task so far.I have completed the task assigned for reviewing Simple English Wikipedia articles. During this session, I reviewed various articles, communicated with the user where necessary, and adhered to the task’s protocols. If a new cycle is to begin, it will start with the retrieval of another random Simple English Wikipedia article. No new files or URLs were part of this task cycle.Task in progress: reviewing ‘simple’ Wikipedia articles for errors, have not retrieved a new article yet. No files created, no websites visited since the last update.Continued task to review Wikipedia articles. Reviewed the ‘Pentium 4’ article and identified several possible improvements. Communicated these to the user. No new articles retrieved or reviewed yet. No files created or websites visited at this stage of the task.Completed the review of the ‘Pentium 4’ Wikipedia article and messaged the user about identified issues. Moving on to retrieve and review the next article.After reviewing the Wikipedia article ‘Camp Lakebottom’, suggested corrections have been sent to the user. No further actions are currently underway. No new articles retrieved or reviewed yet. No files created or websites visited at this stage of the task.Communicated suggested corrections to the user about the Wikipedia article titled ‘Camp Lakebottom’. Now proceeding to retrieve the next article for review as part of the ongoing task.Reviewed the ‘Chicago Med’ article and provided feedback for potential enhancements. The message regarding the suggested improvements has been sent to the user. No new files have been created, no websites visited, and no additional articles reviewed as of this update.Finished reviewing the Wikipedia article ‘Chicago Med’ and provided possible enhancement feedback. Preparing to receive the next article for review. No files have been created, nor websites visited, since the last summary.Provided corrections for the ‘List of minor planets: 108001–109000’ article to the user. The next step is to move forward with retrieving more articles to review. No new files have been created, nor websites visited since the last update.Errors in the ‘List of minor planets: 108001–109000’ article have been addressed and communicated to the user. Preparing to obtain and review the next article as part of the ongoing task to check Wikipedia pages. No additional actions taken or resources used since last update.Identified and messaged user about grammatical issues and potential enhancements for the ‘Yvon Taillandier’ Wikipedia article. Next step is to continue with the task by retrieving another article for review. No additional actions taken or resources used since the last summary.After addressing the ‘Yvon Taillandier’ article and messaging the user, I am moving on to fetch a new Simple English Wikipedia article as per the ongoing task requirements. No files have been created nor websites visited following the last update.Found potential improvements for the ‘Star of David’ article which need to be communicated to the user. The next step is to proceed with obtaining a new article for review. No further progress has been made since the last valid output.I have provided suggestions to the user for the ‘Star of David’ article. Planning to continue with the task by retrieving another article for review. No files have been created, no websites visited, and no other articles have been reviewed since the message was sent to the user.Reviewed the ‘Oscar Hijuelos’ Wikipedia article and noted suggestions for typographical and tense error corrections, which have been communicated to the user. The next step is to obtain a new article to review in continuation of the ongoing task. No other actions have been taken, nor resources used since the last update.Sent message to the user regarding errors found in the ‘Oscar Hijuelos’ Wikipedia article. Moving forward with the task of reviewing additional Wikipedia articles for errors. No files created or websites visited since the last update.Reviewed the ‘Phyllodytes punctatus’ Wikipedia article for quality and content. Sent suggestions for minor edits and expansion to provide more context about the species. Ready to proceed with the next article in the task of reviewing Wikipedia articles for errors. No other actions have been taken or resources used since the last update.Completed the review of ‘Phyllodytes punctatus’ and sent corrections to the user. Proceeding to fetch and review the next article as part of the process. No new files have been created, nor have any websites been visited since the last communication to the user.Suggested corrections and improvements for the ‘Bufonidae’ Wikipedia article and communicated them to the user. The next step is to proceed with reviewing additional articles as part of the task. No other actions have been taken, nor resources used since the last action.Completed review of the ‘Bufonidae’ Wikipedia article and provided feedback to the user. No new files have been created, and no new articles reviewed. Proceeding to the next article in alignment with the task.Identified potential improvements for the Wikipedia article on ‘Andrew Horatio Reeder’ and messaged the user with these suggestions. Will proceed with fetching the next article to review. No new actions have been taken or resources used since the last update.Reviewed the Wikipedia article titled ‘Andrew Horatio Reeder’ and suggested improvements to the user. Heading towards retrieving and reviewing the next article as per the task instructions. No files have been created or websites visited since the last provided summary.Advised that the ‘North Central Timor Regency’ Wikipedia article needs significant expansion to provide a complete overview. Prepared to retrieve and evaluate the next article in line with the task requirements. No further actions have been taken since the last status update.Have been reviewing Simple English Wikipedia articles for grammatical and content errors, and messaging the user with feedback as necessary. No new files have been created, and no websites have been visited since the last update. The next article is pending retrieval. Task progress: ongoing task of reviewing 1000 Wikipedia articles, count unknown.Message sent to user regarding errors found in the ‘Caliphate’ Wikipedia article. Plan to continue reviewing additional articles. No new files created or websites visited. Task progress: ongoing review of ‘simple’ Wikipedia articles, with the next article retrieval pending.A message has been sent to the user regarding errors in the ‘Caliphate’ article, and the next action is to retrieve a random Simple English Wikipedia article as per the task instructions. No new files have been created, no websites visited, and the number of articles reviewed so far is not specified. Continuing task of reviewing Wikipedia articles.Sent message to user regarding errors found in the ‘Pizza Delivery (SpongeBob SquarePants)’ article. Next, I will retrieve another random Simple English Wikipedia article for review as per the ongoing task guidelines. No new files have been created, nor have any websites been visited since the last update. Task progress: ongoing.Task in progress is to review Wikipedia articles for errors. A message regarding errors found in the ‘Pizza Delivery (SpongeBob SquarePants)’ article has been sent to the user. The system prompted to continue with the plan, which is to retrieve and review more articles. No new files created, no other tasks in parallel at the moment. Moving to the next article retrieval.Message sent to user about the errors and expansion opportunities in the ‘Aires Ali’ article. The next step is to continue with the plan of retrieving and reviewing more Simple English Wikipedia articles. No additional actions have been taken or resources used since the last update. Task progress: ongoing review of Wikipedia articles.After sending a message regarding the ‘Aires Ali’ article, the task continues with retrieving the next article. No files have been created or websites visited since the last summary. Task progress: ongoing with the retrieval and review of Simple English Wikipedia articles.Sent a message to the user concerning the briefness and lack of detail in the ‘Fast Times at Ridgemont High’ article. The plan is to continue the task by retrieving and reviewing another article. No new files have been created, nor have any URLs been visited since the last summary. Task progress: ongoing review of Wikipedia articles.The user was messaged with suggestions to improve the ‘Fast Times at Ridgemont High’ article, and I am moving forward to retrieve another article in line with the ongoing task of reviewing Simple English Wikipedia articles. No files have been created, nor websites visited, in the course of this task. Continual progress towards reviewing 1000 articles.A message detailing potential improvements for the ‘West Coast Conference’ Wikipedia article has been sent to the user. The plan is to proceed with retrieving and reviewing additional articles. To date, no new files have been written, nor have any external URLs been visited. Task progress: continuing with the review of Simple English Wikipedia articles.Having messaged the user regarding the West Coast Conference article, I am proceeding to retrieve another random Simple English Wikipedia article as part of the task to review 1000 articles for errors. There have been no files created or websites visited since the last summary. Task progress: ongoing.The user has been notified of the need to expand and verify the content of the ‘Sledge, Mississippi’ Wikipedia article. As no new articles have been retrieved or reviewed since then, the next step is to continue fulfilling the task of reviewing 1000 Simple English Wikipedia articles for errors. No files have been created, and no websites visited in this stage of the task. Task progress: ongoing and continuous.After messaging the user about the Sledge, Mississippi article, the next task is to retrieve another random Simple English Wikipedia article for review. The process to review 1000 Wikipedia articles is ongoing, with the next article pending retrieval. No new actions have been taken since the last update, including file creation or website visits. Task progression is in line with the given instructions.
The Task: go and retrieve simple wikipidea pages and check if they contain any errors like grammar and other stuff and then if there is an error message the user about it giving him the name of the article and the errors in it, and do this for 1000 articles.
|
8ea60da590a8445eea4648d5dc9ddd6a
|
{
"intermediate": 0.3397374749183655,
"beginner": 0.4271845817565918,
"expert": 0.2330779731273651
}
|
34,574
|
Hi
|
5e6bbf36ed1dfb677fdf1e58d4a8685e
|
{
"intermediate": 0.33010533452033997,
"beginner": 0.26984941959381104,
"expert": 0.400045245885849
}
|
34,575
|
how to redirect from admin page to main page in flask app
|
e1ff92a38d6d8438ff7b099541ad35aa
|
{
"intermediate": 0.5667029023170471,
"beginner": 0.20845156908035278,
"expert": 0.22484543919563293
}
|
34,576
|
Есть программа реализации АВЛ-дерева, но по какой-то причине не выполняется балансировка. Как исправить? Вот программа: #include <iostream>
#include<fstream>
#include<string>
#include<cmath>
using namespace std;
class ListNode //элемент списка
{
public:
int data;
ListNode* prev, * next;
public:
ListNode(int data)
{
this->data = data;
this->prev = this->next = NULL;
}
};
class LinkedList //список
{
public:
ListNode* head;
public:
LinkedList() //Инициализация
{
head = NULL;
}
void freeMemory() //Освобождение памяти
{
if (head == NULL)
return;
ListNode* current = head;
ListNode* nextNode;
do
{
nextNode = current->next;
delete current;
current = nextNode;
} while (current != head);
head = NULL;
}
void addSorted(int data) //Добавление элемента в порядке возрастания
{
ListNode* newNode = new ListNode(data);
if (head == NULL) //если список пустой
{
head = newNode;
newNode->next = newNode->prev = newNode;
}
else if (data < head->data) //если новый элемент меньше головы списка
{
newNode->next = head;
newNode->prev = head->prev;
head->prev->next = newNode;
head->prev = newNode;
head = newNode;
}
else if (data > head->prev->data) //если новый элемент больше хвоста списка
{
newNode->next = head;
newNode->prev = head->prev;
head->prev->next = newNode;
head->prev = newNode;
head->prev = newNode;
}
else //если новый элемент располагается где-то в середине списка
{
ListNode* current = head->next;
while (current != head && current->data < data) //поиск элемента, значение которого больше нового
{
current = current->next;
}
newNode->next = current;
newNode->prev = current->prev;
current->prev->next = newNode;
current->prev = newNode;
}
}
void removeBefore(int data) //Удаление элемента перед каждым вхождением заданного
{
if (head == NULL)
{
return;
}
if (head->data == data)
{
ListNode* nodeToRemove = head->prev;
nodeToRemove->prev->next = head;
head->prev = nodeToRemove->prev;
delete nodeToRemove;
}
ListNode* current = head->next;
while (current != head)
{
if (current->data == data)
{
ListNode* nodeToRemove = current->prev;
nodeToRemove->prev->next = current;
current->prev = nodeToRemove->prev;
delete nodeToRemove;
}
current = current->next;
}
}
bool search(int data) //Поиск заданного элемента по значению
{
if (head == NULL)
return false;
ListNode* current = head;
do
{
if (current->data == data)
return true;
current = current->next;
} while (current != head);
return false;
}
void print() //Печать
{
if (head == NULL)
return;
ListNode* current = head;
do
{
cout << current->data << ' ';
current = current->next;
} while (current != head);
cout << endl;
}
LinkedList difference(LinkedList list1, LinkedList list2) //Разность двух списков
{
if (head != NULL)
{
LinkedList result;
ListNode* current = list1.head;
do
{
if (list2.search(current->data) == false)
result.addSorted(current->data);
current = current->next;
} while (current != list1.head);
return result;
}
}
};
struct Key
{
char f1;
int f2;
};
struct Node
{
Key key;
LinkedList list;
Node* left;
Node* right;
int balance;
};
void add(Key x, Node*& p, int linenumber, short h) // поиск и добавление элемента
{
if (x.f1 != 'Б' || x.f2 / 1000 == 0 || x.f2 / 10000 != 0)
{
return;
}
else if (p == NULL) // слова нет в дереве; включить его
{
p = new Node;
p->key = x;
p->list.addSorted(linenumber);
p->balance = 0;
p->left = NULL;
p->right = NULL;
}
else if (x.f2 < p->key.f2)
{
add(x, p->left, linenumber, h);
if (h != 0) // выросла левая ветвь
{
switch (p->balance)
{
case 1:
p->balance = 0;
h = 0;
break;
case 0:
p->balance = -1;
break;
case -1: // балансировка
Node * p1 = p->left;
if (p1->balance == -1) // L-поворот
{
p->left = p1->right;
p1->right = p;
p->balance = 0;
p = p1;
}
else // LR-поворот
{
Node* p2 = p1->right;
p1->right = p2->left;
p2->left = p1;
p->left = p2->right;
p2->right = p;
if (p2->balance == -1)
p->balance = 1;
else
p->balance = 0;
if (p2->balance == 1)
p1->balance = -1;
else
p1->balance = 0;
p = p2;
}
p->balance = 0;
h = 0;
break;
}
}
}
else if (x.f2 > p->key.f2)
{
add(x, p->right, linenumber, h);
if (h != 0) // выросла правая ветвь
{
switch (p->balance)
{
case -1:
p->balance = 0;
h = 0;
break;
case 0:
p->balance = 1;
break;
case 1: // балансировка
Node * p1 = p->right;
if (p1->balance == 1) //R-поворот
{
p->right = p1->left;
p1->left = p;
p->balance = 0;
p = p1;
}
else // RL-поворот
{
Node* p2 = p1->left;
p1->left = p2->right;
p2->right = p1;
p->right = p2->left;
p2->left = p;
if (p2->balance == 1)
p->balance = -1;
else
p->balance = 0;
if (p2->balance == -1)
p1->balance = 1;
else
p1->balance = 0;
p = p2;
}
p->balance = 0;
h = 0;
break;
}
}
}
else
{
p->list.addSorted(linenumber);
h = 0;
}
}
void balance1(Node* p, short h)
{
Node* p1, * p2;
short b1, b2;
switch (p->balance)
{
case -1:
p->balance = 0;
break;
case 0:
p->balance = 1;
h = 0;
break;
case 1: // балансировка
p1 = p->right;
b1 = p1->balance;
if (b1 >= 0) // R-поворот
{
p->right = p1->left;
p1->left = p;
if (b1 == 0)
{
p->balance = 1;
p1->balance = -1;
h = 0;
}
else
{
p->balance = 0;
p1->balance = 0;
}
p = p1;
}
else // RL-поворот
{
p2 = p1->left;
b2 = p2->balance;
p1->left = p2->right;
p2->right = p1;
p->right = p2->left;
p2->left = p;
if (b2 == 1)
p->balance = -1;
else
p->balance = 0;
if (b2 == -1)
p1->balance = 1;
else
p1->balance = 0;
p = p2;
p2->balance = 0;
}
}
}
void balance2(Node* p, short h)
{
Node* p1, * p2;
short b1, b2;
switch (p->balance)
{
case 1:
p->balance = 0;
break;
case 0:
p->balance = 0;
h = 0;
break;
case -1:
p1 = p->left;
b1 = p1->balance;
if (b1 <= 0) // L-поворот
{
p->left = p1->right;
p1->right = p;
if (b1 == 0)
{
p->balance = -1;
p1->balance = 1;
h = 0;
}
else
{
p->balance = 0;
p1->balance = 0;
}
p = p1;
}
else // LR-поворот
{
p2 = p1->right;
b2 = p2->balance;
p1->right = p2->left;
p2->left = p1;
p->left = p2->right;
p2->right = p;
if (b2 == -1)
p->balance = 1;
else
p->balance = 0;
if (b2 == 1)
p1->balance = -1;
else
p1->balance = 0;
p = p2;
p2->balance = 0;
}
}
}
Node* del(Node* r, Node* q, short h)
{
if (r->right != NULL)
{
r->right = del(r->right, q, h);
if (h != 0)
balance2(r, h);
return r;
}
else
{
q->key = r->key;
Node* left = r->left;
delete r;
h = 1;
return left;
}
}
void delet(Key x, Node*& p, short h) // удаление элемента, выше вспомогательные подпрограммы
{
Node* q;
if (p == NULL || x.f1 != 'Б' || x.f2 / 1000 == 0 || x.f2 / 10000 != 0)
{
cout << "Key is not in tree" << endl;
h = 0;
}
else if (x.f2 < p->key.f2)
{
delet(x, p->left, h);
if (h != 0)
balance1(p, h);
}
else if (x.f2 > p->key.f2)
{
delet(x, p->right, h);
if (h != 0)
balance2(p, h);
}
else
{
if (p->left == NULL && p->right == NULL)
{
delete p;
p = NULL;
h = 1;
}
else if (p->left != NULL && p->right == NULL)
{
Node* temp = p->left;
delete p;
p = temp;
h = 1;
}
else if (p->left == NULL && p->right != NULL)
{
Node* temp = p->right;
delete p;
p = temp;
h = 1;
}
else
{
p->list.freeMemory();
Node* temp = p->left;
Node* parent = p;
while (temp->right != NULL)
{
parent = temp;
temp = temp->right;
}
if (parent != p)
parent->right = temp->left;
else
parent->left = temp->left;
p->key = temp->key;
p->list = temp->list;
delete temp;
h = 1;
}
}
}
void search(Key x, Node*& p, short h) // поиск элемента
{
Node* q;
if (p == NULL || x.f1 != 'Б')
{
cout << "В дереве нет такого элемента" << endl;
h = 0;
}
else if (x.f2 < p->key.f2)
{
search(x, p->left, h);
}
else if (x.f2 > p->key.f2)
{
search(x, p->right, h);
}
else
{
cout << "Элемент содержится в строке(ах) входного файла ";
p->list.print();
}
}
ofstream out("outdata.txt");
void walktree(Node* t, short h) // обход дерева справа налево и вывод в файл
{
if (t != NULL)
{
walktree(t->right, h + 1);
out << t->key.f1 << t->key.f2 << endl;
walktree(t->left, h + 1);
}
}
void printtree(Node* t, short h) // печать дерева
{
if (t != NULL)
{
printtree(t->left, h + 1);
for (int i = 1; i <= h; i++)
cout << " ";
cout << t->key.f1 << t->key.f2 << endl;
printtree(t->right, h + 1);
}
}
void deletetree(Node* t, short h) // удаление дерева
{
if (t != NULL)
{
deletetree(t->right, h + 1);
delete t;
deletetree(t->left, h + 1);
}
}
ifstream in("data.txt");
void initialize(Node*& p)
{
Key key;
string line;
int linenumber = 0;
if (in.is_open())
{
while (getline(in, line))
{
++linenumber;
key.f1 = line[0];
key.f2 = 0;
for (int i = 1; i < 5; i++)
{
key.f2 += (line[i] - '0') * pow(10, 4 - i);
}
add(key, p, linenumber, 0);
}
}
}
int main()
{
setlocale(LC_ALL, "rus");
Node* root = NULL;
initialize(root);
walktree(root, 0);
//delet({ 'Б', 9122 }, root, 0);
printtree(root, 0);
in.close();
out.close();
return 0;
}
|
7ab96de6cb8f496d65327b38420a2cb3
|
{
"intermediate": 0.3216214179992676,
"beginner": 0.607682466506958,
"expert": 0.07069610804319382
}
|
34,577
|
Есть программа реализации АВЛ-дерева, но по какой-то причине не выполняется балансировка. Как исправить? Вот программа: #include <iostream>
#include<fstream>
#include<string>
#include<cmath>
using namespace std;
class ListNode //элемент списка
{
public:
int data;
ListNode* prev, * next;
public:
ListNode(int data)
{
this->data = data;
this->prev = this->next = NULL;
}
};
class LinkedList //список
{
public:
ListNode* head;
public:
LinkedList() //Инициализация
{
head = NULL;
}
void freeMemory() //Освобождение памяти
{
if (head == NULL)
return;
ListNode* current = head;
ListNode* nextNode;
do
{
nextNode = current->next;
delete current;
current = nextNode;
} while (current != head);
head = NULL;
}
void addSorted(int data) //Добавление элемента в порядке возрастания
{
ListNode* newNode = new ListNode(data);
if (head == NULL) //если список пустой
{
head = newNode;
newNode->next = newNode->prev = newNode;
}
else if (data < head->data) //если новый элемент меньше головы списка
{
newNode->next = head;
newNode->prev = head->prev;
head->prev->next = newNode;
head->prev = newNode;
head = newNode;
}
else if (data > head->prev->data) //если новый элемент больше хвоста списка
{
newNode->next = head;
newNode->prev = head->prev;
head->prev->next = newNode;
head->prev = newNode;
head->prev = newNode;
}
else //если новый элемент располагается где-то в середине списка
{
ListNode* current = head->next;
while (current != head && current->data < data) //поиск элемента, значение которого больше нового
{
current = current->next;
}
newNode->next = current;
newNode->prev = current->prev;
current->prev->next = newNode;
current->prev = newNode;
}
}
void removeBefore(int data) //Удаление элемента перед каждым вхождением заданного
{
if (head == NULL)
{
return;
}
if (head->data == data)
{
ListNode* nodeToRemove = head->prev;
nodeToRemove->prev->next = head;
head->prev = nodeToRemove->prev;
delete nodeToRemove;
}
ListNode* current = head->next;
while (current != head)
{
if (current->data == data)
{
ListNode* nodeToRemove = current->prev;
nodeToRemove->prev->next = current;
current->prev = nodeToRemove->prev;
delete nodeToRemove;
}
current = current->next;
}
}
bool search(int data) //Поиск заданного элемента по значению
{
if (head == NULL)
return false;
ListNode* current = head;
do
{
if (current->data == data)
return true;
current = current->next;
} while (current != head);
return false;
}
void print() //Печать
{
if (head == NULL)
return;
ListNode* current = head;
do
{
cout << current->data << ' ';
current = current->next;
} while (current != head);
cout << endl;
}
LinkedList difference(LinkedList list1, LinkedList list2) //Разность двух списков
{
if (head != NULL)
{
LinkedList result;
ListNode* current = list1.head;
do
{
if (list2.search(current->data) == false)
result.addSorted(current->data);
current = current->next;
} while (current != list1.head);
return result;
}
}
};
struct Key
{
char f1;
int f2;
};
struct Node
{
Key key;
LinkedList list;
Node* left;
Node* right;
int balance;
};
void add(Key x, Node*& p, int linenumber, short h) // поиск и добавление элемента
{
if (x.f1 != 'Б' || x.f2 / 1000 == 0 || x.f2 / 10000 != 0)
{
return;
}
else if (p == NULL) // слова нет в дереве; включить его
{
p = new Node;
p->key = x;
p->list.addSorted(linenumber);
p->balance = 0;
p->left = NULL;
p->right = NULL;
}
else if (x.f2 < p->key.f2)
{
add(x, p->left, linenumber, h);
if (h != 0) // выросла левая ветвь
{
switch (p->balance)
{
case 1:
p->balance = 0;
h = 0;
break;
case 0:
p->balance = -1;
break;
case -1: // балансировка
Node * p1 = p->left;
if (p1->balance == -1) // L-поворот
{
p->left = p1->right;
p1->right = p;
p->balance = 0;
p = p1;
}
else // LR-поворот
{
Node* p2 = p1->right;
p1->right = p2->left;
p2->left = p1;
p->left = p2->right;
p2->right = p;
if (p2->balance == -1)
p->balance = 1;
else
p->balance = 0;
if (p2->balance == 1)
p1->balance = -1;
else
p1->balance = 0;
p = p2;
}
p->balance = 0;
h = 0;
break;
}
}
}
else if (x.f2 > p->key.f2)
{
add(x, p->right, linenumber, h);
if (h != 0) // выросла правая ветвь
{
switch (p->balance)
{
case -1:
p->balance = 0;
h = 0;
break;
case 0:
p->balance = 1;
break;
case 1: // балансировка
Node * p1 = p->right;
if (p1->balance == 1) //R-поворот
{
p->right = p1->left;
p1->left = p;
p->balance = 0;
p = p1;
}
else // RL-поворот
{
Node* p2 = p1->left;
p1->left = p2->right;
p2->right = p1;
p->right = p2->left;
p2->left = p;
if (p2->balance == 1)
p->balance = -1;
else
p->balance = 0;
if (p2->balance == -1)
p1->balance = 1;
else
p1->balance = 0;
p = p2;
}
p->balance = 0;
h = 0;
break;
}
}
}
else
{
p->list.addSorted(linenumber);
h = 0;
}
}
void balance1(Node* p, short h)
{
Node* p1, * p2;
short b1, b2;
switch (p->balance)
{
case -1:
p->balance = 0;
break;
case 0:
p->balance = 1;
h = 0;
break;
case 1: // балансировка
p1 = p->right;
b1 = p1->balance;
if (b1 >= 0) // R-поворот
{
p->right = p1->left;
p1->left = p;
if (b1 == 0)
{
p->balance = 1;
p1->balance = -1;
h = 0;
}
else
{
p->balance = 0;
p1->balance = 0;
}
p = p1;
}
else // RL-поворот
{
p2 = p1->left;
b2 = p2->balance;
p1->left = p2->right;
p2->right = p1;
p->right = p2->left;
p2->left = p;
if (b2 == 1)
p->balance = -1;
else
p->balance = 0;
if (b2 == -1)
p1->balance = 1;
else
p1->balance = 0;
p = p2;
p2->balance = 0;
}
}
}
void balance2(Node* p, short h)
{
Node* p1, * p2;
short b1, b2;
switch (p->balance)
{
case 1:
p->balance = 0;
break;
case 0:
p->balance = 0;
h = 0;
break;
case -1:
p1 = p->left;
b1 = p1->balance;
if (b1 <= 0) // L-поворот
{
p->left = p1->right;
p1->right = p;
if (b1 == 0)
{
p->balance = -1;
p1->balance = 1;
h = 0;
}
else
{
p->balance = 0;
p1->balance = 0;
}
p = p1;
}
else // LR-поворот
{
p2 = p1->right;
b2 = p2->balance;
p1->right = p2->left;
p2->left = p1;
p->left = p2->right;
p2->right = p;
if (b2 == -1)
p->balance = 1;
else
p->balance = 0;
if (b2 == 1)
p1->balance = -1;
else
p1->balance = 0;
p = p2;
p2->balance = 0;
}
}
}
Node* del(Node* r, Node* q, short h)
{
if (r->right != NULL)
{
r->right = del(r->right, q, h);
if (h != 0)
balance2(r, h);
return r;
}
else
{
q->key = r->key;
Node* left = r->left;
delete r;
h = 1;
return left;
}
}
void delet(Key x, Node*& p, short h) // удаление элемента, выше вспомогательные подпрограммы
{
Node* q;
if (p == NULL || x.f1 != 'Б' || x.f2 / 1000 == 0 || x.f2 / 10000 != 0)
{
cout << "Key is not in tree" << endl;
h = 0;
}
else if (x.f2 < p->key.f2)
{
delet(x, p->left, h);
if (h != 0)
balance1(p, h);
}
else if (x.f2 > p->key.f2)
{
delet(x, p->right, h);
if (h != 0)
balance2(p, h);
}
else
{
if (p->left == NULL && p->right == NULL)
{
delete p;
p = NULL;
h = 1;
}
else if (p->left != NULL && p->right == NULL)
{
Node* temp = p->left;
delete p;
p = temp;
h = 1;
}
else if (p->left == NULL && p->right != NULL)
{
Node* temp = p->right;
delete p;
p = temp;
h = 1;
}
else
{
p->list.freeMemory();
Node* temp = p->left;
Node* parent = p;
while (temp->right != NULL)
{
parent = temp;
temp = temp->right;
}
if (parent != p)
parent->right = temp->left;
else
parent->left = temp->left;
p->key = temp->key;
p->list = temp->list;
delete temp;
h = 1;
}
}
}
void search(Key x, Node*& p, short h) // поиск элемента
{
Node* q;
if (p == NULL || x.f1 != 'Б')
{
cout << "В дереве нет такого элемента" << endl;
h = 0;
}
else if (x.f2 < p->key.f2)
{
search(x, p->left, h);
}
else if (x.f2 > p->key.f2)
{
search(x, p->right, h);
}
else
{
cout << "Элемент содержится в строке(ах) входного файла ";
p->list.print();
}
}
ofstream out("outdata.txt");
void walktree(Node* t, short h) // обход дерева справа налево и вывод в файл
{
if (t != NULL)
{
walktree(t->right, h + 1);
out << t->key.f1 << t->key.f2 << endl;
walktree(t->left, h + 1);
}
}
void printtree(Node* t, short h) // печать дерева
{
if (t != NULL)
{
printtree(t->left, h + 1);
for (int i = 1; i <= h; i++)
cout << " ";
cout << t->key.f1 << t->key.f2 << endl;
printtree(t->right, h + 1);
}
}
void deletetree(Node* t, short h) // удаление дерева
{
if (t != NULL)
{
deletetree(t->right, h + 1);
delete t;
deletetree(t->left, h + 1);
}
}
ifstream in("data.txt");
void initialize(Node*& p)
{
Key key;
string line;
int linenumber = 0;
if (in.is_open())
{
while (getline(in, line))
{
++linenumber;
key.f1 = line[0];
key.f2 = 0;
for (int i = 1; i < 5; i++)
{
key.f2 += (line[i] - '0') * pow(10, 4 - i);
}
add(key, p, linenumber, 0);
}
}
}
int main()
{
setlocale(LC_ALL, "rus");
Node* root = NULL;
initialize(root);
walktree(root, 0);
//delet({ 'Б', 9122 }, root, 0);
printtree(root, 0);
in.close();
out.close();
return 0;
}
|
ef17d5d5f28e28dfad9b99a0f0f37c4d
|
{
"intermediate": 0.3216214179992676,
"beginner": 0.607682466506958,
"expert": 0.07069610804319382
}
|
34,578
|
import gradio as gr
import os
import sys
import json
import requests
MODEL = "gpt-4-1106-preview"
API_URL = os.getenv("API_URL")
DISABLED = os.getenv("DISABLED") == 'True'
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
print (API_URL)
print (OPENAI_API_KEY)
NUM_THREADS = int(os.getenv("NUM_THREADS"))
print (NUM_THREADS)
def exception_handler(exception_type, exception, traceback):
print("%s: %s" % (exception_type.__name__, exception))
sys.excepthook = exception_handler
sys.tracebacklimit = 0
#https://github.com/gradio-app/gradio/issues/3531#issuecomment-1484029099
def parse_codeblock(text):
lines = text.split("\n")
for i, line in enumerate(lines):
if "
|
b57cf4759057387c8e2ba9f2460057ce
|
{
"intermediate": 0.5005274415016174,
"beginner": 0.2965071201324463,
"expert": 0.20296543836593628
}
|
34,579
|
public Resp pageXBInheritedClassInfo(@RequestBody @Validated(ApiOperateConst.QUERY.class) PageXBInheritedClassInfoDTO dto)
|
9fcf3af9b3fba67d361f19c78ee5adbd
|
{
"intermediate": 0.34237220883369446,
"beginner": 0.35664981603622437,
"expert": 0.30097803473472595
}
|
34,580
|
provide me a project using redux toolkit and saga
|
c16a0ee508ef6f3200a939166f130381
|
{
"intermediate": 0.5633506178855896,
"beginner": 0.123529352247715,
"expert": 0.313120037317276
}
|
34,581
|
powershell -ExecutionPolicy Unrestricted Add-AppxPackage -DisableDevelopmentMode -Register $Env:SystemRoot\WinStore\AppxManifest.xml
Add-AppxPackage : Cannot find path 'C:\WINDOWS\WinStore\AppxManifest.xml' because it does not exist.
