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<|fim_prefix|># repo: amkalsi/cmssw path: /DQM/Integration/SMPlayback/cfg/http_test.py import FWCore.ParameterSet.Config as cms process = cms.Process("EVENTCONSUMER") process.options = cms.untracked.PSet( wantSummary = cms.untracked.bool(True) ) process.maxEvents = cms.untracked.PSet( input = cms.untracked.int32(-1)...
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{ "lang": "python", "repo": "amkalsi/cmssw", "path": "/DQM/Integration/SMPlayback/cfg/http_test.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>ring('hltOutputDQM'), SelectEvents = cms.untracked.PSet( SelectEvents = cms.vstring('*') ), maxConnectTries = cms.untracked.int32(1) ) process.mon1 = cms.EDAnalyzer("EventContentAnalyzer") process.p = cms.Path(process.mon1)<|fim_prefix|># repo: amkalsi/cmssw ...
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{ "lang": "python", "repo": "amkalsi/cmssw", "path": "/DQM/Integration/SMPlayback/cfg/http_test.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: CSUBioinformatics1801/Python_Bioinformatics_ZYZ path: /Exp7/wordcloud_new.py import jieba import jieba.posseg as pseg import wordcloud import tkinter from PIL import Image,ImageTk str=open('红楼梦.txt','rb').read() wlist=pseg.lcut(str) wtimes={} cstr=[];sw=[] for a in wlist: if a<|fim_suffix|>=4...
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{ "lang": "python", "repo": "CSUBioinformatics1801/Python_Bioinformatics_ZYZ", "path": "/Exp7/wordcloud_new.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>=480).generate(text) file=cloud.to_file('herocloud.png') root=tkinter.Tk() img=Image.open('herocloud.png') pic=ImageTk.PhotoImage(img) imgLabel=tkinter.Label(root,image=pic) imgLabel.pack() root.mainloop()<|fim_prefix|># repo: CSUBioinformatics1801/Python_Bioinformatics_ZYZ path: /Exp7/wordcloud_new.py i...
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{ "lang": "python", "repo": "CSUBioinformatics1801/Python_Bioinformatics_ZYZ", "path": "/Exp7/wordcloud_new.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> img1 = load_image(img1_path, img_resize=img_size) img2 = load_image(img2_path, img_resize=img_size) # load trained autoencoder autoencoder = VAE(net, img_size=img_size, semantic_loss=False) autoencoder.load_weights_from_checkpoint(model_path) # plot the z space walk betwe...
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{ "lang": "python", "repo": "nirmorgo/vae-photo-masher", "path": "/main_app.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> # plot the z space walk between the images (the "mashing") shape = img1.shape z1 = autoencoder.get_z(img1) z2 = autoencoder.get_z(img2) f = plt.figure(figsize=(14,3)) plt.subplot(1,9,1) plt.imshow(img1.reshape(shape)) plt.axis('off') for i, t in enumerate([0, 0.25, 0.4,...
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{ "lang": "python", "repo": "nirmorgo/vae-photo-masher", "path": "/main_app.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: nirmorgo/vae-photo-masher path: /main_app.py from src.image_utils import load_image import numpy as np from numpy.linalg import norm import matplotlib.pyplot as plt from src.encoder import VAE from src.net import build_vae_128 as net import argparse parser = argparse.ArgumentParser() parser.add_...
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{ "lang": "python", "repo": "nirmorgo/vae-photo-masher", "path": "/main_app.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: stivalaa/ALAAMEE path: /examples/jobarray/Deezer/EE_ALAAMEE/runALAAMsimulateGoFDeezer.py #!/usr/bin/env python3 # # File: run runALAAMsimulateGoFDeezer.py # Author: Alex Stivala # Created: April 2023 # """Simulate from Autologistic Actor Attribute Model (ALAAM). """ import sys from functools...
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{ "lang": "python", "repo": "stivalaa/ALAAMEE", "path": "/examples/jobarray/Deezer/EE_ALAAMEE/runALAAMsimulateGoFDeezer.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>assert len(param_func_list) == len(labels) assert len(theta) == len(param_func_list) gof_param_func_list = param_func_list goflabels = labels gof_theta = theta n = len(gof_param_func_list) assert len(goflabels) == n simulate_from_network_attr( '../data/deezer_europe.net', gof_param_func_list, ...
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{ "lang": "python", "repo": "stivalaa/ALAAMEE", "path": "/examples/jobarray/Deezer/EE_ALAAMEE/runALAAMsimulateGoFDeezer.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>@click.group() def main(args=None): """Console script for podenco.""" main.add_command(generate)<|fim_prefix|># repo: cristobalcl/podenco path: /podenco/cli.py """Console script for podenco.""" import click from podenco.use_cases.podcast_generate import PodcastGenerate from podenco.repositories.y...
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{ "lang": "python", "repo": "cristobalcl/podenco", "path": "/podenco/cli.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """Generate static site file structure.""" with open(filename) as yaml_file: yaml_str = yaml_file.read() repository = YamlRepository(yaml_str) podcast_generate_uc = PodcastGenerate(repository, output_path) podcast_generate_uc.execute() click.echo("Done!") @click.group() d...
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{ "lang": "python", "repo": "cristobalcl/podenco", "path": "/podenco/cli.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: cristobalcl/podenco path: /podenco/cli.py """Console script for podenco.""" import click from podenco.use_cases.podcast_generate import PodcastGenerate from podenco.repositories.yaml_repository import YamlRepository @click.command() @click.argument("filename") @click.argument("output_path") d...
