id stringlengths 3 8 | content stringlengths 100 981k |
|---|---|
4842794 | from django.contrib import admin
from extrequests.models import DataVariant
admin.site.register(DataVariant)
|
4842798 | from ctypes import *
import numpy_allocator
std = CDLL(None)
std.free.argtypes = [c_void_p]
std.free.restype = None
std.memalign.argtypes = [c_size_t, c_size_t]
std.memalign.restype = c_void_p
std.memcpy.argtypes = [c_void_p, c_void_p, c_size_t]
std.memcpy.restype = c_void_p
std.memset.argtypes = [c_void_p, c_int,... |
4842801 | from functools import partial
import numpy as np
from scipy.special import gammainc
from sklearn.neighbors import KernelDensity
from sklearn.utils.extmath import row_norms
from sklearn.utils import check_random_state
from sklearn.model_selection import GridSearchCV
from scipy.stats import multivariate_normal
from mel... |
4842809 | import logging
log = logging.getLogger(__name__)
class NamesMixin(object):
@classmethod
def _flatten_names(cls, collection, data):
if not data or 'names' not in data:
return False
identifiers = data.get('identifiers', {}).get(collection.target, {})
# Flatten "names" attr... |
4842868 | import pymongo.results
import pytest
from aiohttp.test_utils import make_mocked_coro
import virtool.db.core
import virtool.utils
@pytest.fixture
def create_test_collection(mocker, test_motor):
def func(
name="samples", projection=None, silent=False
) -> virtool.db.core.Collection:
processor =... |
4842891 | import numpy as np
from .convertors import default_missing_data_literal
from .lazy_result import LazyArrayResult, LazyStructOfVecResult
from .pyweld import WeldVec, WeldChar, WeldLong, WeldObject
from .weld_utils import get_weld_obj_id, create_weld_object, to_weld_literal, create_empty_weld_object, \
weld_arrays_t... |
4842892 | from ..system import System
from ..utils import Utils
from matplotlib import rcParams
"""
@desc: Class for plotting and visualisation of network and experiment data
"""
class Plot():
"""
@desc: Initiates plot object, gets relation to another object for getting the data
"""
def __init__(self, rel):
... |
4842949 | from django.http import HttpResponse
from tastypie import fields, http
from tastypie.resources import NamespacedModelResource as ModelResource
from tastypie.authentication import ApiKeyAuthentication, SessionAuthentication, MultiAuthentication
from tastypie_oauth.authentication import OAuth2ScopedAuthentication
from ta... |
4843033 | from django.conf import settings
from django.core.exceptions import ImproperlyConfigured
from parler import appsettings as parler_appsettings
from parler.utils import is_supported_django_language, normalize_language_code
if "categories" in settings.INSTALLED_APPS:
# old django-categories style. Keep first for back... |
4843054 | import os
import json
from django.http import HttpResponse
from django.template import RequestContext
from django.shortcuts import render
from logtailer.models import LogsClipboard, LogFile
from django.utils.translation import ugettext as _
from django.views.decorators.csrf import csrf_exempt
from django.contrib.admin.... |
4843073 | from tracker import Tracker
t = Tracker()
def test_numbers_3_4():
data = t.track("EO430454377IN")
assert data != None
|
4843089 | from dataclasses import dataclass, field
from enum import Enum
from unittest import TestCase
from dataclass_factory import Factory, InvalidFieldError
@dataclass
class Foo:
a: int
b: int = field(init=False, default=1)
c: str = "def_value"
class MyEnum(Enum):
one = 1
hello = "hello"
@dataclass
... |
4843119 | code_container = {'borderLeft': 'thin #C8D4E3 solid'}
container_padding_bottom = {
'padding': 0,
'paddingBottom': '15px'
}
notebox = {
'width': '90%',
'margin': '0 auto',
'border': '1px solid lightgrey',
'textAlign': 'center',
'borderRadius': '5px',
'backgroundColor': 'lightgrey'
}
|
4843142 | from model.u_net import get_unet_128, get_unet_256, get_unet_512, get_unet_1024
input_size = 128
max_epochs = 100
batch_size = 16
orig_width = 1918
orig_height = 1280
threshold = 0.5
model_factory = get_unet_128
|
4843201 | import random
import pandas as pd
from pandas import Series
from src.cache.cache import put_labelled_logs
from src.encoding.common import get_encoded_logs, retrieve_proper_encoder
from src.explanation.models import Explanation
from src.jobs.tasks import prediction_task
from src.logs.models import Log
from src.runtim... |
4843214 | import os.path as osp
import glob
import numpy as np
import neuron.ops as ops
from neuron.config import registry
from .dataset import SeqDataset
__all__ = ['DTB70']
@registry.register_module
class DTB70(SeqDataset):
"""`DTB70 <https://github.com/flyers/drone-tracking>`_ Dataset.