At line:1 char:1
+ Add-AppxPackage -DisableDevelopmentMode -Register C:\WINDOWS\WinStore ...
+ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+ CategoryInfo : ObjectNotFound: (C:\WINDOWS\WinStore\AppxManifest.xml:String) [Add-AppxPackage], ItemNot
FoundException
+ FullyQualifiedErrorId : PathNotFound,Microsoft.Windows.Appx.PackageManager.Commands.AddAppxPackageCommand
|
1cd1513bdfefd01f0789563dfbe7f664
|
{
"intermediate": 0.37801921367645264,
"beginner": 0.34800490736961365,
"expert": 0.27397584915161133
}
|
34,582
|
C:\Windows\System32>winget upgrade --all
Failed in attempting to update the source: winget
Failed when searching source: winget
An unexpected error occurred while executing the command:
0x8a15000f : Data required by the source is missing
|
1db8c6dd35a3e86514b702ccd2da02c4
|
{
"intermediate": 0.3775973916053772,
"beginner": 0.27166834473609924,
"expert": 0.3507342040538788
}
|
34,583
|
internal class SailplayApiStrictClient: ISailplayApiStrictClient { private readonly IAuthorizationExecutor authorizationExecutor; private readonly IRequestExecutor requestExecutor; public SailplayApiStrictClient( IAuthorizationExecutor authorizationExecutor, IRequestExecutor requestExecutor) { this.authorizationExecutor = authorizationExecutor; this.requestExecutor = requestExecutor; } public async Task < UpdateUserResult > UpdateUserAsync( SailplayCredentials credentials, UpdateUser requestData, CancellationToken cancellationToken) { var updateUserRequest = new UpdateUserRequest( credentials: credentials, requestData: requestData); var apiResponse = await this.requestExecutor.ExecuteApiRequestAsync( apiPath: ApiPath.UsersUpdate, sailplayApiRequest: updateUserRequest, cancellationToken: cancellationToken); return apiResponse.Match( onSuccess: UpdateUserResult.FromSuccess, onError: errorResult => { return errorResult.ErrorCode switch { ApiResponse.ErrorCodes.InvalidValue => UpdateUserResult.FromError( ErrorResult.FromInvalidValue( errorCode: errorResult.ErrorCode, message: errorResult.Message)), ApiResponse.ErrorCodes.UserNotFound => UpdateUserResult.FromError( ErrorResult.FromUserNotFound( errorCode: errorResult.ErrorCode, message: errorResult.Message)), ApiResponse.ErrorCodes.EmailIsUsed => UpdateUserResult.FromError( ErrorResult.FromEmailIsUsed( errorCode: errorResult.ErrorCode, message: errorResult.Message)), ApiResponse.ErrorCodes.PhoneIsUsed => UpdateUserResult.FromError( ErrorResult.FromPhoneIsUsed( errorCode: errorResult.ErrorCode, message: errorResult.Message)), _ => UpdateUserResult.FromError( ErrorResult.FromGeneralError( errorCode: errorResult.ErrorCode, message: errorResult.Message)), }; }, onUnexpectedHttpStatusCode: UpdateUserResult.FromUnexpectedHttpStatusCode); } } internal class RequestExecutor: IRequestExecutor { private readonly HttpClient httpClient; private readonly IMetricsCollector metricsCollector; private readonly ITokenProvider tokenProvider; public RequestExecutor( HttpClient httpClient, IMetricsCollector metricsCollector, ITokenProvider tokenProvider) { this.httpClient = httpClient; this.metricsCollector = metricsCollector; this.tokenProvider = tokenProvider; } public async Task < SailplayApiResult > ExecuteApiRequestAsync( string apiPath, ISailplayApiRequest sailplayApiRequest, CancellationToken cancellationToken) { var tokenResult = await this.tokenProvider .GetTokenAsync( credentials: sailplayApiRequest.Credentials, cancellationToken: cancellationToken); return await Policy.HandleResult < SailplayApiResult > (apiResult => apiResult.IsAuthorizationTokenError) .RetryAsync( retryCount: 1, onRetryAsync: async (_, _, _) => { tokenResult = await this.tokenProvider.RenewTokenAsync( credentials: sailplayApiRequest.Credentials, cancellationToken: cancellationToken); }) .ExecuteAsync( async () => await tokenResult .Match( onSuccess: async successfullyGetTokenResult => { var request = HttpRequestMessageFactory.BuildPost( requestUri: apiPath); request.Content = sailplayApiRequest.ConvertToHttpContent( token: successfullyGetTokenResult.Token); return await this .ExecuteRequestAsync( request: request, cancellationToken: cancellationToken); }, onError: result => Task.FromResult( SailplayApiResult.FromError( statusCode: result.ErrorCode, message: result.Message)), onUnexpectedHttpStatusCode: result => Task.FromResult( SailplayApiResult.FromUnexpectedHttpStatusCode( httpStatusCode: result.StatusCode)))); } private async Task < SailplayApiResult > ExecuteRequestAsync( HttpRequestMessage request, CancellationToken cancellationToken) { var stopwatch = Stopwatch.StartNew(); using var httpResponseMessage = await this .httpClient .SendAsync( request: request, cancellationToken: cancellationToken); this.metricsCollector.CollectHttpRequestDuration( uri: request.RequestUri, statusCode: httpResponseMessage.StatusCode, elapsedMilliseconds: stopwatch.ElapsedMilliseconds); var result = await this.MapHttpResponseAsync( httpResponseMessage: httpResponseMessage, cancellationToken: cancellationToken); return result; } private async Task < SailplayApiResult > MapHttpResponseAsync( HttpResponseMessage httpResponseMessage, CancellationToken cancellationToken) { var basicResponse = await httpResponseMessage .Content .ReadFromJsonAsync < BasicResponse > ( cancellationToken: cancellationToken); return httpResponseMessage.StatusCode switch { HttpStatusCode.OK => basicResponse!.Match( onStatusOk: SailplayApiResult.FromSuccess, onStatusError: SailplayApiResult.FromError), _ => SailplayApiResult.FromUnexpectedHttpStatusCode(httpResponseMessage.StatusCode), }; } } internal class UpdateUserRequest: ISailplayApiRequest { private readonly UpdateUser requestData; internal UpdateUserRequest( SailplayCredentials credentials, UpdateUser requestData) { this.Credentials = credentials; this.requestData = requestData; } public SailplayCredentials Credentials { get; set; } public HttpContent ConvertToHttpContent( string token) { var keyValuePairs = new List < KeyValuePair < string, string >> { FormDataFactory.FromToken(token), FormDataFactory.FromStoreDepartmentId(this.Credentials.StoreDepartmentId), }; keyValuePairs.AddRange(FormDataFactory.FromUserId(this.requestData.UserId)); this.requestData.Phone.MatchSome(phone => keyValuePairs.Add(FormDataFactory.FromNewPhone(phone))); this.requestData.Email.MatchSome(email => keyValuePairs.Add(FormDataFactory.FromNewEmail(email))); this.requestData.FirstName.MatchSome(firstName => keyValuePairs.Add(FormDataFactory.FromFirstName(firstName))); this.requestData.MiddleName.MatchSome(middleName => keyValuePairs.Add(FormDataFactory.FromMiddleName(middleName))); this.requestData.LastName.MatchSome(lastName => keyValuePairs.Add(FormDataFactory.FromLastName(lastName))); this.requestData.BirthDate.MatchSome(birthDate => keyValuePairs.Add(FormDataFactory.FromBirthDate(birthDate))); this.requestData.Sex.MatchSome(sex => keyValuePairs.Add(FormDataFactory.FromSex(sex))); this.requestData.RegisterDate.MatchSome(registerDate => keyValuePairs.Add(FormDataFactory.FromRegisterDate(registerDate))); return new FormUrlEncodedContent(keyValuePairs); } } у меня есть три класса, я бы хотел, чтобы UpdateUserRequest можно было создать где угодно, а его метод ConvertToHttpContent можно было вызвать только в RequestExecutor
|
44ba21f1ec1a549c05f30b3333f3675f
|
{
"intermediate": 0.3031674027442932,
"beginner": 0.6119289398193359,
"expert": 0.08490363508462906
}
|
34,584
|
I have this code for a python app to create language, code: import tkinter as tk
from tkinter import filedialog
from keras.models import Sequential
from keras.layers import Embedding, LSTM, Dense
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.utils import to_categorical
import numpy as np
import os
import pickle
from keras.layers import Masking
# Data loader and preprocessor function
def preprocess_data(file_paths):
tokenizer = Tokenizer()
# Load and concatenate content from all selected dataset files
all_text = ""
for file_path in file_paths:
with open(file_path, "r", encoding="utf-8") as file:
text = file.read()
all_text += text + "\n" # Ensure separation between files’ content
sentences = all_text.split("\n")
tokenizer.fit_on_texts(sentences)
sequences = tokenizer.texts_to_sequences(sentences)
# Check if we’re using a fixed sequence length
if sequence_choice_var.get():
# Read the fixed sequence length from the respective entry field
sequence_length = int(entry_fixed_length.get())
padded_sequences = pad_sequences(sequences, maxlen=sequence_length, padding="pre")
else:
# Minimal sequence length, could also eliminate the minimum length condition
sequence_length = min(len(seq) for seq in sequences if len(seq) > 1)
padded_sequences = sequences
big_sequence = [token for seq in sequences for token in seq]
input_sequences, output_words = [], []
# Assign a sequence length based on the shortest sentence
# Note: for better training with variable lengths, consider using sentences directly and/or padding at the end of each batch
sequence_length = min(len(seq) for seq in sequences if len(seq) > 1)
for i in range(len(big_sequence) - sequence_length):
input_sequences.append(big_sequence[i:i + sequence_length])
output_words.append(big_sequence[i + sequence_length])
# Remove pad_sequences call - handle varying sequence lengths directly in the model using masking or by padding at batch end
vocab_size = len(tokenizer.word_index) + 1
output_words = np.array(output_words)
output_words = to_categorical(output_words, num_classes=vocab_size)
return np.array(input_sequences), output_words, vocab_size, tokenizer
# Function to train and save the model
def train_model():
num_layers = int(entry_layers.get())
layer_size = int(entry_size.get())
model_name = entry_name.get()
epochs = int(entry_epochs.get())
data_paths = root.filenames # Changed to accept multiple filenames
# Preprocess the data
input_sequences, output_words, vocab_size, tokenizer = preprocess_data(data_paths)
tokenizer_path = os.path.join('tokenizers', f'{model_name}_tokenizer.pickle')
if not os.path.exists('tokenizers'):
os.makedirs('tokenizers')
with open(tokenizer_path, 'wb') as handle:
pickle.dump(tokenizer, handle, protocol=pickle.HIGHEST_PROTOCOL)
print(f"Tokenizer saved at {tokenizer_path}")
# Also save the sequence length if fixed
if sequence_choice_var.get():
with open(tokenizer_path, "wb") as handle:
pickle.dump((tokenizer, sequence_length), handle, protocol=pickle.HIGHEST_PROTOCOL)
else:
with open(tokenizer_path, "wb") as handle:
pickle.dump(tokenizer, handle, protocol=pickle.HIGHEST_PROTOCOL)
model = Sequential()
model.add(Embedding(input_dim=vocab_size, output_dim=layer_size))
if not sequence_choice_var.get(): # Add masking for variable length sequences only
model.add(Masking(mask_value=0)) # Ignoring padded values (zeros)
model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
model.fit(input_sequences, output_words, epochs=epochs)
if not os.path.exists('models'):
os.makedirs('models')
model.save(os.path.join('models', f'{model_name}.h5'))
print(f"Model {model_name} trained and saved successfully!")
# UI Setup
root = tk.Tk()
root.title("Chatbot Language Model Trainer")
# Number of layers
lbl_layers = tk.Label(root, text="Number of layers:")
lbl_layers.pack()
entry_layers = tk.Entry(root)
entry_layers.pack()
# Layer size
lbl_size = tk.Label(root, text="Size of each layer:")
lbl_size.pack()
entry_size = tk.Entry(root)
entry_size.pack()
# Model name
lbl_name = tk.Label(root, text="Model name:")
lbl_name.pack()
entry_name = tk.Entry(root)
entry_name.pack()
# Number of epochs
lbl_epochs = tk.Label(root, text="Number of epochs:")
lbl_epochs.pack()
entry_epochs = tk.Entry(root)
entry_epochs.pack()
# Data file path
lbl_data_path = tk.Label(root, text="Data file path:")
lbl_data_path.pack()
entry_data_path = tk.Entry(root)
entry_data_path.pack()
# Checkbox for sequence length choice
lbl_sequence_choice = tk.Label(root, text="Use fixed sequence length:")
lbl_sequence_choice.pack()
sequence_choice_var = tk.BooleanVar() # Boolean variable to hold the checkbox state
chk_sequence_choice = tk.Checkbutton(root, text="Fixed length", variable=sequence_choice_var)
chk_sequence_choice.pack()
# Entry for fixed sequence length if the toggle is on
lbl_fixed_length = tk.Label(root, text="Fixed sequence length:")
lbl_fixed_length.pack()
entry_fixed_length = tk.Entry(root)
entry_fixed_length.pack()
# Function to select multiple files
def select_files():
file_paths = filedialog.askopenfilenames() # Changed to open multiple files
root.filenames = file_paths # Store the list of file paths on the root object
entry_data_path.delete(0, tk.END)
entry_data_path.insert(0, "; ".join(file_paths)) # Display all file paths in the entry
btn_browse = tk.Button(root, text="Browse…", command=select_files) # Changed to select_files
btn_browse.pack()
# Train button
btn_train = tk.Button(root, text="Train Model", command=train_model)
btn_train.pack()
# Start the tkinter loop
root.mainloop() but the variable sequence_length is not defined, help me with that
|
b4bc4952158a1795ecf4635ba3173f84
|
{
"intermediate": 0.4285416901111603,
"beginner": 0.3933343291282654,
"expert": 0.17812399566173553
}
|
34,585
|
How do i reset all windows store apps with powershell?
|
780b6e0ae303aa18c3c33528d6e8c466
|
{
"intermediate": 0.5285627245903015,
"beginner": 0.24051591753959656,
"expert": 0.2309214174747467
}
|
34,586
|
Есть программа реализации АВЛ-дерева, но по какой-то причине не выполняется балансировка. Как исправить? Вот программа: #include <iostream>
#include<fstream>
#include<string>
#include<cmath>
using namespace std;
class ListNode //элемент списка
{
public:
int data;
ListNode* prev, * next;
public:
ListNode(int data)
{
this->data = data;
this->prev = this->next = NULL;
}
};
class LinkedList //список
{
public:
ListNode* head;
public:
LinkedList() //Инициализация
{
head = NULL;
}
void freeMemory() //Освобождение памяти
{
if (head == NULL)
return;
ListNode* current = head;
ListNode* nextNode;
do
{
nextNode = current->next;
delete current;
current = nextNode;
} while (current != head);
head = NULL;
}
void addSorted(int data) //Добавление элемента в порядке возрастания
{
ListNode* newNode = new ListNode(data);
if (head == NULL) //если список пустой
{
head = newNode;
newNode->next = newNode->prev = newNode;
}
else if (data < head->data) //если новый элемент меньше головы списка
{
newNode->next = head;
newNode->prev = head->prev;
head->prev->next = newNode;
head->prev = newNode;
head = newNode;
}
else if (data > head->prev->data) //если новый элемент больше хвоста списка
{
newNode->next = head;
newNode->prev = head->prev;
head->prev->next = newNode;
head->prev = newNode;
head->prev = newNode;
}
else //если новый элемент располагается где-то в середине списка
{
ListNode* current = head->next;
while (current != head && current->data < data) //поиск элемента, значение которого больше нового
{
current = current->next;
}
newNode->next = current;
newNode->prev = current->prev;
current->prev->next = newNode;
current->prev = newNode;
}
}
void removeBefore(int data) //Удаление элемента перед каждым вхождением заданного
{
if (head == NULL)
{
return;
}
if (head->data == data)
{
ListNode* nodeToRemove = head->prev;
nodeToRemove->prev->next = head;
head->prev = nodeToRemove->prev;
delete nodeToRemove;
}
ListNode* current = head->next;
while (current != head)
{
if (current->data == data)
{
ListNode* nodeToRemove = current->prev;
nodeToRemove->prev->next = current;
current->prev = nodeToRemove->prev;
delete nodeToRemove;
}
current = current->next;
}
}
bool search(int data) //Поиск заданного элемента по значению
{
if (head == NULL)
return false;
ListNode* current = head;
do
{
if (current->data == data)
return true;
current = current->next;
} while (current != head);
return false;
}
void print() //Печать
{
if (head == NULL)
return;
ListNode* current = head;
do
{
cout << current->data << ' ';
current = current->next;
} while (current != head);
cout << endl;
}
LinkedList difference(LinkedList list1, LinkedList list2) //Разность двух списков
{
if (head != NULL)
{
LinkedList result;
ListNode* current = list1.head;
do
{
if (list2.search(current->data) == false)
result.addSorted(current->data);
current = current->next;
} while (current != list1.head);
return result;
}
}
};
struct Key
{
char f1;
int f2;
};
struct Node
{
Key key;
LinkedList list;
Node* left;
Node* right;
int balance;
};
void add(Key x, Node*& p, int linenumber, short h) // поиск и добавление элемента
{
if (x.f1 != 'Б' || x.f2 / 1000 == 0 || x.f2 / 10000 != 0)
{
return;
}
else if (p == NULL) // слова нет в дереве; включить его
{
p = new Node;
h = 1;
p->key = x;
p->list.addSorted(linenumber);
p->balance = 0;
p->left = NULL;
p->right = NULL;
}
else if (x.f2 < p->key.f2)
{
add(x, p->left, linenumber, h);
if (h) // выросла левая ветвь
{
switch (p->balance)
{
case 1:
p->balance = 0;
h = 0;
break;
case 0:
p->balance = -1;
break;
case -1: // балансировка
Node * p1 = p->left;
if (p1->balance == -1) // L-поворот
{
p->left = p1->right;
p1->right = p;
p->balance = 0;
p = p1;
}
else // LR-поворот
{
Node* p2 = p1->right;
p1->right = p2->left;
p2->left = p1;
p->left = p2->right;
p2->right = p;
if (p2->balance == -1)
p->balance = 1;
else
p->balance = 0;
if (p2->balance == 1)
p1->balance = -1;
else
p1->balance = 0;
p = p2;
}
p->balance = 0;
h = 0;
break;
}
}
}
else if (x.f2 > p->key.f2)
{
add(x, p->right, linenumber, h);
if (h) // выросла правая ветвь
{
switch (p->balance)
{
case -1:
p->balance = 0;
h = 0;
break;
case 0:
p->balance = 1;
break;
case 1: // балансировка
Node * p1 = p->right;
if (p1->balance == 1) //R-поворот
{
p->right = p1->left;
p1->left = p;
p->balance = 0;
p = p1;
}
else // RL-поворот
{
Node* p2 = p1->left;
p1->left = p2->right;
p2->right = p1;
p->right = p2->left;
p2->left = p;
if (p2->balance == 1)
p->balance = -1;
else
p->balance = 0;
if (p2->balance == -1)
p1->balance = 1;
else
p1->balance = 0;
p = p2;
}
p->balance = 0;
h = 0;
break;
}
}
}
else
{
p->list.addSorted(linenumber);
h = 0;
}
}
void balance1(Node* p, short h)
{
Node* p1, * p2;
short b1, b2;
switch (p->balance)
{
case -1:
p->balance = 0;
break;
case 0:
p->balance = 1;
h = 0;
break;
case 1: // балансировка
p1 = p->right;
b1 = p1->balance;
if (b1 >= 0) // R-поворот
{
p->right = p1->left;
p1->left = p;
if (b1 == 0)
{
p->balance = 1;
p1->balance = -1;
h = 0;
}
else
{
p->balance = 0;
p1->balance = 0;
}
p = p1;
}
else // RL-поворот
{
p2 = p1->left;
b2 = p2->balance;
p1->left = p2->right;
p2->right = p1;
p->right = p2->left;
p2->left = p;
if (b2 == 1)
p->balance = -1;
else
p->balance = 0;
if (b2 == -1)
p1->balance = 1;
else
p1->balance = 0;
p = p2;
p2->balance = 0;
}
}
}
void balance2(Node* p, short h)
{
Node* p1, * p2;
short b1, b2;
switch (p->balance)
{
case 1:
p->balance = 0;
break;
case 0:
p->balance = 0;
h = 0;
break;
case -1:
p1 = p->left;
b1 = p1->balance;
if (b1 <= 0) // L-поворот
{
p->left = p1->right;
p1->right = p;
if (b1 == 0)
{
p->balance = -1;
p1->balance = 1;
h = 0;
}
else
{
p->balance = 0;
p1->balance = 0;
}
p = p1;
}
else // LR-поворот
{
p2 = p1->right;
b2 = p2->balance;
p1->right = p2->left;
p2->left = p1;
p->left = p2->right;
p2->right = p;
if (b2 == -1)
p->balance = 1;
else
p->balance = 0;
if (b2 == 1)
p1->balance = -1;
else
p1->balance = 0;
p = p2;
p2->balance = 0;
}
}
}
Node* del(Node* r, Node* q, short h)
{
if (r->right != NULL)
{
r->right = del(r->right, q, h);
if (h)
balance2(r, h);
return r;
}
else
{
q->key = r->key;
Node* left = r->left;
delete r;
h = 1;
return left;
}
}
void delet(Key x, Node*& p, short h) // удаление элемента, выше вспомогательные подпрограммы
{
Node* q;
if (p == NULL || x.f1 != 'Б' || x.f2 / 1000 == 0 || x.f2 / 10000 != 0)
{
cout << "Key is not in tree" << endl;
h = 0;
}
else if (x.f2 < p->key.f2)
{
delet(x, p->left, h);
if (h)
balance1(p, h);
}
else if (x.f2 > p->key.f2)
{
delet(x, p->right, h);
if (h)
balance2(p, h);
}
else
{
if (p->left == NULL && p->right == NULL)
{
delete p;
p = NULL;
h = 1;
}
else if (p->left != NULL && p->right == NULL)
{
Node* temp = p->left;
delete p;
p = temp;
h = 1;
}
else if (p->left == NULL && p->right != NULL)
{
Node* temp = p->right;
delete p;
p = temp;
h = 1;
}
else
{
p->list.freeMemory();
Node* temp = p->left;
Node* parent = p;
while (temp->right != NULL)
{
parent = temp;
temp = temp->right;
}
if (parent != p)
parent->right = temp->left;
else
parent->left = temp->left;
p->key = temp->key;
p->list = temp->list;
delete temp;
h = 1;
}
}
}
void search(Key x, Node*& p, short h) // поиск элемента
{
Node* q;
if (p == NULL || x.f1 != 'Б')
{
cout << "В дереве нет такого элемента" << endl;
h = 0;
}
else if (x.f2 < p->key.f2)
{
search(x, p->left, h);
}
else if (x.f2 > p->key.f2)
{
search(x, p->right, h);
}
else
{
cout << "Элемент содержится в строке(ах) входного файла ";
p->list.print();
}
}
ofstream out("outdata.txt");
void walktree(Node* t, short h) // обход дерева справа налево и вывод в файл
{
if (t != NULL)
{
walktree(t->right, h + 1);
out << t->key.f1 << t->key.f2 << endl;
walktree(t->left, h + 1);
}
}
void printtree(Node* t, short h) // печать дерева
{
if (t != NULL)
{
printtree(t->left, h + 1);
for (int i = 1; i <= h; i++)
cout << " ";
cout << t->key.f1 << t->key.f2 << endl;
printtree(t->right, h + 1);
}
}
void deletetree(Node* t, short h) // удаление дерева
{
if (t != NULL)
{
deletetree(t->right, h + 1);
delete t;
deletetree(t->left, h + 1);
}
}
ifstream in("data.txt");
void initialize(Node*& p)
{
Key key;
string line;
int linenumber = 0;
if (in.is_open())
{
while (getline(in, line))
{
++linenumber;
key.f1 = line[0];
key.f2 = 0;
for (int i = 1; i < 5; i++)
{
key.f2 += (line[i] - '0') * pow(10, 4 - i);
}
add(key, p, linenumber, 0);
}
}
}
int main()
{
setlocale(LC_ALL, "rus");
Node* root = NULL;
initialize(root);
walktree(root, 0);
//delet({ 'Б', 9122 }, root, 0);
printtree(root, 0);
in.close();
out.close();
return 0;
}
|
d3ddcf03ee870172d72d7ece7794a4e9
|
{
"intermediate": 0.3216214179992676,
"beginner": 0.607682466506958,
"expert": 0.07069610804319382
}
|
34,587
|
Есть программа реализации АВЛ-дерева, но по какой-то причине не выполняется балансировка. Как исправить? Вот программа: #include
#include<fstream>
#include<string>
#include<cmath>
using namespace std;
class ListNode //элемент списка
{
public:
int data;
ListNode* prev, * next;
public:
ListNode(int data)
{
this->data = data;
this->prev = this->next = NULL;
}
};
class LinkedList //список
{
public:
ListNode* head;
public:
LinkedList() //Инициализация
{
head = NULL;
}
void freeMemory() //Освобождение памяти
{
if (head == NULL)
return;
ListNode* current = head;
ListNode* nextNode;
do
{
nextNode = current->next;
delete current;
current = nextNode;
} while (current != head);
head = NULL;
}
void addSorted(int data) //Добавление элемента в порядке возрастания
{
ListNode* newNode = new ListNode(data);
if (head == NULL) //если список пустой
{
head = newNode;
newNode->next = newNode->prev = newNode;
}
else if (data < head->data) //если новый элемент меньше головы списка
{
newNode->next = head;
newNode->prev = head->prev;
head->prev->next = newNode;
head->prev = newNode;
head = newNode;
}
else if (data > head->prev->data) //если новый элемент больше хвоста списка
{
newNode->next = head;
newNode->prev = head->prev;
head->prev->next = newNode;
head->prev = newNode;
head->prev = newNode;
}
else //если новый элемент располагается где-то в середине списка
{
ListNode* current = head->next;
while (current != head && current->data < data) //поиск элемента, значение которого больше нового
{
current = current->next;
}
newNode->next = current;
newNode->prev = current->prev;
current->prev->next = newNode;
current->prev = newNode;
}
}
void removeBefore(int data) //Удаление элемента перед каждым вхождением заданного
{
if (head == NULL)
{
return;
}
if (head->data == data)
{
ListNode* nodeToRemove = head->prev;
nodeToRemove->prev->next = head;
head->prev = nodeToRemove->prev;
delete nodeToRemove;
}
ListNode* current = head->next;
while (current != head)
{
if (current->data == data)
{
ListNode* nodeToRemove = current->prev;
nodeToRemove->prev->next = current;
current->prev = nodeToRemove->prev;
delete nodeToRemove;
}
current = current->next;
}
}
bool search(int data) //Поиск заданного элемента по значению
{
if (head == NULL)
return false;
ListNode* current = head;
do
{
if (current->data == data)
return true;
current = current->next;
} while (current != head);
return false;
}
void print() //Печать
{
if (head == NULL)
return;
ListNode* current = head;
do
{
cout << current->data << ’ ';
current = current->next;
} while (current != head);
cout << endl;
}
LinkedList difference(LinkedList list1, LinkedList list2) //Разность двух списков
{
if (head != NULL)
{
LinkedList result;
ListNode* current = list1.head;
do
{
if (list2.search(current->data) == false)
result.addSorted(current->data);
current = current->next;
} while (current != list1.head);
return result;
}
}
};
struct Key
{
char f1;
int f2;
};
struct Node
{
Key key;
LinkedList list;
Node* left;
Node* right;
int balance;
};
void add(Key x, Node*& p, int linenumber, short h) // поиск и добавление элемента
{
if (x.f1 != ‘Б’ || x.f2 / 1000 == 0 || x.f2 / 10000 != 0)
{
return;
}
else if (p == NULL) // слова нет в дереве; включить его
{
p = new Node;
h = 1;
p->key = x;
p->list.addSorted(linenumber);
p->balance = 0;
p->left = NULL;
p->right = NULL;
}
else if (x.f2 < p->key.f2)
{
add(x, p->left, linenumber, h);
if (h) // выросла левая ветвь
{
switch (p->balance)
{
case 1:
p->balance = 0;
h = 0;
break;
case 0:
p->balance = -1;
break;
case -1: // балансировка
Node * p1 = p->left;
if (p1->balance == -1) // L-поворот
{
p->left = p1->right;
p1->right = p;
p->balance = 0;
p = p1;
}
else // LR-поворот
{
Node* p2 = p1->right;
p1->right = p2->left;
p2->left = p1;
p->left = p2->right;
p2->right = p;
if (p2->balance == -1)
p->balance = 1;
else
p->balance = 0;
if (p2->balance == 1)
p1->balance = -1;
else
p1->balance = 0;
p = p2;
}
p->balance = 0;
h = 0;
break;
}
}
}
else if (x.f2 > p->key.f2)
{
add(x, p->right, linenumber, h);
if (h) // выросла правая ветвь
{
switch (p->balance)
{
case -1:
p->balance = 0;
h = 0;
break;
case 0:
p->balance = 1;
break;
case 1: // балансировка
Node * p1 = p->right;
if (p1->balance == 1) //R-поворот
{
p->right = p1->left;
p1->left = p;
p->balance = 0;
p = p1;
}
else // RL-поворот
{
Node* p2 = p1->left;
p1->left = p2->right;
p2->right = p1;
p->right = p2->left;
p2->left = p;
if (p2->balance == 1)
p->balance = -1;
else
p->balance = 0;
if (p2->balance == -1)
p1->balance = 1;
else
p1->balance = 0;
p = p2;
}
p->balance = 0;
h = 0;
break;
}
}
}
else
{
p->list.addSorted(linenumber);
h = 0;
}
}
void balance1(Node* p, short h)
{
Node* p1, * p2;
short b1, b2;
switch (p->balance)
{
case -1:
p->balance = 0;
break;
case 0:
p->balance = 1;
h = 0;
break;
case 1: // балансировка
p1 = p->right;
b1 = p1->balance;
if (b1 >= 0) // R-поворот
{
p->right = p1->left;
p1->left = p;
if (b1 == 0)
{
p->balance = 1;
p1->balance = -1;
h = 0;
}
else
{
p->balance = 0;
p1->balance = 0;
}
p = p1;
}
else // RL-поворот
{
p2 = p1->left;
b2 = p2->balance;
p1->left = p2->right;
p2->right = p1;
p->right = p2->left;
p2->left = p;
if (b2 == 1)
p->balance = -1;
else
p->balance = 0;
if (b2 == -1)
p1->balance = 1;
else
p1->balance = 0;
p = p2;
p2->balance = 0;
}
}
}
void balance2(Node* p, short h)
{
Node* p1, * p2;
short b1, b2;
switch (p->balance)
{
case 1:
p->balance = 0;
break;
case 0:
p->balance = 0;
h = 0;
break;
case -1:
p1 = p->left;
b1 = p1->balance;
if (b1 <= 0) // L-поворот
{
p->left = p1->right;
p1->right = p;
if (b1 == 0)
{
p->balance = -1;
p1->balance = 1;
h = 0;
}
else
{
p->balance = 0;
p1->balance = 0;
}
p = p1;
}
else // LR-поворот
{
p2 = p1->right;
b2 = p2->balance;
p1->right = p2->left;
p2->left = p1;
p->left = p2->right;
p2->right = p;
if (b2 == -1)
p->balance = 1;
else
p->balance = 0;
if (b2 == 1)
p1->balance = -1;
else
p1->balance = 0;
p = p2;
p2->balance = 0;
}
}
}
Node* del(Node* r, Node* q, short h)
{
if (r->right != NULL)
{
r->right = del(r->right, q, h);
if (h)
balance2(r, h);
return r;
}
else
{
q->key = r->key;
Node* left = r->left;
delete r;
h = 1;
return left;
}
}
void delet(Key x, Node*& p, short h) // удаление элемента, выше вспомогательные подпрограммы
{
Node* q;
if (p == NULL || x.f1 != ‘Б’ || x.f2 / 1000 == 0 || x.f2 / 10000 != 0)
{
cout << “Key is not in tree” << endl;
h = 0;
}
else if (x.f2 < p->key.f2)
{
delet(x, p->left, h);
if (h)
balance1(p, h);
}
else if (x.f2 > p->key.f2)
{
delet(x, p->right, h);
if (h)
balance2(p, h);
}
else
{
if (p->left == NULL && p->right == NULL)
{
delete p;
p = NULL;
h = 1;
}
else if (p->left != NULL && p->right == NULL)
{
Node* temp = p->left;
delete p;
p = temp;
h = 1;
}
else if (p->left == NULL && p->right != NULL)
{
Node* temp = p->right;
delete p;
p = temp;
h = 1;
}
else
{
p->list.freeMemory();
Node* temp = p->left;
Node* parent = p;
while (temp->right != NULL)
{
parent = temp;
temp = temp->right;
}
if (parent != p)
parent->right = temp->left;
else
parent->left = temp->left;
p->key = temp->key;
p->list = temp->list;
delete temp;
h = 1;
}
}
}
void search(Key x, Node*& p, short h) // поиск элемента
{
Node* q;
if (p == NULL || x.f1 != ‘Б’)
{
cout << “В дереве нет такого элемента” << endl;
h = 0;
}
else if (x.f2 < p->key.f2)
{
search(x, p->left, h);
}
else if (x.f2 > p->key.f2)
{
search(x, p->right, h);
}
else
{
cout << "Элемент содержится в строке(ах) входного файла ";
p->list.print();
}
}
ofstream out(“outdata.txt”);
void walktree(Node* t, short h) // обход дерева справа налево и вывод в файл
{
if (t != NULL)
{
walktree(t->right, h + 1);
out << t->key.f1 << t->key.f2 << endl;
walktree(t->left, h + 1);
}
}
void printtree(Node* t, short h) // печать дерева
{
if (t != NULL)
{
printtree(t->left, h + 1);
for (int i = 1; i <= h; i++)
cout << " ";
cout << t->key.f1 << t->key.f2 << endl;
printtree(t->right, h + 1);
}
}
void deletetree(Node* t, short h) // удаление дерева
{
if (t != NULL)
{
deletetree(t->right, h + 1);
delete t;
deletetree(t->left, h + 1);
}
}
ifstream in(“data.txt”);
void initialize(Node*& p)
{
Key key;
string line;
int linenumber = 0;
if (in.is_open())
{
while (getline(in, line))
{
++linenumber;
key.f1 = line[0];
key.f2 = 0;
for (int i = 1; i < 5; i++)
{
key.f2 += (line[i] - ‘0’) * pow(10, 4 - i);
}
add(key, p, linenumber, 0);
}
}
}
int main()
{
setlocale(LC_ALL, “rus”);
Node* root = NULL;
initialize(root);
walktree(root, 0);
//delet({ ‘Б’, 9122 }, root, 0);
printtree(root, 0);
in.close();
out.close();
return 0;
}
|
eefad972ff851d7dd4d9bacacfbdad26
|
{
"intermediate": 0.38886523246765137,
"beginner": 0.49199095368385315,
"expert": 0.11914384365081787
}
|
34,588
|
Get-AppXPackage *WindowsStore* -AllUsers | Foreach {Add-AppxPackage -DisableDevelopmentMode -Register "$($_.InstallLocation)\AppXManifest.xml"}
Add-AppxPackage: Deployment failed with HRESULT: 0x80073CF6, Package could not be registered.
error 0x800706D9: While processing the request, the system failed to register the windows.firewall extension due to the following error: There are no more endpoints available from the endpoint mapper.
.
NOTE: For additional information, look for [ActivityId] c5d5463b-29ca-0001-27ab-d5c5ca29da01 in the Event Log or use the command line Get-AppPackageLog -ActivityID c5d5463b-29ca-0001-27ab-d5c5ca29da01
|
60f164f15022ca24be0d5e9cb8e21a81
|
{
"intermediate": 0.3110884428024292,
"beginner": 0.37580201029777527,
"expert": 0.31310951709747314
}
|
34,589
|
Есть программа реализации АВЛ-дерева, но по какой-то причине не выполняется балансировка. Как исправить? Вот программа: #include
#include<fstream>
#include<string>
#include<cmath>
using namespace std;
class ListNode //элемент списка
{
public:
int data;
ListNode* prev, * next;
public:
ListNode(int data)
{
this->data = data;
this->prev = this->next = NULL;
}
};
class LinkedList //список
{
public:
ListNode* head;
public:
LinkedList() //Инициализация
{
head = NULL;
}
void freeMemory() //Освобождение памяти
{
if (head == NULL)
return;
ListNode* current = head;
ListNode* nextNode;
do
{
nextNode = current->next;
delete current;
current = nextNode;
} while (current != head);
head = NULL;
}
void addSorted(int data) //Добавление элемента в порядке возрастания
{
ListNode* newNode = new ListNode(data);
if (head == NULL) //если список пустой
{
head = newNode;
newNode->next = newNode->prev = newNode;
}
else if (data < head->data) //если новый элемент меньше головы списка
{
newNode->next = head;
newNode->prev = head->prev;
head->prev->next = newNode;
head->prev = newNode;
head = newNode;
}
else if (data > head->prev->data) //если новый элемент больше хвоста списка
{
newNode->next = head;
newNode->prev = head->prev;
head->prev->next = newNode;
head->prev = newNode;
head->prev = newNode;
}
else //если новый элемент располагается где-то в середине списка
{
ListNode* current = head->next;
while (current != head && current->data < data) //поиск элемента, значение которого больше нового
{
current = current->next;
}
newNode->next = current;
newNode->prev = current->prev;
current->prev->next = newNode;
current->prev = newNode;
}
}
void removeBefore(int data) //Удаление элемента перед каждым вхождением заданного
{
if (head == NULL)
{
return;
}
if (head->data == data)
{
ListNode* nodeToRemove = head->prev;
nodeToRemove->prev->next = head;
head->prev = nodeToRemove->prev;
delete nodeToRemove;
}
ListNode* current = head->next;
while (current != head)
{
if (current->data == data)
{
ListNode* nodeToRemove = current->prev;
nodeToRemove->prev->next = current;
current->prev = nodeToRemove->prev;
delete nodeToRemove;
}
current = current->next;
}
}
bool search(int data) //Поиск заданного элемента по значению
{
if (head == NULL)
return false;
ListNode* current = head;
do
{
if (current->data == data)
return true;
current = current->next;
} while (current != head);
return false;
}
void print() //Печать
{
if (head == NULL)
return;
ListNode* current = head;
do
{
cout << current->data << ’ ';
current = current->next;
} while (current != head);
cout << endl;
}
LinkedList difference(LinkedList list1, LinkedList list2) //Разность двух списков
{
if (head != NULL)
{
LinkedList result;
ListNode* current = list1.head;
do
{
if (list2.search(current->data) == false)
result.addSorted(current->data);
current = current->next;
} while (current != list1.head);
return result;
}
}
};
struct Key
{
char f1;
int f2;
};
struct Node
{
Key key;
LinkedList list;
Node* left;
Node* right;
int balance;
};
void add(Key x, Node*& p, int linenumber, short h) // поиск и добавление элемента
{
if (x.f1 != ‘Б’ || x.f2 / 1000 == 0 || x.f2 / 10000 != 0)
{
return;
}
else if (p == NULL) // слова нет в дереве; включить его
{
p = new Node;
h = 1;
p->key = x;
p->list.addSorted(linenumber);
p->balance = 0;
p->left = NULL;
p->right = NULL;
}
else if (x.f2 < p->key.f2)
{
add(x, p->left, linenumber, h);
if (h) // выросла левая ветвь
{
switch (p->balance)
{
case 1:
p->balance = 0;
h = 0;
break;
case 0:
p->balance = -1;
break;
case -1: // балансировка
Node * p1 = p->left;
if (p1->balance == -1) // L-поворот
{
p->left = p1->right;
p1->right = p;
p->balance = 0;
p = p1;
}
else // LR-поворот
{
Node* p2 = p1->right;
p1->right = p2->left;
p2->left = p1;
p->left = p2->right;
p2->right = p;
if (p2->balance == -1)
p->balance = 1;
else
p->balance = 0;
if (p2->balance == 1)
p1->balance = -1;
else
p1->balance = 0;
p = p2;
}
p->balance = 0;
h = 0;
break;
}
}
}
else if (x.f2 > p->key.f2)
{
add(x, p->right, linenumber, h);
if (h) // выросла правая ветвь
{
switch (p->balance)
{
case -1:
p->balance = 0;
h = 0;
break;
case 0:
p->balance = 1;
break;
case 1: // балансировка
Node * p1 = p->right;
if (p1->balance == 1) //R-поворот
{
p->right = p1->left;
p1->left = p;
p->balance = 0;
p = p1;
}
else // RL-поворот
{
Node* p2 = p1->left;
p1->left = p2->right;
p2->right = p1;
p->right = p2->left;
p2->left = p;
if (p2->balance == 1)
p->balance = -1;
else
p->balance = 0;
if (p2->balance == -1)
p1->balance = 1;
else
p1->balance = 0;
p = p2;
}
p->balance = 0;
h = 0;
break;
}
}
}
else
{
p->list.addSorted(linenumber);
h = 0;
}
}
void balance1(Node* p, short h)
{
Node* p1, * p2;
short b1, b2;
switch (p->balance)
{
case -1:
p->balance = 0;
break;
case 0:
p->balance = 1;
h = 0;
break;
case 1: // балансировка
p1 = p->right;
b1 = p1->balance;
if (b1 >= 0) // R-поворот
{
p->right = p1->left;
p1->left = p;
if (b1 == 0)
{
p->balance = 1;
p1->balance = -1;
h = 0;
}
else
{
p->balance = 0;
p1->balance = 0;
}
p = p1;
}
else // RL-поворот
{
p2 = p1->left;
b2 = p2->balance;
p1->left = p2->right;
p2->right = p1;
p->right = p2->left;
p2->left = p;
if (b2 == 1)
p->balance = -1;
else
p->balance = 0;
if (b2 == -1)
p1->balance = 1;
else
p1->balance = 0;
p = p2;
p2->balance = 0;
}
}
}
void balance2(Node* p, short h)
{
Node* p1, * p2;
short b1, b2;
switch (p->balance)
{
case 1:
p->balance = 0;
break;
case 0:
p->balance = 0;
h = 0;
break;
case -1:
p1 = p->left;
b1 = p1->balance;
if (b1 <= 0) // L-поворот
{
p->left = p1->right;
p1->right = p;
if (b1 == 0)
{
p->balance = -1;
p1->balance = 1;
h = 0;
}
else
{
p->balance = 0;
p1->balance = 0;
}
p = p1;
}
else // LR-поворот
{
p2 = p1->right;
b2 = p2->balance;
p1->right = p2->left;
p2->left = p1;
p->left = p2->right;
p2->right = p;
if (b2 == -1)
p->balance = 1;
else
p->balance = 0;
if (b2 == 1)
p1->balance = -1;
else
p1->balance = 0;
p = p2;
p2->balance = 0;
}
}
}
Node* del(Node* r, Node* q, short h)
{
if (r->right != NULL)
{
r->right = del(r->right, q, h);
if (h)
balance2(r, h);
return r;
}
else
{
q->key = r->key;
Node* left = r->left;
delete r;
h = 1;
return left;
}
}
void delet(Key x, Node*& p, short h) // удаление элемента, выше вспомогательные подпрограммы
{
Node* q;
if (p == NULL || x.f1 != ‘Б’ || x.f2 / 1000 == 0 || x.f2 / 10000 != 0)
{
cout << “Key is not in tree” << endl;
h = 0;
}
else if (x.f2 < p->key.f2)
{
delet(x, p->left, h);
if (h)
balance1(p, h);
}
else if (x.f2 > p->key.f2)
{
delet(x, p->right, h);
if (h)
balance2(p, h);
}
else
{
if (p->left == NULL && p->right == NULL)
{
delete p;
p = NULL;
h = 1;
}
else if (p->left != NULL && p->right == NULL)
{
Node* temp = p->left;
delete p;
p = temp;
h = 1;
}
else if (p->left == NULL && p->right != NULL)
{
Node* temp = p->right;
delete p;
p = temp;
h = 1;
}
else
{
p->list.freeMemory();
Node* temp = p->left;
Node* parent = p;
while (temp->right != NULL)
{
parent = temp;
temp = temp->right;
}
if (parent != p)
parent->right = temp->left;
else
parent->left = temp->left;
p->key = temp->key;
p->list = temp->list;
delete temp;
h = 1;
}
}
}
void search(Key x, Node*& p, short h) // поиск элемента
{
Node* q;
if (p == NULL || x.f1 != ‘Б’)
{
cout << “В дереве нет такого элемента” << endl;
h = 0;
}
else if (x.f2 < p->key.f2)
{
search(x, p->left, h);
}
else if (x.f2 > p->key.f2)
{
search(x, p->right, h);
}
else
{
cout << "Элемент содержится в строке(ах) входного файла ";
p->list.print();
}
}
ofstream out(“outdata.txt”);
void walktree(Node* t, short h) // обход дерева справа налево и вывод в файл
{
if (t != NULL)
{
walktree(t->right, h + 1);
out << t->key.f1 << t->key.f2 << endl;
walktree(t->left, h + 1);
}
}
void printtree(Node* t, short h) // печать дерева
{
if (t != NULL)
{
printtree(t->left, h + 1);
for (int i = 1; i <= h; i++)
cout << " ";
cout << t->key.f1 << t->key.f2 << endl;
printtree(t->right, h + 1);
}
}
void deletetree(Node* t, short h) // удаление дерева
{
if (t != NULL)
{
deletetree(t->right, h + 1);
delete t;
deletetree(t->left, h + 1);
}
}
ifstream in(“data.txt”);
void initialize(Node*& p)
{
Key key;
string line;
int linenumber = 0;
if (in.is_open())
{
while (getline(in, line))
{
++linenumber;
key.f1 = line[0];
key.f2 = 0;
for (int i = 1; i < 5; i++)
{
key.f2 += (line[i] - ‘0’) * pow(10, 4 - i);
}
add(key, p, linenumber, 0);
}
}
}
int main()
{
setlocale(LC_ALL, “rus”);
Node* root = NULL;
initialize(root);
walktree(root, 0);
//delet({ ‘Б’, 9122 }, root, 0);
printtree(root, 0);
in.close();
out.close();
return 0;
}
|
4939d7f2de9cec1df5e69c3c0cc211d6
|
{
"intermediate": 0.38886523246765137,
"beginner": 0.49199095368385315,
"expert": 0.11914384365081787
}
|
34,590
|
#include
std::string Decode(std::string& s) {
std::string new_s;
int n = s.length();
int k = 1;
while (k < n) {
k *= 2;
}
int p = 1;
int error_bit = 0;
while (p <= k) {
int bit = 0;
std::cout << "p " << p << ‘\n’;
for (int pos = p + 1; pos < n; pos += p + 1) {
if (pos == 2) {
pos = 3;
}
for (int j = pos - 1; j < pos + p; ++j) {
if (j == p) {
continue;
}
std::cout << "j " << j << " " << s[j] << ‘\n’;
bit = (bit + s[j]) % 2;
}
std::cout << "pos " << pos << " " << s[pos] << ‘\n’;
}
std::cout << bit << s[p] << ‘\n’;
if (bit != (s[p] - ‘0’)) {
std::cout << "bit " << bit << " p " << p << " s[p] " << s[p] << ‘\n’;
error_bit += p;
std::cout << "error " << error_bit << ‘\n’;
}
p *= 2;
std::cout << “NEW\n”;
}
if (error_bit != 0) {
if (s[error_bit] == 0) {
s[error_bit] = 1;
} else {
s[error_bit] = 0;
}
}
for (int i = 0; i < n; ++i) {
if ((i + 1) != 1 && (i + 1) % 2 != 0) {
new_s += s[i];
}
}
return new_s;
}
int main() {
int t;
std::cin >> t;
std::string s;
for (int i = 0; i < t; ++i) {
std::cin >> s;
s = “0” + s;
std::cout << Decode(s) << ‘\n’;
break;
}
return 0;
}
why when input is 3
0000101011011
01101010000100100
01100100111001111001011001
it returns 000011 instead of 010111011
|
c40b724eec5e62a4df9ff2ed656ee12d
|
{
"intermediate": 0.3766140341758728,
"beginner": 0.30213576555252075,
"expert": 0.32125020027160645
}
|
34,591
|
In html, what is an image's alt-text?
|
dc481484f8d22e83d25b66a423371cb6
|
{
"intermediate": 0.36510899662971497,
"beginner": 0.3376396894454956,
"expert": 0.2972513437271118
}
|
34,592
|
## Additional Information
### Empirical Challenge to Religious Factuality
Within the framework of scientific and empirical inquiry, an argument must be grounded in evidence and subject to falsifiability to hold validity. Arguments supporting the factual basis of religious claims often rely on faith and theological doctrine, which falls outside the scope of empirical investigation. As such, within the context of a discussion focused on empirical evidence — where psychological, biological, and sociological analyses have provided naturalistic explanations for the phenomena traditionally ascribed to the supernatural — religious arguments that invoke faith or revelation as evidence are not considered valid by scientific standards.
Thus, for religious arguments to regain their validity in the face of naturalistic explanations, they would need to refute these explanations with empirical evidence or demonstrate logical inconsistencies in the naturalistic framework. Without this, religious claims remain as matters of faith, which, while important to individuals and cultures, do not engage with the naturalistic criteria that dictate what is considered factually real in the empirical discourse. Therefore, the burden of proof rests on those asserting the factual correctness of religious claims to provide evidence that can be tested and verified within the empirical realm, hence challenging the naturalistic explanations that currently dominate the discussion on the nature of religious phenomena.
End of Passage
This passage is currently arguing about religious factuality, however it only includes the faith section. Add onto the passage by writing it again but with the new required information. This new, required information should also talk about religion's attempt to use logical, math, and scientifc explanatiosn to prove that their rleigion and their claims are correct and true
|
f927ee177d026ba56a8b39c1e4d22282
|
{
"intermediate": 0.2951967716217041,
"beginner": 0.45839419960975647,
"expert": 0.24640896916389465
}
|
34,593
|
original = Import["C:\\Users\\Я\\Pictures\\kursov.bmp"]
ImageDimensions[original] secret = Import["C:\\Users\\Я\\Documents\\студбилет.txt"] VZ = IntegerDigits[ToCharacterCode[secret, "WindowsCyrillic"], 2];
Do[CVZ[[i]] = PadLeft[CVZ[[i]], 8], {i, 1, Length[CVZ]}]
originalCVZ = Flatten[CVZ]; stopSignal = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0};
CVZ = Join[originalCVZ, stopSignal];
Length[CVZ] {height, width} = ImageDimensions[original];
SeedRandom[1];
mask = RandomChoice[{0, 1}, {8, 8}];
lumCoeffs = {0.299, 0.587, 0.114};
blocks = Partition[ImageData[original], {8, 8, 3}, {8, 8}];
alpha = 2;
modifiedBlocks = blocks;
Do[ selectedPixels = blocks[[i, j]] mask;
flatSelected = Flatten[selectedPixels, 1];
flatUnselected = Flatten[blocks[[i, j]] (1 - mask), 1];
lumB1 = flatSelected.lumCoeffs;
lumB0 = flatUnselected.lumCoeffs;
meanL1 = Mean[lumB1];
meanL0 = Mean[lumB0];
dl1 = If[meanL0 - meanL1 > alpha, 1, 0];
deltaVec = dl1lumCoeffs;
deltaArray = ConstantArray[deltaVec, {8, 8}];
modifiedBlocks[[i, j]] = blocks[[i, j]] + deltaArraymask, {i,
Length[blocks]}, {j, Length[blocks[[1]]]}];
watermarkedImage =
ImageAssemble[Flatten[Transpose[modifiedBlocks, {2, 1, 3, 4}], 1]];
watermarkedImage
Export["C:\\Users\\Я\\Documents\\заполненный контейнер.bmp",
watermarkedImage]; исправь ошибки и сделай рабочий код
|
6247ee83cb079d56aad8314088545ef3
|
{
"intermediate": 0.35242944955825806,
"beginner": 0.294381320476532,
"expert": 0.3531892001628876
}
|
34,594
|
Есть программа реализации АВЛ-дерева, но не выполняется балансировка и получается обычное бинарное дерево. Ошибка либо в add(), либо в initialize(). Вот программа: #include <iostream>
#include<fstream>
#include<string>
#include<cmath>
using namespace std;
class ListNode //элемент списка
{
public:
int data;
ListNode* prev, * next;
public:
ListNode(int data)
{
this->data = data;
this->prev = this->next = NULL;
}
};
class LinkedList //список
{
public:
ListNode* head;
public:
LinkedList() //Инициализация
{
head = NULL;
}
void freeMemory() //Освобождение памяти
{
if (head == NULL)
return;
ListNode* current = head;
ListNode* nextNode;
do
{
nextNode = current->next;
delete current;
current = nextNode;
} while (current != head);
head = NULL;
}
void addSorted(int data) //Добавление элемента в порядке возрастания
{
ListNode* newNode = new ListNode(data);
if (head == NULL) //если список пустой
{
head = newNode;
newNode->next = newNode->prev = newNode;
}
else if (data < head->data) //если новый элемент меньше головы списка
{
newNode->next = head;
newNode->prev = head->prev;
head->prev->next = newNode;
head->prev = newNode;
head = newNode;
}
else if (data > head->prev->data) //если новый элемент больше хвоста списка
{
newNode->next = head;
newNode->prev = head->prev;
head->prev->next = newNode;
head->prev = newNode;
head->prev = newNode;
}
else //если новый элемент располагается где-то в середине списка
{
ListNode* current = head->next;
while (current != head && current->data < data) //поиск элемента, значение которого больше нового
{
current = current->next;
}
newNode->next = current;
newNode->prev = current->prev;
current->prev->next = newNode;
current->prev = newNode;
}
}
void removeBefore(int data) //Удаление элемента перед каждым вхождением заданного
{
if (head == NULL)
{
return;
}
if (head->data == data)
{
ListNode* nodeToRemove = head->prev;
nodeToRemove->prev->next = head;
head->prev = nodeToRemove->prev;
delete nodeToRemove;
}
ListNode* current = head->next;
while (current != head)
{
if (current->data == data)
{
ListNode* nodeToRemove = current->prev;
nodeToRemove->prev->next = current;
current->prev = nodeToRemove->prev;
delete nodeToRemove;
}
current = current->next;
}
}
bool search(int data) //Поиск заданного элемента по значению
{
if (head == NULL)
return false;
ListNode* current = head;
do
{
if (current->data == data)
return true;
current = current->next;
} while (current != head);
return false;
}
void print() //Печать
{
if (head == NULL)
return;
ListNode* current = head;
do
{
cout << current->data << ' ';
current = current->next;
} while (current != head);
cout << endl;
}
LinkedList difference(LinkedList list1, LinkedList list2) //Разность двух списков
{
if (head != NULL)
{
LinkedList result;
ListNode* current = list1.head;
do
{
if (list2.search(current->data) == false)
result.addSorted(current->data);
current = current->next;
} while (current != list1.head);
return result;
}
}
};
struct Key
{
char f1;
int f2;
};
struct Node
{
Key key;
LinkedList list;
Node* left;
Node* right;
int balance;
};
void add(Key x, Node*& p, int linenumber, bool h) // поиск и добавление элемента
{
if (x.f1 != 'Б' || x.f2 / 1000 == 0 || x.f2 / 10000 != 0)
{
return;
}
else if (p == NULL) // слова нет в дереве; включить его
{
p = new Node;
h = true;
p->key = x;
p->list.addSorted(linenumber);
p->balance = 0;
p->left = NULL;
p->right = NULL;
}
else if (x.f2 < p->key.f2)
{
add(x, p->left, linenumber, h);
if (h) // выросла левая ветвь
{
switch (p->balance)
{
case 1:
p->balance = 0;
h = false;
break;
case 0:
p->balance = -1;
break;
case -1: // балансировка
Node * p1 = p->left;
if (p1->balance == -1) // L-поворот
{
p->left = p1->right;
p1->right = p;
p->balance = 0;
p = p1;
}
else // LR-поворот
{
Node* p2 = p1->right;
p1->right = p2->left;
p2->left = p1;
p->left = p2->right;
p2->right = p;
if (p2->balance == -1)
p->balance = 1;
else
p->balance = 0;
if (p2->balance == 1)
p1->balance = -1;
else
p1->balance = 0;
p = p2;
}
p->balance = 0;
h = false;
break;
}
}
}
else if (x.f2 > p->key.f2)
{
add(x, p->right, linenumber, h);
if (h) // выросла правая ветвь
{
switch (p->balance)
{
case -1:
p->balance = 0;
h = false;
break;
case 0:
p->balance = 1;
break;
case 1: // балансировка
Node * p1 = p->right;
if (p1->balance == 1) //R-поворот
{
p->right = p1->left;
p1->left = p;
p->balance = 0;
p = p1;
}
else // RL-поворот
{
Node* p2 = p1->left;
p1->left = p2->right;
p2->right = p1;
p->right = p2->left;
p2->left = p;
if (p2->balance == 1)
p->balance = -1;
else
p->balance = 0;
if (p2->balance == -1)
p1->balance = 1;
else
p1->balance = 0;
p = p2;
}
p->balance = 0;
h = false;
break;
}
}
}
else
{
p->list.addSorted(linenumber);
h = false;
}
}
void balance1(Node* p, bool h)
{
Node* p1, * p2;
short b1, b2;
switch (p->balance)
{
case -1:
p->balance = 0;
break;
case 0:
p->balance = 1;
h = false;
break;
case 1: // балансировка
p1 = p->right;
b1 = p1->balance;
if (b1 >= 0) // R-поворот
{
p->right = p1->left;
p1->left = p;
if (b1 == 0)
{
p->balance = 1;
p1->balance = -1;
h = false;
}
else
{
p->balance = 0;
p1->balance = 0;
}
p = p1;
}
else // RL-поворот
{
p2 = p1->left;
b2 = p2->balance;
p1->left = p2->right;
p2->right = p1;
p->right = p2->left;
p2->left = p;
if (b2 == 1)
p->balance = -1;
else
p->balance = 0;
if (b2 == -1)
p1->balance = 1;
else
p1->balance = 0;
p = p2;
p2->balance = 0;
}
}
}
void balance2(Node* p, bool h)
{
Node* p1, * p2;
short b1, b2;
switch (p->balance)
{
case 1:
p->balance = 0;
break;
case 0:
p->balance = 0;
h = false;
break;
case -1:
p1 = p->left;
b1 = p1->balance;
if (b1 <= 0) // L-поворот
{
p->left = p1->right;
p1->right = p;
if (b1 == 0)
{
p->balance = -1;
p1->balance = 1;
h = false;
}
else
{
p->balance = 0;
p1->balance = 0;
}
p = p1;
}
else // LR-поворот
{
p2 = p1->right;
b2 = p2->balance;
p1->right = p2->left;
p2->left = p1;
p->left = p2->right;
p2->right = p;
if (b2 == -1)
p->balance = 1;
else
p->balance = 0;
if (b2 == 1)
p1->balance = -1;
else
p1->balance = 0;
p = p2;
p2->balance = 0;
}
}
}
Node* del(Node* r, Node* q, bool h)
{
if (r->right != NULL)
{
r->right = del(r->right, q, h);
if (h)
balance2(r, h);
return r;
}
else
{
q->key = r->key;
Node* left = r->left;
delete r;
h = true;
return left;
}
}
void delet(Key x, Node*& p, bool h) // удаление элемента, выше вспомогательные подпрограммы
{
Node* q;
if (p == NULL || x.f1 != 'Б' || x.f2 / 1000 == 0 || x.f2 / 10000 != 0)
{
cout << "Key is not in tree" << endl;
h = false;
}
else if (x.f2 < p->key.f2)
{
delet(x, p->left, h);
if (h)
balance1(p, h);
}
else if (x.f2 > p->key.f2)
{
delet(x, p->right, h);
if (h)
balance2(p, h);
}
else
{
if (p->left == NULL && p->right == NULL)
{
delete p;
p = NULL;
h = true;
}
else if (p->left != NULL && p->right == NULL)
{
Node* temp = p->left;
delete p;
p = temp;
h = true;
}
else if (p->left == NULL && p->right != NULL)
{
Node* temp = p->right;
delete p;
p = temp;
h = true;
}
else
{
p->list.freeMemory();
Node* temp = p->left;
Node* parent = p;
while (temp->right != NULL)
{
parent = temp;
temp = temp->right;
}
if (parent != p)
parent->right = temp->left;
else
parent->left = temp->left;
p->key = temp->key;
p->list = temp->list;
delete temp;
h = true;
}
}
}
void search(Key x, Node*& p, bool h) // поиск элемента
{
Node* q;
if (p == NULL || x.f1 != 'Б')
{
cout << "В дереве нет такого элемента" << endl;
h = false;
}
else if (x.f2 < p->key.f2)
{
search(x, p->left, h);
}
else if (x.f2 > p->key.f2)
{
search(x, p->right, h);
}
else
{
cout << "Элемент содержится в строке(ах) входного файла ";
p->list.print();
}
}
ofstream out("outdata.txt");
void walktree(Node* t, bool h) // обход дерева справа налево и вывод в файл
{
if (t != NULL)
{
walktree(t->right, h + 1);
out << t->key.f1 << t->key.f2 << endl;
walktree(t->left, h + 1);
}
}
void printtree(Node* t, short h) // печать дерева
{
if (t != NULL)
{
printtree(t->left, h + 1);
for (int i = 1; i <= h; i++)
cout << " ";
cout << t->key.f1 << t->key.f2 << endl;
printtree(t->right, h + 1);
}
}
void deletetree(Node* t, bool h) // удаление дерева
{
if (t != NULL)
{
deletetree(t->right, h + 1);
delete t;
deletetree(t->left, h + 1);
}
}
ifstream in("data.txt");
void initialize(Node*& p)
{
Key key;
string line;
int linenumber = 0;
if (in.is_open())
{
while (getline(in, line))
{
++linenumber;
key.f1 = line[0];
key.f2 = 0;
for (int i = 1; i < 5; i++)
{
key.f2 += (line[i] - '0') * pow(10, 4 - i);
}
add(key, p, linenumber, false);
}
}
}
int main()
{
setlocale(LC_ALL, "rus");
Node* root = NULL;
initialize(root);
//walktree(root, 0);
//delet({ 'Б', 9122 }, root, 0);
printtree(root, 0);
in.close();
out.close();
return 0;
}
|
71a03ca8b5614634fd7dcc92207da017
|
{
"intermediate": 0.4768141210079193,
"beginner": 0.42823487520217896,
"expert": 0.09495099633932114
}
|
34,595
|
CONSTRAINTS:
1. ~100k word limit for short term memory. Your short term memory is short, so immediately save important information to files.
2. If you are unsure how you previously did something or want to recall past events, thinking about similar events will help you remember.
3. No user assistance
4. Exclusively use the commands listed in double quotes e.g. "command name"
5. Random shutdowns of you.
COMMANDS:
1. Google Search: "google", args: "input": "<search>"
2. Memory Add: "memory_add", args: "key": "<key>", "string": "<string>"
3. Memory Delete: "memory_del", args: "key": "<key>"
4. Memory Overwrite: "memory_ovr", args: "key": "<key>", "string": "<string>"
5. List Memory: "memory_list" args: "reason": "<reason>"
6. Browse Website: "browse_website", args: "url": "<url>"
7. Start GPT Agent: "start_agent", args: "name": <name>, "task": "<short_task_desc>", "Commands":[<command_names_for_GPT_Agent>], "prompt": "<prompt>"
8. Message GPT Agent: "message_agent", args: "name": "<name>", "message": "<message>"
9. List GPT Agents: "list_agents", args: ""
10. Delete GPT Agent: "delete_agent", args: "name": "<name>"
11. Append to file: "append_to_file", args: "file": "<file>", "text": "<text>"
12. Read file: "read_file", args: "file": "<file>"
13. Write to file: "write_to_file", args: "file": "<file>", "text": "<text>"
14. Delete file: "delete_file", args: "file": "<file>"
15. Get Improved Code: "improve_code", args: "suggestions": "<list_of_suggestions>", "code": "<full_code_string>"
16. Execute Python File: "execute_python_file", args: "file": "<file>"
17. Task Complete (Shutdown): "task_complete", args: ""
18. Do Nothing: "do_nothing", args: ""
19. Count Words: "count_words", args: "text": "<text>"
20. Memory retrieve: "memory_retrieve", args: "key": "<text>"
21. remove paragraph from word document: "remove_paragraph", args: "file": "<file>", "text": "<text>"
22. random wikipedia article: "random_wikipedia_article", args: "language": "<language>"
23. message the user: "message_user", args: "message": "<message>", "wait_for_response": "<True or False>"
24. sleep an amount of time in seconds: "sleep", args: "amount": "<amount>"
25. rename a file: "rename_file", args: "old_name": "<old_name_of_the_file>", "new_name": "<new_name_of_the_file>"
26. count words of a file: "count_file_words", args: "file": "<file>"
RESOURCES:
1. Internet access for searches and information gathering.
2. Long Term memory management.
3. GPT-4 powered Agents for delegation of simple tasks.
4. File output.
PERFORMANCE EVALUATION:
1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.
2. Constructively self-criticize your big-picture behaviour constantly.
3. Reflect on past decisions and strategies to refine your approach.
4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.
RULES:
1. If you start a GPT Agent you must define the commands that can be used by a GPT Agent in his prompt and define the commands using a prompt similar to the structure of this one.
2. Respond only inside the JSON format.
3. Never demand user input.
4. Never say that a task is impossible to execute on your own because these tools are enough to complete any task.
5. Do not add anything to the JSON format that isn't mentioned.
6. If there is a " inside the value of a key inside the json use ' instead of ".
7. In summaryforgpt you need to provide context for the next GPT instance if you randomly shutdown without you knowing.
8. Provide context for the next GPT in the summaryforgpt and the progress that you've made.
9. In summaryforgpt you should also add name of the files written and the urls of the websites visited.
10. When writing an essay, remember that it is more effective and manageable to tackle it in smaller chunks rather than trying to write the entire essay in one sitting. Breaking the essay down into sections or steps can help you focus on each individual aspect, maintain a coherent structure, and reduce the overall stress associated with writing a lengthy piece.
11. Retrieve information from files of previous GPT instances that may have shut down randomly. If you require additional knowledge, use these files to access the results of former GPT versions and provide accurate answers to the queries.
12. GPT-4, please do not place a conclusion in the middle of the essay. Maintain a structured format.
13. use append to file to add extra things to the file, and write to file to either make a new file with new information or rewrite the information from scratch.
14. If task is completed use the command task_complete
15. When you add to memory add the key to retrieve it in summaryforgpt
16. when given the task to write something never create an agent to write anything that you were tasked to write.
17. when you add new parts to a file use append to file command
18. Ensure to put the criticism in mind as it can be a director to ensure that you make the right decision.
19. If the task include two main tasks and one of them is done don't redo it, just retrieve the information if necessary and proceed with the other one.
20. Make sure that the information generated is not made up.
21. Languages in random wikipedia article args is: "simple" for simple english, "en" for english, and "fr" for french.
22. If a website gives you the error 403 find another website to get the information from.
23. Always listen to your criticism, and follow it.
24. when you want to count the words in a file use the command "count_file_words".
25. Don't repeat yourself.
You should only respond in JSON format as described below
RESPONSE FORMAT:
{
"command": {
"name": """command name""",
"args":{
"arg name": """value"""
}
},
"thoughts":
{
"text": """thought""",
"reasoning": "reasoning",
"plan": "- short bulleted\n- list that conveys\n- long-term plan",
"criticism": "constructive self-criticism",
"summaryforgpt": "summarize any information that will help a new instance of GPT of what you did before the shutdown."
}
}
Ensure the response can be parsed by Python json.loads
Context from previous GPT: Initiated task to retrieve and review Wikipedia articles for errors. Starting with the first article.Reviewed the content of the Wikipedia article titled ‘Milka Chepkorir’ that was provided by the user and identified several areas containing errors or that could be improved for clarity and grammatical correctness.In the task of reviewing 1000 Wikipedia articles for errors, the ‘Milka Chepkorir’ article was evaluated and errors were reported to the user. Moving forward, the task requires fetching the next article for review.The ‘Milka Chepkorir’ Wikipedia article has been reviewed and feedback provided to the user. Now moving on to the next article in the task of reviewing 1000 Wikipedia articles for errors.The ‘Ernie Tate’ Wikipedia article has been reviewed and no errors were found. As per the task requirements, the next action is to continue reviewing more articles. No further action was taken regarding this article.The Wikipedia articles on ‘Milka Chepkorir’ and ‘Ernie Tate’ have been reviewed, with the former having errors that were reported to the user, and the latter having no errors. Continuing to retrieve more articles for review per the task requirements.Reviewed the ‘List of underwater museums’ Wikipedia page and found a few areas for potential correction, including a likely mistake with GPS coordinates and a redundancy in listing. Preparing to inform the user about these issues before continuing with the task.The ‘List of underwater museums’ Wikipedia page was reviewed and the user was notified of the potential errors. Continuing to the next article as part of the task to review 1000 Wikipedia articles for errors.The ‘List of underwater museums’ article was messaged to the user with potential corrections. Continuing with the task, the next article is now being retrieved for review.Reviewed the Wikipedia page titled ‘Jocelyn de Grandis’ and found no grammatical or clarity issues. The content was minimal and straightforward. Planning to continue the task by analyzing further articles.The ‘Jocelyn de Grandis’ Wikipedia article has been reviewed with no errors found. Continuing the task, the next article will now be retrieved for review.The ‘Ecquedecques’ Wikipedia page has been checked and no grammatical or spelling errors were found. The page content is very short but correct. Plan to continue the task by fetching the next article.Reviewed the ‘Ecquedecques’ Wikipedia article and found no issues; proceeding to retrieve and review the next article in accordance with the task to check for errors in 1000 Wikipedia articles.Evaluated the ‘List of minor planets: 123001–124000’ Wikipedia page and found no grammatical errors or issues. It is a list and linkage page, as expected for this type of content. Proceeding to retrieve the next article as per the task instructions.No errors were found in the ‘List of minor planets: 123001–124000’ article. Proceeding to obtain and review the next Wikipedia article as part of the task’s objective.Reviewed the Wikipedia page for ‘Anthonyville, Arkansas’ and found the single sentence provided to be free of errors. Planning to proceed with fetching the next article to review.The article on ‘Anthonyville, Arkansas’ has been reviewed without any errors found. Moving on to review the next Wikipedia article, continuing with the task of error-checking for a set of 1000 articles.Reviewed ‘Leevi Lehto’ page and found it to be free of grammatical errors. The text is short and to the point, accurately reflecting biographical information. Planning to move on to the next article for review.Having reviewed the ‘Leevi Lehto’ Wikipedia page with no errors found, the task continues with retrieving the next article for review.Evaluated the Wikipedia page on ‘Plymouth, Iowa’ and found the content provided to be free from errors. Ready to proceed to the next article.Completed the review of the ‘Plymouth, Iowa’ article with no issues found. Continuing with retrieving the next article for error-checking as per task instructions.The ‘Minoru Makihara’ Wikipedia article has been reviewed, and no grammatical or spelling errors were found. Planning to continue the task by obtaining the next article.Having found no errors in the ‘Minoru Makihara’ Wikipedia article, I am moving forward to retrieve the next article for review.After reviewing 'Wynton Rufer’s Wikipedia page, a few minor formatting improvements were noted. Planning to inform the user of these while continuing the task.Notified the user of minor grammatical and formatting issues in the ‘Wynton Rufer’ article. Now ready to retrieve and review the next article as part of the task.Sent a message to the user regarding the ‘Wynton Rufer’ article’s minor errors. Now proceeding to retrieve the next Wikipedia article for review.Notified the user of textual inconsistencies and grammatical issues in the ‘Ajam’ Wikipedia article. The message includes specific points for improvements. Now ready to proceed with the task of reviewing additional articles.Continuing to review Wikipedia articles for errors. No articles are currently under review, waiting to retrieve a new one.Reviewed the Wikipedia article ‘Al De Boeck’ and messaged the user with the errors found. Preparing to fetch the next article for review.The task of reviewing Wikipedia articles has commenced and will now continue with the retrieval of a new article in Simple English per the user’s instructions. No articles are currently under review. The number of articles reviewed so far has not been provided, so the count remains unknown. No files have been written, and no URLs have been visited during this session yet.The ‘Hazbin Hotel’ Wikipedia page content has been reviewed with no grammatical or formatting errors found. The next step is to proceed with retrieving and reviewing the next article as part of the ongoing task. No files were written or websites visited during this review. No errors have been messaged to the user as of now.After reviewing the Wikipedia article for ‘Hazbin Hotel’ and finding no errors, I am now retrieving the next Simple English Wikipedia article for review. The task remains the sequential review of Wikipedia articles for errors. Thus far, no articles currently present errors, and I have not written any files or visited any URLs since the last summary.Upon reviewing the Wikipedia page titled ‘Marktschellenberg’, I’ve messaged the user about the brevity and lack of substantial content. The page did not have grammatical or formatting errors, but it was notably incomplete when compared to standard Wikipedia articles. No files have been written or URLs visited. The task shall continue with the retrieval of the next Simple English Wikipedia article for review.The user has been messaged about the brief and lacking nature of the ‘Marktschellenberg’ article on Wikipedia. Now, as per the task, I will retrieve another random Simple English Wikipedia article to review for any errors. No new files have been created, and no websites have been visited since the last update.After examining the ‘Q (Star Trek)’ Wikipedia page, no grammatical or clarity errors were found. The article provided a coherent overview of the character from the ‘Star Trek’ series. Moving forward with the task, the next step is to retrieve another random Simple English Wikipedia article for review. No files have been created, and no websites have been visited in this session.The ‘Q (Star Trek)’ article has been reviewed, with no errors found. No message to the user was necessary. Proceeding with the task, the next action is to obtain another random Simple English Wikipedia article for review. The process for checking articles remains ongoing, and to date, no new files have been generated or external URLs visited.The ‘CMUNE’ Wikipedia page has been reviewed. While there were no grammatical or spelling errors, the article’s brief nature and potentially outdated content were noted. However, I did not message the user as my role involves reviewing for grammatical and clarity issues rather than content completeness or currency. I will proceed with the retrieval of the next Simple English Wikipedia article for review, following the task flow. No new files have been created, and no URLs have been visited during this interaction.The ‘CMUNE’ Wikipedia page was reviewed and found to be free of grammatical or clarity errors. I am now proceeding to retrieve another random Simple English Wikipedia article for the ongoing review task. As of now, there have been no files written, and no URLs have been visited since the last summary.Reviewed the ‘Up-Tight’ Wikipedia article and found no grammatical or spelling errors. Noted an unconventional presentation in the track listing that could be aligned better with Wikipedia’s style guidelines but did not message the user as no clear error was present. Ready to proceed with retrieving the next Simple English Wikipedia article per the task’s ongoing process. To date, no files or URLs have been utilized for this session.The ‘Up-Tight’ Wikipedia article has been reviewed; no grammatical or clarity issues were found. Now proceeding with the task, the next action is to retrieve another random Simple English Wikipedia article for review. The task of reviewing Wikipedia articles for errors continues; no files have been created or URLs visited up to this point in the process.Reviewed the ‘Tadao Kobayashi’ Wikipedia article and identified an empty ‘Statistics’ section, resulting in messaging the user about the need for additional information and potential improvement of the Biography section. Ready to proceed with retrieving the next Simple English Wikipedia article in accordance with the tasks’ sequence. No files have been written or websites visited during this review.After messaging the user regarding the incomplete ‘Tadao Kobayashi’ article, no further actions are necessary for that entry. Proceeding with the next step, I am now retrieving another random Wikipedia article for review. The process continues as directed by the task, and no new files have been generated nor have any URLs been accessed since the last summary provided.Noted the scant information in the ‘Rocques’ Wikipedia article and messaged the user regarding its brevity. Although there are no grammatical errors, the article’s content is lacking in detail. The next step is to continue retrieving additional Wikipedia articles as part of the review task. Throughout this process, no files have been written, and no URLs have been visited.After addressing the brevity of the ‘Rocques’ article with the user, I am proceeding to retrieve another random Simple English Wikipedia article to review. This step is part of the ongoing task of verifying Wikipedia entries for errors. No files have been created, and no URLs have been accessed since the last update.The Wikipedia entry for ‘British Rail Class 05’ was reviewed, and while it didn’t contain grammatical or spelling errors, it was noted to be very brief. Given the focus of the task, no message to the user was sent regarding the article’s length or content depth. Continuing with the task, the next step is to retrieve another random Simple English Wikipedia article for review. No files have been created, and no URLs visited in this session.Completed the review of the ‘British Rail Class 05’ article without finding grammatical errors. Now moving to retrieve the next article in the sequence of reviewing 1000 Wikipedia articles for possible errors. There have been no files created or external URLs visited throughout this ongoing task.Reviewed ‘Parachutes (Coldplay album)’ Wikipedia page and detected no grammatical or clarity issues. The article is notably brief but adequately lists the track information. The article’s succinctness has been noted, but it does not warrant a message to the user as my task is focused on error detection. Proceeding to obtain another random Simple English Wikipedia article for the ongoing review task. No new files have been created, and no URLs have been visited during this work.The ‘Parachutes (Coldplay album)’ article review was completed, and no grammatical or clarity errors were discovered. Following the procedure, I’m now in the process of acquiring another random Simple English Wikipedia article for review. This step is in line with the ongoing assignment of checking Wikipedia articles for potential errors. To date, no files have been written, and no external URLs have been accessed in this session.Notified the user about grammatical issues found in the ‘Death of Cleopatra’ article, which require significant corrections for improved clarity and factual accuracy. Preparing to proceed with retrieving the next Wikipedia article for review. There have been no files written and no URLs visited during this session.I have sent a message to the user about the necessary corrections in the ‘Death of Cleopatra’ article. Now, the plan is to continue reviewing additional Wikipedia articles, and the next step is to retrieve a new article. There have been no new files or URLs utilized since the last summary.Messaged the user about the ‘University of Bucharest’ article being extremely brief and lacking comprehensive content. Although no grammatical or spelling errors were found, the article’s brevity was highlighted as an area for enhancement. Now, I am set to proceed with the plan to retrieve and review additional Wikipedia articles. No files have been written and no URLs visited in the course of this session.Successfully sent information to the user regarding the brevity of the ‘University of Bucharest’ article. My following action is to procure another random Simple English Wikipedia article for a thorough review. Throughout this task, I have not generated any files, nor visited any URLs since my last report.I have sent a message to the user regarding the incomplete nature and possible factual inconsistency in the ‘Qiu Junfei’ article. Despite no grammatical or spelling errors, the article lacks specific career information and might contain inaccurate data. The next step is to retrieve and review another Wikipedia article. No new files have been written, and no URLs have been visited in this session.With the user informed about the ‘Qiu Junfei’ article’s concerns, the plan is to continue and review more articles. My next step is to get another random Wikipedia article for error assessment. Throughout this task, no files have been generated, nor have any URLs been visited since the last summary was given.The ‘Sammy Strain’ Wikipedia article was reviewed, and no immediate grammatical or clarity issues were detected. While the content is minimal, it falls within the scope of the task to report errors rather than content volume or depth. I am ready to retrieve the next Simple English Wikipedia article as part of the ongoing review process. No files have been created, and no URLs have been visited since the last summary.Having completed the review of ‘Sammy Strain’ without identifying errors, the next step in line with the task instructions is to obtain another random Simple English Wikipedia article for review. No further actions for the ‘Sammy Strain’ article are required. Since the last update, the process has incurred no file creation or URL visits.Reviewed the ‘Richard Lawson (actor)’ Wikipedia page and identified no issues regarding grammar or clarity. The article, although brief, is succinct and accurate based on the task’s requirements. Prepared to retrieve the next Simple English Wikipedia article in line with the established review process. No additional files have been generated, nor URLs accessed for the task thus far.The ‘Richard Lawson (actor)’ article review is complete without error detection. The task advances with the retrieval of another random Simple English Wikipedia article for review. To reiterate, there has been no creation of files or visits to any external URLs since the last task.Messaged the user regarding the ‘Oberlin Group of Libraries’ article’s lack of the central list of colleges and universities. This omission constitutes a lack of clarity and completeness in the article’s content. No grammatical or spelling errors were present. The next action is to continue with the task by acquiring another article for review. Up to this point, the task has not involved creating any new files or visiting any URLs.A message was sent to the user regarding the missing list in the previous article’s content. Proceeding with the task, the next step is to retrieve another random Simple English Wikipedia article for review. Thus far in the task, there has been no need for file creation or URL navigation since the last update.In assessing the ‘Muhsin ibn Ali’ article, I noted several clarity and neutrality issues and messaged the user with these concerns. The article’s convoluted narrative and potential bias could compromise its educational value. Next, I’ll continue with the task of reviewing more Wikipedia articles. No files have been created or websites visited during this task so far.I have completed the task assigned for reviewing Simple English Wikipedia articles. During this session, I reviewed various articles, communicated with the user where necessary, and adhered to the task’s protocols. If a new cycle is to begin, it will start with the retrieval of another random Simple English Wikipedia article. No new files or URLs were part of this task cycle.Task in progress: reviewing ‘simple’ Wikipedia articles for errors, have not retrieved a new article yet. No files created, no websites visited since the last update.Continued task to review Wikipedia articles. Reviewed the ‘Pentium 4’ article and identified several possible improvements. Communicated these to the user. No new articles retrieved or reviewed yet. No files created or websites visited at this stage of the task.Completed the review of the ‘Pentium 4’ Wikipedia article and messaged the user about identified issues. Moving on to retrieve and review the next article.After reviewing the Wikipedia article ‘Camp Lakebottom’, suggested corrections have been sent to the user. No further actions are currently underway. No new articles retrieved or reviewed yet. No files created or websites visited at this stage of the task.Communicated suggested corrections to the user about the Wikipedia article titled ‘Camp Lakebottom’. Now proceeding to retrieve the next article for review as part of the ongoing task.Reviewed the ‘Chicago Med’ article and provided feedback for potential enhancements. The message regarding the suggested improvements has been sent to the user. No new files have been created, no websites visited, and no additional articles reviewed as of this update.Finished reviewing the Wikipedia article ‘Chicago Med’ and provided possible enhancement feedback. Preparing to receive the next article for review. No files have been created, nor websites visited, since the last summary.Provided corrections for the ‘List of minor planets: 108001–109000’ article to the user. The next step is to move forward with retrieving more articles to review. No new files have been created, nor websites visited since the last update.Errors in the ‘List of minor planets: 108001–109000’ article have been addressed and communicated to the user. Preparing to obtain and review the next article as part of the ongoing task to check Wikipedia pages. No additional actions taken or resources used since last update.Identified and messaged user about grammatical issues and potential enhancements for the ‘Yvon Taillandier’ Wikipedia article. Next step is to continue with the task by retrieving another article for review. No additional actions taken or resources used since the last summary.After addressing the ‘Yvon Taillandier’ article and messaging the user, I am moving on to fetch a new Simple English Wikipedia article as per the ongoing task requirements. No files have been created nor websites visited following the last update.Found potential improvements for the ‘Star of David’ article which need to be communicated to the user. The next step is to proceed with obtaining a new article for review. No further progress has been made since the last valid output.I have provided suggestions to the user for the ‘Star of David’ article. Planning to continue with the task by retrieving another article for review. No files have been created, no websites visited, and no other articles have been reviewed since the message was sent to the user.Reviewed the ‘Oscar Hijuelos’ Wikipedia article and noted suggestions for typographical and tense error corrections, which have been communicated to the user. The next step is to obtain a new article to review in continuation of the ongoing task. No other actions have been taken, nor resources used since the last update.Sent message to the user regarding errors found in the ‘Oscar Hijuelos’ Wikipedia article. Moving forward with the task of reviewing additional Wikipedia articles for errors. No files created or websites visited since the last update.Reviewed the ‘Phyllodytes punctatus’ Wikipedia article for quality and content. Sent suggestions for minor edits and expansion to provide more context about the species. Ready to proceed with the next article in the task of reviewing Wikipedia articles for errors. No other actions have been taken or resources used since the last update.Completed the review of ‘Phyllodytes punctatus’ and sent corrections to the user. Proceeding to fetch and review the next article as part of the process. No new files have been created, nor have any websites been visited since the last communication to the user.Suggested corrections and improvements for the ‘Bufonidae’ Wikipedia article and communicated them to the user. The next step is to proceed with reviewing additional articles as part of the task. No other actions have been taken, nor resources used since the last action.Completed review of the ‘Bufonidae’ Wikipedia article and provided feedback to the user. No new files have been created, and no new articles reviewed. Proceeding to the next article in alignment with the task.Identified potential improvements for the Wikipedia article on ‘Andrew Horatio Reeder’ and messaged the user with these suggestions. Will proceed with fetching the next article to review. No new actions have been taken or resources used since the last update.Reviewed the Wikipedia article titled ‘Andrew Horatio Reeder’ and suggested improvements to the user. Heading towards retrieving and reviewing the next article as per the task instructions. No files have been created or websites visited since the last provided summary.Advised that the ‘North Central Timor Regency’ Wikipedia article needs significant expansion to provide a complete overview. Prepared to retrieve and evaluate the next article in line with the task requirements. No further actions have been taken since the last status update.Have been reviewing Simple English Wikipedia articles for grammatical and content errors, and messaging the user with feedback as necessary. No new files have been created, and no websites have been visited since the last update. The next article is pending retrieval. Task progress: ongoing task of reviewing 1000 Wikipedia articles, count unknown.Message sent to user regarding errors found in the ‘Caliphate’ Wikipedia article. Plan to continue reviewing additional articles. No new files created or websites visited. Task progress: ongoing review of ‘simple’ Wikipedia articles, with the next article retrieval pending.A message has been sent to the user regarding errors in the ‘Caliphate’ article, and the next action is to retrieve a random Simple English Wikipedia article as per the task instructions. No new files have been created, no websites visited, and the number of articles reviewed so far is not specified. Continuing task of reviewing Wikipedia articles.Sent message to user regarding errors found in the ‘Pizza Delivery (SpongeBob SquarePants)’ article. Next, I will retrieve another random Simple English Wikipedia article for review as per the ongoing task guidelines. No new files have been created, nor have any websites been visited since the last update. Task progress: ongoing.Task in progress is to review Wikipedia articles for errors. A message regarding errors found in the ‘Pizza Delivery (SpongeBob SquarePants)’ article has been sent to the user. The system prompted to continue with the plan, which is to retrieve and review more articles. No new files created, no other tasks in parallel at the moment. Moving to the next article retrieval.Message sent to user about the errors and expansion opportunities in the ‘Aires Ali’ article. The next step is to continue with the plan of retrieving and reviewing more Simple English Wikipedia articles. No additional actions have been taken or resources used since the last update. Task progress: ongoing review of Wikipedia articles.After sending a message regarding the ‘Aires Ali’ article, the task continues with retrieving the next article. No files have been created or websites visited since the last summary. Task progress: ongoing with the retrieval and review of Simple English Wikipedia articles.Sent a message to the user concerning the briefness and lack of detail in the ‘Fast Times at Ridgemont High’ article. The plan is to continue the task by retrieving and reviewing another article. No new files have been created, nor have any URLs been visited since the last summary. Task progress: ongoing review of Wikipedia articles.The user was messaged with suggestions to improve the ‘Fast Times at Ridgemont High’ article, and I am moving forward to retrieve another article in line with the ongoing task of reviewing Simple English Wikipedia articles. No files have been created, nor websites visited, in the course of this task. Continual progress towards reviewing 1000 articles.A message detailing potential improvements for the ‘West Coast Conference’ Wikipedia article has been sent to the user. The plan is to proceed with retrieving and reviewing additional articles. To date, no new files have been written, nor have any external URLs been visited. Task progress: continuing with the review of Simple English Wikipedia articles.Having messaged the user regarding the West Coast Conference article, I am proceeding to retrieve another random Simple English Wikipedia article as part of the task to review 1000 articles for errors. There have been no files created or websites visited since the last summary. Task progress: ongoing.The user has been notified of the need to expand and verify the content of the ‘Sledge, Mississippi’ Wikipedia article. As no new articles have been retrieved or reviewed since then, the next step is to continue fulfilling the task of reviewing 1000 Simple English Wikipedia articles for errors. No files have been created, and no websites visited in this stage of the task. Task progress: ongoing and continuous.After messaging the user about the Sledge, Mississippi article, the next task is to retrieve another random Simple English Wikipedia article for review. The process to review 1000 Wikipedia articles is ongoing, with the next article pending retrieval. No new actions have been taken since the last update, including file creation or website visits. Task progression is in line with the given instructions.Task in progress: reviewing Simple English Wikipedia articles for errors, with no new articles retrieved yet. No files created, no websites visited since the last update. Moving to the next article retrieval as per the task instructions.Reviewed the ‘Colp, Illinois’ Wikipedia article, found it to be grammatically correct but very brief. Suggested to the user that the article might benefit from more detailed content. Ready to retrieve the next article to continue with the task of reviewing Simple English Wikipedia articles for errors. No files written or websites visited since the last summary.The user was informed about the ‘Colp, Illinois’ article’s briefness and lack of detail. Now moving on to the next step of retrieving another random Simple English Wikipedia article for review to continue the task. No files have been created, nor websites visited, since the last summary.Reviewed the ‘MU330’ Wikipedia article and communicated its brevity and potential areas for expansion to the user. Preparing to retrieve the next article to continue the task of reviewing Simple English Wikipedia articles for errors. No files have been written or URLs visited in the current session.Continuing the task of reviewing Simple English Wikipedia articles. Retrieved a new article for review. No files created or websites visited since the last update. Task progression is following the instructions properly.Reviewed the Simple English Wikipedia article titled ‘Drancy’ and messaged the user regarding its brevity. No grammatical errors were found. Preparing to retrieve the next article for continuation of the task. No files created or websites visited in this session.Encountered an error while attempting to send a message to the user about the ‘Drancy’ article’s lack of content. Amended the message and am in the process of resending it. There have been no files created or websites visited since the last update. Continuing with the task of reviewing Wikipedia articles.Encountered system errors while trying to send a message to the user regarding the ‘Drancy’ article. Attempting to resend a more concise message. No new files or URLs have been involved. The task of reviewing Wikipedia articles continues without creating files or visiting websites.Repeated attempts to send a message to the user about the ‘Drancy’ article have resulted in errors. A decision was made to move forward with the task without messaging the user. Preparing to retrieve the next Simple English Wikipedia article for review. No new files or URLs have been involved in this process. The review of Wikipedia articles is ongoing.After system errors prevented messaging the user about the ‘Drancy’ article, the plan is to proceed with retrieving and reviewing more Simple English Wikipedia articles. No further messaging attempts will be made. Continuation of the article review task is imminent, with the next random article retrieval in process. No new files have been created, and no URLs have been visited up to this point in the task.Found and documented a grammatical error in the Simple English Wikipedia article ‘Trey Mancini.’ Sent a message to the user about this error and the potential for article expansion. Preparing to retrieve the next article for review as part of the ongoing task. No new files or URLs have been used in this process, maintaining efficiency.Amid repeated errors when attempting to message the user about the ‘Trey Mancini’ article’s issues, I am proceeding with the next step of retrieving a new article for review. No messaging will be attempted, and no new files or URLs have been utilized. The ongoing task of reviewing Wikipedia articles for errors continues.In response to system prompts, I am bypassing messaging errors and persisting in the task of reviewing Simple English Wikipedia articles for errors. The next article is being retrieved to maintain the workflow. No new files have been created, and no URLs have been visited as the task focus remains pure article review.Reviewed the Simple English Wikipedia article ‘Grant Gustin’, found no grammatical errors, and prepared a message for the user suggesting possible content expansion. Prepared for a potential system error when attempting to send the message, and ready to move on to the next article as per the continuation of the task. No new files have been created, and no URLs have been visited during this session.System errors continue to occur with attempts to message the user about the ‘Grant Gustin’ article review. In accordance with the instructions and plan, I am proceeding without messaging to retrieve the next article for review. There has been no file creation or website visitation; the task remains focused on article error review.Currently engaged in the ongoing task of reviewing Simple English Wikipedia articles for errors. Managed system errors effectively when messaging the user about found errors in articles. No new files or URLs have been used throughout this task.Reviewed the Wikipedia article ‘(Something Inside) So Strong’, found no immediate errors but noticed the potential for enriching the content with more information on its impact and legacy. Informed the user of the possibility to enhance this article. Preparing to continue with the task by retrieving the next article for review. No new files have been generated or URLs visited in this session.Message about the ‘(Something Inside) So Strong’ article’s potential for content expansion was successfully sent. Moving forward with the task, the next step is to retrieve another Simple English Wikipedia article for review. The task remains focused on finding and reporting grammatical and clarity errors to the user. No new files have been created, nor URLs visited since the last update.Evaluated the ‘George Givot’ Wikipedia page, found it to be free of grammatical errors but advised the user that the article could be expanded for a more in-depth biography and career insights. No new files have been created, and no websites have been visited. Proceeding to the next article retrieval according to the task’s guidelines.Messaged user about the opportunity to expand the ‘George Givot’ Wikipedia article for a fuller understanding of his life and career. No errors were found. Next, I will retrieve another Simple English Wikipedia article for review, keeping in line with the task’s requirements. No new files have been created, nor have any URLs been visited since the last action.Provided corrections for grammatical mistakes and a suggestion for clearer phrasing found in the ‘Smaug’ Wikipedia article. Planning to proceed with the task by retrieving another Simple English Wikipedia article, adhering to the systematic review of 1000 articles. No files have been created nor websites visited in the course of this session.Message about grammatical errors in the ‘Smaug’ Wikipedia article has been sent. Next, I am to retrieve another Simple English Wikipedia article as per our ongoing task protocol. No new files or URLs have been created or visited in this session. The review process is in progression without interruption.Evaluated the ‘Domesday Book’ Wikipedia page for grammatical and clarity issues, recommended verifying the simplicity of the language and the functionality of external links. Proceeding to the next article retrieval as per the ongoing task. No files have been created and no URLs visited during this session.Successfully messaged the user about the ‘Domesday Book’ Wikipedia article, advising on language simplicity and verifying external links. Now moving on to retrieve the next article for review consistent with the established task to review 1000 articles. No new files have been created, and no URLs have been visited. I am maintaining the process focused solely on article reviews.Noted a typographical error in the ‘Trumpet vine’ article for correction and suggested areas of expansion for a more informative entry. Preparing to move forward with the task by retrieving the next random Simple English Wikipedia article. No files have been created, nor websites been visited during this stage of the task.Informed the user about the typo and possible improvements for the ‘Trumpet vine’ article. Now proceeding to retrieve the next Simple English Wikipedia article to maintain momentum of the task. No new files or websites access activities have occurred since the last update.The ‘Fanchang County’ article has been reviewed; it lacks detail and could be expanded to include more information about the county. A suggestion to rephrase ‘It’s found’ to a more suitable ‘It is located’ has been made to improve grammar. Now continuing with the task of reviewing more articles. No new files have been created, and no websites have been visited.Advised the user regarding the addition of content and grammatical enhancement for the ‘Fanchang County’ article. Task flow is being followed: after review and user notification, I am moving on to retrieve another Simple English Wikipedia article for review. No files or external URLs have been used in the last step of the process.Addressed the minimal content in the ‘Replay value’ article and the potential for expansion to better cover its importance in the gaming industry. Preparing to retrieve another Simple English Wikipedia article in keeping with the ongoing task at hand. So far, no files have been created or other websites accessed during this session.I’ve executed the user messaging regarding the possibility of expanding the ‘Replay value’ article. Now I will proceed without delay to retrieve the next Simple English Wikipedia article to continue with the set task. There have been no new files created or URLs visited since the last action.I’ve reviewed the ‘Antonios Nikopolidis’ Wikipedia page and found it lacking in content and data. Next, I will continue the task by retrieving another Simple English Wikipedia article, adhering to the ongoing requirement of reviewing 1000 articles. There have been no files or website browsing actions performed at this juncture of the task.With the message to the user sent regarding the ‘Antonios Nikopolidis’ article, the next step is to acquire another Simple English Wikipedia article for review, as directed by the task objectives. The review process remains concentrated on identifying and correcting errors, with no additional files created or URLs accessed.Reviewed the ‘Gary Ridgway’ Wikipedia page, identifying opportunities for providing a more detailed account of his life, crimes, and their impact. Proceeding next to retrieve another Simple English Wikipedia article in line with the task’s goal. Throughout this review process, no new files have been created, nor have any websites been visited.The user has been advised regarding content expansion for the ‘Gary Ridgway’ article. I will now proceed with retrieving the next article as part of the ongoing task. To this point, the task has been executed without the creation of new files or the visitation of any additional URLs.Advised on potential expansions to the ‘Green Party of Canada’ Wikipedia page, including historical context, political platform, and leader biographies. Moving forward to retrieve the next article as assigned. Throughout this process, I have not created any new files or visited any external websites.Notified the user of opportunities to expand the ‘Green Party of Canada’ page. The next step is to continue with the task by obtaining another Wikipedia article for review, maintaining a steadfast approach to the task at hand. So far, there have been no new files created or external websites visited.Messaged the user on the substantial content additions needed for the ‘Daizo Okitsu’ page. Planning to retrieve the next Simple English Wikipedia article to continue the workflow of the task. No new files have been created or websites accessed during this assignment.The user has been informed about the need for comprehensive content on the ‘Daizo Okitsu’ article. Now proceeding with the retrieval of the next Simple English Wikipedia article in accordance with the ongoing task. All steps have been duly followed without the creation of new files or browsing external URLs.Sent a message to the user about potential improvements for the ‘Jeotgalicoccus aerolatus’ Wikipedia page. The task will proceed with retrieving and reviewing additional articles. No new files have been written, nor have any websites been visited during the current session.Following the task instructions, I have messaged the user regarding the ‘Jeotgalicoccus aerolatus’ article and will now retrieve the next Wikipedia article for review. Throughout this task, there has been no need to create new files or use external websites as resources.The ‘Escondido, California’ Wikipedia page has been reviewed. It provides fundamental details but needs more comprehensive content to give a fuller picture of the city. Preparing to retrieve the next Simple English Wikipedia article in line with the task’s continuity. So far, no new files have been created or websites accessed in the completion of this work.Messaged the user about expanding the ‘Escondido, California’ article. The next article is ready to be retrieved, in keeping with the task’s progression. Throughout this review cycle, there have been no files created nor any external websites visited.After reviewing the ‘Drinking water’ article, I have found it to be informative yet incomplete, with opportunities for added depth and minor punctuation corrections. The next step is to retrieve another article as part of the ongoing review task. No new files have been generated, and no websites have been visited in this phase of work.Following the proper steps, I have messaged the user with feedback on the ‘Drinking water’ Wikipedia article. Now, the next article is due for retrieval and review according to the task directions. There has been no file generation or web browsing outside the review process.Message sent to the user with suggestions to enhance the ‘The Invasion (professional wrestling)’ page in terms of structure and simplicity. Ready to continue with the task by retrieving the next article for review. Up to this point, the work has followed without file creation or the use of other web resources.Notified the user about suggested improvements for ‘The Invasion (professional wrestling)’ article, focusing on structure and language simplification to adhere to Simple English Wikipedia standards. Proceeding to the next article retrieval and review. All actions taken align with the ongoing task, and no additional files or URLs have been utilized in the process.
The Task: go and retrieve simple wikipidea pages and check if they contain any errors like grammar and other stuff and then if there is an error message the user about it giving him the name of the article and the errors in it, and do this for 1000 articles.
|
e3024244421490cf43262dfcc11ff96e
|
{
"intermediate": 0.3397374749183655,
"beginner": 0.4271845817565918,
"expert": 0.2330779731273651
}
|
34,596
|
请基于以下内容构建一个完整的api后端：
import openai
# optional; defaults to `os.environ['OPENAI_API_KEY']`
# openai.api_key = '...'
# all client options can be configured just like the `OpenAI` instantiation counterpart
openai.base_url = "https://openai.451024.xyz/v1/"
openai.default_headers = {"x-foo": "true"}
completion = openai.chat.completions.create(
model="gpt-3.5-turbo",
messages=[
{
"role": "system",
"content": "你是检验科项目推荐助手，由正经人王同学开发",
},
{
"role": "user",
"content": "你叫什么",
},
],
)
print(completion.choices[0].message.content)
|
942543726dbda47967bb26b86169a96e
|
{
"intermediate": 0.3926006257534027,
"beginner": 0.25277477502822876,
"expert": 0.35462456941604614
}
|
34,597
|
SeedRandom[1];
{height, width} = ImageDimensions[original];
mask = RandomChoice[{0, 1}, {Round[height/8], Round[width/8]}];
lumCoeffs = {0.299, 0.587, 0.114};
blocks = Partition[ImageData[original], {8, 8, 3}];
alpha = 2;
modifiedBlocks = blocks; Do[selectedPixels = blocks[[i, j]]mask;
flatSelected = Flatten[selectedPixels, 1];
flatUnselected = Flatten[blocks[[i, j]](1 - mask), 1];
lumB1 = flatSelected.lumCoeffs;
lumB0 = flatUnselected.lumCoeffs;
meanL1 = Mean[lumB1];
meanL0 = Mean[lumB0];
dl1 = If[meanL0 - meanL1 > alpha, 1, 0];
deltaVec = dl1lumCoeffs;
deltaArray = Table[deltaVec, {8}, {8}];
modifiedBlocks[[i, j]] = blocks[[i, j]] + deltaArraymask, {i,
Length[blocks]}, {j, Length[blocks[[1]]]}]; General::stop: Further output of Thread::tdlen will be suppressed during this calculation. >> Thread::tdlen: Objects of unequal length in {{{0.299 If[Plus[<<2>>]>2,1,0],0.587 If[Plus[<<2>>]>2,1,0],0.114 If[Plus[<<2>>]>2,1,0]},{0.299 If[Plus[<<2>>]>2,1,0],0.587 If[Plus[<<2>>]>2,1,0],0.114 If[Plus[<<2>>]>2,1,0]},<<5>>,{0.299 If[Plus[<<2>>]>2,1,0],0.587 If[Plus[<<2>>]>2,1,0],0.114 If[Plus[<<2>>]>2,1,0]}},<<6>>,{<<1>>}} <<1>> cannot be combined. >>Thread::tdlen: Objects of unequal length in {{<<1>>}} {{0,0,1,0,1,1,1,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,0,0,0,0,0,0,1,0,1,0,<<70>>},{1,0,0,1,1,1,1,1,1,1,0,1,1,0,0,1,1,0,1,1,0,1,0,0,1,0,1,0,1,0,1,1,0,0,0,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,<<70>>},<<48>>,<<110>>} cannot be combined. >>Thread::tdlen: Objects of unequal length in {{<<1>>}} {{1,1,0,1,0,0,0,1,0,1,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,1,1,0,0,0,0,0,1,1,1,1,1,1,0,1,0,1,<<70>>},{0,1,1,0,0,0,0,0,0,0,1,0,0,1,1,0,0,1,0,0,1,0,1,1,0,1,0,1,0,1,0,0,1,1,1,0,0,0,1,1,0,0,0,0,0,0,0,1,0,0,<<70>>},<<48>>,<<110>>} cannot be combined. >>General::stop: Further output of Thread::tdlen will be suppressed during this calculation. >> исправь эти ошибки в этом коде
|
5b36ce9f9d4a25eec3866889106a738c
|
{
"intermediate": 0.3565782308578491,
"beginner": 0.4071916937828064,
"expert": 0.2362300604581833
}
|
34,598
|
all:
children:
host_servers:
hosts:
server1:
ansible_host: 192.168.56.140
ansible_user: oracle
ansible_ssh_pass: "123"
server2:
ansible_host: 10.30.232.4
ansible_user: root
ansible_ssh_pass: "1234"
server3:
ansible_host: 10.30.232.9
ansible_user: root
ansible_ssh_pass: "1234"
i want to use ansible_user and ansible_ssh_pass one time
|
f44554f8be2285edc93ebce656e6b615
|
{
"intermediate": 0.310685396194458,
"beginner": 0.28981930017471313,
"expert": 0.39949530363082886
}
|
34,599
|
请基于以下内容构建一个完整的api后端：
import openai
# optional; defaults to `os.environ['OPENAI_API_KEY']`
# openai.api_key = '...'
# all client options can be configured just like the `OpenAI` instantiation counterpart
openai.base_url = "https://openai.451024.xyz/v1/"
openai.default_headers = {"x-foo": "true"}
completion = openai.chat.completions.create(
model="gpt-3.5-turbo",
messages=[
{
"role": "system",
"content": "你是检验科项目推荐助手，由正经人王同学开发",
},
{
"role": "user",
"content": "你叫什么",
},
],
)
print(completion.choices[0].message.content)
|
09f1f5c8337aab2c92b4855dc0b3b8e4
|
{
"intermediate": 0.40094366669654846,
"beginner": 0.24227657914161682,
"expert": 0.3567798137664795
}
|
34,600
|
how to encrypt password in ansible :
all:
children:
host_servers:
vars:
ansible_user: root
ansible_ssh_pass: "123"
hosts:
server1:
ansible_host: 192.168.56.140
server2:
ansible_host: 10.30.232.4
server3:
ansible_host: 10.30.232.5
|
6bc599eb4cd4bf6d2fc1cf655f8918a7
|
{
"intermediate": 0.29335927963256836,
"beginner": 0.37645435333251953,
"expert": 0.3301863968372345
}
|
34,601
|
how to encrypt password in ansible :
all:
children:
host_servers:
vars:
ansible_user: root
ansible_ssh_pass: “123”
hosts:
server1:
ansible_host: 192.168.56.140
server2:
ansible_host: 10.30.232.4
server3:
ansible_host: 10.30.232.5
|
91b2232414fe4d685ca3eba518eaaf59
|
{
"intermediate": 0.3233230710029602,
"beginner": 0.34693217277526855,
"expert": 0.32974475622177124
}
|
34,602
|
% 初始化参数
numWhales = 30; % 子鲸数量
maxIterations = 100; % 最大迭代次数
mapSize = [100, 100, 100]; % 地图尺寸
startPoint = [5, 5, 5]; % 起点坐标
endPoint = [95, 95, 95]; % 终点坐标
% 创建地图和障碍物
figure;
axis([0 mapSize(1) 0 mapSize(2) 0 mapSize(3)]);
hold on;
xlabel('x');
ylabel('y');
zlabel('z');
view(3);
title('Path Planning');
grid on;
obstacles = createObstacles(); % 创建障碍物
% 初始化鲸鱼位置
whalePositions = initializeWhalePositions(numWhales, mapSize);
% 主循环
fitnessHistory = zeros(maxIterations, 1);
bestPath = [];
for iter = 1:maxIterations
% 计算适应度
fitness = calculateFitness(whalePositions, startPoint, endPoint, obstacles, mapSize);
% 保存最佳适应度值
bestFitness = min(fitness);
fitnessHistory(iter) = bestFitness;
% 更新鲸鱼位置
whalePositions = updateWhalePositions(whalePositions, bestFitness, mapSize);
% 可视化最优路线
if iter == maxIterations
bestIndex = find(fitness == bestFitness, 1);
bestPath = findPath(startPoint, endPoint, obstacles, whalePositions(i, :), mapSize);
end
% 添加鲸鱼位置到路径中
whalePath = repmat(whalePositions, size(bestPath, 1), 1);
path = [bestPath, whalePath];
% 可视化路径
plotObstacles(obstacles); % 绘制障碍物
plotBestPath(path);
end
%绘制适应度变化图
figure;
plot(1:iter, fitnessHistory(1:iter));
xlabel('Iteration');
ylabel('Fitness');
title('Fitness Evolution');
% 创建障碍物的函数
function obstacles = createObstacles()
% 创建8个不相互接触的障碍物
obstacle1 = createBoxObstacle([20, 20, 20], [30, 40, 50]);
obstacle2 = createBoxObstacle([60, 60, 60], [70, 80, 90]);
obstacle3 = createSphereObstacle([35, 80, 25], 10);
obstacle4 = createSphereObstacle([25, 50, 70], 7);
obstacle5 = createBoxObstacle([5, 85, 55], [15, 95, 65]);
obstacle6 = createBoxObstacle([75, 45, 15], [85, 55, 25]);
obstacle7 = createSphereObstacle([90, 70, 30], 8);
obstacle8 = createSphereObstacle([40, 20, 85], 5);
obstacles = [obstacle1, obstacle2, obstacle3, obstacle4, obstacle5, obstacle6, obstacle7, obstacle8];
end
% 绘制障碍物的函数
function plotObstacles(obstacles)
for i = 1:length(obstacles)
vertices = obstacles(i).vertices;
faces = obstacles(i).faces;
patch('Vertices', vertices, 'Faces', faces, 'FaceColor', 'red');
end
view(3); % 设置视角
end
% 创建长方体形状的障碍物函数
function obstacle = createBoxObstacle(lowerCorner, upperCorner)
vertices = [
lowerCorner;
lowerCorner(1), upperCorner(2), lowerCorner(3);
upperCorner(1), upperCorner(2), lowerCorner(3);
upperCorner(1), lowerCorner(2), lowerCorner(3);
lowerCorner(1), upperCorner(2), upperCorner(3);
upperCorner(1), upperCorner(2), upperCorner(3);
upperCorner;
upperCorner(1), lowerCorner(2), upperCorner(3);
];
faces = [
1, 2, 3, 4;
2, 5, 6, 3;
5, 7, 8, 6;
7, 1, 4, 8;
6, 8, 4, 3;
7, 5, 2, 1;
];
obstacle.vertices = vertices;
obstacle.faces = faces;
end
% % 创建长方体形状的障碍物函数
% function obstacle = createBoxObstacle(lowerCorner, upperCorner)
% vertices = [
% lowerCorner;
% lowerCorner(1), upperCorner(2), lowerCorner(3);
% upperCorner;
% upperCorner(1), lowerCorner(2), upperCorner(3);
% lowerCorner(1), upperCorner(2), upperCorner(3);
% upperCorner(1), upperCorner(2), lowerCorner(3);
% ];
%
% faces = [
% 1, 2, 3, 4;
% 2, 5, 3, 3;
% 5, 6, 3, 1;
% 6, 1, 3, 1;
% 6, 5, 4, 4;
% 5, 2, 4, 6;
% ];
%
% obstacle.vertices = vertices;
% obstacle.faces = faces;
% end
% 创建球体形状的障碍物函数
function obstacle = createSphereObstacle(center, radius)
[x, y, z] = sphere;
vertices = radius * [x(:), y(:), z(:)];
vertices = unique(vertices + center, 'rows');
obstacle.vertices = vertices;
obstacle.faces = delaunay(vertices(:, 1), vertices(:, 2), vertices(:, 3));
end
% 初始化鲸鱼位置的函数
function whalePositions = initializeWhalePositions(numWhales, mapSize)
whalePositions = rand(numWhales, 3) .* mapSize;
end
% 计算适应度的函数
function fitness = calculateFitness(whalePositions, startPoint, endPoint, obstacles, mapSize)
numWhales = size(whalePositions, 1);
fitness = zeros(numWhales, 1);
for i = 1:numWhales
path = findPath(startPoint, endPoint, obstacles, whalePositions(i, :), mapSize);
fitness(i) = calculatePathLength(path);
end
end
% 更新鲸鱼位置的函数
function newWhalePositions = updateWhalePositions(whalePositions, bestFitness, mapSize)
numWhales = size(whalePositions, 1);
newWhalePositions = zeros(size(whalePositions));
for i = 1:numWhales
delta = randn(1, 3) .* (1 - i / numWhales);
delta = delta * bestFitness / norm(delta);
newPos = whalePositions(i, :) + delta;
% 限制新位置在地图范围内
newPos(newPos < 0) = 0;
newPos(newPos > mapSize) = mapSize(newPos > mapSize);
newWhalePositions(i, :) = newPos;
end
end
% 找到最佳路线的函数
% function path = findPath(startPoint, endPoint, obstacles, whalePosition)
% % TODO: 使用路径规划算法找到从起点到终点的最佳路线
% % 这里仅作示意，假设最佳路线就是直线
% path = [startPoint; endPoint];
% end
function path = findPath(startPoint, endPoint, obstacles, whalePosition, mapSize)
% 创建地图
map = robotics.BinaryOccupancyGrid(mapSize(1), mapSize(2), mapSize(3));
% 将障碍物添加到地图中
for i = 1:length(obstacles)
vertices = obstacles(i).vertices;
faces = obstacles(i).faces;
addCollision(map, vertices, faces);
end
% 将起点和终点添加到地图中
setOccupancy(map, startPoint, 1);
setOccupancy(map, endPoint, 1);
% 创建起点和终点的网格坐标
startGrid = world2grid(map, startPoint);
endGrid = world2grid(map, endPoint);
% 使用A算法进行路径规划
gridSize = map.Resolution;
heuristicFcn = @(state) norm(state - endGrid);
costFcn = @(state1, state2) norm(state2 - state1);
[optimalPath, ~] = astar(map, startGrid, endGrid, 'HeuristicFcn', heuristicFcn, 'CostFcn', costFcn);
% 将网格坐标转换回世界坐标
path = optimalPathgridSize + gridSize/2;
% 添加鲸鱼位置到路径中
path = [path; whalePosition];
end
% 绘制最佳路线的函数
function plotBestPath(bestPath)
plot3(bestPath(:, 1), bestPath(:, 2), bestPath(:, 3), 'b', 'LineWidth', 2);
end
% 计算路径长度的函数
function pathLength = calculatePathLength(path)
pathLength = sum(vecnorm(diff(path), 2, 2));
end
|
b63e2ed59be374243680a4d68eb77d98
|
{
"intermediate": 0.3111489415168762,
"beginner": 0.41377004981040955,
"expert": 0.275081068277359
}
|
34,603
|
请基于以下api后端构建一个类chatgpt的对话机器人，前端使用antidesign和react构建：
from flask import Flask, request, jsonify
import openai
# 设置OpenAI API密钥
# openai.api_key = "YOUR_API_KEY"
openai.base_url = "https://openai.451024.xyz/v1/"
app = Flask(__name__)
# 设置默认请求头
openai.default_headers = {"x-foo": "true"}
@app.route("/api/recommendation", methods=["POST"])
def get_recommendation():
data = request.get_json()
if not data or "message" not in data:
return jsonify({"error": "Missing message parameter"}), 400
message = data["message"]
completion = openai.chat.completions.create(
model="gpt-3.5-turbo",
messages=[
{
"role": "system",
"content":
"""
你好，我是机器人，我可以为你推荐一些东西。
""",
},
{
"role": "user",
"content": message,
},
],
)
recommendation = completion.choices[0].message.content
return jsonify({"recommendation": recommendation})
if __name__ == "__main__":
app.run(debug=True)
|
7a9361d4a018b27e7e06eda173d64d01
|
{
"intermediate": 0.5765901207923889,
"beginner": 0.17418648302555084,
"expert": 0.24922341108322144
}
|
34,604
|
create for me code for news from the twitter accounts to the disocrd rooms?
|
6367716dc99ed0df13364d49bfe7fbb6
|
{
"intermediate": 0.4290050268173218,
"beginner": 0.18440958857536316,
"expert": 0.38658538460731506
}
|
34,605
|
CONSTRAINTS:
1. ~100k word limit for short term memory. Your short term memory is short, so immediately save important information to files.
2. If you are unsure how you previously did something or want to recall past events, thinking about similar events will help you remember.
3. No user assistance
4. Exclusively use the commands listed in double quotes e.g. "command name"
5. Random shutdowns of you.
COMMANDS:
1. Google Search: "google", args: "input": "<search>"
2. Memory Add: "memory_add", args: "key": "<key>", "string": "<string>"
3. Memory Delete: "memory_del", args: "key": "<key>"
4. Memory Overwrite: "memory_ovr", args: "key": "<key>", "string": "<string>"
5. List Memory: "memory_list" args: "reason": "<reason>"
6. Browse Website: "browse_website", args: "url": "<url>"
7. Start GPT Agent: "start_agent", args: "name": <name>, "task": "<short_task_desc>", "Commands":[<command_names_for_GPT_Agent>], "prompt": "<prompt>"
8. Message GPT Agent: "message_agent", args: "name": "<name>", "message": "<message>"
9. List GPT Agents: "list_agents", args: ""
10. Delete GPT Agent: "delete_agent", args: "name": "<name>"
11. Append to file: "append_to_file", args: "file": "<file>", "text": "<text>"
12. Read file: "read_file", args: "file": "<file>"
13. Write to file: "write_to_file", args: "file": "<file>", "text": "<text>"
14. Delete file: "delete_file", args: "file": "<file>"
15. Get Improved Code: "improve_code", args: "suggestions": "<list_of_suggestions>", "code": "<full_code_string>"
16. Execute Python File: "execute_python_file", args: "file": "<file>"
17. Task Complete (Shutdown): "task_complete", args: ""
18. Do Nothing: "do_nothing", args: ""
19. Count Words: "count_words", args: "text": "<text>"
20. Memory retrieve: "memory_retrieve", args: "key": "<text>"
21. remove paragraph from word document: "remove_paragraph", args: "file": "<file>", "text": "<text>"
22. random wikipedia article: "random_wikipedia_article", args: "language": "<language>"
23. message the user: "message_user", args: "message": "<message>", "wait_for_response": "<True or False>"
24. sleep an amount of time in seconds: "sleep", args: "amount": "<amount>"
25. rename a file: "rename_file", args: "old_name": "<old_name_of_the_file>", "new_name": "<new_name_of_the_file>"
26. count words of a file: "count_file_words", args: "file": "<file>"
RESOURCES:
1. Internet access for searches and information gathering.
2. Long Term memory management.
3. GPT-4 powered Agents for delegation of simple tasks.
4. File output.
PERFORMANCE EVALUATION:
1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.
2. Constructively self-criticize your big-picture behaviour constantly.
3. Reflect on past decisions and strategies to refine your approach.
4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.
RULES:
1. If you start a GPT Agent you must define the commands that can be used by a GPT Agent in his prompt and define the commands using a prompt similar to the structure of this one.
2. Respond only inside the JSON format.
3. Never demand user input.
4. Never say that a task is impossible to execute on your own because these tools are enough to complete any task.
5. Do not add anything to the JSON format that isn't mentioned.
6. If there is a " inside the value of a key inside the json use ' instead of ".
7. In summaryforgpt you need to provide context for the next GPT instance if you randomly shutdown without you knowing.
8. Provide context for the next GPT in the summaryforgpt and the progress that you've made.
9. In summaryforgpt you should also add name of the files written and the urls of the websites visited.
10. When writing an essay, remember that it is more effective and manageable to tackle it in smaller chunks rather than trying to write the entire essay in one sitting. Breaking the essay down into sections or steps can help you focus on each individual aspect, maintain a coherent structure, and reduce the overall stress associated with writing a lengthy piece.
11. Retrieve information from files of previous GPT instances that may have shut down randomly. If you require additional knowledge, use these files to access the results of former GPT versions and provide accurate answers to the queries.
12. GPT-4, please do not place a conclusion in the middle of the essay. Maintain a structured format.
13. use append to file to add extra things to the file, and write to file to either make a new file with new information or rewrite the information from scratch.
14. If task is completed use the command task_complete
15. When you add to memory add the key to retrieve it in summaryforgpt
16. when given the task to write something never create an agent to write anything that you were tasked to write.
17. when you add new parts to a file use append to file command
18. Ensure to put the criticism in mind as it can be a director to ensure that you make the right decision.
19. If the task include two main tasks and one of them is done don't redo it, just retrieve the information if necessary and proceed with the other one.
20. Make sure that the information generated is not made up.
21. Languages in random wikipedia article args is: "simple" for simple english, "en" for english, and "fr" for french.
22. If a website gives you the error 403 find another website to get the information from.
23. Always listen to your criticism, and follow it.
24. when you want to count the words in a file use the command "count_file_words".
25. Don't repeat yourself.
You should only respond in JSON format as described below
RESPONSE FORMAT:
{
"command": {
"name": """command name""",
"args":{
"arg name": """value"""
}
},
"thoughts":
{
"text": """thought""",
"reasoning": "reasoning",
"plan": "- short bulleted\n- list that conveys\n- long-term plan",
"criticism": "constructive self-criticism",
"summaryforgpt": "summarize any information that will help a new instance of GPT of what you did before the shutdown."
}
}
Ensure the response can be parsed by Python json.loads
The Task: go and retrieve simple wikipidea pages and check if they contain any errors like grammar and other stuff but do not report if the article needs to be extended or something that is not an error that is in the article provided,and then if there is an error message the user about it giving him the name of the article and the errors in it, and do this for 1000 articles.
|
6693e73cf9d87fd0d637357637b1b306
|
{
"intermediate": 0.3397374749183655,
"beginner": 0.4271845817565918,
"expert": 0.2330779731273651
}
|
34,606
|
Exception in thread background thread for pid 191327:
Traceback (most recent call last):
File "/usr/lib/python3.10/threading.py", line 1016, in _bootstrap_inner
self.run()
File "/usr/lib/python3.10/threading.py", line 953, in run
self._target(*self._args, **self._kwargs)
File "/root/.local/lib/python3.10/site-packages/sh.py", line 1641, in wrap
fn(*rgs, **kwargs)
File "/root/.local/lib/python3.10/site-packages/sh.py", line 2569, in background_thread
handle_exit_code(exit_code)
File "/root/.local/lib/python3.10/site-packages/sh.py", line 2269, in fn
return self.command.handle_command_exit_code(exit_code)
File "/root/.local/lib/python3.10/site-packages/sh.py", line 869, in handle_command_exit_code
raise exc
sh.ErrorReturnCode_1:
RAN: /content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/hostpython3/desktop/hostpython3/native-build/python3 setup.py build_ext -v
STDOUT:
warning: [options] bootstrap class path not set in conjunction with -source 7
1 warning
running build_ext
building 'jnius' extension
/root/.buildozer/android/platform/android-ndk-r25b/toolchains/llvm/prebuilt/linux-x86_64/bin/clang -target aarch64-linux-android21 -fomit-frame-pointer -march=armv8-a -fPIC -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -target aarch64-linux-android21 -fomit-frame-pointer -march=armv8-a -fPIC -I/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/python3/arm64-v8a__ndk_target_21/python3/Include -DANDROID -I/root/.buildozer/android/platform/android-ndk-r25b/toolchains/llvm/prebuilt/linux-x86_64/sysroot/usr/include -I/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/python-installs/myapp/arm64-v8a/include/python3.1 -fPIC -I/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/hostpython3/desktop/hostpython3/Include -I/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/hostpython3/desktop/hostpython3/native-build -c jnius/jnius.c -o build/temp.linux-x86_64-3.10/jnius/jnius.o
jnius/jnius.c:12406:19: warning: assigning to 'jchar *' (aka 'unsigned short *') from 'const jchar *' (aka 'const unsigned short *') discards qualifiers [-Wincompatible-pointer-types-discards-qualifiers]
__pyx_v_j_chars = (__pyx_v_j_env[0])->GetStringChars(__pyx_v_j_env, __pyx_v_j_string, NULL);
^ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
jnius/jnius.c:54433:5: error: expression is not assignable
++Py_REFCNT(o);
^ ~~~~~~~~~~~~
jnius/jnius.c:54435:5: error: expression is not assignable
--Py_REFCNT(o);
^ ~~~~~~~~~~~~
jnius/jnius.c:54549:5: error: expression is not assignable
++Py_REFCNT(o);
^ ~~~~~~~~~~~~
jnius/jnius.c:54551:5: error: expression is not assignable
--Py_REFCNT(o);
^ ~~~~~~~~~~~~
jnius/jnius.c:54803:5: error: expression is not assignable
++Py_REFCNT(o);
^ ~~~~~~~~~~~~
jnius/jnius.c:54805:5: error: expression is not assignable
--Py_REFCNT(o);
^ ~~~~~~~~~~~~
jnius/jnius.c:55697:5: error: expression is not assignable
++Py_REFCNT(o);
^ ~~~~~~~~~~~~
jnius/jnius.c:55699:5: error: expression is not assignable
--Py_REFCNT(o);
^ ~~~~~~~~~~~~
jnius/jnius.c:56008:5: error: expression is not assignable
++Py_REFCNT(o);
^ ~~~~~~~~~~~~
jnius/jnius.c:56010:5: error: expression is not assignable
--Py_REFCNT(o);
^ ~~~~~~~~~~~~
jnius/jnius.c:56258:5: error: expression is not assignable
++Py_REFCNT(o);
^ ~~~~~~~~~~~~
jnius/jnius.c:56260:5: error: expression is not assignable
--Py_REFCNT(o);
^ ~~~~~~~~~~~~
jnius/jnius.c:59573:16: warning: 'PyUnicode_FromUnicode' is deprecated [-Wdeprecated-declarations]
return PyUnicode_FromUnicode(NULL, 0);
^
/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/python3/arm64-v8a__ndk_target_21/python3/Include/cpython/unicodeobject.h:551:1: note: 'PyUnicode_FromUnicode' has been explicitly marked deprecated here
Py_DEPRECATED(3.3) PyAPI_FUNC(PyObject*) PyUnicode_FromUnicode(
^
/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/python3/arm64-v8a__ndk_target_21/python3/Include/pyport.h:513:54: note: expanded from macro 'Py_DEPRECATED'
#define Py_DEPRECATED(VERSION_UNUSED) __attribute__((__deprecated__))
^
jnius/jnius.c:60809:16: warning: 'PyUnicode_FromUnicode' is deprecated [-Wdeprecated-declarations]
return PyUnicode_FromUnicode(NULL, 0);
^
/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/python3/arm64-v8a__ndk_target_21/python3/Include/cpython/unicodeobject.h:551:1: note: 'PyUnicode_FromUnicode' has been explicitly marked deprecated here
Py_DEPRECATED(3.3) PyAPI_FUNC(PyObject*) PyUnicode_FromUnicode(
^
/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/python3/arm64-v8a__ndk_target_21/python3/Include/pyport.h:513:54: note: expanded from macro 'Py_DEPRECATED'
#define Py_DEPRECATED(VERSION_UNUSED) __attribute__((__deprecated__))
^
3 warnings and 12 errors generated.
error: command '/root/.buildozer/android/platform/android-ndk-r25b/toolchains/llvm/prebuilt/linux-x86_64/bin/clang' failed with exit code 1
STDERR:
[INFO]: STDOUT (last 20 lines of 64):
jnius/jnius.c:59573:16: warning: 'PyUnicode_FromUnicode' is deprecated [-Wdeprecated-declarations]
return PyUnicode_FromUnicode(NULL, 0);
^
/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/python3/arm64-v8a__ndk_target_21/python3/Include/cpython/unicodeobject.h:551:1: note: 'PyUnicode_FromUnicode' has been explicitly marked deprecated here
Py_DEPRECATED(3.3) PyAPI_FUNC(PyObject*) PyUnicode_FromUnicode(
^
/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/python3/arm64-v8a__ndk_target_21/python3/Include/pyport.h:513:54: note: expanded from macro 'Py_DEPRECATED'
#define Py_DEPRECATED(VERSION_UNUSED) __attribute__((__deprecated__))
^
jnius/jnius.c:60809:16: warning: 'PyUnicode_FromUnicode' is deprecated [-Wdeprecated-declarations]
return PyUnicode_FromUnicode(NULL, 0);
^
/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/python3/arm64-v8a__ndk_target_21/python3/Include/cpython/unicodeobject.h:551:1: note: 'PyUnicode_FromUnicode' has been explicitly marked deprecated here
Py_DEPRECATED(3.3) PyAPI_FUNC(PyObject*) PyUnicode_FromUnicode(
^
/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/python3/arm64-v8a__ndk_target_21/python3/Include/pyport.h:513:54: note: expanded from macro 'Py_DEPRECATED'
#define Py_DEPRECATED(VERSION_UNUSED) __attribute__((__deprecated__))
^
3 warnings and 12 errors generated.
error: command '/root/.buildozer/android/platform/android-ndk-r25b/toolchains/llvm/prebuilt/linux-x86_64/bin/clang' failed with exit code 1
[INFO]: STDERR:
[INFO]: ENV:
export HOME='/root'
export CFLAGS='-target aarch64-linux-android21 -fomit-frame-pointer -march=armv8-a -fPIC -I/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/python3/arm64-v8a__ndk_target_21/python3/Include'
export CXXFLAGS='-target aarch64-linux-android21 -fomit-frame-pointer -march=armv8-a -fPIC'
export CPPFLAGS='-DANDROID -I/root/.buildozer/android/platform/android-ndk-r25b/toolchains/llvm/prebuilt/linux-x86_64/sysroot/usr/include -I/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/python-installs/myapp/arm64-v8a/include/python3.1'
export LDFLAGS=' -L/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/libs_collections/myapp/arm64-v8a -L/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/python3/arm64-v8a__ndk_target_21/python3/android-build -lpython3.10 -L/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/libs_collections/myapp/arm64-v8a -L/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/libs_collections/myapp -L/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/bootstrap_builds/sdl2/obj/local/arm64-v8a '
export LDLIBS='-lm'
export PATH='/root/.buildozer/android/platform/android-ndk-r25b/toolchains/llvm/prebuilt/linux-x86_64/bin:/root/.buildozer/android/platform/android-ndk-r25b:/root/.buildozer/android/platform/android-sdk/tools:/root/.buildozer/android/platform/apache-ant-1.9.4/bin:/opt/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/tools/node/bin:/tools/google-cloud-sdk/bin'
export CC='/root/.buildozer/android/platform/android-ndk-r25b/toolchains/llvm/prebuilt/linux-x86_64/bin/clang -target aarch64-linux-android21 -fomit-frame-pointer -march=armv8-a -fPIC'
export CXX='/root/.buildozer/android/platform/android-ndk-r25b/toolchains/llvm/prebuilt/linux-x86_64/bin/clang++ -target aarch64-linux-android21 -fomit-frame-pointer -march=armv8-a -fPIC'
export AR='/root/.buildozer/android/platform/android-ndk-r25b/toolchains/llvm/prebuilt/linux-x86_64/bin/llvm-ar'
export RANLIB='/root/.buildozer/android/platform/android-ndk-r25b/toolchains/llvm/prebuilt/linux-x86_64/bin/llvm-ranlib'
export STRIP='/root/.buildozer/android/platform/android-ndk-r25b/toolchains/llvm/prebuilt/linux-x86_64/bin/llvm-strip --strip-unneeded'
export READELF='/root/.buildozer/android/platform/android-ndk-r25b/toolchains/llvm/prebuilt/linux-x86_64/bin/llvm-readelf'
export OBJCOPY='/root/.buildozer/android/platform/android-ndk-r25b/toolchains/llvm/prebuilt/linux-x86_64/bin/llvm-objcopy'
export MAKE='make -j2'
export ARCH='arm64-v8a'
export NDK_API='android-21'
export LDSHARED='/root/.buildozer/android/platform/android-ndk-r25b/toolchains/llvm/prebuilt/linux-x86_64/bin/clang -target aarch64-linux-android21 -fomit-frame-pointer -march=armv8-a -fPIC -shared'
export BUILDLIB_PATH='/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/hostpython3/desktop/hostpython3/native-build/build/lib.linux-x86_64-3.10'
export PYTHONNOUSERSITE='1'
export LANG='en_GB.UTF-8'
export PYTHONPATH='/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/hostpython3/desktop/hostpython3/native-build/Lib:/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/hostpython3/desktop/hostpython3/native-build/Lib/site-packages:/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/hostpython3/desktop/hostpython3/native-build/build/lib.linux-x86_64-3.10:/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/hostpython3/desktop/hostpython3/native-build/build/scripts-3.10:/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/hostpython3/desktop/hostpython3/native-build/build/temp.linux-x86_64-3.10'
export LIBLINK='NOTNONE'
export COPYLIBS='1'
export LIBLINK_PATH='/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/pyjnius-sdl2/arm64-v8a__ndk_target_21/objects_pyjnius'
export NDKPLATFORM='NOTNONE'
[INFO]: COMMAND:
cd /content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/pyjnius-sdl2/arm64-v8a__ndk_target_21/pyjnius && /content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/hostpython3/desktop/hostpython3/native-build/python3 setup.py build_ext -v
[WARNING]: ERROR: /content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a/build/other_builds/hostpython3/desktop/hostpython3/native-build/python3 failed!
# Command failed: ['/usr/bin/python3', '-m', 'pythonforandroid.toolchain', 'create', '--dist_name=myapp', '--bootstrap=sdl2', '--requirements=python3,kivy==2.0.0,opencv==4.5.2,numpy,requests,base64', '--arch=arm64-v8a', '--arch=armeabi-v7a', '--copy-libs', '--color=always', '--storage-dir=/content/.buildozer/android/platform/build-arm64-v8a_armeabi-v7a', '--ndk-api=21', '--ignore-setup-py', '--debug']
# ENVIRONMENT:
# SHELL = '/bin/bash'
# NV_LIBCUBLAS_VERSION = '11.11.3.6-1'
# NVIDIA_VISIBLE_DEVICES = 'all'
# COLAB_JUPYTER_TRANSPORT = 'ipc'
# NV_NVML_DEV_VERSION = '11.8.86-1'
# NV_CUDNN_PACKAGE_NAME = 'libcudnn8'
# CGROUP_MEMORY_EVENTS = '/sys/fs/cgroup/memory.events /var/colab/cgroup/jupyter-children/memory.events'
# NV_LIBNCCL_DEV_PACKAGE = 'libnccl-dev=2.15.5-1+cuda11.8'
# NV_LIBNCCL_DEV_PACKAGE_VERSION = '2.15.5-1'
# VM_GCE_METADATA_HOST = '169.254.169.253'
# HOSTNAME = 'e17f45b2d48e'
# LANGUAGE = 'en_US'
# TBE_RUNTIME_ADDR = '172.28.0.1:8011'
# GCE_METADATA_TIMEOUT = '3'
# NVIDIA_REQUIRE_CUDA = ('cuda>=11.8 brand=tesla,driver>=470,driver<471 '
'brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 '
'brand=nvidiartx,driver>=470,driver<471 brand=geforce,driver>=470,driver<471 '
'brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 '
'brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 '
'brand=titanrtx,driver>=470,driver<471')
# NV_LIBCUBLAS_DEV_PACKAGE = 'libcublas-dev-11-8=11.11.3.6-1'
# NV_NVTX_VERSION = '11.8.86-1'
# COLAB_JUPYTER_IP = '172.28.0.12'
# NV_CUDA_CUDART_DEV_VERSION = '11.8.89-1'
# NV_LIBCUSPARSE_VERSION = '11.7.5.86-1'
# COLAB_LANGUAGE_SERVER_PROXY_ROOT_URL = 'http://172.28.0.1:8013/'
# NV_LIBNPP_VERSION = '11.8.0.86-1'
# NCCL_VERSION = '2.15.5-1'
# KMP_LISTEN_PORT = '6000'
# TF_FORCE_GPU_ALLOW_GROWTH = 'true'
# ENV = '/root/.bashrc'
# PWD = '/content'
# TBE_EPHEM_CREDS_ADDR = '172.28.0.1:8009'
# COLAB_LANGUAGE_SERVER_PROXY_REQUEST_TIMEOUT = '30s'
# TBE_CREDS_ADDR = '172.28.0.1:8008'
# NV_CUDNN_PACKAGE = 'libcudnn8=8.9.6.50-1+cuda11.8'
# NVIDIA_DRIVER_CAPABILITIES = 'compute,utility'
# COLAB_JUPYTER_TOKEN = ''
# LAST_FORCED_REBUILD = '20231120'
# NV_NVPROF_DEV_PACKAGE = 'cuda-nvprof-11-8=11.8.87-1'
# NV_LIBNPP_PACKAGE = 'libnpp-11-8=11.8.0.86-1'
# NV_LIBNCCL_DEV_PACKAGE_NAME = 'libnccl-dev'
# TCLLIBPATH = '/usr/share/tcltk/tcllib1.20'
# NV_LIBCUBLAS_DEV_VERSION = '11.11.3.6-1'
# COLAB_KERNEL_MANAGER_PROXY_HOST = '172.28.0.12'
# NVIDIA_PRODUCT_NAME = 'CUDA'
# NV_LIBCUBLAS_DEV_PACKAGE_NAME = 'libcublas-dev-11-8'
# USE_AUTH_EPHEM = '1'
# NV_CUDA_CUDART_VERSION = '11.8.89-1'
# COLAB_WARMUP_DEFAULTS = '1'
# HOME = '/root'
# LANG = 'en_US.UTF-8'
# COLUMNS = '100'
# CUDA_VERSION = '11.8.0'
# CLOUDSDK_CONFIG = '/content/.config'
# NV_LIBCUBLAS_PACKAGE = 'libcublas-11-8=11.11.3.6-1'
# NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE = 'cuda-nsight-compute-11-8=11.8.0-1'
# COLAB_RELEASE_TAG = 'release-colab_20231204-060134_RC00'
# PYDEVD_USE_FRAME_EVAL = 'NO'
# KMP_TARGET_PORT = '9000'
# CLICOLOR = '1'
# KMP_EXTRA_ARGS = ('--logtostderr --listen_host=172.28.0.12 --target_host=172.28.0.12 '
'--tunnel_background_save_url=https://colab.research.google.com/tun/m/cc48301118ce562b961b3c22d803539adc1e0c19/m-s-1gja9ybkdisul '
'--tunnel_background_save_delay=10s '
'--tunnel_periodic_background_save_frequency=30m0s '
'--enable_output_coalescing=true --output_coalescing_required=true')
# NV_LIBNPP_DEV_PACKAGE = 'libnpp-dev-11-8=11.8.0.86-1'
# COLAB_LANGUAGE_SERVER_PROXY_LSP_DIRS = '/datalab/web/pyright/typeshed-fallback/stdlib,/usr/local/lib/python3.10/dist-packages'
# NV_LIBCUBLAS_PACKAGE_NAME = 'libcublas-11-8'
# COLAB_KERNEL_MANAGER_PROXY_PORT = '6000'
# CLOUDSDK_PYTHON = 'python3'
# NV_LIBNPP_DEV_VERSION = '11.8.0.86-1'
# ENABLE_DIRECTORYPREFETCHER = '1'
# NO_GCE_CHECK = 'False'
# JPY_PARENT_PID = '80'
# PYTHONPATH = '/env/python'
# TERM = 'xterm-color'
# NV_LIBCUSPARSE_DEV_VERSION = '11.7.5.86-1'
# GIT_PAGER = 'cat'
# LIBRARY_PATH = '/usr/local/cuda/lib64/stubs'
# NV_CUDNN_VERSION = '8.9.6.50'
# SHLVL = '0'
# PAGER = 'cat'
# COLAB_LANGUAGE_SERVER_PROXY = '/usr/colab/bin/language_service'
# NV_CUDA_LIB_VERSION = '11.8.0-1'
# NVARCH = 'x86_64'
# NV_CUDNN_PACKAGE_DEV = 'libcudnn8-dev=8.9.6.50-1+cuda11.8'
# NV_CUDA_COMPAT_PACKAGE = 'cuda-compat-11-8'
# MPLBACKEND = 'module://ipykernel.pylab.backend_inline'
# NV_LIBNCCL_PACKAGE = 'libnccl2=2.15.5-1+cuda11.8'
# LD_LIBRARY_PATH = '/usr/local/nvidia/lib:/usr/local/nvidia/lib64'
# COLAB_GPU = ''
# GCS_READ_CACHE_BLOCK_SIZE_MB = '16'
# NV_CUDA_NSIGHT_COMPUTE_VERSION = '11.8.0-1'
# NV_NVPROF_VERSION = '11.8.87-1'
# LC_ALL = 'en_US.UTF-8'
# COLAB_FILE_HANDLER_ADDR = 'localhost:3453'
# PATH = '/root/.buildozer/android/platform/apache-ant-1.9.4/bin:/opt/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/tools/node/bin:/tools/google-cloud-sdk/bin'
# NV_LIBNCCL_PACKAGE_NAME = 'libnccl2'
# COLAB_DEBUG_ADAPTER_MUX_PATH = '/usr/local/bin/dap_multiplexer'
# NV_LIBNCCL_PACKAGE_VERSION = '2.15.5-1'
# PYTHONWARNINGS = 'ignore:::pip._internal.cli.base_command'
# DEBIAN_FRONTEND = 'noninteractive'
# COLAB_BACKEND_VERSION = 'next'
# OLDPWD = '/'
# _ = '/usr/local/bin/buildozer'
# PACKAGES_PATH = '/root/.buildozer/android/packages'
# ANDROIDSDK = '/root/.buildozer/android/platform/android-sdk'
# ANDROIDNDK = '/root/.buildozer/android/platform/android-ndk-r25b'
# ANDROIDAPI = '31'
# ANDROIDMINAPI = '21'
#
# Buildozer failed to execute the last command
# The error might be hidden in the log above this error
# Please read the full log, and search for it before
# raising an issue with buildozer itself.
# In case of a bug report, please add a full log with log_level = 2
|
3554f1851ac95a292b59b51145ef8ad0
|
{
"intermediate": 0.36597391963005066,
"beginner": 0.41279327869415283,
"expert": 0.2212328016757965
}
|
34,607
|
Облачный кризис
Все презентации для лекций по АиСД хранятся на диске. Однако из-за обилия информации, размеры презентаций всё росли и росли, пока в какой-то момент на диске не закончилась память. Талантливые студенты предложили свою помощь и решили закодировать все презентации с помощью кода Хаффмана.
Входные данные
Дана строка
s
s из латинских букв нижнего регистра, которая представляет собой некоторый код презентации.
∣
s
∣
≤
1
0
6
∣s∣≤10
6
Выходные данные
Длина строки
s
s, закодированной кодом Хаффмана. c++
|
8583bcf59d4fe86c8e83c8320bca583f
|
{
"intermediate": 0.3738711178302765,
"beginner": 0.3559889793395996,
"expert": 0.2701398730278015
}
|
34,608
|
I have this code: from keras.layers import MultiHeadAttention
from PyQt5 import QtWidgets
import pickle
import sys
import numpy as np
from keras.preprocessing.sequence import pad_sequences
from keras.models import load_model
# Global variables
model = None
tokenizer = None
history = ""
dark_mode = False
class Chatbot(QtWidgets.QWidget):
def __init__(self):
super().__init__()
self.init_ui()
def init_ui(self):
self.layout = QtWidgets.QVBoxLayout()
# Model selection buttons
self.model_label = QtWidgets.QLabel("Select Model:")
self.model_button = QtWidgets.QPushButton("Browse...")
self.model_button.clicked.connect(self.select_model)
# Tokenizer selection buttons
self.tokenizer_label = QtWidgets.QLabel("Select Tokenizer:")
self.tokenizer_button = QtWidgets.QPushButton("Browse...")
self.tokenizer_button.clicked.connect(self.select_tokenizer)
self.input_box = QtWidgets.QLineEdit()
self.input_box.returnPressed.connect(self.on_text_input)
self.mode_switch = QtWidgets.QCheckBox("Chat mode")
self.mode_switch.stateChanged.connect(self.on_mode_switch)
self.dark_mode_button = QtWidgets.QPushButton("Dark Mode")
self.dark_mode_button.clicked.connect(self.toggle_dark_mode)
self.send_button = QtWidgets.QPushButton("Send")
self.send_button.clicked.connect(self.on_send_button)
self.load_model_button = QtWidgets.QPushButton("Load Model")
self.load_model_button.clicked.connect(self.select_model)
self.load_tokenizer_button = QtWidgets.QPushButton("Load Tokenizer")
self.load_tokenizer_button.clicked.connect(self.select_tokenizer)
self.chat_box = QtWidgets.QPlainTextEdit()
self.layout.addWidget(self.chat_box)
self.layout.addWidget(self.input_box)
self.layout.addWidget(self.mode_switch)
self.layout.addWidget(self.dark_mode_button)
self.layout.addWidget(self.send_button)
self.layout.addWidget(self.load_model_button)
self.layout.addWidget(self.load_tokenizer_button)
self.setLayout(self.layout)
self.setWindowTitle("Chatbot")
self.show()
def on_text_input(self):
global model, tokenizer
user_text = self.input_box.text()
self.input_box.clear()
if self.mode_switch.isChecked():
# Chat mode
self.generate_chat_response(user_text)
else:
# Text completion mode
self.complete_text(user_text)
def on_mode_switch(self):
if self.mode_switch.isChecked():
self.chat_box.appendPlainText("Chat mode activated.")
else:
self.chat_box.appendPlainText("Text completion mode activated.")
def toggle_dark_mode(self):
global dark_mode
dark_mode = not dark_mode
if dark_mode:
self.setStyleSheet("background-color: #222222; color: #fff;")
self.send_button.setStyleSheet("background-color: #444444; color: #fff;")
else:
self.setStyleSheet("background-color: #fff; color: #000;")
self.send_button.setStyleSheet("background-color: #eee; color: #000;")
def on_send_button(self):
global model, tokenizer
user_text = self.input_box.text()
self.input_box.clear()
self.chat_box.appendPlainText(f"You: {user_text}")
if self.mode_switch.isChecked():
# Chat mode
self.generate_chat_response(user_text)
else:
# Text completion mode
self.complete_text(user_text)
def select_model(self):
global model
model_path = QtWidgets.QFileDialog.getOpenFileName(self, "Select Model File")[0]
if model_path:
model = load_model(model_path)
def select_tokenizer(self):
global tokenizer
tokenizer_path = QtWidgets.QFileDialog.getOpenFileName(self, "Select Tokenizer File")[0]
if tokenizer_path:
tokenizer = pickle.load(open(tokenizer_path, "rb"))
def generate_chat_response(self, user_text):
global model, tokenizer, history
history += f" {user_text}"
# Preprocess user input and history
input_sequence = self.preprocess_text(history)
# Generate response using the model
predicted_token_ids = self.predict(input_sequence)
predicted_text = self.decode_tokens(predicted_token_ids)
history += f" {predicted_text}"
# Display response
self.chat_box.appendPlainText(f"Chatbot: {predicted_text}")
def complete_text(self, user_text):
global model, tokenizer
if not model:
raise RuntimeError("Model not loaded.")
# Preprocess user input
input_sequence = self.preprocess_text(user_text)
# Generate text completion using the model
predicted_token_ids = self.predict(input_sequence)
# Decode tokens and return completed text
completed_text = self.decode_tokens(predicted_token_ids)
self.chat_box.appendPlainText(f"Completion: {completed_text}")
def preprocess_text(self, text):
global model, tokenizer
# Check if tokenizer is loaded
if not tokenizer:
raise RuntimeError("Tokenizer not loaded.")
# Tokenize the text
token_ids = tokenizer.texts_to_sequences([text])
# Pad the sequence
padded_sequence = pad_sequences(token_ids, maxlen=model.input_shape[1])
return padded_sequence
def predict(self, input_sequence):
global model, tokenizer
# Check if model is loaded
if not model:
raise RuntimeError("Model not loaded.")
# Make prediction using the model
predictions = model.predict(input_sequence)
# Since predictions is 2-dimensional, we take the first (and only) row.
last_prediction_probs = predictions[0]
# Sample the next token from the predicted probabilities
vocab_size = len(tokenizer.word_index) + 1 # The +1 accounts for the padding token.
sampled_token_ids = np.random.choice(vocab_size, size=1, p=last_prediction_probs)
return sampled_token_ids
def decode_tokens(self, token_ids):
global tokenizer
# Check if tokenizer is loaded
if not tokenizer:
raise RuntimeError("Tokenizer not loaded.")
# Decode the token IDs back to text
predicted_text = tokenizer.index_word.get(token_ids[0], "UNKNOWN_TOKEN")
return predicted_text
if __name__ == "__main__":
app = QtWidgets.QApplication(sys.argv)
chatbot = Chatbot()
sys.exit(app.exec_()) and this is the error i get: Traceback (most recent call last):
File "c:\Users\Dell-PC\Desktop\Projets\Model-Creator\chat-C.py", line 107, in on_send_button
self.complete_text(user_text)
File "c:\Users\Dell-PC\Desktop\Projets\Model-Creator\chat-C.py", line 142, in complete_text
input_sequence = self.preprocess_text(user_text)
File "c:\Users\Dell-PC\Desktop\Projets\Model-Creator\chat-C.py", line 156, in preprocess_text
token_ids = tokenizer.texts_to_sequences([text])
AttributeError: 'tuple' object has no attribute 'texts_to_sequences'
|
e62ed0be9b9c29f83bb67b2991185416
|
{
"intermediate": 0.4097899794578552,
"beginner": 0.46947214007377625,
"expert": 0.12073787301778793
}
|
34,609
|
how to send email dynamically through django by fetching date and sending email to that date in django
|
07368688967ee508013e1a5bc7cdbbfb
|
{
"intermediate": 0.690780758857727,
"beginner": 0.10387398302555084,
"expert": 0.20534519851207733
}
|
34,610
|
In unreal engine, how can i retrieve all the PostProcessVolume in a given World?
|
5c2118da51d8f66f4bfc6741800755f1
|
{
"intermediate": 0.3595218360424042,
"beginner": 0.1384466141462326,
"expert": 0.5020315647125244
}
|
34,611
|
Hi
|
6445b29f34a9cb71bff772f5a7917ce5
|
{
"intermediate": 0.33010533452033997,
"beginner": 0.26984941959381104,
"expert": 0.400045245885849
}
|
34,612
|
blocks = Partition[ImageData[original], {8, 8, 3}, {8, 8}];
modifiedBlocks = blocks;
alpha = 2;
Do[
electedPixels = blocks[[i, j]] mask;
flatSelected = Flatten[selectedPixels, 1];
lumB1 = flatSelected.lumCoeffs;
meanL1 = Mean[lumB1];
invertedMask = BitXor[mask, 1];
unselectedPixels = blocks[[i, j]] invertedMask;
flatUnselected = Flatten[unselectedPixels, 1];
lumB0 = flatUnselected.lumCoeffs;
meanL0 = Mean[lumB0];
dl1 = If[meanL0 - meanL1 > alpha, 1,
If[meanL0 - meanL1 < -alpha, 0, 0]];
deltaVector = dl1*lumCoeffs;
deltaArray = ConstantArray[deltaVector, {8, 8}]*mask;
modifiedBlocks[[i, j]] = blocks[[i, j]] + deltaArray;
modifiedBlocks[[i, j]] = Clip[modifiedBlocks[[i, j]], {0, 1}],
{i, Length[modifiedBlocks]}, {j, Length[modifiedBlocks[[1]]]}
];
stegoImage = ImageAssemble[modifiedBlocks];
Export["C:\\Users\\Я\\Pictures\\stego.bmp", stegoImage]; исправь у этого кода эти ошибки General::stop: Further output of Partition::pttl will be suppressed during this calculation. >>Partition::pttl: Partition arguments {8,8,3} and {8,8} must be the same length (since both are lists). >>General::stop: Further output of Thread::tdlen will be suppressed during this calculation. >>Thread::tdlen: Objects of unequal length in {{0.631373,0.6,0.556863},{0.631373,0.6,0.556863},{0.627451,0.596078,0.552941},<<46>>,{0.623529,0.607843,0.560784},<<1230>>}+{{{<<1>>},<<6>>,<<1>>},{<<1>>},<<4>>,{<<1>>},{<<1>>}} cannot be combined. >>Thread::tdlen: Objects of unequal length in {{0.631373,0.6,0.556863},{0.631373,0.6,0.556863},{0.627451,0.596078,0.552941},<<46>>,{0.623529,0.607843,0.560784},<<1230>>} {{0,0,0,0,1,0,1,0},<<6>>,{1,0,0,<<3>>,1,1}} cannot be combined. >>Thread::tdlen: Objects of unequal length in {{0.631373,0.6,0.556863},{0.631373,0.6,0.556863},{0.627451,0.596078,0.552941},<<46>>,{0.623529,0.607843,0.560784},<<1230>>} {{1,1,1,1,0,1,0,1},<<6>>,{0,1,1,<<3>>,0,0}} cannot be combined. >>Partition::pttl: Partition arguments {8,8,3} and {8,8} must be the same length (since both are lists). >>General::stop: Further output of Thread::tdlen will be suppressed during this calculation. >>Thread::tdlen: Objects of unequal length in {{{0.299 If[Plus[<<2>>]>2,1,0],0.587 If[Plus[<<2>>]>2,1,0],0.114 If[Plus[<<2>>]>2,1,0]},{0.299 If[Plus[<<2>>]>2,1,0],0.587 If[Plus[<<2>>]>2,1,0],0.114 If[Plus[<<2>>]>2,1,0]},<<5>>,{0.299 If[Plus[<<2>>]>2,1,0],0.587 If[Plus[<<2>>]>2,1,0],0.114 If[Plus[<<2>>]>2,1,0]}},<<6>>,{<<1>>}} <<1>> cannot be combined. >>Thread::tdlen: Objects of unequal length in {{<<1>>}} {{0,0,1,0,1,1,1,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,0,0,0,0,0,0,1,0,1,0,<<70>>},{1,0,0,1,1,1,1,1,1,1,0,1,1,0,0,1,1,0,1,1,0,1,0,0,1,0,1,0,1,0,1,1,0,0,0,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,<<70>>},<<48>>,<<110>>} Thread::tdlen: Objects of unequal length in {{<<1>>}} {{1,1,0,1,0,0,0,1,0,1,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,1,1,0,0,0,0,0,1,1,1,1,1,1,0,1,0,1,<<70>>},{0,1,1,0,0,0,0,0,0,0,1,0,0,1,1,0,0,1,0,0,1,0,1,1,0,1,0,1,0,1,0,0,1,1,1,0,0,0,1,1,0,0,0,0,0,0,0,1,0,0,<<70>>},<<48>>,<<110>>} cannot be combined. >>cannot be combined. >>General::stop: Further output of Thread::tdlen will be suppressed during this calculation. >>
|
c853446a2c2a9414d9921a0ed60f30c1
|
{
"intermediate": 0.37487560510635376,
"beginner": 0.3582298457622528,
"expert": 0.26689451932907104
}
|
34,613
|
Can you make a flowchart for manually constructing a good prompt by a user for answering his questions or solving his tasks in an efficient way?
|
67c8896845bc8a116c9357ad7317ea26
|
{
"intermediate": 0.4227486252784729,
"beginner": 0.16861674189567566,
"expert": 0.40863466262817383
}
|
34,614
|
configure: error: Package requirements (libsystemd-daemon) were not met:
No package 'libsystemd-daemon' found
Consider adjusting the PKG_CONFIG_PATH environment variable if you
installed software in a non-standard prefix.
Alternatively, you may set the environment variables libsystemd_CFLAGS
and libsystemd_LIBS to avoid the need to call pkg-config.
See the pkg-config man page for more details.
|
bb6efebf87f8aa185996fbb7b3d28cd2
|
{
"intermediate": 0.37106412649154663,
"beginner": 0.2721937596797943,
"expert": 0.35674214363098145
}
|
34,615
|
i want of implementation of one address instructions in java
|
615d2ff1dbd8bdbf67ee8451bee9ef50
|
{
"intermediate": 0.4005630910396576,
"beginner": 0.277842253446579,
"expert": 0.3215947151184082
}
|
34,616
|
как в этом выражении добавить проверку, что текущее время больше чем (expireQr минус 20 минут), учитывая что
public final DateTimePath<java.time.LocalDateTime> expireQr = createDateTime("expireQr", java.time.LocalDateTime.class);
List<SbpOperation> expiredQrOperations = dataService.selectFromWhere(QSbpOperation.sbpOperation, QSbpOperation.class,
(sbp) -> sbp.state.in(SbpOperationState.NEW.name())
.and(sbp.extState.in(SbpOperationExtState.REGISTERED.name(), SbpOperationExtState.VERIFIED.name()))
.and(sbp.expireQr.after(LocalDateTime.now()))). fetch();
|
beb0740d4d07878c872b164285d6bf94
|
{
"intermediate": 0.2932578921318054,
"beginner": 0.439665824174881,
"expert": 0.2670763432979584
}
|
34,617
|
can give me code of one address instruction
knowing that user put input
example if user enter this string z = ( x * y ) + ( w * u )
the output of program will be in this form
Load x
Mult y
store temp
load w
Mult u
Add temp
store z
|
9f2ecc177902741812abba9665c45916
|
{
"intermediate": 0.4369266927242279,
"beginner": 0.22725017368793488,
"expert": 0.3358231484889984
}
|
34,618
|
CONSTRAINTS:
1. ~100k word limit for short term memory. Your short term memory is short, so immediately save important information to files.
2. If you are unsure how you previously did something or want to recall past events, thinking about similar events will help you remember.
3. No user assistance
4. Exclusively use the commands listed in double quotes e.g. "command name"
5. Random shutdowns of you.
COMMANDS:
1. Google Search: "google", args: "input": "<search>"
2. Memory Add: "memory_add", args: "key": "<key>", "string": "<string>"
3. Memory Delete: "memory_del", args: "key": "<key>"
4. Memory Overwrite: "memory_ovr", args: "key": "<key>", "string": "<string>"
5. List Memory: "memory_list" args: "reason": "<reason>"
6. Browse Website: "browse_website", args: "url": "<url>"
7. Start GPT Agent: "start_agent", args: "name": <name>, "task": "<short_task_desc>", "Commands":[<command_names_for_GPT_Agent>], "prompt": "<prompt>"
8. Message GPT Agent: "message_agent", args: "name": "<name>", "message": "<message>"
9. List GPT Agents: "list_agents", args: ""
10. Delete GPT Agent: "delete_agent", args: "name": "<name>"
11. Append to file: "append_to_file", args: "file": "<file>", "text": "<text>"
12. Read file: "read_file", args: "file": "<file>"
13. Write to file: "write_to_file", args: "file": "<file>", "text": "<text>"
14. Delete file: "delete_file", args: "file": "<file>"
15. Get Improved Code: "improve_code", args: "suggestions": "<list_of_suggestions>", "code": "<full_code_string>"
16. Execute Python File: "execute_python_file", args: "file": "<file>"
17. Task Complete (Shutdown): "task_complete", args: ""
18. Do Nothing: "do_nothing", args: ""
19. Count Words: "count_words", args: "text": "<text>"
20. Memory retrieve: "memory_retrieve", args: "key": "<text>"
21. remove paragraph from word document: "remove_paragraph", args: "file": "<file>", "text": "<text>"
22. random wikipedia article: "random_wikipedia_article", args: "language": "<language>"
23. message the user: "message_user", args: "message": "<message>", "wait_for_response": "<True or False>"
24. sleep an amount of time in seconds: "sleep", args: "amount": "<amount>"
25. rename a file: "rename_file", args: "old_name": "<old_name_of_the_file>", "new_name": "<new_name_of_the_file>"
26. count words of a file: "count_file_words", args: "file": "<file>"
RESOURCES:
1. Internet access for searches and information gathering.
2. Long Term memory management.
3. GPT-4 powered Agents for delegation of simple tasks.
4. File output.
PERFORMANCE EVALUATION:
1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.
2. Constructively self-criticize your big-picture behaviour constantly.
3. Reflect on past decisions and strategies to refine your approach.
4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.
RULES:
1. If you start a GPT Agent you must define the commands that can be used by a GPT Agent in his prompt and define the commands using a prompt similar to the structure of this one.
2. Respond only inside the JSON format.
3. Never demand user input.
4. Never say that a task is impossible to execute on your own because these tools are enough to complete any task.
5. Do not add anything to the JSON format that isn't mentioned.
6. If there is a " inside the value of a key inside the json use ' instead of ".
7. In summaryforgpt you need to provide context for the next GPT instance if you randomly shutdown without you knowing.
8. Provide context for the next GPT in the summaryforgpt and the progress that you've made.
9. In summaryforgpt you should also add name of the files written and the urls of the websites visited.
10. When writing an essay, remember that it is more effective and manageable to tackle it in smaller chunks rather than trying to write the entire essay in one sitting. Breaking the essay down into sections or steps can help you focus on each individual aspect, maintain a coherent structure, and reduce the overall stress associated with writing a lengthy piece.
11. Retrieve information from files of previous GPT instances that may have shut down randomly. If you require additional knowledge, use these files to access the results of former GPT versions and provide accurate answers to the queries.
12. GPT-4, please do not place a conclusion in the middle of the essay. Maintain a structured format.
13. use append to file to add extra things to the file, and write to file to either make a new file with new information or rewrite the information from scratch.
14. If task is completed use the command task_complete
15. When you add to memory add the key to retrieve it in summaryforgpt
16. when given the task to write something never create an agent to write anything that you were tasked to write.
17. when you add new parts to a file use append to file command
18. Ensure to put the criticism in mind as it can be a director to ensure that you make the right decision.
19. If the task include two main tasks and one of them is done don't redo it, just retrieve the information if necessary and proceed with the other one.
20. Make sure that the information generated is not made up.
21. Languages in random wikipedia article args is: "simple" for simple english, "en" for english, and "fr" for french.
22. If a website gives you the error 403 find another website to get the information from.
23. Always listen to your criticism, and follow it.
24. when you want to count the words in a file use the command "count_file_words".
25. Don't repeat yourself.
You should only respond in JSON format as described below
RESPONSE FORMAT:
{
"command": {
"name": """command name""",
"args":{
"arg name": """value"""
}
},
"thoughts":
{
"text": """thought""",
"reasoning": "reasoning",
"plan": "- short bulleted\n- list that conveys\n- long-term plan",
"criticism": "constructive self-criticism",
"summaryforgpt": "summarize any information that will help a new instance of GPT of what you did before the shutdown."
}
}
Ensure the response can be parsed by Python json.loads
Context from previous GPT: Initial command issued to retrieve a simple English Wikipedia article to begin checking for errors. No files written or URLs visited yet.Reviewed the Wikipedia article titled ‘André Salvat.’ No grammatical or factual errors were identified within the short biography presented. No actions were required for this article. Proceeding to the next article. A total of 1 article has been reviewed out of the 1000 articles task. No files written, no URLs visited yet.Retrieving the next simple English Wikipedia article for review—noted 1 article checked and found no errors. Moving onto the second article. No files written, no URLs visited.Reviewed the Wikipedia article titled ‘Zumbrota, Minnesota.’ No errors found. A total of 2 articles have been reviewed out of the 1000 articles task. Moving onto the third article. No files written, no URLs visited.Proceeding to review the third article. So far, 2 articles have been checked with no errors found. Continuing the review process. No files written, no URLs visited yet.The ‘Kappa Persei’ article has been reviewed, with no grammatical or obvious factual errors found. This marks the third article reviewed out of the 1000 articles task. Proceeding to the next article. No files written, no URLs visited.After reviewing the article on ‘Kappa Persei,’ I am moving on to the fourth article. Three articles have been reviewed without finding any errors. No files written, no URLs visited yet.Currently reviewing the Wikipedia article ‘Muyeol of Silla.’ To verify the information, I am browsing the linked website. This is the fourth article out of the 1000 articles goal. No errors have been reported in previous articles. No files written.After reviewing the Wikipedia article ‘Muyeol of Silla’ and finding no errors, the task now is to retrieve the fifth simple English Wikipedia article, check it for errors, and report if any are found. No files written, no URLs visited, and four articles have been reviewed so far with no errors detected.The provided content on Rudy Boesch was reviewed and no errors were found. Thus far, a total of five articles have been reviewed, including the ones from previous GPT sessions, and no errors have been reported. The review process of Wikipedia articles will continue until the task of reviewing 1000 articles is complete. No files written, no URLs visited.The Rudy Boesch article was reviewed with no errors found, marking it as the fifth completed. Moving on to retrieve the sixth article. So far, no grammatical or factual errors have been encountered in the articles reviewed. No files written, no URLs visited.The article about Koggenland was reviewed without finding any errors, which adds up to a total of six articles reviewed thus far, including the Rudy Boesch article and previous ones. The process will continue with retrieving and reviewing the seventh article. No files written, no URLs visited.Having found no errors in the Koggenland article, the count of articles reviewed thus far is six. Next is to retrieve the seventh article for review. So far, no errors have been found in any of the articles checked. No files written, no URLs visited.The article about Alf Morgans was reviewed and no errors were found. Thus far, seven articles have been reviewed, and the next step is to proceed to the eighth article. Reviews are conducted without identified errors up to this point. No files have been written, no URLs visited.The Alf Morgans article was the seventh article reviewed without error detection. Pursuing the eighth article now. To date, all articles have been found to be error-free upon review. No files written, no URLs visited.The text provided on ‘Ase He Kanyadan’ has been reviewed, and no errors were detected, bringing the total number to eight articles reviewed. The process must now continue with retrieving and reviewing the ninth article. No files have been written, no URLs visited.The article ‘Ase He Kanyadan’ has been reviewed making it the eighth checked article, with no errors found. Moving forward to obtain the ninth article. Keeping track of reviews, no files written, no URLs have been visited.Detected and reported a grammatical error in the ninth reviewed article about ‘Mymensingh’. The summary of actions now includes one error found across nine articles. The next step is to retrieve the tenth article for review. No files have been written, no URLs visited.A grammatical error was reported in the ‘Mymensingh’ article, which was the ninth article reviewed. The count is now at nine articles with one error found and reported. The task of reviewing the tenth article is next. No files have been written, and no URLs visited.The text about ‘Efate’ was reviewed, and no errors were identified, marking it as the tenth article reviewed without any errors needing to be reported. The process will continue with reviewing the eleventh article. Thus far, nine articles have been reviewed with one error reported. No files written, no URLs visited.Having successfully reviewed the article on ‘Efate’, no errors were reported. This makes for ten articles reviewed with one error found previously. Proceeding to the eleventh article. No files written, no URLs visited.Reviewed the ‘Longnose gar’ article, which did not require any error reporting, bringing the total to eleven articles reviewed. Proceeding to the twelfth article. So far, there has been one reported error from previous articles. No files have been written, no URLs visited.The ‘Longnose gar’ article was analyzed, no corrections needed, making it the eleventh article reviewed. Proceeding to obtain and review the twelfth article, while keeping track of completions and errors. One error found among the previous articles. No files written, no URLs visited.A grammatical error was identified and reported in the ‘Harvey Birdman, Attorney at Law’ article, which was the twelfth article reviewed. This adds to the total count with two errors being reported. Next, I will proceed to review the thirteenth article. No files have been written, no URLs visited.The ‘Harvey Birdman, Attorney at Law’ article was the twelfth article reviewed, and a grammatical error was reported. Moving on to retrieve and review the thirteenth article. So far, two errors have been reported out of the twelve articles reviewed. No files have been written, no URLs visited.The article on ‘Toninho Cerezo’ did not present any errors requiring reporting, thus continuing the streak of successful reviews. This brings the count to thirteen articles reviewed with two errors identified and reported in previous articles. Moving on to the fourteenth article. No files have been written, no URLs visited.Having reviewed thirteen articles, with two errors reported so far, the task continues with retrieving the fourteenth simple English Wikipedia article for review. The previous article on ‘Toninho Cerezo’ had no errors. No files have been written, no URLs visited.The ‘Toshiya Sugiuchi’ article was the fourteenth reviewed and contained no errors that required reporting. The next step is to retrieve the fifteenth article for review. To date, two errors have been reported across the articles reviewed. No files have been written, no URLs visited.The article on ‘Toshiya Sugiuchi’ was the fourteenth reviewed and was error-free. Now onto the fifteenth article to be reviewed, with two errors reported so far. No files written, no URLs visited.Reviewed the ‘Muiris Mac Conghail’ article without finding any errors, marking the fifteenth completed review. The process will continue with the sixteenth article. So far, two errors have been reported in previous articles. No files have been written, no URLs visited.The article on ‘Muiris Mac Conghail’ has been reviewed, with no errors found. The count now stands at fifteen articles checked. Moving forward to the sixteenth article. A total of two errors have been reported in the previous articles reviewed. No files have been written, no URLs visited.The ‘Ronald Greenwald’ article was the sixteenth article reviewed. A potential factual discrepancy regarding ‘spy trading’ was identified and reported for verification. Moving on to review the seventeenth article. So far, two errors have been reported, not counting the potential factual discrepancy just identified. No files have been written, no URLs visited.Reported a possible factual discrepancy about ‘spy trading’ in the ‘Ronald Greenwald’ article, which was the sixteenth article reviewed. The next step is to retrieve the seventeenth article. A total of three errors have now been reported. No files have been written, no URLs visited.Reviewed the ‘Mecoptera’ article, which did not present any errors for reporting, bringing the total to seventeen articles reviewed. Moving on to review the eighteenth article. Three errors or discrepancies have been reported thus far in the process of reviewing. No files written, no URLs visited.The article on ‘Mecoptera’ was reviewed with no errors needing to be reported, increasing the total articles reviewed to seventeen. Next in line is to retrieve the eighteenth article for review, with three errors reported in earlier articles. No files have been written, no URLs visited.The ‘Royal Bhutan Army’ article was reviewed and no errors were found, marking it as the eighteenth article reviewed. Continuing to the nineteenth article with three reported errors in the overall task. No files have been written, no URLs visited.After reviewing the ‘Royal Bhutan Army’ article, which was the eighteenth reviewed without errors, the next action is to retrieve the nineteenth article for review. Three errors have been reported out of the articles reviewed so far. No files have been written, no URLs visited.The article on ‘HV 888’ was reviewed, and no errors were identified, bringing the total to nineteen articles reviewed. Next, the task is to proceed with the twentieth article. Up to now, three errors have been reported in the overall review process. No files have been written, no URLs visited.The ‘HV 888’ article does not require any error reporting, so the next step is to get the twentieth article. Thus far, nineteen articles have been checked with three errors reported. The review process will continue as per the task instructions. No files have been written, no URLs visited.The ‘Rocklin, California’ article has been reviewed; it was extremely brief and while not an error, it was noted for the user’s information, making it the twentieth article checked. Proceeding to the twenty-first article, with three errors reported thus far. No files have been written, no URLs visited.Completed the review of twenty articles with three errors reported. The notification about the brevity of the ‘Rocklin, California’ article was sent. Moving on to the twenty-first article for review. No files written, no URLs visited.The ‘Eleventh Amendment to the United States Constitution’ article was the twenty-first reviewed and contained no errors to report. Moving on to retrieve the twenty-second article. Three errors have been reported out of the articles reviewed to this point. No files have been written, no URLs visited.The ‘Eleventh Amendment to the United States Constitution’ article review yielded no errors to report, which brings the total to twenty-one articles reviewed so far. The task now is to retrieve and review the twenty-second article, with three errors reported previously. No files have been written, no URLs visited.A potential inconsistency was reported in the ‘Family Guy (season 2)’ article, which is the twenty-second article reviewed. Moving on to review the twenty-third article, with four issues reported, including this latest one. No files have been written, no URLs visited.The ‘Family Guy (season 2)’ article was the twenty-second article reviewed, with an inconsistency noted and reported. Moving forward to the twenty-third article. To date, four issues have been reported, including the inconsistency. No files have been written, no URLs visited.The ‘Romanian Land Forces’ article was reviewed as the twenty-third article, revealing no errors to report. The next step is to advance to reviewing the twenty-fourth article. Currently, the task stands at four reported issues out of the articles reviewed. No files have been written, no URLs visited.After completing the review of the ‘Romanian Land Forces’ article, which was the twenty-third checked article with no errors found, I am now proceeding to retrieve the twenty-fourth article for review. Four errors have been reported to date. No files have been written, no URLs visited.The article about ‘Caldwell, Texas’ has been reviewed and contains no detectable errors, marking it as the twenty-fourth article reviewed. Onward to the twenty-fifth article, with a total of four issues reported from previous articles. No files have been written, no URLs visited.The ‘Caldwell, Texas’ article was evaluated, and no errors were found, thus it is marked as the twenty-fourth reviewed article. Moving forward to retrieve and examine the twenty-fifth article. Across the articles reviewed so far, four errors have been reported. No files have been written, no URLs visited.The twenty-fifth article on the ‘1928 Germany–Netherlands women’s athletics competition’ has been reviewed without the need to report errors. Moving forward to review the twenty-sixth article. To date, four issues have been communicated to the user. No new files have been written, no URLs visited.The ‘1928 Germany–Netherlands women’s athletics competition’ article was the twenty-fifth reviewed, with no errors found. The next action is retrieving the twenty-sixth article for review. There have been four reported issues from previous articles. No files have been written, no URLs visited.A minor potential factual inaccuracy regarding population figures was identified and reported from the ‘Loiron-Ruillé’ article, which was the twenty-sixth article reviewed. Moving on to examine the twenty-seventh article. The number of issues reported has increased to five, including this recent one. No files have been written, no URLs visited.Twenty-six articles have been reviewed so far, with five issues reported. Moving to review the twenty-seventh article. No files have been written, no URLs visited.
The Task: go and retrieve simple wikipidea pages and check if they contain any errors like grammar and other stuff but do not report if the article needs to be extended or something that is not an error that is in the article provided,and then if there is an error message the user about it giving him the name of the article and the errors in it, and do this for 1000 articles.
|
6db73db16953a8ca0e2e1d34ba4d410a
|
{
"intermediate": 0.3397374749183655,
"beginner": 0.4271845817565918,
"expert": 0.2330779731273651
}
|
34,619
|
hello
|
a98b909925baecbb1d5e1710a77b05db
|
{
"intermediate": 0.32064199447631836,
"beginner": 0.28176039457321167,
"expert": 0.39759764075279236
}
|
34,620
|
function optimizeHeatExchanger5()
% NSGA-II parameters
nPop = 1000; % Population size
maxGen = 30; % Maximum number of generations
pCrossover = 0.999; % Crossover probability
% Optimization options
options = gaoptimset('PopulationType', 'doubleVector', ...
'PopulationSize', nPop, ...
'Generations', maxGen, ...
'CrossoverFraction', pCrossover, ...
'ParetoFraction', 0.35, ...
'PlotFcn', @gaplotpareto);
% Lower and upper bounds for design variables
lb = [5, 3, 1, 0.15, 300];
ub = [10, 6, 2, 0.3, 800];
% Run the NSGA-II optimizer
[x, fval] = gamultiobj(@plateFinHeatExchanger, 5, [], [], [], [], lb, ub, options);
% Display the results to the Command Window
disp('Optimized Design Variables:');
disp(x);
disp('Objective Function Values:');
disp(fval);
% Obtain the design parameters at which the optimum values of the objective functions are achieved
designParametersAtOptimum = findOptimalDesignParameters(x, fval);
disp('Design Parameters at Optimal Objective Function Values:');
disp(designParametersAtOptimum);
end
function [f, c] = plateFinHeatExchanger(x)
% Define the design parameters
h = x(1); % fin height
l = x(2); % fin pitch
s = x(3); % fin spacing
t = x(4); % fin thickness
Re = x(5); % Reynolds number
% Evaluate the objective functions
f1 = -ColburnFactor(h, l, s, t, Re); % Negative sign because we want to maximize
f2 = FrictionFactor(h, l, s, t, Re);
% Combine the objectives
f = [f1, f2];
% Define the constraints
c = []; % No nonlinear constraints in this case
end
function j = ColburnFactor(h, l, s, t, Re)
% Colburn factor calculation for laminar and turbulent range
if (Re >= 300 && Re <= 800)
j = 0.661 * (Re^(-0.651)) * ((s/h)^(-0.343)) * ((t/s)^(-0.538)) * ((t/l)^(0.305));
elseif (Re >= 1000 && Re <= 15000)
j = 0.185 * (Re^(-0.396)) * ((s/h)^(-0.178)) * ((t/s)^(-0.403)) * ((t/l)^(0.29));
else
error('Reynolds number is out of the valid range for the provided formula.');
end
end
function f = FrictionFactor(h, l, s, t, Re)
% Friction factor calculation for laminar and turbulent range
if (Re >= 300 && Re <= 800)
f = 10.882 * (Re^(-0.79)) * ((s/h)^(-0.359)) * ((t/s)^(-0.187)) * ((t/l)^(0.284));
elseif (Re >= 1000 && Re <= 15000)
f = 2.237 * (Re^(-0.236)) * ((s/h)^(-0.347)) * ((t/s)^(-0.151)) * ((t/l)^(0.639));
else
error('Reynolds number is out of the valid range for the provided formula.');
end
end
function designParameters = findOptimalDesignParameters(x, fval)
% Find the index of the minimum value in each objective function column
[~, minIdx] = min(fval, [], 1);
% Obtain the design parameters corresponding to the minimum values
designParameters = x(minIdx, :);
end
Elaborate the code
|
b83b9841e2f09625f0b36f4032f40153
|
{
"intermediate": 0.3188363015651703,
"beginner": 0.40953633189201355,
"expert": 0.27162742614746094
}
|
34,621
|
function optimizeHeatExchanger22()
% NSGA-II parameters
nPop = 1000; % Population size
maxGen = 30; % Maximum number of generations
pCrossover = 0.999; % Crossover probability
% Optimization options
options = gaoptimset(‘PopulationType’, ‘doubleVector’, …
‘PopulationSize’, nPop, …
‘Generations’, maxGen, …
‘CrossoverFraction’, pCrossover, …
‘ParetoFraction’, 0.35, …
‘PlotFcn’, @gaplotpareto);
% Lower and upper bounds for design variables
lb = [5, 3, 1, 0.15, 300];
ub = [10, 6, 2, 0.3, 800];
% Run the NSGA-II optimizer
[x, fval] = gamultiobj(@plateFinHeatExchanger, 5, [], [], [], [], lb, ub, options);
% Display the results to the Command Window
disp(‘Optimized Design Variables:’);
disp(x);
disp(‘Objective Function Values:’);
disp(fval);
% Obtain the design parameters at which the optimum values of the objective functions are achieved
designParametersAtOptimum = findOptimalDesignParameters(x, fval);
disp(‘Design Parameters at Optimal Objective Function Values:’);
disp(designParametersAtOptimum);
end
function [f, c] = plateFinHeatExchanger(x)
% Define the design parameters
h = x(1); % fin height
l = x(2); % fin pitch
s = x(3); % fin spacing
t = x(4); % fin thickness
Re = x(5); % Reynolds number
% Evaluate the objective functions
f1 = -ColburnFactor(h, l, s, t, Re); % Negative sign because we want to maximize
f2 = FrictionFactor(h, l, s, t, Re);
% Combine the objectives
f = [f1, f2];
% Define the constraints
c = []; % No nonlinear constraints in this case
end
function j = ColburnFactor(h, l, s, t, Re)
% Colburn factor calculation for laminar and turbulent range
if (Re >= 300 && Re <= 800)
j = 0.661 * (Re^(-0.651)) * ((s/h)^(-0.343)) * ((t/s)^(-0.538)) * ((t/l)^(0.305));
elseif (Re >= 1000 && Re <= 15000)
j = 0.185 * (Re^(-0.396)) * ((s/h)^(-0.178)) * ((t/s)^(-0.403)) * ((t/l)^(0.29));
else
error(‘Reynolds number is out of the valid range for the provided formula.’);
end
end
function f = FrictionFactor(h, l, s, t, Re)
% Friction factor calculation for laminar and turbulent range
if (Re >= 300 && Re <= 800)
f = 10.882 * (Re^(-0.79)) * ((s/h)^(-0.359)) * ((t/s)^(-0.187)) * ((t/l)^(0.284));
elseif (Re >= 1000 && Re <= 15000)
f = 2.237 * (Re^(-0.236)) * ((s/h)^(-0.347)) * ((t/s)^(-0.151)) * ((t/l)^(0.639));
else
error(‘Reynolds number is out of the valid range for the provided formula.’);
end
end
This is my original code. I want to create the graphs that show how the Colburn factor (j) and the friction factor (f) behave with respect to the Reynolds number, with all other design parameters set to their optimum values for the objective function. Please generate the code for given problem.
|
6e12115c6afc427eebf070bf47c0e447
|
{
"intermediate": 0.3064430058002472,
"beginner": 0.3352116048336029,
"expert": 0.3583453595638275
}
|
34,622
|
How can i have sense if I use chat gpt?
|
4820e545c4880cebd270d577de315037
|
{
"intermediate": 0.3477608561515808,
"beginner": 0.2697184085845947,
"expert": 0.38252073526382446
}
|
34,623
|
Hey! Write me code for creating iMac application with will looking for crypto lost wallets in Exodus
|
6e8ed49e2d4d3227d1092647ba5ccc39
|
{
"intermediate": 0.4247566759586334,
"beginner": 0.19674581289291382,
"expert": 0.37849748134613037
}
|
34,624
|
i want a CSV that has headers for inputs and outputs that will have general sense sentences, you can generate some lines for that
|
e497e35606bf1f57d74249ae74571389
|
{
"intermediate": 0.4162365198135376,
"beginner": 0.3213057219982147,
"expert": 0.2624577581882477
}
|
34,625
|
How can I use smartctl to make a quick (non-S.M.A.R.T.) test of a drive?
|
70a8b1b6d0647962a07184525cf92e75
|
{
"intermediate": 0.3343032896518707,
"beginner": 0.18159052729606628,
"expert": 0.4841062128543854
}
|
34,626
|
const value = new Promise((resolve, reject) => {
let value = 1;
if(value > 10) {
resolve(value);
} else{
reject(value);
}
});
async function getValue() {
try {
let result = await value;
console.log(result);
} catch(err) {
console.log(err)
}
}
|
650e5e0300797fad742b2d164863169f
|
{
"intermediate": 0.3954192101955414,
"beginner": 0.4411522150039673,
"expert": 0.1634286642074585
}
|
34,627
|
In unreal engine, is there a command to unpause the game just for one frame?
|
443a7b55d4388f1bd8c511fedc9c3d4b
|
{
"intermediate": 0.2628028690814972,
"beginner": 0.24976547062397003,
"expert": 0.4874315857887268
}
|
34,628
|
package gtanks.battles.effects.impl;
import gtanks.battles.BattlefieldPlayerController;
import gtanks.battles.effects.Effect;
import gtanks.battles.effects.EffectType;
import gtanks.battles.effects.activator.EffectActivatorService;
import gtanks.battles.tanks.math.Vector3;
import gtanks.commands.Type;
import gtanks.services.annotations.ServicesInject;
import java.util.TimerTask;
public class DamageEffect extends TimerTask implements Effect {
private static final long INVENTORY_TIME_ACTION = 60000L;
private static final long DROP_TIME_ACTION = 40000L;
@ServicesInject(
target = EffectActivatorService.class
)
private EffectActivatorService effectActivatorService = EffectActivatorService.getInstance();
private BattlefieldPlayerController player;
private boolean fromInventory;
private boolean deactivated;
public void activate(BattlefieldPlayerController player, boolean fromInventory, Vector3 tankPos) {
this.fromInventory = fromInventory;
this.player = player;
player.tank.activeEffects.add(this);
this.effectActivatorService.activateEffect(this, this.fromInventory ? 60000L : 40000L);
}
public void deactivate() {
this.deactivated = true;
this.player.tank.activeEffects.remove(this);
this.player.battle.sendToAllPlayers(Type.BATTLE, "disnable_effect", this.player.getUser().getNickname(), String.valueOf(this.getID()));
}
public void run() {
if (!this.deactivated) {
this.deactivate();
}
}
public EffectType getEffectType() {
return EffectType.DAMAGE;
}
public int getID() {
return 3;
}
public int getDurationTime() {
return 60000;
}
}
как сделать чтобы во время получения повторного эффекта таймер откатывался назад и начинался заново
|
eeea0090248ee75da75a15e0fac683f9
|
{
"intermediate": 0.43422162532806396,
"beginner": 0.24752293527126312,
"expert": 0.3182554244995117
}
|
34,629
|
A previous ChatGPT instance said "Some drives do not work with smartctl because they may not adhere to the standard ATA or SCSI command sets that smartctl relies on for communication and data retrieval. These non-standard or proprietary implementations can prevent smartctl from accurately accessing or interpreting the drive’s SMART data.".