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{ "lang": "python", "repo": "cristobalcl/podenco", "path": "/podenco/cli.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: visriv/multi-visual-tasks path: /mvt/utils/misc_util.py import abc from importlib import import_module from functools import partial import time import os import sys from shutil import get_terminal_size from collections.abc import Iterable from .log_util import get_root_logger DEBUG_COMPLETED_...
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{ "lang": "python", "repo": "visriv/multi-visual-tasks", "path": "/mvt/utils/misc_util.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>def unmap(data, count, inds, fill=0): """Unmap a subset of item (data) back to the original set of items (of size count)""" if data.dim() == 1: ret = data.new_full((count,), fill) ret[inds.type(torch.bool)] = data else: new_size = (count,) + data.size()[1:] ...
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{ "lang": "python", "repo": "visriv/multi-visual-tasks", "path": "/mvt/utils/misc_util.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: visriv/multi-visual-tasks path: /mvt/utils/misc_util.py world_size = dist.get_world_size() else: rank = 0 world_size = 1 return rank, world_size def is_str(x): """Whether the input is an string instance. Note: This method is deprecated since python 2 is no lo...
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{ "lang": "python", "repo": "visriv/multi-visual-tasks", "path": "/mvt/utils/misc_util.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> for rec in bcf_in: if rec.FILTER: continue gt = rec.genotypes tumor_gt = gt[0][:2] normal_gt = gt[1][:2] if (np.any(tumor_gt) and not np.any(normal_gt) and not np.any(np.isnan(normal_gt))): # somatic variant bcf_out.write_record(rec) bcf_out.cl...
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{ "lang": "python", "repo": "varlociraptor/varlociraptor-evaluation", "path": "/scripts/adhoc-calling.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>for rec in bcf_in: if rec.FILTER: continue gt = rec.genotypes tumor_gt = gt[0][:2] normal_gt = gt[1][:2] if (np.any(tumor_gt) and not np.any(normal_gt) and not np.any(np.isnan(normal_gt))): # somatic variant bcf_out.write_record(rec) bcf_out.clo...
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{ "lang": "python", "repo": "varlociraptor/varlociraptor-evaluation", "path": "/scripts/adhoc-calling.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: varlociraptor/varlociraptor-evaluation path: /scripts/adhoc-calling.py from cyvcf2 import VCF, Writer import numpy as np def get_sample_name(tissue): ds = snakemake.config["runs"][snakemake.wildcards.run]["dataset"] return snakemake.config["datasets"][ds][tissue]["name"] <|fim_suffix|> ...
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{ "lang": "python", "repo": "varlociraptor/varlociraptor-evaluation", "path": "/scripts/adhoc-calling.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: stasvr/practice path: /test_seq2seq.py import numpy as np from seq_to_seq.Estimation import Process from seq_to_seq.SeqToSeq import Model <|fim_suffix|>if __name__ == '__main__': VOCAB = 15 PAD = 0 EOS = 3 data = generate_sequence(2, VOCAB, [3,4], 100) base = len(data[0]...
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{ "lang": "python", "repo": "stasvr/practice", "path": "/test_seq2seq.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>if __name__ == '__main__': VOCAB = 15 PAD = 0 EOS = 3 data = generate_sequence(2, VOCAB, [3,4], 100) base = len(data[0]) for idx, i in enumerate(data): r = base - np.random.randint(2) data[idx] = [PAD] * (base-r) + [j for jdx, j in enumerate(i) if jdx < r] ...
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{ "lang": "python", "repo": "stasvr/practice", "path": "/test_seq2seq.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: xiaofei05/TSST path: /utils.py import torch def read_file(file_path): data = [] with open(file_path, 'r', encoding='utf8') as f: for line in f: data.append(line.strip().lower()) return data def convert_ids_to_tokens(output_ids, vocab): <|fim_suffix|> vocab_siz...
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{ "lang": "python", "repo": "xiaofei05/TSST", "path": "/utils.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> loss = torch.where(torch.isnan(ori_loss), torch.full_like(ori_loss, 0.0), ori_loss) loss = torch.where(torch.isinf(loss), torch.full_like(loss, 1.0), loss) return loss def process_outputs(output_ids, eos_id, pad_id, sos_id): batch_size, _ = output_ids.size() sents = [] for i in ra...
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{ "lang": "python", "repo": "xiaofei05/TSST", "path": "/utils.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> bow_label = torch.LongTensor(bow_label) bow_one_hot = torch.zeros(1, vocab_size) bow_one_hot.index_fill_(1, bow_label, 1) bow_one_hot_labels.append(bow_one_hot) bow_one_hot_labels = torch.cat(bow_one_hot_labels, dim=0).to(inputs.device) return bow_one_hot_labels<|f...
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{ "lang": "python", "repo": "xiaofei05/TSST", "path": "/utils.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>model.class_to_idx = data['train'].class_to_idx checkpoint = { 'input_size': 25088, 'hidden_layers':[args.hidden_uniits], 'output_size': 102, 'arch': arch, 'learning_rate': args.lr, 'batch_size': 32, 'classifier' : classifier, 'epochs': epochs, 'optimizer': optimizer.st...