Publication:
``Vis... |
4843230 | import qiskit
import os
import shutil
if __name__ == '__main__':
path = os.path.abspath(qiskit.__file__)
print(path)
# path for aer provider
path_provider = path.replace('__init__.py',
'providers/aer/backends/aerbackend.py')
print(path_provider)
fixed_file = './... |
4843291 | import sys
import imp
import os
from six import iteritems
from enum import IntEnum
from contextlib import contextmanager
import json
def get_so_paths(dir_name):
dir_name = os.path.join(os.path.dirname(__file__), dir_name)
list_dir = os.listdir(dir_name) if os.path.isdir(dir_name) else []
return [os.path.j... |
4843301 | from __future__ import print_function
board = []
size = 8
def danger(row, col):
""" Return if there is a danger by placing queen in
a given row, col
"""
for (i, j) in board:
if row == i: return True
if col == j: return True
if abs(row - i) == abs(col - j): return True
r... |
4843319 | import torch
from torch.optim.optimizer import Optimizer
class Vadam(Optimizer):
"""
Implementation of Vadam: https://arxiv.org/pdf/1806.04854.pdf
Based on: https://github.com/emtiyaz/vadam
Arguments:
params (iterable): iterable of parameters to optimize or dicts defining
p... |
4843322 | import os
from subprocess import call
import sys, time
# Job id and gpu_id
if len(sys.argv) > 2:
job_id = int(sys.argv[1])
gpu_id = str(sys.argv[2])
print('job_id: {}, gpu_id: {}'.format(job_id, gpu_id))
elif len(sys.argv) > 1:
job_id = int(sys.argv[1])
gpu_id = '0'
print('job_id: {}, missing g... |
4843332 | from __future__ import division, absolute_import, print_function
import os
import sys
import re
__all__ = ['uses_accelerate_framework', 'get_sgemv_fix']
def uses_accelerate_framework(info):
""" Returns True if Accelerate framework is used for BLAS/LAPACK """
# If we're not building on Darwin (macOS), don't u... |
4843375 | from typing import Callable, Optional, Any
from thinc.layers.pytorchwrapper import forward as pt_forward
from thinc.layers.pytorchwrapper import convert_pytorch_default_inputs, convert_pytorch_default_outputs
from thinc.api import registry, Model
from .hf_shim import HFShim
@registry.layers("HFWrapper.v1")
def HFWr... |
4843378 | from __future__ import annotations
from typing import Any, Iterable, TypeVar, overload
from typing_extensions import get_args, get_origin
import inspect
from magicgui.widgets import create_widget, Container, PushButton
from magicgui.widgets._bases.value_widget import UNSET, ValueWidget
_V = TypeVar("_V")
class Li... |
4843411 | import flexmock
import pytest
import requests
from argo.workflows.client import ApiClient
from argo.workflows.client.models import (
V1alpha1CronWorkflow,
V1alpha1Parameter,
V1alpha1Template,
V1Container,
)
from argo.workflows.dsl import CronWorkflow
from argo.workflows.dsl.tasks import dependencies, ... |
4843420 | from django.test import TestCase
from dcim.models import Site
class NaturalOrderByManagerTest(TestCase):
"""
Ensure consistent natural ordering given myriad sample data. We use dcim.Site as our guinea pig because it's simple.
