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#!/usr/bin/env python #********************************************************************** # Gnu Cash to CSV (export_csv.py) # # Copyright 2012 <NAME> <<EMAIL>> #
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memset(rows,0,sizeof rows); memset(cols,0,sizeof cols);
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std::string QEMU_allocate_tun(QemuContext &ctx); std::string QEMU_allocate_macvtap(QemuContext &ctx, const struct Network &); std::string generateRandomMACAddress(); std::string QEMU_Generate_Link_Name(std::string prefix, int length); void QEMU_delete_link(QemuContext &ctx, std::string interface); int QEMU_OpenQMPSocket(QemuContext &ctx);
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face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) faces = face_cascade.detectMultiScale(gray, 1.3, 5) while 1: for (x,y,w,h) in faces: cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2) roi_gray = gray[y:y+h, x:x+w] roi_color = img[y:y+h, x:x+w] cv2.imshow("Image",img) k = cv2.waitKey(30) & 0xff if k == 27: break cv2.destroyAllWindows()
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let node_path = ctx.mk_node_path_from_tablet(tid).into_ct(); let sid = node_path.sid.clone(); if let Some(lid) = query_leader_map.get(&sid) { // Recall we already validated that `lid` is no lower than the // one at this node's LeaderMap. ctx.send_to_ct_lid(node_path.clone(), common_query, lid.clone()); } else { ctx.send_to_ct(node_path.clone(), common_query); } // Add the TabletGroup into the TMStatus. tm_status.tm_state.insert(node_path, None); if let Some(lid) = query_leader_map.get(&sid) { tm_status.leaderships.insert(sid, lid.clone()); } else {
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lambdex_definition_place[0], lambdex_definition_place[1], ),
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float side, int iterations, int v0, int v1, int v2, int v3,
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return template = self.options[i][0] self.window.run_command('dart_stagehand', {'template': template}) def get_templates(self): sdk = SDK() out = check_output([sdk.path_to_pub, 'global', 'run', 'stagehand', '--machine'],
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/// Parse a `BitString` from an ASN.1 `Any` value to test decoding behaviors. fn parse_bitstring_from_any(bytes: &[u8]) -> Result<BitString<'_>> { Any::new(Tag::BitString, bytes)?.try_into() } #[test] fn decode_empty_bitstring() { let bs = parse_bitstring_from_any(&[0]).unwrap(); assert_eq!(bs.as_ref(), &[]); }
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<button type="submit" class="btn btn-outline-primary btn-sm btn-rounded waves-effect"><i class="fas fa-save"></i> Salvar</button> </div> </form>
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@Contextual("mysql") public void testFlyway() {
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import java.util.Date; import java.util.Iterator; public class ReservaBll implements ICRUD_GENERIC { ReservaDal dal; public ReservaBll() throws Exception { dal = new ReservaDal(); }
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} class BillingNotFoundException extends BadRequestException { public $code = 3; public $msg = "Billing not found"; } class CustomerNotAuthorizedException extends BadRequestException { public $code = 3; public $msg = "Customer not authorized"; }
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# Create cards composer card create -p /tmp/composer/mother/efi-network-mother.json -u PeerAdmin -c /tmp/composer/mother/Admin@mother.efi.com-cert.pem -k /tmp/composer/mother/*_sk -r PeerAdmin -r ChannelAdmin -f PeerAdmin@efi-network-mother.card
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from corehq.util.log import with_progress_bar CHILD_PROPERTIES = ['case_id', 'owner_id', 'opened_on', 'modified_on', 'name', 'aadhar_number', 'dob', 'died'] SOURCE_FIELDS = CHILD_PROPERTIES + ['indices'] CSV_HEADERS = CHILD_PROPERTIES + ['owner_name', 'hh_id', 'hh_name', 'hh_closed_on']
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fn = 'MODELS/'+SH+'/DFM2.pkl' model = ImportModel(fn) Models2[SH] = model AllDates = sorted(set([str(a)[:10] for a in Models2['H&G'].alldates]))
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--chr=${CHR} \ --regionStart=5000000 \ --regionEnd=7000000 \ --buffer=500000 \ --bamlist=${BAM_LIST_FILE} \ --posfile=${SNP_POS_FILE} \ --reference_haplotype_file=${REF_HAP_FILE} \ --reference_legend_file=${REF_LEGEND_FILE} \ --genetic_map_file=${GEN_MAP_FILE} \ --output_gt_phased_genotypes=TRUE \