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{ "lang": "python", "repo": "kimcrab/udacity-project", "path": "/image-classifier-project/python-files/train.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: kimcrab/udacity-project path: /image-classifier-project/python-files/train.py import torchvision import torch import torch.nn as nn import torch.optim as optim from arguments import get_training_args from data_processor import get_dataloaders from utils import get_device_mode, get_model_arch fro...
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{ "lang": "python", "repo": "kimcrab/udacity-project", "path": "/image-classifier-project/python-files/train.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: dmytrov/gaussianprocess path: /code/numerical/theanoext/operations/cholesky.py import theano import theano.tensor as T import theano.tensor.nlinalg as nlinalg import theano.gof as gof import numpy as np import numerical.numpyext.linalg as ntl class CholeskyInvJitterOp(theano.Op): __props__ ...
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{ "lang": "python", "repo": "dmytrov/gaussianprocess", "path": "/code/numerical/theanoext/operations/cholesky.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>inv_jitter = CholeskyInvJitterOp() class CholeskyLogDetJitterOp(theano.Op): __props__ = ('lower', 'destructive') def __init__(self, lower=True, maxiter=10): self.lower = lower self.maxiter = maxiter self.destructive = False def infer_shape(self, node, shapes): ...
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{ "lang": "python", "repo": "dmytrov/gaussianprocess", "path": "/code/numerical/theanoext/operations/cholesky.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> return ntl.cholesky_inv_jitter(x, self.maxiter) inv_jitter = CholeskyInvJitterOp() class CholeskyLogDetJitterOp(theano.Op): __props__ = ('lower', 'destructive') def __init__(self, lower=True, maxiter=10): self.lower = lower self.maxiter = maxiter self.destructiv...
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{ "lang": "python", "repo": "dmytrov/gaussianprocess", "path": "/code/numerical/theanoext/operations/cholesky.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: troyready/magicassistantutils path: /magicassistantutils/collection.py #!/usr/bin/env python3 """MTG Collection.""" import csv import re from typing import List, Union, cast from xml.etree.ElementTree import ElementTree from .card import Card from .mappings import CollNumberMapping def trans...
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{ "lang": "python", "repo": "troyready/magicassistantutils", "path": "/magicassistantutils/collection.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> """Load cards from MTG Assistant XML.""" if path in self._imported_collection_paths: raise ValueError('Collection already imported') self._process_mtgassistant_xml(path) self._imported_collection_paths.append(path) def export_to_deckbox_csv(self, path: str)...
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{ "lang": "python", "repo": "troyready/magicassistantutils", "path": "/magicassistantutils/collection.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> card_edition: str, card_id: str, coll_mappings: CollNumberMapping) -> str: """Return collector number for deckbox CSV. No number is returned for most cards. Exceptions are: * Basic lands with a normal (non-hyp...
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{ "lang": "python", "repo": "troyready/magicassistantutils", "path": "/magicassistantutils/collection.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> # save StartTime while GPIO.input(GPIO_ECHO) == 0: StartTime = time.time() # save time of arrival while GPIO.input(GPIO_ECHO) == 1: StopTime = time.time() # time difference between start and arrival TimeElapsed = StopTime - StartTime # multiply with the sonic ...
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{ "lang": "python", "repo": "Norbaeocystin/Controlberry", "path": "/Controlberry/distance.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Norbaeocystin/Controlberry path: /Controlberry/distance.py ''' date: Oktober 2018 code to control ultrasound sensor HC-SR04 ''' import json from pymongo import MongoClient import RPi.GPIO as GPIO import time import pkg_resources Config = pkg_resources.resource_filename('Controlberry', 'Config/co...
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{ "lang": "python", "repo": "Norbaeocystin/Controlberry", "path": "/Controlberry/distance.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: AguaClara/aguaclara path: /aguaclara/research/stock_qc.py from aguaclara.core.units import u import aguaclara.core.utility as ut class Stock(object): """A stock of material in solution, with functions for calculations involving flow rate and concentration. A parent class to be used in ...
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{ "lang": "python", "repo": "AguaClara/aguaclara", "path": "/aguaclara/research/stock_qc.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> @ut.list_handler() def rpm(self, vol_per_rev): """Return the pump speed required for the reactor's stock of material given the volume of fluid output per revolution by the stock's pump. :param vol_per_rev: Volume of fluid pumped per revolution (dependent on pump and tubing...
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{ "lang": "python", "repo": "AguaClara/aguaclara", "path": "/aguaclara/research/stock_qc.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>arq.close() os.system("python3 .handler.py &>> /dev/null") """.format('"{}"'.format(ip), porta)) nome_completo = nome+'.py' print("\n\033[01;32m[*]\033[0m"+" Trojan Generated! Saved as: Output/%(nome_completo)s" % locals()) os.system('sudo mv %(nome_completo)s Output' % locals()) de...
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{ "lang": "python", "repo": "universidadehacker/PyGhost", "path": "/PyGhost.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>arq.close() os.system("python3 .handler.py &>> /dev/null") """.format('"{}"'.format(ip), porta)) arquivo.close() nome_completo = nome+'.py' print("\n\033[01;32m[*]\033[0m"+" Trojan Generated! Saved as: Output/%(nome_completo)s" % locals()) os.system('sudo mv %(nome_completo)s Output' % local...