"""
def setUp(self):
return
def evaluate_ordering(self, names... |
4843424 | from django.shortcuts import render
from .service import GitHub
from django.conf import settings
def criar_chamado(request):
if request.method == "POST":
github = GitHub(settings.USERNAME, settings.PASSWORD)
github.access(settings.REPOSITORY, settings.OWNER)
retorno = github.create_issue... |
4843439 | from __future__ import division
import random
import math
import os
from collections import defaultdict
from sklearn import linear_model
import numpy as np
from sklearn.naive_bayes import GaussianNB
import itertools
import sys
max_inp = 50000
printsuite=0
minInp =5
random.seed(2)
sens_arg = int(sys.argv[2])
X=[]
Y... |
4843474 | from __future__ import absolute_import
input_name = '../examples/multi_physics/piezo_elasticity.py'
output_name = 'test_piezo_elasticity.vtk'
from tests_basic import TestInput
class Test( TestInput ):
def from_conf( conf, options ):
return TestInput.from_conf( conf, options, cls = Test )
from_conf =... |
4843477 | import re
import httpx
from lxml import etree
from thefuzz import fuzz
from urllib.parse import quote
from nonebot.log import logger
from nonebot.adapters.cqhttp import Message, MessageSegment
from baike import getBaike
async def get_nbnhhsh(keyword: str, force: bool = False):
url = 'https://lab.magi... |
4843551 | import networkx as nx
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib as mpl
import os
import math
import copy
from collections import defaultdict
import sqlite3
import pickle
import anndata
import diffxpy.api as de
from statsmodels.stats.multitest import multipletests
import mu... |
4843590 | import sys
from rpython.memory.gc.semispace import SemiSpaceGC
from rpython.memory.gc.semispace import GCFLAG_EXTERNAL, GCFLAG_FORWARDED
from rpython.memory.gc.semispace import GC_HASH_TAKEN_ADDR
from rpython.memory.gc import env
from rpython.rtyper.lltypesystem.llmemory import NULL, raw_malloc_usage
from rpython.rtype... |
4843636 | from __future__ import print_function
import io
import os
import ast
import sys
import warnings
import unicodedata
__all__ = [
"pprint", "pformat", "isreadable", "isrecursive", "saferepr",
"PrettyPrinter",
]
#
# Py2/Py3 compatibility stuff
#
try:
from collections import OrderedDict, defaultdict, Counte... |
4843668 | import logging
from .definitions import *
class Register:
'''
Basic class to handle device registers.
A register is a combination of:
- characteristic
- data converter for READ
- data converter for WRITE
'''
logger = logging.getLogger(Constants.LOGGER_IO_NAME)
def __init__(self, name, address, translator... |
4843674 | import pydef_core.cell as cc
import pydef_core.defect as dc
import pydef_core.defect_study as ds
import pydef_core.defects_concentration as pdp
import matplotlib.pyplot as plt
directory = './tests/test_files/'
# ------------------------------------------------------ HOST CELL -----------------------------------------... |
4843696 | from django.db import models
class User(models.Model):
username = models.CharField(max_length=40)
email = models.CharField(max_length=35, unique=True, primary_key=True)
password = models.CharField(max_length=20)
class Location(models.Model):
city = models.CharField(max_length=30)
region = models.CharField(max_le... |
4843717 | import os
import pytest
@pytest.fixture
def example_yaml_filename() -> str:
"""Example yml definition file."""