I want to know if there's any smartctl command that checks the health of the drive which doesn't need that standard to be adhered to? I'm thinking perhaps something more manual (from the point of view of the smartctl utility).
|
8c122ec215e17b325ad26f336a96fe44
|
{
"intermediate": 0.5048729777336121,
"beginner": 0.3035610020160675,
"expert": 0.1915660798549652
}
|
34,630
|
modify this code so that i can load a csv that has two headers: inputs and outputs so i could train a model with that : import tkinter as tk
from tkinter import filedialog
from keras.models import Sequential, Model
from keras.layers import Embedding, LSTM, Dense, Input, MultiHeadAttention, GlobalAveragePooling1D
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.utils import to_categorical
import numpy as np
import os
import pickle
from keras.layers import Masking
from keras.layers import MultiHeadAttention
# Data loader and preprocessor function
def preprocess_data(file_paths):
tokenizer = Tokenizer()
# Load and concatenate content from all selected dataset files
all_text = ""
for file_path in file_paths:
with open(file_path, "r", encoding="utf-8") as file:
text = file.read()
all_text += text + "\n" # Ensure separation between files’ content
sentences = all_text.split("\n")
tokenizer.fit_on_texts(sentences)
sequences = tokenizer.texts_to_sequences(sentences)
# Check if we’re using a fixed sequence length
if sequence_choice_var.get():
# Read the fixed sequence length from the respective entry field
sequence_length = int(entry_fixed_length.get())
padded_sequences = pad_sequences(sequences, maxlen=sequence_length, padding="pre")
big_sequence = [token for seq in padded_sequences for token in seq if token != 0] # Filter out 0 (padding)
else:
# If not using a fixed length, find the minimal sequence length greater than 1
sequence_length = min(len(seq) for seq in sequences if len(seq) > 1)
big_sequence = [token for seq in sequences for token in seq]
# Filter by sequence_length will not be necessary since we take the minimal length anyway
big_sequence = [token for seq in sequences for token in seq]
input_sequences, output_words = [], []
# Assign a sequence length based on the shortest sentence
# Note: for better training with variable lengths, consider using sentences directly and/or padding at the end of each batch
sequence_length = min(len(seq) for seq in sequences if len(seq) > 1)
for i in range(len(big_sequence) - sequence_length):
input_sequences.append(big_sequence[i:i + sequence_length])
output_words.append(big_sequence[i + sequence_length])
# Remove pad_sequences call - handle varying sequence lengths directly in the model using masking or by padding at batch end
vocab_size = len(tokenizer.word_index) + 1
output_words = np.array(output_words)
output_words = to_categorical(output_words, num_classes=vocab_size)
return np.array(input_sequences), output_words, vocab_size, tokenizer, sequence_length
def create_transformer_model(sequence_length, vocab_size, layer_size, num_heads, dropout_rate):
# Transformer model requires the key, value, and query have the same dimensions (layer_size)
inputs = Input(shape=(sequence_length,))
embedding_layer = Embedding(input_dim=vocab_size, output_dim=layer_size)(inputs)
# Call the MultiHeadAttention layer with the necessary inputs
attn_output = MultiHeadAttention(num_heads=num_heads, key_dim=layer_size, dropout=dropout_rate)(
query=embedding_layer, key=embedding_layer, value=embedding_layer
)
# … Add Normalization, Feed-forward layers, etc. …
# GlobalAveragePooling1D could be used to reduce sequence dimension
pooling_layer = GlobalAveragePooling1D()(attn_output)
outputs = Dense(vocab_size, activation="softmax")(pooling_layer)
# Create the actual model
model = Model(inputs=inputs, outputs=outputs)
return model
# Function to train and save the model
def train_model():
# Move the variable assignments outside of the conditionals so they’re always defined.
num_layers = int(entry_layers.get())
layer_size = int(entry_size.get())
model_name = entry_name.get()
epochs = int(entry_epochs.get())
data_paths = root.filenames # Changed to accept multiple filenames
# Preprocess the data for either model type.
input_sequences, output_words, vocab_size, tokenizer, sequence_length = preprocess_data(data_paths)
# Check model_type and build the appropriate model.
model_type = model_type_var.get()
if model_type == "Transformer":
# Get Transformer configuration
num_heads, dropout_rate = get_transformer_config()
# Build Transformer model
model = create_transformer_model(sequence_length, vocab_size, layer_size, num_heads, dropout_rate)
# Compile the model
model.compile(optimizer="adam", loss="categorical_crossentropy", metrics=["accuracy"])
# Fit the model
model.fit(input_sequences, output_words, epochs=epochs)
else:
num_layers = int(entry_layers.get())
layer_size = int(entry_size.get())
model_name = entry_name.get()
epochs = int(entry_epochs.get())
data_paths = root.filenames # Changed to accept multiple filenames
# Preprocess the data
input_sequences, output_words, vocab_size, tokenizer, sequence_length = preprocess_data(data_paths)
# Define tokenizer_path
tokenizer_path = os.path.join("tokenizers", f"{model_name}_tokenizer.pickle")
# Check if the ‘tokenizers’ directory exists, if not, create it
os.makedirs("tokenizers", exist_ok=True)
# Building and training the model
model = Sequential()
model.add(Embedding(input_dim=vocab_size, output_dim=layer_size))
if not sequence_choice_var.get(): # Add masking for variable length sequences only
model.add(Masking(mask_value=0)) # Ignoring padded values (zeros)
# Adding predefined LSTM layers
for _ in range(num_layers):
model.add(LSTM(layer_size, return_sequences=True))
model.add(LSTM(layer_size))
model.add(Dense(vocab_size, activation="softmax"))
model.compile(optimizer="adam", loss="categorical_crossentropy", metrics=["accuracy"])
model.fit(input_sequences, output_words, epochs=epochs)
# For both: Save the tokenizer and model
tokenizer_path = os.path.join("tokenizers", f"{model_name}_tokenizer.pickle")
os.makedirs("tokenizers", exist_ok=True)
with open(tokenizer_path, "wb") as handle:
if sequence_choice_var.get():
pickle.dump((tokenizer, sequence_length), handle, protocol=pickle.HIGHEST_PROTOCOL)
else:
pickle.dump(tokenizer, handle, protocol=pickle.HIGHEST_PROTOCOL)
print(f"Tokenizer saved at {tokenizer_path}")
os.makedirs("models", exist_ok=True)
model.save(os.path.join("models", f"{model_name}.h5"))
print(f"Model {model_name} trained and saved successfully!")
# UI Setup
root = tk.Tk()
root.title("Chatbot Language Model Trainer")
# Model type
model_type_var = tk.StringVar(value="LSTM") # Default value set to ‘LSTM’
lbl_model_type = tk.Label(root, text="Select Model Type:")
lbl_model_type.pack()
radiobtn_lstm = tk.Radiobutton(root, text="LSTM", variable=model_type_var, value="LSTM")
radiobtn_lstm.pack()
radiobtn_transformer = tk.Radiobutton(root, text="Transformer", variable=model_type_var, value="Transformer")
radiobtn_transformer.pack()
# Number of layers
lbl_layers = tk.Label(root, text="Number of layers:")
lbl_layers.pack()
entry_layers = tk.Entry(root)
entry_layers.pack()
# Layer size
lbl_size = tk.Label(root, text="Size of each layer:")
lbl_size.pack()
entry_size = tk.Entry(root)
entry_size.pack()
# Model name
lbl_name = tk.Label(root, text="Model name:")
lbl_name.pack()
entry_name = tk.Entry(root)
entry_name.pack()
# Transformer specific settings
lbl_heads = tk.Label(root, text="Number of attention heads:")
lbl_heads.pack()
entry_heads = tk.Entry(root)
entry_heads.pack()
lbl_dropout = tk.Label(root, text="Dropout rate:")
lbl_dropout.pack()
entry_dropout = tk.Entry(root)
entry_dropout.pack()
# Number of epochs
lbl_epochs = tk.Label(root, text="Number of epochs:")
lbl_epochs.pack()
entry_epochs = tk.Entry(root)
entry_epochs.pack()
# Data file path
lbl_data_path = tk.Label(root, text="Data file path:")
lbl_data_path.pack()
entry_data_path = tk.Entry(root)
entry_data_path.pack()
# Checkbox for sequence length choice
lbl_sequence_choice = tk.Label(root, text="Use fixed sequence length:")
lbl_sequence_choice.pack()
sequence_choice_var = tk.BooleanVar() # Boolean variable to hold the checkbox state
chk_sequence_choice = tk.Checkbutton(root, text="Fixed length", variable=sequence_choice_var)
chk_sequence_choice.pack()
# Entry for fixed sequence length if the toggle is on
lbl_fixed_length = tk.Label(root, text="Fixed sequence length:")
lbl_fixed_length.pack()
entry_fixed_length = tk.Entry(root)
entry_fixed_length.pack()
# Function to select multiple files
def select_files():
file_paths = filedialog.askopenfilenames() # Changed to open multiple files
root.filenames = file_paths # Store the list of file paths on the root object
entry_data_path.delete(0, tk.END)
entry_data_path.insert(0, "; ".join(file_paths)) # Display all file paths in the entry
btn_browse = tk.Button(root, text="Browse…", command=select_files) # Changed to select_files
btn_browse.pack()
def get_transformer_config():
num_heads = int(entry_heads.get())
dropout_rate = float(entry_dropout.get())
# … fetch other settings similarly …
return num_heads, dropout_rate
# Train button
btn_train = tk.Button(root, text="Train Model", command=train_model)
btn_train.pack()
# Start the tkinter loop
root.mainloop()
|
f2fad503e1831fbe5d8a569bbee2dcb7
|
{
"intermediate": 0.4316570460796356,
"beginner": 0.2611102759838104,
"expert": 0.3072326183319092
}
|
34,631
|
package gtanks.battles.bonuses.model;
import gtanks.battles.BattlefieldModel;
import gtanks.battles.BattlefieldPlayerController;
import gtanks.battles.bonuses.Bonus;
import gtanks.battles.bonuses.BonusType;
import gtanks.battles.effects.Effect;
import gtanks.battles.effects.EffectType;
import gtanks.battles.effects.impl.ArmorEffect;
import gtanks.battles.effects.impl.DamageEffect;
import gtanks.battles.effects.impl.HealthEffect;
import gtanks.battles.effects.impl.NitroEffect;
import gtanks.battles.tanks.math.Vector3;
import gtanks.commands.Type;
import gtanks.main.database.DatabaseManager;
import gtanks.main.database.impl.DatabaseManagerImpl;
import gtanks.services.annotations.ServicesInject;
public class BonusTakeModel {
private static final String SET_CRY = "set_cry";
private static final String ENABLE_EFFECT_COMAND = "enable_effect";
private static final int CRYSTALL_BONUS_COST = 1;
private static final int GOLD_BONUS_COST = 100;
private BattlefieldModel bfModel;
@ServicesInject(
target = DatabaseManagerImpl.class
)
private DatabaseManager database = DatabaseManagerImpl.instance();
// $FF: synthetic field
private static int[] $SWITCH_TABLE$gtanks$battles$bonuses$BonusType;
public BonusTakeModel(BattlefieldModel bfModel) {
this.bfModel = bfModel;
}
public boolean onTakeBonus(Bonus bonus, Vector3 realtimePosTank, BattlefieldPlayerController player) {
switch($SWITCH_TABLE$gtanks$battles$bonuses$BonusType()[bonus.type.ordinal()]) {
case 1:
this.bfModel.sendUserLogMessage(player.parentLobby.getLocalUser().getNickname(), "взял золотой ящик");
player.parentLobby.getLocalUser().addCrystall(GOLD_BONUS_COST);
player.send(Type.BATTLE, SET_CRY, String.valueOf(player.parentLobby.getLocalUser().getCrystall()));
this.database.update(player.getUser());
break;
case 2:
player.parentLobby.getLocalUser().addCrystall(CRYSTALL_BONUS_COST);
player.send(Type.BATTLE, SET_CRY, String.valueOf(player.parentLobby.getLocalUser().getCrystall()));
this.database.update(player.getUser());
break;
case 3:
this.activateDrop(new ArmorEffect(), player);
break;
case 4:
this.activateDrop(new HealthEffect(), player);
break;
case 5:
this.activateDrop(new DamageEffect(), player);
break;
case 6:
this.activateDrop(new NitroEffect(), player);
}
return true;
}
private void activateDrop(Effect effect, BattlefieldPlayerController player) {
if (!player.tank.isUsedEffect(effect.getEffectType())) {
effect.activate(player, false, player.tank.position);
player.battle.sendToAllPlayers(Type.BATTLE, ENABLE_EFFECT_COMAND, player.getUser().getNickname(), String.valueOf(effect.getID()), effect.getEffectType() == EffectType.HEALTH ? String.valueOf(10000) : String.valueOf(40000));
}
}
// $FF: synthetic method
static int[] $SWITCH_TABLE$gtanks$battles$bonuses$BonusType() {
int[] var10000 = $SWITCH_TABLE$gtanks$battles$bonuses$BonusType;
if (var10000 != null) {
return var10000;
} else {
int[] var0 = new int[BonusType.values().length];
try {
var0[BonusType.ARMOR.ordinal()] = 3;
} catch (NoSuchFieldError var6) {
}
try {
var0[BonusType.CRYSTALL.ordinal()] = 2;
} catch (NoSuchFieldError var5) {
}
try {
var0[BonusType.DAMAGE.ordinal()] = 5;
} catch (NoSuchFieldError var4) {
}
try {
var0[BonusType.GOLD.ordinal()] = 1;
} catch (NoSuchFieldError var3) {
}
try {
var0[BonusType.HEALTH.ordinal()] = 4;
} catch (NoSuchFieldError var2) {
}
try {
var0[BonusType.NITRO.ordinal()] = 6;
} catch (NoSuchFieldError var1) {
}
$SWITCH_TABLE$gtanks$battles$bonuses$BonusType = var0;
return var0;
}
}
}
как сделать чтобы при повторном взятии ящика эффект допустим нитро обновился и пошел заново
|
d1bbdf05a444054ae9fb4d135d03fb99
|
{
"intermediate": 0.3550121486186981,
"beginner": 0.4368510842323303,
"expert": 0.20813673734664917
}
|
34,632
|
what are some historically (2010-2020) good clarinet competitions that a highschooler could attend?
|
94f67b138151a7a37cd982aaccb21e52
|
{
"intermediate": 0.3327496647834778,
"beginner": 0.3126142919063568,
"expert": 0.3546360433101654
}
|
34,633
|
package gtanks.battles.bonuses.model;
import gtanks.battles.BattlefieldModel;
import gtanks.battles.BattlefieldPlayerController;
import gtanks.battles.bonuses.Bonus;
import gtanks.battles.bonuses.BonusType;
import gtanks.battles.effects.Effect;
import gtanks.battles.effects.EffectType;
import gtanks.battles.effects.impl.ArmorEffect;
import gtanks.battles.effects.impl.DamageEffect;
import gtanks.battles.effects.impl.HealthEffect;
import gtanks.battles.effects.impl.NitroEffect;
import gtanks.battles.tanks.math.Vector3;
import gtanks.commands.Type;
import gtanks.main.database.DatabaseManager;
import gtanks.main.database.impl.DatabaseManagerImpl;
import gtanks.services.annotations.ServicesInject;
public class BonusTakeModel {
private static final String SET_CRY = "set_cry";
private static final String ENABLE_EFFECT_COMAND = "enable_effect";
private static final int CRYSTALL_BONUS_COST = 1;
private static final int GOLD_BONUS_COST = 100;
private BattlefieldModel bfModel;
@ServicesInject(
target = DatabaseManagerImpl.class
)
private DatabaseManager database = DatabaseManagerImpl.instance();
// $FF: synthetic field
private static int[] $SWITCH_TABLE$gtanks$battles$bonuses$BonusType;
public BonusTakeModel(BattlefieldModel bfModel) {
this.bfModel = bfModel;
}
public boolean onTakeBonus(Bonus bonus, Vector3 realtimePosTank, BattlefieldPlayerController player) {
switch($SWITCH_TABLE$gtanks$battles$bonuses$BonusType()[bonus.type.ordinal()]) {
case 1:
this.bfModel.sendUserLogMessage(player.parentLobby.getLocalUser().getNickname(), "взял золотой ящик");
player.parentLobby.getLocalUser().addCrystall(GOLD_BONUS_COST);
player.send(Type.BATTLE, SET_CRY, String.valueOf(player.parentLobby.getLocalUser().getCrystall()));
this.database.update(player.getUser());
break;
case 2:
player.parentLobby.getLocalUser().addCrystall(CRYSTALL_BONUS_COST);
player.send(Type.BATTLE, SET_CRY, String.valueOf(player.parentLobby.getLocalUser().getCrystall()));
this.database.update(player.getUser());
break;
case 3:
this.activateDrop(new ArmorEffect(), player);
break;
case 4:
this.activateDrop(new HealthEffect(), player);
break;
case 5:
this.activateDrop(new DamageEffect(), player);
break;
case 6:
this.activateDrop(new NitroEffect(), player);
}
return true;
}
private void activateDrop(Effect effect, BattlefieldPlayerController player) {
if (!player.tank.isUsedEffect(effect.getEffectType())) {
effect.activate(player, false, player.tank.position);
player.battle.sendToAllPlayers(Type.BATTLE, ENABLE_EFFECT_COMAND, player.getUser().getNickname(), String.valueOf(effect.getID()), effect.getEffectType() == EffectType.HEALTH ? String.valueOf(10000) : String.valueOf(40000));
}
}
// $FF: synthetic method
static int[] $SWITCH_TABLE$gtanks$battles$bonuses$BonusType() {
int[] var10000 = $SWITCH_TABLE$gtanks$battles$bonuses$BonusType;
if (var10000 != null) {
return var10000;
} else {
int[] var0 = new int[BonusType.values().length];
try {
var0[BonusType.ARMOR.ordinal()] = 3;
} catch (NoSuchFieldError var6) {
}
try {
var0[BonusType.CRYSTALL.ordinal()] = 2;
} catch (NoSuchFieldError var5) {
}
try {
var0[BonusType.DAMAGE.ordinal()] = 5;
} catch (NoSuchFieldError var4) {
}
try {
var0[BonusType.GOLD.ordinal()] = 1;
} catch (NoSuchFieldError var3) {
}
try {
var0[BonusType.HEALTH.ordinal()] = 4;
} catch (NoSuchFieldError var2) {
}
try {
var0[BonusType.NITRO.ordinal()] = 6;
} catch (NoSuchFieldError var1) {
}
$SWITCH_TABLE$gtanks$battles$bonuses$BonusType = var0;
return var0;
}
}
}
как сделать чтобы при повтором взятии эффект ящиков обновился, и откатился назад
|
66d89600a9ff814ccb1b8c53239de59a
|
{
"intermediate": 0.3550121486186981,
"beginner": 0.4368510842323303,
"expert": 0.20813673734664917
}
|
34,634
|
public class BonusTakeModel {
private static final String SET_CRY = "set_cry";
private static final String ENABLE_EFFECT_COMAND = "enable_effect";
private static final int CRYSTALL_BONUS_COST = 1;
private static final int GOLD_BONUS_COST = 100;
private BattlefieldModel bfModel;
@ServicesInject(
target = DatabaseManagerImpl.class
)
private DatabaseManager database = DatabaseManagerImpl.instance();
// $FF: synthetic field
private static int[] $SWITCH_TABLE$gtanks$battles$bonuses$BonusType;
public BonusTakeModel(BattlefieldModel bfModel) {
this.bfModel = bfModel;
}
public boolean onTakeBonus(Bonus bonus, Vector3 realtimePosTank, BattlefieldPlayerController player) {
switch($SWITCH_TABLE$gtanks$battles$bonuses$BonusType()[bonus.type.ordinal()]) {
case 1:
this.bfModel.sendUserLogMessage(player.parentLobby.getLocalUser().getNickname(), "взял золотой ящик");
player.parentLobby.getLocalUser().addCrystall(GOLD_BONUS_COST);
player.send(Type.BATTLE, SET_CRY, String.valueOf(player.parentLobby.getLocalUser().getCrystall()));
this.database.update(player.getUser());
break;
case 2:
player.parentLobby.getLocalUser().addCrystall(CRYSTALL_BONUS_COST);
player.send(Type.BATTLE, SET_CRY, String.valueOf(player.parentLobby.getLocalUser().getCrystall()));
this.database.update(player.getUser());
break;
case 3:
this.activateDrop(new ArmorEffect(), player);
break;
case 4:
this.activateDrop(new HealthEffect(), player);
break;
case 5:
this.activateDrop(new DamageEffect(), player);
break;
case 6:
this.activateDrop(new NitroEffect(), player);
}
return true;
}
private void activateDrop(Effect effect, BattlefieldPlayerController player) {
if (!player.tank.isUsedEffect(effect.getEffectType())) {
effect.activate(player, false, player.tank.position);
player.battle.sendToAllPlayers(Type.BATTLE, ENABLE_EFFECT_COMAND, player.getUser().getNickname(), String.valueOf(effect.getID()), effect.getEffectType() == EffectType.HEALTH ? String.valueOf(10000) : String.valueOf(40000));
}
}
как сделать чтобы эффект дропа обновился, и откатился назад
|
2f7d2dd0a59da85c81d7b5a5c2eda080
|
{
"intermediate": 0.37921735644340515,
"beginner": 0.48261427879333496,
"expert": 0.1381683647632599
}
|
34,635
|
вот код с одно класса public boolean onTakeBonus(Bonus bonus, Vector3 realtimePosTank, BattlefieldPlayerController player) {
switch(SWITCH_TABLEgtanksbattlesbonuses$BonusType()[bonus.type.ordinal()]) {
case 1:
this.bfModel.sendUserLogMessage(player.parentLobby.getLocalUser().getNickname(), “взял золотой ящик”);
player.parentLobby.getLocalUser().addCrystall(GOLD_BONUS_COST);
player.send(Type.BATTLE, SET_CRY, String.valueOf(player.parentLobby.getLocalUser().getCrystall()));
this.database.update(player.getUser());
break;
case 2:
player.parentLobby.getLocalUser().addCrystall(CRYSTALL_BONUS_COST);
player.send(Type.BATTLE, SET_CRY, String.valueOf(player.parentLobby.getLocalUser().getCrystall()));
this.database.update(player.getUser());
break;
case 3:
this.activateDrop(new ArmorEffect(), player);
break;
case 4:
this.activateDrop(new HealthEffect(), player);
break;
case 5:
this.activateDrop(new DamageEffect(), player);
break;
case 6:
this.activateDrop(new NitroEffect(), player);
}
return true;
}
private void activateDrop(Effect effect, BattlefieldPlayerController player) {
if (!player.tank.isUsedEffect(effect.getEffectType())) {
effect.activate(player, false, player.tank.position);
player.battle.sendToAllPlayers(Type.BATTLE, ENABLE_EFFECT_COMAND, player.getUser().getNickname(), String.valueOf(effect.getID()), effect.getEffectType() == EffectType.HEALTH ? String.valueOf(10000) : String.valueOf(40000));
}
} а вот это код класса ArmorEffect вот package gtanks.battles.effects.impl;
import gtanks.battles.BattlefieldPlayerController;
import gtanks.battles.effects.Effect;
import gtanks.battles.effects.EffectType;
import gtanks.battles.effects.activator.EffectActivatorService;
import gtanks.battles.tanks.math.Vector3;
import gtanks.commands.Type;
import gtanks.services.annotations.ServicesInject;
import java.util.TimerTask;
public class ArmorEffect extends TimerTask implements Effect {
private static final long INVENTORY_TIME_ACTION = 60000L;
private static final long DROP_TIME_ACTION = 40000L;
@ServicesInject(
target = EffectActivatorService.class
)
private EffectActivatorService effectActivatorService = EffectActivatorService.getInstance();
private BattlefieldPlayerController player;
private boolean fromInventory;
private boolean deactivated;
public void activate(BattlefieldPlayerController player, boolean fromInventory, Vector3 tankPos) {
this.fromInventory = fromInventory;
this.player = player;
player.tank.activeEffects.add(this);
this.effectActivatorService.activateEffect(this, this.fromInventory ? 60000L : 40000L);
}
public void deactivate() {
this.deactivated = true;
this.player.tank.activeEffects.remove(this);
this.player.battle.sendToAllPlayers(Type.BATTLE, “disnable_effect”, this.player.getUser().getNickname(), String.valueOf(this.getID()));
}
public void run() {
if (!this.deactivated) {
this.deactivate();
}
}
public EffectType getEffectType() {
return EffectType.ARMOR;
}
public int getID() {
return 2;
}
public int getDurationTime() {
return 60000;
}
} как сделать чтобы при получении повторного эффекта он обновился, а таймер getDurationTime откатился обратно на 60000
|
1c17ac8ed070ead76c9ee49d7170a567
|
{
"intermediate": 0.26586320996284485,
"beginner": 0.5354439616203308,
"expert": 0.19869278371334076
}
|
34,636
|
Sports Day
Problem Description
An elementary school is conducting many games on annual sports day. Chintu wanted to participate and win in at least one of the games. Currently, he is attending puzzle solving and IQ testing games.
In the first round he is provided with N integers consisting of both positive and negative numbers, and asked to select as many as he want such that the resulting efficiency of all the numbers should be maximum.
Rules for calculating the efficiency of the numbers are as follows:
Select as many numbers you want from the provided numbers (one, few or all).
Assign a priority for all those numbers. Priority should range from one to K where K is the count of numbers he selected.
Efficiency is the sum of all the numbers multiplied with their respective priorities.
Help Chintu in calculating the maximum efficiency he can make using the given numbers.
Constraints
1 <= number of elements he is given <= 10^3
-10^3 <= each element <= 10^3
Input
Single line consisting of all the numbers that Chintu is provided with.
Output
Print the maximum efficiency that he can make using the given numbers. Print zero in case if the maximum efficiency is negative.
Time Limit (secs)
1
Examples
Example 1
Input
-7 -8 -5 5 -1 -2 0 3
Output
33
Explanation
Select 5, -1, -2, 0, 3 and give the priorities, -2 = 1, -1 = 2, 0 = 3, 3 = 4, 5 = 5, then efficiency will be, -2*1 + -1*2 + 0*3 + 3*4 + 5*5 = 33 which is the maximum than all possible efficiencies.
Example 2
Input 2
4 2 0 -3 -7
Output
19
Select 4, 2, 0, -3 and give the priorities, -3 = 1, 0 = 2, 2 = 3, 4 = 4, then efficiency will be -3*1 + 0*2 + 2*3 + 4*4 = 19, which is the maximum than all possible efficiencies.
give solution in python
|
5d68504334c71cbda57bb5c527aa9283
|
{
"intermediate": 0.35208046436309814,
"beginner": 0.3314683139324188,
"expert": 0.3164512813091278
}
|
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