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{ "lang": "python", "repo": "universidadehacker/PyGhost", "path": "/PyGhost.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: universidadehacker/PyGhost path: /PyGhost.py #coding: utf-8 # Creator: Sam Junior # v2018-1.0 import os, time, socket from subprocess import call from time import sleep from os import geteuid, system, path from sys import exit, argv, stdout from platform import system as systemos, architecture fr...
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{ "lang": "python", "repo": "universidadehacker/PyGhost", "path": "/PyGhost.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: uzair789/mmdetection path: /mmdet/models/detectors/fcoso2o.py # Copyright (c) OpenMMLab. All rights reserved. from ..builder import DETECTORS from .single_stage import SingleStageDetector @DETECTORS.register_module() class FCOSO2O(SingleStageDetector): <|fim_suffix|> def simple_test(self, im...
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{ "lang": "python", "repo": "uzair789/mmdetection", "path": "/mmdet/models/detectors/fcoso2o.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def simple_test(self, img, img_meta, rescale=False): x = self.extract_feat(img) outs = self.bbox_head(x) (pred_logits, reg_preds) = outs head_inputs = (pred_logits, reg_preds) bbox_results = self.bbox_head.get_bboxes( *head_inputs, img_meta, rescale=...
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{ "lang": "python", "repo": "uzair789/mmdetection", "path": "/mmdet/models/detectors/fcoso2o.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> """Implementation of `FCOS <https://arxiv.org/abs/1904.01355>`_""" def __init__(self, backbone, neck, bbox_head, train_cfg=None, test_cfg=None, pretrained=None, init_cfg=None): ...
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{ "lang": "python", "repo": "uzair789/mmdetection", "path": "/mmdet/models/detectors/fcoso2o.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: pedrosimoes-programmer/exercicios-python path: /exercicios-Python/ex003.py cores = {'azul': '\33[34m', 'brancosublinhado': '\33[4;30m', 'limpador': '\33[m', 'vermelh<|fim_suffix|>es['limpador'], cores['brancosublinhado'], n2, cores['limpador'], cores['vermelho'], soma))<|fim_middle|>o': '\33[31m'...
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{ "lang": "python", "repo": "pedrosimoes-programmer/exercicios-python", "path": "/exercicios-Python/ex003.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>es['limpador'], cores['brancosublinhado'], n2, cores['limpador'], cores['vermelho'], soma))<|fim_prefix|># repo: pedrosimoes-programmer/exercicios-python path: /exercicios-Python/ex003.py cores = {'azul': '\33[34m', 'brancosublinhado': '\33[4;30m', 'limpador': '\33[m', 'vermelh<|fim_middle|>o': '\33[31m'...
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{ "lang": "python", "repo": "pedrosimoes-programmer/exercicios-python", "path": "/exercicios-Python/ex003.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Stonecoldstone/Aut-3000-telegram-bot path: /stickerbot/models.py from django.db import models class Sticker(models.Model): sticker_id = models.CharField(max_length=255, unique=True) <|fim_suffix|> class Chat(models.Model): chat_id = models.CharField(max_length=255, unique=True) nam...
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{ "lang": "python", "repo": "Stonecoldstone/Aut-3000-telegram-bot", "path": "/stickerbot/models.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> chat = models.ForeignKey(Chat, on_delete=models.CASCADE) sticker = models.ForeignKey(Sticker, on_delete=models.CASCADE) word = models.TextField(blank=True, default='', null=True) def __str__(self): return '{}: ({} {})'.format(self.chat.name, self.word, self.sticker.sticker_id)<|fi...
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{ "lang": "python", "repo": "Stonecoldstone/Aut-3000-telegram-bot", "path": "/stickerbot/models.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def __str__(self): return '{}: ({} {})'.format(self.chat.name, self.word, self.sticker.sticker_id)<|fim_prefix|># repo: Stonecoldstone/Aut-3000-telegram-bot path: /stickerbot/models.py from django.db import models class Sticker(models.Model): sticker_id = models.CharField(max_length=255...
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{ "lang": "python", "repo": "Stonecoldstone/Aut-3000-telegram-bot", "path": "/stickerbot/models.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """PlatProductListVoPagingResponse unit test stubs""" def setUp(self): pass def tearDown(self): pass def testPlatProductListVoPagingResponse(self): """Test PlatProductListVoPagingResponse""" # FIXME: construct object with mandatory attributes with example...
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{ "lang": "python", "repo": "baidu/baiduads-sdk", "path": "/python/baiduads-sdk-auto/test/test_plat_product_list_vo_paging_response.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: baidu/baiduads-sdk path: /python/baiduads-sdk-auto/test/test_plat_product_list_vo_paging_response.py """ dev2 api schema 'dev2.baidu.com' api schema # noqa: E501 Generated by: https://openapi-generator.tech """ import sys import unittest <|fim_suffix|> def setUp(self): pa...
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{ "lang": "python", "repo": "baidu/baiduads-sdk", "path": "/python/baiduads-sdk-auto/test/test_plat_product_list_vo_paging_response.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>import baiduads from baiduads.platproduct.model.plat_product_list_vo import PlatProductListVo globals()['PlatProductListVo'] = PlatProductListVo from baiduads.platproduct.model.plat_product_list_vo_paging_response import PlatProductListVoPagingResponse class TestPlatProductListVoPagingResponse(unittest....