return os.path.join(os.getcwd(), "crowdsales", "unit-test.yml")
|
4843817 | from {{ cookiecutter.package_slug }}.operator import data
import pytest
import urllib
def test_get_data():
with pytest.raises(urllib.error.URLError):
data.get_data('fake_url', 'fake_location')
|
4843818 | import opengm
import vigra
import numpy
import sys
if __name__ == "__main__":
args = sys.argv
if len(args)!=8 :
print "Usage: ", args[0] , " infile outfile red green blue T lambda"
sys.exit(0)
img = vigra.readImage(args[1])
if img.shape[2]!=3:
print "Image must be RGB"
sys.exit(0)
T = float(args[... |
4843832 | import tensorflow as tf
from network.vgg import VGG16
from network.vgg_with_dropout import VGG16Dropout
class Cifar10Trainer(object):
"""
Train a network using MNIST data or a dataset following
"""
def __init__(self, learning_rate, device_name, isdropout):
self.ph_images = tf.placeholder(tf.fl... |
4843836 | import os
import numpy as np
import PIL.Image
import scipy.io as sio
import torch
from torch.utils import data
import cv2
class MyData(data.Dataset): # inherit
"""
load data in a folder
"""
mean_rgb = np.array([0.447, 0.407, 0.386])
std_rgb = np.array([0.244, 0.250, 0.253])
def __init__(self,... |
4843853 | from typing import Any, Optional
from schema import Schema
from dev import environment
from dev.task import Task
class Env(Task):
__schema__ = Schema({str: str})
__description__ = 'Set env variables for current command'
def up(self, args: Optional[Any], extra_args: Optional[Any]) -> None:
if no... |
4843867 | from .views import ArticleListView, ArticleDetailView
from django.urls import path
urlpatterns = [
path('', ArticleListView.as_view(), name='article-list'),
path('<int:pk>/', ArticleDetailView.as_view(), name='article-detail'),
] |
4843912 | from pitop.core.mixins import Recreatable, Stateful
from pitop.pma import ServoMotor, ServoMotorSetting
from pitop.robotics.two_servo_assembly_calibrator import TwoServoAssemblyCalibrator
class PincerController(Stateful, Recreatable):
"""Represents a pincer that uses two servo motors connected parallel to
eac... |
4843922 | from django import forms
from django.contrib.auth.forms import UserCreationForm
from django.contrib.auth.models import User
from django.core.exceptions import ValidationError
class CreateUserForm(UserCreationForm):
class Meta:
model = User
fields = ['username', 'email', '<PASSWORD>', '<PASSWORD>']
def __init__... |
4843929 | import psycopg2
from sqlalchemy import create_engine
from sqlalchemy.orm import scoped_session, sessionmaker
from sqlalchemy.ext.declarative import declarative_base
import config
pg_conf = config.__dict__.get('BINGO_POSTGRES')
def connect(self):
return psycopg2.connect(**pg_conf)
engine = create_engine('postgre... |
4843944 | import argparse
import ast
import os.path as osp
import mmcv
import pandas as pd
from tqdm import tqdm
IMG_SIZE = 1024
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("--mosaics-path", default="/data/mosaics.json")
parser.add_argument("--annotation-path", default="/data/train.cs... |
4843961 | import torch
import nestedtensor
import utils
from torch.nn import functional as F
import random
class DETRNestedTensor(object):
def __init__(self, tensors, mask):
self.tensors = tensors
self.mask = mask
def to(self, *args, **kwargs):
cast_tensor = self.tensors.to(*args, **kwargs)
... |
4843995 | class dotSetTemporaryColors_t(object):
# no doc
AllObjects=None
aObjectIDs=None
aObjectSubIDs=None
Color=None
nObjects=None
|
4844027 | from django.conf.urls import url
from . import views
urlpatterns = [
url('^cookies-test/$', views.cookies_test, name='cookie-test')