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# where # TP = succesfully amplified accessions # FN = possible accessions that were not amplified
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from .foo import Foo __all__ = ['Foo']
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return database.sql_exec(database.DATABASE_FILE, query, query_args, False) def get_data_by_name(username, fields=('*',), case_sensitive=False): """Retrieves the data of a user with the given name.""" if not case_sensitive: query = (f'SELECT {",".join(fields)} FROM users WHERE ' 'LOWER(username) = ? LIMIT 1') query_args = [username.lower()] else: query = (f'SELECT {",".join(fields)} FROM users WHERE ' 'username = ? LIMIT 1')
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#define QEventType_CMScrolled (Qt::QEventType)(1004) extern PACKAGE TApplication* Application; extern PACKAGE TScreen* Screen; extern PACKAGE Qcontrols::TMouse* Mouse; extern PACKAGE TMetaClass*HintWindowClass; extern PACKAGE TFormWidgetCreatedHook FormWidgetCreatedHook; extern PACKAGE TCustomForm* __fastcall GetParentForm(Qcontrols::TControl* Control); extern PACKAGE TCustomForm* __fastcall ValidParentForm(Qcontrols::TControl* Control);
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describe('DMRs-germ-chr20.csv') if __name__ == '__main__': main()
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if __name__ == '__main__': datatype = sys.argv[1] tree_count = sys.argv[2] sz = sys.argv[3] project = sys.argv[4] prefix = "/home/saikatc/Research/OpenNMT-py/defj_experiment/" data_path = prefix + "data/raw/" + datatype model_base = prefix + "models/" + datatype + "." augmented_token_model = model_base + 'augmented.token.' + project + '-best-acc.pt' structure_model = model_base + 'rule-best-acc.pt' src_token = data_path + '/test/' + project + '/prev.augmented.token'
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'email' => 'E-Mail Address', 'password_copy' => 'Create a password that contains at least one character from each of the following categories: lower-case characters (a-z), upper-case characters (A-Z), digits (0-9), and non-alphanumeric symbols (%, $, !, etc.).', 'password' => 'Password', 'confirm_password' => '<PASSWORD>', 'register' => 'Register', ];
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def test_Wavelet3D_PyWt(self): """Test the adjoint operator for the 3D Wavelet transform """ for i in range(self.max_iter): print("Process Wavelet3D PyWt test '{0}'...", i) wavelet_op_adj = WaveletN(wavelet_name="sym8", nb_scale=4, dim=3,
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it("return the correct rect") { let expectedRect = CGRect(x: 0, y: 0, width: 3, height: 3) expect(actualRect).to(equal(expectedRect)) } } context("with .topLeft") { beforeEach { sut = .topLeft actualRect = sut.rect(forImage: testImage) }
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plt.colorbar() plt.title('Vertex-Vertex distances for sphere(9802 vertices)') plt.xlabel('Vertex i') plt.ylabel('Vertex j') plt.show()
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# reset indexes df_test = df_test.reset_index(drop=True) df_train_val = df_train_val.reset_index(drop=True) # pickle dataframes df_test.to_pickle('./df_test.pkl') df_train_val.to_pickle('./df_train_val.pkl')
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key=Callback(SeasonExtractEmbedded, rating_key=rating_key, language=lang, base_title=show.section.title, display_items=display_items, item_title=item_title, title=title,
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exp_work_flows = [ ['startexperiment/', 'consent', 'preexperiment/AN/',
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pub use quartiles::Quartiles;
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CHARACTERISTIC_UUID = "f000aa65-0451-4000-b000-000000000000" # <--- Change to the characteristic you want to enable notifications from. ADDRESS = ( "24:71:89:cc:09:05" # <--- Change to your device's address here if you are using Windows or Linux if platform.system() != "Darwin"
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/// </summary> public class SqlScaleoutConfiguration : ScaleoutConfiguration { private int _tableCount = 1; public SqlScaleoutConfiguration(string connectionString)
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subsample = data[idxs] return subsample ## Note: matrices are indexed like mat[rows, cols]. If only one is provided, it is interpreted as mat[rows].
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from .latex_report_builder import LatexReportBuilder from .markdown_report_builder import MarkdownReportBuilder from .json_report_builder import JsonReportBuilder from .html_report_builder import JinjaHtmlReportBuilder
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import torch.nn as nn from distributions_tor import GaussianDistributionNetwork from utils_tor import init_param_openaibaselines
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public string Main(string arg0, string arg1) { return "Main(string arg0, string arg1)"; } [Action(IsDefault = false)] public string Main(int argument) { return "Main(int argument)"; }
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use CharToImage\Drive\Output\PngOut; $input = new PngIn; $output = new PngOut; $cti = new CharToImage($input, $output, './wzblog.png'); $str = file_get_contents('./text.txt');
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: QWidget(parent, Qt::Tool | //Tool does not force focus changes upon shows Qt::FramelessWindowHint | //No decorations
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phone_number = models.CharField(max_length=20, unique=True)
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docker build --pull --no-cache --tag docker-registry.intrafind.net/intrafind/sis-sitesearch:latest . docker push docker-registry.intrafind.net/intrafind/sis-sitesearch:latest ssh <EMAIL> docker rm -f if-sitesearch ssh <EMAIL>.sitesearch.cloud docker run -d --name if-sitesearch \ --env SIS_API_SERVICE_URL=$SIS_API_SERVICE_URL \ --env SERVICE_SECRET=$SERVICE_SECRET \ --env SIS_SERVICE_HOST=$SIS_SERVICE_HOST \ --env WOO_COMMERCE_CONSUMER_KEY="$WOO_COMMERCE_CONSUMER_KEY" \
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from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals from jewish.date import InvalidDateError from jewish.date import JewishDate from jewish.date import JewishDateError
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def forward(self, x):
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// CHECK: define i8 @call_foreign_fn() #[no_mangle] pub fn call_foreign_fn() -> u8 {
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valid_image_file_formats = {'png', 'jpg'}
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BrowseTheWeb_Mocked = mock.Mock(spec=BrowseTheWeb) BrowseTheWeb_Mocked.browser = mock.Mock() return AnActor.named("Tester").who_can( AuthenticateWith2FA_Mocked, BrowseTheWeb_Mocked ) @pytest.fixture(scope="function") def APITester() -> AnActor:
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params = file_rw.load_object('%s/%s/10wt/forecast_%s_2state_powercut_levy.pl' % (root_dir, res, res)) levy_sigma1 = [] levy_alpha1 = [] levy_sigma2 = [] levy_alpha2 = [] for j in params.hop_parameters[0]: levy_sigma1.append(j[2]) levy_alpha1.append(j[0]) for j in params.hop_parameters[1]: levy_sigma2.append(j[2]) levy_alpha2.append(j[0])
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rustup target add $TARGET fi sudo pip install --upgrade pip sudo pip install virtualenv --upgrade }
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// ProductCode.swift // ChallengeCore // // Created by Lorenzo Di Vita on 30/9/21. //
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content = message.content[1:] if message.author.bot: return with open("./configi.json", 'r') as configjsonFile: config_data = json.load(configjsonFile) if message.channel.id == int(config_data[str(message.guild.id)]["kanalpropozycje"]): if message.content.startswith("%"): await message.delete() await channel.send(f"**Komentarz {message.author}:** {content}")
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self.filteredPosts = self.postsArray.filter { user in let tag = user!["caption"] as? String return(tag?.lowercased().contains(searchText.lowercased()))! } tableview.reloadData() } }
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inicio = time() result = busca_binaria_it(lista, num) fim = time() tempo_gasto = fim-inicio print('resultado', result) return tempo_gasto if __name__ == '__main__': l = criaLista()
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useLocation, } from 'react-router-dom';
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if __name__ == '__main__': MDPairWCA.main()
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from astropy.coordinates.matrix_utilities import matrix_transpose from astropy.coordinates.builtin_frames.icrs import ICRS import spiceypy as spice __all__ = ['MCMF'] DEFAULT_OBSTIME = Time('J2000', scale='tt') @format_doc(base_doc, components="", footer="") class MCMF(BaseCoordinateFrame): """ A coordinate or frame in the lunar "Mean Earth/ Mean Rotation frame". This is a "Moon-Centered/Moon-Fixed" frame, defined by an X axis through the mean position
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static void Main(string[] args) {
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STANDARD_STORAGE_CLASS = "STANDARD" """Storage class for objects accessed more than once per month. See: https://cloud.google.com/storage/docs/storage-classes """ NEARLINE_STORAGE_CLASS = "NEARLINE" """Storage class for objects accessed at most once per month. See: https://cloud.google.com/storage/docs/storage-classes
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# Plot first decoded track print("Example Model Generated Track") plot_track(decoded_tracks[0]) # Filter Track decoded_tracks = filter_tracks(decoded_tracks, p_min) # Plot first filtered track
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# distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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Note: m and n will be at most 100. """ class Solution(object): def uniquePaths(self, m, n): """
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import os.path
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#endif #include <boost/asio.hpp>
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PointToPointHelper p2p; p2p.SetDeviceAttribute ("DataRate", StringValue ("5Mbps")); p2p.SetChannelAttribute ("Delay", StringValue ("2ms"));
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"""Convert a PostgreSQL query result to a dict""" resp = [] for row in result: resp.append(dict(zip(columns, row))) if single_object: return resp[0] return resp
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var deltaX = _lastMousePoint.X - e.X; var deltaY = _lastMousePoint.Y - e.Y; _lastMousePoint = e.Location; var inflate = 5F;
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} } mutating func notUsername() { isNotUsernameEnabled = true delegate?.reload() }
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pub mod velocity; pub mod movement;
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inputs = tf.keras.Input(input_shape) x = feat_ex(inputs) x = layers.GlobalAveragePooling2D()(x) x = layers.Dropout(0.5)(x) yh = layers.Dense( 10, kernel_regularizer=regularizers.l2(0.0001), activation="softmax" )(x) model = tf.keras.Model(inputs, yh) print(model.summary()) return model #######################################
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public static final String FILE_NAME = "build.gradle"; private String applicationId; private String supportLibraryVersion; public BuildGradle(String modulePath) { super(modulePath + "/" + FILE_NAME); for (String line : codelines) { if (line.contains("applicationId")) { applicationId = FileUtils.getStringBetweenQuotes(line);
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inner, event, } } fn to_wstr(s: &str) -> Vec<u16> { OsStr::new(s).encode_wide().chain(iter::once(0)).collect() }
ise-uiuc/Magicoder-OSS-Instruct-75K
use App\Http\Requests\ProductDetailFeed\CreateRequest; use App\Http\Requests\ProductDetailFeed\UpdateRequest; use App\Http\Resources\ProductDetailFeed\ListCollection; use App\Models\ProductDetailFeed; use App\Shared\APIResponse; use Illuminate\Support\Facades\Gate; use Symfony\Component\HttpFoundation\Response; use Illuminate\Http\Request; class ProductFeedController extends Controller { /** * Display a listing of the resource.
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namespace tensorflow { namespace { constexpr char kBaseApiDef[] = "tensorflow/core/api_def/base_api/*.pbtxt"; constexpr char kPythonApiDef[] = "tensorflow/core/api_def/python_api/*.pbtxt"; constexpr bool kUseApiDef = false;
ise-uiuc/Magicoder-OSS-Instruct-75K
<reponame>csal90/LeetHub<filename>maximum-subarray/maximum-subarray.py class Solution: def maxSubArray(self, nums: List[int]) -> int: maxsofar = nums[0] maxendinghere = nums[0] for i in range(1, len(nums)): maxendinghere = max(nums[i], nums[i] + maxendinghere) maxsofar = max(maxsofar, maxendinghere) return maxsofar
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let rule = ruleset.get(&id).unwrap(); let next_next = next .iter() .map(|remain| rule.matches(ruleset, remain)) .filter(|v| !v.is_empty()) .flatten() .collect();
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class NetworkNotificationReceiver : public pqxx::notification_receiver { public: NetworkNotificationReceiver(PostgreSQL *p, pqxx::connection &c, const std::string &channel); virtual ~NetworkNotificationReceiver() {
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public class AuthenticateCommand : IRequest<string> { public string UserName { get; set; } public string Password { get; set; } }
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date
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screen.controller.amountEdit.setText(amountStr); screen.controller.send(null); }); } private void updateTitleForBroadcast() { final int peers = sendResult.tx.getConfidence().numBroadcastPeers(); titleLabel.setText(String.format("Broadcasting ... seen by %d peers", peers)); }
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print ""
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qsort(_ignores.data(), _ignores.size(), sizeof(_ignores.front()), compareMyType); } void KMeansClustering::RemoveIgnore(std::string & ignores) { int att = _dataframe.GetAttributeIndex(ignores); auto result = std::find(_ignores.begin(), _ignores.end(), att); if (result != _ignores.end())
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def __init__(self, opts): # TODO: Add things like no. of hidden layers to opts pass class LSTM(nn.Module): # This class is largely derived from # https://stackabuse.com/time-series-prediction-using-lstm-with-pytorch-in-python on 20210701. def __init__(self, input_size=2, hidden_layer_size=100, output_size=2): # param input_size: number of components in input vector # param output_size: number of components in output vector # param hidden_layer_size: number of components in hidden layer super().__init__()
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new = text[int(i):int(i+len(word))] if new == word: res.append([i,i+len(word)-1]) return sorted(res)
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def test_terminalwriter_computes_width():
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base_url += ':%d' % server.port return urlparse.urljoin(base_url, url) @step(r'I visit site page "([^"]*)"') def visit_page(self, page): """ Visit the specific page of the site. """ self.given('I visit "%s"' % site_url(page))
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# # model.compile(loss={'output':'binary_crossentropy'}, optimizer=Adam()) # model.compile(loss={'output':'categorical_crossentropy'}, optimizer=Adam(options.lr))
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.match(MessageType.Location.class, request ->
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image_np = cv2.cvtColor(image_np, cv2.COLOR_BGR2GRAY) #(T, thresh) = cv2.threshold(image_np, 0, 255, cv2.THRESH_BINARY) cv2.imwrite("imgs/{}.jpg".format(count),image_np)
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), migrations.AlterField( model_name='sitesettings', name='TELEGRAM_TOKEN', field=models.CharField(blank=True, default='', help_text='The token assigned by the BothFather', max_length=50, verbose_name='Token for the telegram bot'), ), ]
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'customer_identity_type' => 'NIF', 'serial' => '43962', 'number' => '3213124', 'date' => '18/05/2018', 'total_net_amount' => '8000', 'total_amount' => '10000', 'included_vat' => '21', 'observations' => 'La Factura ha sigut realitzada correctament', 'lines' => '4',
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} } /// An error with an associated span. #[derive(Debug)] pub struct SpannedError {
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ReturnStruct ConstructReturnStruct(unsigned char a, Embedded b, unsigned char c) { ReturnStruct ret; ret.a = a; ret.b = b; ret.c = c; return ret; }
ise-uiuc/Magicoder-OSS-Instruct-75K
def check_edge_condition(px, py, pyaw, start_x, start_y, start_yaw, end_x, end_y, end_yaw): assert (abs(px[0] - start_x) <= 0.01) assert (abs(py[0] - start_y) <= 0.01) assert (abs(pyaw[0] - start_yaw) <= 0.01) assert (abs(px[-1] - end_x) <= 0.01) assert (abs(py[-1] - end_y) <= 0.01) assert (abs(pyaw[-1] - end_yaw) <= 0.01) def test_1(): start_x = 1.0 # [m] start_y = 1.0 # [m]
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def predict(self, row): pred = self.model.predict(row) return pred def save(self): if self.model is not None: joblib.dump(self.model, Path(__file__).parent / "model_objects" /"ml_model.joblib") else: raise TypeError("There is no model object. Train the model with model.train() first or ensure artifact is the correct uri.") def load(self, artifact_uri): # will try and load an existing trained model artifact if it exists. try: self.model = joblib.load(self.root_path / "mlruns" / "0" / artifact_uri / "artifacts" / "ml_model.joblib") except:
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return data[newFeat],data[['mpg']]
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# (http://stackoverflow.com/a/8720632 and http://stackoverflow.com/a/9459208) bg = Image.new("RGBA", im.size, bg_colour + (255,))
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return all_kmers
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class Command(BaseCommand): help = "Exports a user information as a set of environment variables" def add_arguments(self, parser): parser.add_argument("user_id", type=int) def handle(self, *args, **options): user_id = options["user_id"] user = User.objects.get(id=user_id).bot_user() if not user:
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boo = self._makeOne(__name__='boo') inst = DummyInst() boo.set(inst, 0) self.assertEqual(inst.boo, False)
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'start_date' => Carbon::now(), 'end_date' => Carbon::now()->addYear(1), 'position' => $faker->randomElement(['pa', 'kpa', 'ppk', 'pptk', 'bendahara']), 'status' => 'active' ]; });
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@hello_blueprint.route('/') @hello_blueprint.route('/hello') def index():
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