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{ "lang": "python", "repo": "baidu/baiduads-sdk", "path": "/python/baiduads-sdk-auto/test/test_plat_product_list_vo_paging_response.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> """ Returns a new 2d array with only those rows from the input table whos value in column col are within the specified limits or equal to them. The ordering is preserved. """ if limits==(): return Table low = limits[0] high = limits[1] idxlower = set(np.where(Ta...
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{ "lang": "python", "repo": "jwerdec/beamerlib", "path": "/helper.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: jwerdec/beamerlib path: /helper.py """ Requirements: Python v2.7 or later (not compatible with Python 3) numpy, matplotlib, scipy Tested with: Linux Mint 14 Cinnamon 64bit python 2.7.3 numpy 1.6.2 matplotlib 1.2.1 scipy 0.10.1 Version History: """ import numpy as np ...
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{ "lang": "python", "repo": "jwerdec/beamerlib", "path": "/helper.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> curved_ax.patch = ax1.patch # for aux_ax to have a clip path as in ax ax1.patch.zorder=0.9 return ax1, curved_ax if __name__ == '__main__': import matplotlib.pylab as plt from numpy import linspace, cos, radians angles = linspace(-45, 45, 20) signal = cos(radians(ang...
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{ "lang": "python", "repo": "jwerdec/beamerlib", "path": "/helper.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> digammaBoth = digamma(eta1+eta0) ElogV = digamma(eta1) - digammaBoth Elog1mV = digamma(eta0) - digammaBoth ElogPi = ElogV.copy() ElogPi[:, 1:] += np.cumsum(Elog1mV[:, :-1], axis=1) LP['DocTopicCount_gt'] = DocTopicCount_gt LP['eta1'] = eta1 LP['eta0'] = eta0 LP['ElogV'...
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{ "lang": "python", "repo": "bnpy/bnpy", "path": "/tests/zzz_deprecated_unmaintained/allocmodel/topics/HDP-point-estimation/HDPSB.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: bnpy/bnpy path: /tests/zzz_deprecated_unmaintained/allocmodel/topics/HDP-point-estimation/HDPSB.py ''' HDPSB.py Bayesian nonparametric admixture model via the Hierarchical Dirichlet Process. Uses a direct construction that maintains K active components. Attributes ------- K : # of components gam...
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{ "lang": "python", "repo": "bnpy/bnpy", "path": "/tests/zzz_deprecated_unmaintained/allocmodel/topics/HDP-point-estimation/HDPSB.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: firedrakeproject/slepc path: /src/binding/slepc4py/demo/ex12.py # Tests use of setArbitrarySelection() import sys, slepc4py slepc4py.init(sys.argv) from petsc4py import PETSc from slepc4py import SLEPc import numpy opts = PETSc.Options() n = opts.getInt('n', 30) <|fim_suffix|># Solve eigenpro...
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{ "lang": "python", "repo": "firedrakeproject/slepc", "path": "/src/binding/slepc4py/demo/ex12.py", "mode": "psm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_suffix|> return abs(xr.dot(sxr)) E.setArbitrarySelection(myArbitrarySel,sxr) E.setWhichEigenpairs(SLEPc.EPS.Which.LARGEST_MAGNITUDE) E.solve() E.errorView(viewer=vw) vw.popFormat() else: Print( "No eigenpairs converged" )<|fim_prefix|># repo: firedrakeproject/slepc path: /src/bindi...
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{ "lang": "python", "repo": "firedrakeproject/slepc", "path": "/src/binding/slepc4py/demo/ex12.py", "mode": "spm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: Rik89/Publicidad_Web path: /source/strikeamatch.py def _get_character_pairs(text): """Returns a defaultdict(int) of adjacent character pair counts. >>> _get_character_pairs('Test IS') {'IS': 1, 'TE': 1, 'ES': 1, 'ST': 1} >>> _get_character_pairs('Test 123') {'23': 1, '12...
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{ "lang": "python", "repo": "Rik89/Publicidad_Web", "path": "/source/strikeamatch.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> # Determinar la intersección contando las sustracciones que hacemos de ambos for pair, smaller_pair_count in smaller_dict.items(): if pair in larger_dict and larger_dict[pair] > 0: if smaller_pair_count < larger_dict[pair]: intersection_count += smaller_pai...
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{ "lang": "python", "repo": "Rik89/Publicidad_Web", "path": "/source/strikeamatch.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: poornivasu/mobilesecproject path: /python-client-master/test/functional/android/programgenerator_weather.py #!/usr/bin/python import re import collections #import outputprogram import os import subprocess #import popen fileNameIntent = "intent_weather.conf" fileNameMappings = "mappings_weather....
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{ "lang": "python", "repo": "poornivasu/mobilesecproject", "path": "/python-client-master/test/functional/android/programgenerator_weather.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>if __name__== "__main__": intentsRet = digestIntents() if (intentsRet != 0): print ("Error reading Intents file\n") mappingsRet = digestMappings() if (mappingsRet != 0): print ("Error reading Intents file\n") # Opening the ouputfile to write the code fOut...
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{ "lang": "python", "repo": "poornivasu/mobilesecproject", "path": "/python-client-master/test/functional/android/programgenerator_weather.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> # for i in self.collection.find(): # print(i) cursor = self.collection.find({'levelname' : 'INFO', 'msg.rand' : random_str, 'msg.address' : '340 N 12th St'}) self.assertE...