]
|
4844076 | import weakref
from typing import TYPE_CHECKING
from bxcommon.messages.abstract_message import AbstractMessage
from bxcommon.messages.abstract_message_factory import AbstractMessageFactory
from bxcommon.network.abstract_socket_connection_protocol import AbstractSocketConnectionProtocol
from bxgateway.connections.abstr... |
4844118 | import re
from pathlib import Path
from typing import List
import yaml
import requests
import ics
import arrow
from pythoncz import app
feeds_datafile = Path(app.root_path) / "static/data/events_feeds.yml"
data = []
def preprocess_ical(text: str) -> List[str]:
"""Removes VALARM ACTION:NONE from the iCal file ... |
4844133 | print(list(map(lambda x: x & 1, range(-3, 4))))
print(list(map(abs, range(-3, 4))))
print(list(map(set, [[i] for i in range(-3, 4)])))
print(list(map(pow, range(4), range(4))))
|
4844168 | import re
regex = "Host \S+ " "in vlan (\d+) " "is flapping between port " "(\S+) and port (\S+)"
ports = set()
with open("log.txt") as f:
for m in re.finditer(regex, f.read()):
vlan = m.group(1)
ports.add(m.group(2))
ports.add(m.group(3))
print("Петля между портами {} в VLAN {}".format(... |
4844193 | from django.apps import AppConfig
class ExampleAppConfig(AppConfig):
name = "app"
verbose_name = "Example App"
|
4844196 | from objmodel import Class, Instance, TYPE, OBJECT
def test_isinstance():
# Python code
class A(object):
pass
class B(A):
pass
b = B()
assert isinstance(b, B)
assert isinstance(b, A)
assert isinstance(b, object)
assert not isinstance(b, type)
# Object model code
... |
4844224 | from binascii import hexlify
from logging import getLogger
from re import sub
from struct import unpack
from sqlite_dissect.constants import ENDIANNESS
from sqlite_dissect.constants import LOGGER_NAME
from sqlite_dissect.constants import WAL_INDEX_CHECKPOINT_INFO_LENGTH
from sqlite_dissect.constants import WAL_INDEX_FI... |
4844226 | from QGraphViz.DotParser.DotParser import DotParser
from QGraphViz.DotParser.Graph import Graph, GraphType
from QGraphViz.DotParser.Node import Node
from QGraphViz.DotParser.Edge import Edge
|
4844302 | import random
import tcr_embedding.evaluation.WrapperFunctions as Wrapper
import tcr_embedding.evaluation.Metrics as Metrics
import scanpy as sc
from anndata import AnnData
def run_clustering_evaluation(data_full, embedding_function, source_data='val', name_label='clonotype',
cluster_pa... |
4844305 | from . import Model, CollectionModel
class Template(Model):
"""
A Template object model (Message Template)
.. attribute:: id
.. attribute:: name
.. attribute:: content
.. attribute:: lastModified
"""
class Templates(CollectionModel):
name = "templates"
form = "template"
... |
4844318 | from FileIO import *
filename,results,n,k,tau,directory,prefix,max_normal,bound_heuristic,normal_bound_heuristic, heuristic_lb, heuristic_ub, num_processes, bounds_only, multi_event, force, get_values, interval_selection, num_intervals, read_depth_file, graph_format, runBAF, ratio_dev, min_frac, tumorfile, normalfile,... |
4844365 | import cupy as cp
from numpy.testing import assert_almost_equal
from cucim.skimage import data
def test_binary_blobs():
blobs = data.binary_blobs(length=128)
assert_almost_equal(blobs.mean(), 0.5, decimal=1)
blobs = data.binary_blobs(length=128, volume_fraction=0.25)
assert_almost_equal(blobs.mean(),... |
4844368 | import urllib.parse
class urls:
"""Create a URL object."""
@classmethod
def parse_url_query(cls, url):
"""Parse the querystring from a URL."""
return urllib.parse.parse_qs(url)
@classmethod
def page_num_from_url(cls, url):
"""Pull page number from URL."""
queries ... |
4844381 | import FWCore.ParameterSet.Config as cms
energyOverMomentumTree = cms.EDAnalyzer('EOP',
src = cms.InputTag('TrackRefitter')
)
|
4844393 | import numpy as np
from sklearn import preprocessing
from numpy import random
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
import pandas as pd
def show_accuracy(predictLabel,Label):
Label = np.ravel(Label).tolist()
predictLabel = predictLabel.tolist()
count = ... |
4844422 | import unittest
from stensorflow.basic.basic_class.pair import SharedPair, SharedPairBase, SharedTensorBase
from stensorflow.basic.basic_class.private import PrivateTensor
import tensorflow as tf
import numpy as np
import datetime
from stensorflow.global_var import StfConfig
from stensorflow.basic.operator.order import... |
4844454 | import pytest
from icevision.all import *
@pytest.fixture
def coco_bbox_parser(coco_dir):
return parsers.COCOBBoxParser(coco_dir / "annotations.json", coco_dir / "images")
@pytest.fixture
def coco_mask_parser(coco_dir):
return parsers.COCOMaskParser(coco_dir / "annotations.json", coco_dir / "images")
def ... |
4844467 | import sys
#Map commands to whether short or long; and name for debug purposes
mipi_commands = {0x05 : (False, "DCS_SHORT_WRITE"),
0x15 : (False, "DCS_SHORT_WRITE"),
0x39 : (True, "DCS_LONG_WRITE"),
0x37 : (False, "SET_MAXIMUM_RETURN_PACKET_SIZE")} #test only to match... |
4844500 | from __future__ import division
from __future__ import print_function
from past.utils import old_div
import sys
sys.path.insert(1, "../../../")
import h2o
from tests import pyunit_utils
from h2o.estimators.gam import H2OGeneralizedAdditiveEstimator
from h2o.grid.grid_search import H2OGridSearch
# In this test, we ch... |
4844503 | import itertools
import numpy as np
import matplotlib.pyplot as plt
import scipy as s
import scipy.stats as stats
#We use two dimensional (multivariate) Normal distribution (http://en.wikipedia.org/wiki/Multivariate_normal_distribution)
#as a proposal distribution with proposal_mean as it's center and proposal_std as... |
4844512 | from setuptools import setup, find_packages
from setuptools.command.test import test
from multiprocessing import freeze_support
import os
import sys
import unittest
def discover_and_run_tests():
# get setup.py directory
setup_file = sys.modules['__main__'].__file__
setup_dir = os.path.abspath(os.path.dirn... |
4844581 | from sklearn.datasets import load_files
from sklearn.model_selection import train_test_split
def load_datasets():
dataset = load_files('review_polarity/txt_sentoken', shuffle=False)
docs_traindev, docs_test, y_traindev, y_test = train_test_split(
dataset.data, dataset.target, test_size=0.25, random_st... |
4844592 | from bge import logic
def main(cont):
own = cont.owner
own.linearVelocity[1] = 0.0
own.linearVelocity[0] = 0.0
#active animation
cont.activate('idle') |
4844615 | import numpy as np
from ..core.utils import indices_len, fix_loc, filter_cols
from ..table.module import TableModule
from ..table.table import Table
from ..table.dshape import dshape_projection
from ..core.decorators import process_slot, run_if_any
from .. import SlotDescriptor
class LinearMap(TableModule):
input... |
4844627 | import re
from datetime import datetime
from difflib import SequenceMatcher
from city_scrapers_core.constants import COMMISSION
from city_scrapers_core.items import Meeting
from city_scrapers_core.spiders import CityScrapersSpider
class ChiSsa52Spider(CityScrapersSpider):
name = "chi_ssa_52"
agency = "Chicag... |
4844630 | from utils import CSVScraper
class GreaterSudburyPersonScraper(CSVScraper):
# http://opendata.greatersudbury.ca/datasets/elected-officials-2018-csv
csv_url = 'https://opendata.arcgis.com/datasets/5ed33c8d634942c3918b62d32a9eedab_0.csv'
|
4844656 | import unittest
from rck.core.graph import IntervalAdjacencyGraph
from rck.core.structures import Position, Strand, Segment, Adjacency, AdjacencyType
class TestIntervalAdjacencyGraph(unittest.TestCase):
def setUp(self):
self.p1 = Position(chromosome="1", coordinate=1, strand=Strand.REVERSE)
self.... |
4844737 | import cv2
import numpy as np
from .models import load_model
from .utils import crop_face, draw_face
from .pcn import pcn_detect
nets = load_model()
def detect(img):
if type(img) == str:
img = cv2.imread(img)
winlist = pcn_detect(img, nets)
return winlist
def crop(img, winlist, size=200):
... |
4844749 | from typing import Iterable, Mapping, Sequence, Tuple
Index = int
Indices = Sequence[Index]
Offset = int
Word = str
Text = Sequence[Word]
FeatureName = str
FeatureValue = float
Feature = Tuple[FeatureName, FeatureValue]
FeatureVector = Iterable[Feature]
FeatureWindow = Iterable[Tuple[Offset, FeatureVector]]
StringV... |
4844786 | import numpy as np
import sys
from utils import draw_episode
def cos_sim(x):
x /= np.linalg.norm(x, axis=1)[:, np.newaxis]
sim = np.dot(x, x.T)
return sim
def one_shot_classification(test_data, num_shots, num_classes, compute_similarities, k_neighbours=1,
num_episodes=10000):... |
4844787 | from django.contrib import admin
from .models import Event
admin.site.register(Event, list_display=["kind", "email", "created_at"], list_filter=["created_at", "kind"], search_fields=["email", "data"])
|
4844842 | from nose.tools import *
from nlpre import token_replacement
# I'm not sure how ampersand's are typically used in the literature,
# but the replacement adds spaces to it
class Token_Test:
@classmethod
def setup_class(cls):
cls.parser = token_replacement()
def ampersand_test(self):
doc = ... |
4844843 | from django.conf.urls import *
from canvas.shortcuts import direct_to_template
from canvas.view_guards import require_staff
urlpatterns = patterns('drawquest.apps.whitelisting.views',
url(r'^$', 'moderation'),
url(r'^/divvy/(?P<id_range>[0-9]-[0-9])$', 'moderation'),
url(r'^/flagged$', 'flag_queue'),
... |
4844901 | def flux(x):
return 0.5*x*x
def minf(a,b):
if b<=0:
return flux(b)
elif a>=0:
return flux(a)
else:
return 0.0
def maxf(a,b):
return max(flux(a),flux(b))
|
4844914 | MODEL_TYPE = 'smplx'
GEODESICS_PATH = f'data/metadata/geodesics/{MODEL_TYPE}/{MODEL_TYPE.upper()}_NEUTRAL_geodesic_dist.npy'
HD_OPERATOR_PATH = f'data/metadata/hd_model/{MODEL_TYPE}/HD_{MODEL_TYPE.upper()}_NEUTRAL_vert_regressor_sparse.npz'
PVCOR_PATH = f'data/metadata/hd_model/{MODEL_TYPE}/HD_{MODEL_TYPE.upper()}_NEUT... |
4844929 | import torch
import torch.nn as nn
import os
class Concat_BCEWithLogitsLoss(nn.Module):
def __init__(self, top_k_percent_pixels=None,
hard_example_mining_step=100000):
super(Concat_BCEWithLogitsLoss, self).__init__()
self.top_k_percent_pixels = top_k_percent_pixels
if top_k... |
4844944 | import numpy as np
from ant_colony import AntColony
distances = np.array([[np.inf, 2, 2, 5, 7],
[2, np.inf, 4, 8, 2],
[2, 4, np.inf, 1, 3],
[5, 8, 1, np.inf, 2],
[7, 2, 3, 2, np.inf]])
ant_colony = AntColony(distances, 1, 1, 100,... |
4845071 | from typing import Optional
from deca.gui.vfs_widgets import used_color_calc
from deca.db_view import VfsView
from deca.db_processor import VfsNode
from deca.ff_types import *
from deca.dxgi_types import dxgi_name_db
from PySide2.QtCore import QAbstractItemModel, QModelIndex, Qt, Signal
from PySide2.QtGui import QColor... |
4845120 | import torch
import torch.nn as nn
import math
# From https://discuss.pytorch.org/t/is-there-anyway-to-do-gaussian-filtering-for-an-image-2d-3d-in-pytorch/12351/3
def get_gaussian_kernel(kernel_size=3, pad=2, sigma=2, channels=3):
# Create a x, y coordinate grid of shape (kernel_size, kernel_size, 2)
x_coord ... |
4845157 | import pytest
import os
from collections import OrderedDict
import time
import redis
import glob
from gtmcore.dataset import Manifest
from gtmcore.inventory.inventory import InventoryManager
from gtmcore.fixtures.datasets import mock_dataset_with_cache_dir, mock_dataset_with_manifest, helper_append_file, \
USERNA... |
4845167 | import importlib
import json
import os
import sys
import warnings
from packaging import version
import h5py
from astroNN.config import custom_model_path_reader
from astroNN.models.apogee_models import (
ApogeeBCNN,
ApogeeCVAE,
ApogeeCNN,
ApogeeBCNNCensored,
ApogeeDR14GaiaDR2BCNN,
ApogeeKplerEch... |
4845187 | from composeml.data_slice.extension import DataSliceContext, DataSliceFrame
class DataSliceGenerator:
"""Generates data slices for the lable maker."""
def __init__(
self, window_size, gap=None, min_data=None, max_data=None, drop_empty=True
):
self.window_size = window_size
self.ga... |
4845213 | import numpy as np
from maddux.environment import Environment
from maddux.objects import Ball
from maddux.robots import simple_human_arm
def arm_animation():
"""Animate the arm moving to touch a ball"""
# Declare a human arm
q0 = np.array([0.5, 0.2, 0, 0.5, 1.5])
human_arm = simple_human_arm(2.0, 2.0,... |
4845218 | from django.core.management.base import BaseCommand
from olympia.users.models import UserProfile
class Command(BaseCommand):
"""Make sure we are correctly anonymizing deleted users."""
help = 'Re-anonymize already deleted users.'
def handle(self, *args, **options):
for user in UserProfile.object... |
4845220 | import torch
import torch.nn as nn
import torch.nn.functional as F
MODEL_UNET_2D = 'unet2d'
class ConvDONormReLu2D(nn.Sequential):
def __init__(self, in_ch, out_ch, dropout_p: float = 0.0, norm: str = 'bn'):
super().__init__()
self.add_module('conv', nn.Conv2d(in_ch, out_ch, 3, padding=1))
... |
4845231 | from typing import List
from guet import __version__ as version
from guet.steps.check.check import Check
class VersionCheck(Check):
def __init__(self):
super().__init__(version)
def should_stop(self, args: List[str]) -> bool:
return '--version' in args or '-v' in args
|
4845232 | from twisted.internet import defer
#import txmongo
#from txmongo import gridfs
#from txmongo.collection import errors as mongo_errors
from tornado.ioloop import IOLoop
import motor
from pymongo.read_preferences import ReadPreference
from base import config
connection = None
db = None
fs = None
fs_avatars = None
de... |
4845253 | import os
from .common import * # noqa
exacute_backend = os.environ.get("EXAQUTE_BACKEND")
print("EXAQUTE_BACKEND=", exacute_backend)
if exacute_backend:
exacute_backend = exacute_backend.lower()
if not exacute_backend:
print("ExaQUte backend: Local")
from .local import * # noqa
elif exacute_backend =... |
4845259 | import os
import matplotlib
import numpy as np
# in case you are running on machine without display, e.g. server
if not os.environ.get('DISPLAY', '') and matplotlib.rcParams['backend'] != 'agg':
print('No display found. Using non-interactive Agg backend.')
# https://matplotlib.org/faq/usage_faq.html
matpl... |
4845269 | import scapy.all as scapy
import argparse
def get_arguments():
parser = argparse.ArgumentParser()
parser.add_argument("-i", "--interface", dest="interface",
help="Interface name")
options = parser.parse_args()
return options
def get_mac(ip):
arp_request = scapy.ARP(pdst=i... |
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