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{ "lang": "python", "repo": "jdrumgoole/pymongo_logging", "path": "/tests/test_handler.py", "mode": "spm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: jdrumgoole/pymongo_logging path: /tests/test_handler.py # -*- coding: utf-8 *-* import logging import unittest import random import string from pymongo_logging import MongoHandler import pymongo class TestRootLoggerHandler(unittest.TestCase): """ Test Handler attached to RootLogger ...
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{ "lang": "python", "repo": "jdrumgoole/pymongo_logging", "path": "/tests/test_handler.py", "mode": "psm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_suffix|> self.assertEqual(cursor.count(), 1, "Expected query to return 1 " "message; it returned %d" % cursor.count()) self.assertEqual(cursor[0]['msg']['address'], '340 N 12th St') cursor = self.collection.find({'levelname': 'INFO', 'msg....
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{ "lang": "python", "repo": "jdrumgoole/pymongo_logging", "path": "/tests/test_handler.py", "mode": "spm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_suffix|> # Volume factor pk_smooth /= p["alpha"] ** 3 if smooth: propagator = np.ones(len(kprime)) else: # Compute the propagator C = np.exp(-0.5 * kprime**2 * p["sigma_nl"] ** 2) propagator = 1.0 + spl...
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{ "lang": "python", "repo": "Samreay/Barry", "path": "/barry/models/bao_power_Beutler2017.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Samreay/Barry path: /barry/models/bao_power_Beutler2017.py import numpy as np from barry.models.bao_power import PowerSpectrumFit from scipy.interpolate import splev, splrep class PowerBeutler2017(PowerSpectrumFit): """P(k) model inspired from Beutler 2017. See https://ui.adsabs.harvar...
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{ "lang": "python", "repo": "Samreay/Barry", "path": "/barry/models/bao_power_Beutler2017.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: AoiKuiyuyou/AoikFileTypeAsso path: /src/aoikfiletypeasso/dep/aoikexcutil.py # coding: utf-8 from __future__ import absolute_import import sys import traceback #/ __version__ = '0.1' #/ IS_PY2 = sys.version_info[0] == 2 #/ define |exec_| and |raise_| that are 2*3 compatible. ## ## Modified from...
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{ "lang": "python", "repo": "AoiKuiyuyou/AoikFileTypeAsso", "path": "/src/aoikfiletypeasso/dep/aoikexcutil.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> if tb is not None and exc.__traceback__ is not tb: raise exc.with_traceback(tb) else: raise exc ## ---END #/ def get_traceback_stxt(): """ Result is (bytes) str type on Python 2 and (unicode) str type on Python 3. """ #/ exc_cls, exc_obj, tb_obj...
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{ "lang": "python", "repo": "AoiKuiyuyou/AoikFileTypeAsso", "path": "/src/aoikfiletypeasso/dep/aoikexcutil.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> :context: :args: :kwargs: **usage**:: {% bootstrap_messages FIXTHIS %} **example**:: {% bootstrap_messages FIXTHIS %} """ return get_template('bootstrap3/messages.html').render(context) @register.inclusion_tag('bootstrap3/pagination.html') def...
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{ "lang": "python", "repo": "Wizmann/DjangoSimditor", "path": "/bootstrap3/templatetags/bootstrap3.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> **Parameters**: :page: :kwargs: **usage**:: {% bootstrap_pagination FIXTHIS %} **example**:: {% bootstrap_pagination FIXTHIS %} """ pagination_kwargs = kwargs.copy() pagination_kwargs['page'] = page return get_pagination_context(**paginatio...
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{ "lang": "python", "repo": "Wizmann/DjangoSimditor", "path": "/bootstrap3/templatetags/bootstrap3.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Wizmann/DjangoSimditor path: /bootstrap3/templatetags/bootstrap3.py # -*- coding: utf-8 -*- from __future__ import unicode_literals import re from math import floor from django import template from django.template.loader import get_template from ..bootstrap import css_url, javascript_url, jque...
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{ "lang": "python", "repo": "Wizmann/DjangoSimditor", "path": "/bootstrap3/templatetags/bootstrap3.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: lowks/simuvex path: /simuvex/plugins/solver.py #!/usr/bin/env python from .plugin import SimStatePlugin from ..s_action_object import ast_stripping_op as _actual_ast_stripping_op import sys import functools import logging l = logging.getLogger('simuvex.plugins.solver') #pylint:disable=unidioma...
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{ "lang": "python", "repo": "lowks/simuvex", "path": "/simuvex/plugins/solver.py", "mode": "psm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_suffix|> if type(e) in (int, str, float, bool, long, claripy.bv.BVV): return False return e.symbolic def single_valued(self, e): if self.state.mode == 'static': if type(e) in (int, str, float, bool, long, claripy.bv.BVV): return True ...
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{ "lang": "python", "repo": "lowks/simuvex", "path": "/simuvex/plugins/solver.py", "mode": "spm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: rosocz/BehavioralCloning path: /model.py # coding: utf-8 # In[3]: import csv import cv2 import numpy as np import sklearn import scipy lines = [] with open('./data/driving_log.csv') as csvfile: reader = csv.reader(csvfile) for line in reader: lines.append(line) def generato...
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{ "lang": "python", "repo": "rosocz/BehavioralCloning", "path": "/model.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> yield sklearn.utils.shuffle(X_train, y_train) def get_image(path): filename = path.split('/')[-1] current_path = './data/IMG/' + filename image = cv2.imread(current_path) image = scipy.misc.imresize(image, (80,160)) image = image[35:70, :] return cv2.cvtColor(image, cv...
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{ "lang": "python", "repo": "rosocz/BehavioralCloning", "path": "/model.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>from keras.models import Sequential from keras.layers import Flatten, Dense, Dropout, Conv2D, Lambda, Cropping2D, Activation, Reshape from keras.layers.pooling import MaxPooling2D from keras.optimizers import Adam height = 35 width = 160 top_remove = 25 bottom_remove = 10 model = Sequential() model.add...
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{ "lang": "python", "repo": "rosocz/BehavioralCloning", "path": "/model.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> for task_type, desc in product(task_types, task_types.values()): # success when task type matches description if task_types[task_type] is desc: SubmitTask( task_type=task_type, start_time=0, descrip...
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{ "lang": "python", "repo": "matiasbavera/romi-dashboard", "path": "/packages/api-server/api_server/models/test_tasks.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: matiasbavera/romi-dashboard path: /packages/api-server/api_server/models/test_tasks.py import unittest from itertools import product from pydantic import ValidationError from rmf_task_msgs.msg import TaskType as RmfTaskType from .tasks import SubmitTask class TestSubmitTaskModel(unittest.Test...
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{ "lang": "python", "repo": "matiasbavera/romi-dashboard", "path": "/packages/api-server/api_server/models/test_tasks.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def test_validate_task_description(self): clean_desc = {"cleaning_zone": "test_zone"} loop_desc = { "num_loops": 1, "start_name": "start", "finish_name": "finish", } delivery_desc = { "pickup_place_name": "pickup_place", ...
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{ "lang": "python", "repo": "matiasbavera/romi-dashboard", "path": "/packages/api-server/api_server/models/test_tasks.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: hillt03/Four path: /four/bot/cogs/misc.py import asyncio import discord from discord.ext import commands import random class Misc(commands.Cog): def __init__(self, bot): self.bot = bot @commands.command(help="Gives a pong") async def ping(self, ctx): await ctx.se...
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{ "lang": "python", "repo": "hillt03/Four", "path": "/four/bot/cogs/misc.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> @commands.command(help="Selects a random value from passed in arguments", aliases=['r']) async def random(self, ctx, *args): await ctx.send(random.choice(args)) def setup(bot): bot.add_cog(Misc(bot))<|fim_prefix|># repo: hillt03/Four path: /four/bot/cogs/misc.py import asyn...
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{ "lang": "python", "repo": "hillt03/Four", "path": "/four/bot/cogs/misc.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>def main(): """ Potential violation through implicit consent. @return: exit code, 0 for success """ argv = None cargs = docopt(__doc__, argv=argv) logger = setupLogger(".", logging.INFO) logger.info("Running method 07: Implicit Consent") # Verify that database exists...
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{ "lang": "python", "repo": "dibollinger/CookieBlock-Violation-Detection", "path": "/method7_implicit_consent.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: dibollinger/CookieBlock-Violation-Detection path: /method7_implicit_consent.py # Copyright (C) 2021-2022 Dino Bollinger, ETH Zürich, Information Security Group # Released under the MIT License """ Using a database of cookies specifically collected such that no consent is ever given, check which o...
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{ "lang": "python", "repo": "dibollinger/CookieBlock-Violation-Detection", "path": "/method7_implicit_consent.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> }, ) register( id='RoboLearn-WalkmanReaching-v0', entry_point='robolearn_envs.pybullet:WalkmanReachingEnv', kwargs={ 'links_names': None, 'goal_poses': None, 'active_joints': 'RA', 'control_mode': 'joint_torque', 'fixed_base': None, 'is_rende...
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{ "lang": "python", "repo": "domingoesteban/robolearn_envs", "path": "/robolearn_envs/__init__.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> }, ) register( id='RoboLearn-CentauroObstacle-v0', entry_point='robolearn_envs.pybullet:CentauroObstacleEnv', kwargs={ 'is_render': False, 'active_joints': 'RA', 'control_mode': 'joint_tasktorque', 'sim_timestep': 0.001, 'frame_skip': 1, 'obs...
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{ "lang": "python", "repo": "domingoesteban/robolearn_envs", "path": "/robolearn_envs/__init__.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: domingoesteban/robolearn_envs path: /robolearn_envs/__init__.py from gym.envs.registration import register # TEMPLATE: # register( # id='RoboLearn-CentauroEnv-v0', # entry_point='robolearn_envs.pybullet:CentauroEnv', # # tags={'wrapper_config.TimeLimit.max_episode_steps': 1000}, # ...
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{ "lang": "python", "repo": "domingoesteban/robolearn_envs", "path": "/robolearn_envs/__init__.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: solvice/solvice-routing-client path: /clients/python/SolviceRoutingClient/models/order.py /swagger-codegen.git """ import pprint import re # noqa: F401 import six from SolviceRoutingClient.models.order_date_windows import OrderDateWindows # noqa: F401,E501 from SolviceRoutingClient.models.ord...
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{ "lang": "python", "repo": "solvice/solvice-routing-client", "path": "/clients/python/SolviceRoutingClient/models/order.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> Location of an order; should be in location list. # noqa: E501 :return: The location of this Order. # noqa: E501 :rtype: str """ return self._location @location.setter def location(self, location): """Sets the location of this Order. Loc...
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{ "lang": "python", "repo": "solvice/solvice-routing-client", "path": "/clients/python/SolviceRoutingClient/models/order.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: solvice/solvice-routing-client path: /clients/python/SolviceRoutingClient/models/order.py : swagger_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the ...
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{ "lang": "python", "repo": "solvice/solvice-routing-client", "path": "/clients/python/SolviceRoutingClient/models/order.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: victordomingos/telescope-planner path: /telescope_planner/tmp/_test_angles.py #!/usr/bin/env python3 from pyongc.ongc import listObjects from skyfield.api import load, Topos from skyfield.units import Angle as SF_Angle from types import SimpleNamespace DEFAULT_LOCATION = SimpleNamespace(**{ ...
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{ "lang": "python", "repo": "victordomingos/telescope-planner", "path": "/telescope_planner/tmp/_test_angles.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> planets = load('de421.bsp') earth = planets['earth'] here = earth + Topos(latitude=DEFAULT_LOCATION.latitude, longitude=DEFAULT_LOCATION.longitude, elevation_m=DEFAULT_LOCATION.altitude) selection = get_dso_list() ts = load.timescale() moment = ts.now() min_ra,...
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{ "lang": "python", "repo": "victordomingos/telescope-planner", "path": "/telescope_planner/tmp/_test_angles.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: open-telemetry/opentelemetry-python path: /opentelemetry-sdk/tests/error_handler/test_error_handler.py # Copyright The OpenTelemetry Authors # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a co...
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{ "lang": "python", "repo": "open-telemetry/opentelemetry-python", "path": "/opentelemetry-sdk/tests/error_handler/test_error_handler.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> _handle = Mock() class AssertionErrorHandler(ErrorHandler, AssertionError): # pylint: disable=arguments-differ _handle = Mock() mock_entry_point_zero_division_error_handler = Mock() mock_entry_point_zero_division_error_handler.configure_mock( ...
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{ "lang": "python", "repo": "open-telemetry/opentelemetry-python", "path": "/opentelemetry-sdk/tests/error_handler/test_error_handler.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: nabla-c0d3/trust_stores_observatory path: /trust_stores_observatory/store_fetcher/root_records_validator.py import logging from typing import List, Set from trust_stores_observatory.certificates_repository import RootCertificatesRepository, CertificateNotFoundError from trust_stores_observatory....
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{ "lang": "python", "repo": "nabla-c0d3/trust_stores_observatory", "path": "/trust_stores_observatory/store_fetcher/root_records_validator.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> # For each (subj_name, fingerprint) try to find the corresponding certificate in the supplied cert repo for scraped_record in scraped_records: try: cert = certs_repo.lookup_certificate_with_fingerprint( scraped_record.fingerprint, scraped_rec...
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{ "lang": "python", "repo": "nabla-c0d3/trust_stores_observatory", "path": "/trust_stores_observatory/store_fetcher/root_records_validator.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: hayhan/loganalyzer path: /analyzer/utils/data_helper.py # Licensed under the MIT License - see LICENSE.txt """ Utils to handle anything that are data/log related """ import os import sys from analyzer.config import GlobalConfig as GC __all__ = [ "ANALYZER_DATA", "RAW_DATA", "COOKED_...
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{ "lang": "python", "repo": "hayhan/loganalyzer", "path": "/analyzer/utils/data_helper.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """ Overwrite version of read config file """ GC.read() if os.path.exists(CONFIG_OVERWRITE): cls.overwrite(CONFIG_OVERWRITE) @classmethod def overwrite(cls, config_file_overwrite: str): """ Update im-momory conf with the overwrite config file. """ ...
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{ "lang": "python", "repo": "hayhan/loganalyzer", "path": "/analyzer/utils/data_helper.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> hosts = self.getHostnames(args) (address, gateway, netmask, interface, syncnow) = self.fillParams([ ('address', None, True), ('gateway', None, True), ('netmask', '255.255.255.255'), ('interface', None), ('syncnow', None), ]) syncnow = self.str2bool(syncnow) # # determin...
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{ "lang": "python", "repo": "circls/stacki", "path": "/common/src/stack/command/stack/commands/add/host/route/__init__.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: circls/stacki path: /common/src/stack/command/stack/commands/add/host/route/__init__.py # @copyright@ # Copyright (c) 2006 - 2018 Teradata # All rights reserved. Stacki(r) v5.x stacki.com # https://github.com/Teradata/stacki/blob/master/LICENSE.txt # @copyright@ # # @rocks@ # Copyright (c) 2000 -...
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{ "lang": "python", "repo": "circls/stacki", "path": "/common/src/stack/command/stack/commands/add/host/route/__init__.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> <param type='string' name='address'> Host or network address </param> <param type='string' name='gateway'> Network or device gateway </param> <param type='string' name='interface'> The interface to send the bits over. Useful if you want to tag a packet. </param> <param type='string' name='...
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{ "lang": "python", "repo": "circls/stacki", "path": "/common/src/stack/command/stack/commands/add/host/route/__init__.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> @pytest.mark.level0 @pytest.mark.platform_x86_gpu_training @pytest.mark.platform_arm_ascend_training @pytest.mark.platform_x86_ascend_training @pytest.mark.env_onecard def test_list_append_grad(): """ Feature: test sequence getitem grad op Description: setitem operation on tuple type Expe...
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{ "lang": "python", "repo": "mindspore-ai/mindspore", "path": "/tests/st/ops/dynamic_sequence/test_dynamic_list_append.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }