id stringlengths 3 8 | content stringlengths 100 981k |
|---|---|
11566898 | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch_geometric.nn as pyg_nn
import torch_geometric.utils as pyg_utils
class SkipLastGNN(nn.Module):
def __init__(self, input_dim, hidden_dim, output_dim, args):
super(SkipLastGNN, self).__init__()
self.args = args
... |
11566915 | import logging
import pathlib
from dataclasses import dataclass
import pytorch_lightning as pl
from omegaconf import DictConfig
from nuplan.planning.script.builders.model_builder import build_torch_module_wrapper
from nuplan.planning.script.builders.training_builder import (
build_lightning_datamodule,
build_... |
11566929 | from typing import List, Iterable
from requests import Response
import json
from TM1py.Exceptions.Exceptions import TM1pyRestException
from TM1py.Services.ObjectService import ObjectService
from TM1py.Services.RestService import RestService
from TM1py.Utils import format_url
from TM1py.Objects.Sandbox import Sandbox
... |
11566947 | from __future__ import absolute_import
from collections import OrderedDict
from ..utils import to_torch
from torch.autograd import Variable
def extract_cnn_feature(model, inputs):
model.eval()
inputs = Variable(to_torch(inputs))
outputs = model(inputs)[0]
outputs = outputs.data.cpu()
return outp... |
11566966 | import array
import struct
import mmh2
def write_deps(f, alldeps):
signature = '# ninjadeps\n'
version = 4
paths = []
for out, mtime, deps in alldeps:
paths.append(out)
paths.extend(deps)
paths = set(paths)
pathids = {path: _id for _id, path, in enumerate(paths)}
f.writ... |
11566985 | try:
from PyQt5.QtWidgets import *
from PyQt5.QtGui import *
from PyQt5.QtCore import *
except ImportError:
from PySide2.QtWidgets import *
from PySide2.QtGui import *
from PySide2.QtCore import *
from ..widgets import LocationField
class MaterialOptionsWidget(QWidget):
def __init__(self)... |
11566998 | import os
import pytest
import enaml
from jinja2 import Template
TEMPLATE_DIR = os.path.dirname(__file__)
with enaml.imports():
from pages import HelloWorld, Simple
@pytest.fixture
def app():
from web.core.app import WebApplication
app = WebApplication.instance() or WebApplication()
yield app
def t... |
11567067 | from tempfile import mkdtemp
from shutil import rmtree
import urllib
from helpers import DATA_FILE, DATA_URL
from archivekit import Collection, open_archive
from archivekit.store.file import FileStore
from archivekit.types.source import Source
from archivekit.util import checksum
def test_basic_package():
path =... |
11567075 | import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
import numpy as np
from .layers import dense_layer, highway_layer
import time
mnist = input_data.read_data_sets("../data/MNIST_data", one_hot=True) # load mnist data for training and testing
input_shape = 784 # 28x28x1, number of pi... |
11567124 | import yaml
from dotmap import DotMap
def extend_dict(extend_me, extend_by):
if isinstance(extend_me, dict):
for k, v in extend_by.iteritems():
if k in extend_me:
extend_dict(extend_me[k], v)
else:
extend_me[k] = v
else:
if isinstance(ext... |
11567125 | import json
import uuid
from pathlib import Path
from urllib.parse import urlparse
from datetime import datetime
import html2text
import requests
from bs4 import BeautifulSoup
source_url = 'http://tomaugspurger.github.io/modern-5-tidy.html'
IP_URL = 'http://www.instapaper.com/text?u={url}'
QVR_NOTEBOOK = '/Users/kr... |
11567191 | import sys
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
try:
dataFileName = sys.argv[1]
except IndexError:
print("USAGE: python plotEnergies.py 'filename'")
sys.exit(0)
HFEnergy3 = 3.161921401722216
HFEnergy6 = 20.71924844033019
numPart... |
11567195 | import numpy
from amuse.test import amusetest
from amuse.units import nbody_system
from amuse.units import units
from amuse.ic import limepy
class TestLimepy(amusetest.TestCase):
def test1(self):
cluster=limepy.Limepy(5, 1, N=100).result
self.assertAlmostEqual(cluster.total_mass().number, 1.0... |
11567225 | import angr
import logging
l = logging.getLogger(name=__name__)
class CallReturn(angr.SimProcedure):
NO_RET = True
def run(self):
l.info("A factory.call_state-created path returned!")
return
|
11567233 | import re
import string
import typing as t
from pathlib import Path
def raw(data: t.ByteString) -> str:
"""Returns string of printable characters. Replacing non-printable characters
with '.', or CHR(46)
``"""
return "".join(
[chr(byte) if byte >= 0x20 and byte < 0x7F else chr(46) for byte in ... |
11567245 | import os
import cv2
import json
import torch
import logging
import detectron2
import numpy as np
from detectron2.structures import ImageList
from detectron2.modeling.poolers import ROIPooler
from sklearn.metrics.pairwise import cosine_similarity
from defrcn.dataloader import build_detection_test_loader
from defrcn.eva... |
11567257 | from typing import Any, Union
from typing import Dict, Hashable
import numpy as np
from cumm import tensorview as tv
import json
from collections import abc
from functools import reduce
JSON_INDEX_KEY = "__cumm_io_json_index"
NPDTYPE_TO_JSONARRAY_MAP = {
np.dtype(np.uint64): tv.uint64,
np.dtype(np.uint32): t... |
11567283 | from keras.layers import Highway as KerasHighway
class Highway(KerasHighway):
"""
Keras' `Highway` layer does not support masking, but it easily could, just by returning the
mask. This `Layer` makes this possible.
"""
def __init__(self, **kwargs):
super(Highway, self).__init__(**kwargs)
... |
11567287 | from django.db import models
from django.contrib.auth.models import User
# Create your models here.
class BrokerZerodhaTxn(models.Model):
bzt_id = models.AutoField(primary_key=True)
bzt_user = models.ForeignKey(User, on_delete=models.DO_NOTHING)
bzt_tdate = models.DateField(blank=True, null=True)
bzt... |
11567321 | from xv_leak_tools.test_components.ip_tool.ip_tool_builder import IPToolBuilder
def register(factory):
factory.register(IPToolBuilder())
|
11567379 | import json
import os
import sys
from collections import OrderedDict
def build_entry(file_name, industries, regions, malwares):
title = file_name.split('.')[0].upper()
# entry = {
# "pb_file": file_name,
# "title": title,
# "industries": industries,
# "regions": regions,
... |
11567386 | class CONTENT_STATUS:
IN_PROGRESS = 0
COMPLETE = 1
class EXIT_STATUS:
SYSETM_EXIT = 0
ERROR_EXIT = 1
USER_QUIT = 2
class POC_RESULT_STATUS:
FAIL = 0
SUCCESS = 1
RETRAY = 2
class TARGET_MODE_STATUS:
FILE = 9
SINGLE = 8
IPMASK = 7
RANGE = 6
API = 5
class PROXY_T... |
11567406 | from setuptools import setup
setup(name='aenet',
version='0.1',
author='<NAME>, <NAME>',
packages=['aenet'],
install_requires=['numpy', 'moviepy', 'theano', 'lasagne'],
zip_safe=False)
|
11567444 | NAME_PREFIX_SEPARATOR = "_"
ENDPOINTS_SEPARATOR = ", "
CSI_CONTROLLER_SERVER_WORKERS = 10
# array types
ARRAY_TYPE_XIV = 'A9000'
ARRAY_TYPE_SVC = 'SVC'
ARRAY_TYPE_DS8K = 'DS8K'
ALL_ARRAY_TYPES = [ARRAY_TYPE_XIV, ARRAY_TYPE_SVC, ARRAY_TYPE_DS8K]
|
11567445 | description = 'Lenght devices for polarisation analysis'
group = 'lowlevel'
devices = dict(
lsd1 = device('nicos.devices.generic.ManualMove',
description = 'distance sample-deflector 1',
default = 613,
unit = 'mm',
fmtstr = '%.0f',
abslimits = (0, 1000),
),
lsd2 = d... |
11567451 | from typing import List, cast
import fannypack
import numpy as np
import torch.utils.data
import torchfilter
# These need to externally set before training
buddy: fannypack.utils.Buddy
filter_model: torchfilter.base.Filter
trajectories: List[torchfilter.types.TrajectoryNumpy]
num_workers: int
def configure(
*,
... |
11567453 | import pandas as pd
class FeatureExtractor():
def __init__(self):
pass
def fit(self, X_df, y):
pass
def transform(self, X_df):
X_df.index = range(len(X_df))
X_df_new = pd.concat(
[X_df.get(['instant_t', 'windspeed', 'latitude', 'longitude',
... |
11567477 | import bpy
import os
import time
class Init(object):
def __init__(self):
self.StartTime = 0.0
self.VertCount = 0
# Addon Folder Name
self.FolderName = os.path.basename(os.path.dirname(__file__))
# Solidify Name (use Modifire and Material)
self.Soli... |
11567487 | from twindb_backup.status.binlog_status import BinlogStatus
def test_eq(raw_binlog_status):
status_1 = BinlogStatus(raw_binlog_status)
status_2 = BinlogStatus(raw_binlog_status)
assert status_1 == status_2
def test_ne(raw_binlog_status):
status_1 = BinlogStatus(raw_binlog_status)
status_2 = Bin... |
11567538 | import os
import sys
import jinja2
from rdflib import ConjunctiveGraph, URIRef
from rdflib.namespace import DCTERMS, RDFS, FOAF
from rdflib.namespace import Namespace
FM = Namespace('https://purl.org/fair-metrics/terms/')
fairGraph = ConjunctiveGraph()
fairGraph.parse('http://purl.org/fair-ontology#', format='trig')... |
11567562 | import abc
from dataclasses import dataclass
import math
import torch
from .basedist import ExponentialFamily
from .basedist import ConjugateLikelihood
__all__ = ['NormalFullCovariance', 'NormalFullCovarianceStdParams']
@dataclass(init=False, eq=False, unsafe_hash=True)
class NormalFullCovarianceStdParams(torch.nn.... |
11567574 | import sys
def align_the_unaligned(unalnd_nodes,words,is_alnd_words):
ret_alns = {}
for (node, prev) in unalnd_nodes:
aln = -1
bestscr = 10000
for i in range(len(words)):
if not is_alnd_words[i]:
scr = abs(prev-i)
if scr < bestscr:
... |
11567579 | import json
import sys
import os
import argparse
from model.pfn import *
import torch
from transformers import AlbertTokenizer, AutoTokenizer
import re
def map_origin_word_to_bert(words, tokenizer):
bep_dict = {}
current_idx = 1
for word_idx, word in enumerate(words):
bert_word = t... |
11567583 | import os
from collections import OrderedDict
import yaml
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import Sequential as Seq, Linear, ReLU
from . import constants
"""Config schemas
This file loads config files and computes some extra stuff.
For example, ... |
11567585 | token = "<PASSWORD> token"
bot_invite = "bot's invite"
support_server = "https://discord.gg/aBM5xz6"
dev = 548163406537162782 #you can change it yours but I would really appreciate if you keep it the same
extensions = ['cogs.events', 'cogs.setup', 'cogs.dev',
'cogs.messages', 'cogs.misc', 'cogs.help']
... |
11567599 | import argparse
import os
cmd_opt = argparse.ArgumentParser(description='DS')
cmd_opt.add_argument('-seed', type=int, default=0, help='seed')
cmd_opt.add_argument('-phase', type=str, default='train', help='training or testing phase')
# hyperparameters for training
cmd_opt.add_argument('-loss_type', type=str, default... |
11567630 | from dataclasses import dataclass, field
from typing import Any, Dict, List, Type
from .destinations import Destination, DestinationFactory
from .transformers import Transformer
@dataclass
class Pipeline(Destination):
transformers: List[Type[Transformer]]
destinations: List[Destination]
@classmethod
... |
11567664 | filename = 'python_first_run.txt'
with open(filename, mode = 'w') as write_file:
write_file.write('Congratulations! You ran your first python script!') |
11567679 | from pygbif.gbifutils import (
check_data,
stop,
gbif_baseurl,
gbif_GET,
get_meta,
parse_results,
len2,
)
def nodes(
data="all",
uuid=None,
q=None,
identifier=None,
identifierType=None,
limit=100,
offset=None,
isocode=None,
**kwargs
):
"""
Nodes me... |
11567681 | from mu.harness.project import StoreUpdate
from mu.harness.sub_sim import SubSim
from mu.protogen import stores_pb2
from mu.protogen import mcp3427_pb2
MCP3427_KEY = (stores_pb2.MuStoreType.MCP3427, 0)
NUM_MCP3427_CHANNELS = 2
class Mcp3427(SubSim):
# val1 writes channel1 of mcp3427, val2 channel2
def update_... |
11567747 | from django.test import TestCase
from django.shortcuts import reverse
from events.models import Event, User, Category
from comments.models import Comment
class CommentDeleteViewTest(TestCase):
def setUp(self):
self.user = User.objects.create_user(username='iyanu', password=<PASSWORD>, email='<EMAIL>')
... |
11567748 | import torch
from .Container import Container
class Parallel(Container):
def __init__(self, inputDimension, outputDimension):
super(Parallel, self).__init__()
self.inputDimension = inputDimension
self.outputDimension = outputDimension
self.totalOutputSize = None
def updateOut... |
11567755 | import os
import pytest
import torch
from kale.embed.gripnet import TypicalGripNetEncoder
from kale.utils.download import download_file_by_url
pose_url = "https://github.com/pykale/data/raw/main/graphs/pose.pt"
@pytest.fixture(scope="module")
def pose_data(download_path):
download_file_by_url(pose_url, downloa... |
11567785 | from jivago.lang.registry import ParametrizedAnnotation
@ParametrizedAnnotation
def MyAnnotation(param1: str, param2: str):
return lambda x: x
@MyAnnotation(param1="foo", param2="baz")
class MyAnnotatedClass(object):
pass
|
11567788 | import os
import torch
from torch.utils.data.dataset import Dataset
from torch.utils.data import DataLoader
import numpy as np
import os
from PIL import Image
def create_list_file_in_directory(datadir):
i = 0
os.remove(os.path.join(datadir,'data.txt'))
for single_label in os.listdir(datadir):
s... |
11567794 | from .base import API
from .routing import Router
from .. import urls
class UserMgmtAPI(API):
__router, route = Router.new()
@route('users.get')
def _perform(self, user_id, **kwargs):
"""
https://visibility.amp.cisco.com/iroh/user-mgmt/index.html#/User/get_iroh_user_mgmt_users__user_id_
... |
11567811 | class ParseMetaException(Exception):
def __init__(self):
super(ParseMetaException, self).__init__('Error parsing Meta data')
|
11567838 | from typing import Optional, Union
from pyuploadcare.transformations.base import BaseTransformation, StrEnum
class VideoFormat(StrEnum):
webm = "webm"
ogg = "ogg"
mp4 = "mp4"
class ResizeMode(StrEnum):
preserve_ratio = "preserve_ratio"
change_ratio = "change_ratio"
scale_crop = "scale_crop"... |
11567864 | from django.core.management.base import BaseCommand, CommandError
from django.conf import settings
from django.db import connections
from rental.models import SubRegion, House, HouseEtc, RegionTS, HouseTS
from crawlerrequest.models import RequestTS
import json
class Command(BaseCommand):
help = 'All migration tas... |
11567866 | class Error:
"""
Base Error Class
"""
def __init__(self):
self.message = ""
def __repr__(self):
return str({
"message": self.message
})
|
11567897 | from collections import OrderedDict
from copy import deepcopy
import numpy as np
import torch
import torch.optim as optim
from torch import nn as nn
from torch import autograd
from torch.autograd import Variable
import torch.nn.functional as F
import rlkit.torch.pytorch_util as ptu
from rlkit.core.eval_util import c... |
11567899 | import abc
class Callback(abc.ABC):
def on_epoch_begin(self, trainer):
pass
def on_epoch_end(self, trainer):
pass
def on_training_step_begin(self, trainer):
pass
def on_training_step_end(self, trainer):
pass
|
11567942 | import demo_hic_et_nunc.models as models
from demo_hic_et_nunc.types.hen_minter.parameter.mint_objkt import MintOBJKTParameter
from demo_hic_et_nunc.types.hen_minter.storage import HenMinterStorage
from demo_hic_et_nunc.types.hen_objkts.parameter.mint import MintParameter
from demo_hic_et_nunc.types.hen_objkts.storage ... |
11567944 | from typing import Union
from Util.geometry import Position, Pose, Line, intersection_between_segments, intersection_between_line_and_segment, \
closest_point_on_segment
class Area:
def __init__(self, a, b):
neg_x, pos_x = min(a.x, b.x), max(a.x, b.x)
neg_y, pos_y = min(a.y, b.y), max(a.y, b.... |
11567999 | import io
import os
import json
import random
import numpy as np
import tensorflow as tf
from pathlib import Path
from common.kb import load_kb
from collections import defaultdict
from nltk import wordpunct_tokenize
from configs import configs as _config
from nltk.tokenize import RegexpTokenizer
def preprocess_senten... |
11568006 | class Solution:
def reverseWords(self, s: str) -> str:
lis = s.split()
return " ".join(reversed([ss[: : -1] for ss in lis])) |
11568038 | import pytest
from src.graphs import BLACK
from src.graphs import clone_graph
from src.graphs import fill_surrounded_regions
from src.graphs import flip_color
from src.graphs import GraphNode
from src.graphs import is_minimally_connected
from src.graphs import search_maze
from src.graphs import WHITE
class TestSearc... |
11568067 | import unittest
import pulse as p
class TestBPM(unittest.TestCase):
"""This test Class is for variances()"""
def test_range_of_bpm(self):
"""
This function assures that variances()
returns a one dimensional matrix.
"""
testing_uid = "1kzd0DmeunLGEeB0nWLFFaIfuFZn"
pul... |
11568070 | from django.urls import path, re_path
from . import views
app_name = "twitter"
urlpatterns = [
path("", view=views.HomeView.as_view(), name="home"),
path("likes/", view=views.FavoriteListView.as_view(), name="favorite_list"),
re_path(
r"^(?P<screen_name>\w+)/$",
view=views.UserDetailView... |
11568148 | from collections import namedtuple
import os
import shutil
import sys
import tempfile
import yaml
from passpie.importers import find_importer, BaseImporter, get_instances
from passpie.importers.default_importer import DefaultImporter
from passpie.importers.pysswords_importer import PysswordsImporter
def mock_open()... |
11568154 | import numpy as np
from scipy.misc import imsave
import os
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.init as init
import torch.nn.functional as F
import torchvision
from torchvision import models
from torch.autograd import Variable
from torch.utils.data import DataLoade... |
11568160 | import pytest
from pythondi import inject, Provider, configure_after_clear
class Repo:
def __init__(self):
pass
class SQLRepo:
def __init__(self):
pass
class Usecase:
def __init__(self):
pass
class UserUsecase:
def __init__(self):
pass
def test_sync_inject_with... |
11568191 | from typing import Optional, List, Dict, Any, Union
import discord
from personate.utils.logger import logger
import random
class UpdateableMessageWrapper:
'''This contains a discord.WebhookMessage or a discord.Message object, and has a method for updating its content, by passing down the kwargs from the call.'''
... |
11568208 | XK_kra = 0x3a2
XK_kappa = 0x3a2
XK_Rcedilla = 0x3a3
XK_Itilde = 0x3a5
XK_Lcedilla = 0x3a6
XK_Emacron = 0x3aa
XK_Gcedilla = 0x3ab
XK_Tslash = 0x3ac
XK_rcedilla = 0x3b3
XK_itilde = 0x3b5
XK_lcedilla = 0x3b6
XK_emacron = 0x3ba
XK_gcedilla = 0x3bb
XK_tslash = 0x3bc
XK_ENG = 0x3bd
XK_eng = 0x3bf
XK_Amacron = 0x3c0
XK_Iogone... |
11568224 | from typing import Tuple
import tensorflow as tf
def get_inference_function(model: tf.keras.Model, input_shape: Tuple[int, int]):
"""Return convertible inference function with provided model."""
def inference_func(inputs):
return model(inputs, training=False)
tensor_spec = tf.TensorSpec(shape=(... |
11568252 | import argparse
import logging
import sys
import os
parentdir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
os.sys.path.insert(0, parentdir)
from builders import builder
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Controller for the fuzzing framework.')
subparser... |
11568271 | import sqlite3
import os
from ... import ErsiliaBase
SLUGDB_FILE = ".slug.db"
class SlugDb(ErsiliaBase):
def __init__(self, config_json=None):
ErsiliaBase.__init__(self, config_json=config_json)
self.file_path = os.path.join(self.eos_dir, SLUGDB_FILE)
self._table = "slugs"
self.cr... |
11568343 | import pykd
import re
from common.v_0_1_1.common_utils import *
pyLog = PyLog(r'C:\local\tmp\TTT-taskhost-get-addUrl.txt')
util = Util(pyLog)
pyLog.log2Scr('='*10 + ' Start ' + '='*10)
util.runCmd(r'bc *;g')
#util.runCmd(r'bp rpcrt4!Invoke')
#util.runCmd(r'bp wininet!s_UrlCacheAddUrl')
util.runCmd(r'bp wininet!CC... |
11568361 | import numpy as np
# Function to retrun the list of isotope index for an input element
def get_list_iso_index(specie, inst):
specie_list = []
for i_gl in range(0,len(inst.history.isotopes)):
if (specie+'-') in inst.history.isotopes[i_gl]:
specie_list.append(i_gl)
return specie_list
# L... |
11568365 | import logging
# Config for logger
class Config:
base_url = "wss://api.bale.ai/v1/bots/"
request_timeout = 5
use_graylog = False
graylog_host = "127.0.01"
graylog_port = 12201
log_level = logging.DEBUG # DEBUG | INFO | ERROR | WARNING | CRITICAL
log_facility_name = "python_bale_bot"
... |
11568373 | import re
import musicbrainzngs
from .base import BaseScraper
musicbrainzngs.set_useragent("salmon", "1.0", "<EMAIL>")
class MusicBrainzBase(BaseScraper):
url = site_url = "https://musicbrainz.org"
release_format = "/release/{rls_id}"
regex = re.compile("^https?://(?:www\.)?musicbrainz.org/release/([a... |
11568392 | from football_packing.packing import packing
from football_packing.plot_packing import plot_packing
|
11568398 | from ibis.expr.types import TableExpr
import pytest
from sql_to_ibis import query
from sql_to_ibis.tests.utils import (
assert_ibis_equal_show_diff,
assert_state_not_change,
join_params,
resolved_columns,
)
@assert_state_not_change
def test_distinct(forest_fires):
"""
Test use of the distinct... |
11568450 | import os
from .base import BaseDataset
from .registry import DATASETS
@DATASETS.register_module
class FolderDataset(BaseDataset):
extension_names = ['.jpg', '.png', '.bmp', '.jpeg']
def __init__(self, *args, **kwargs):
super(FolderDataset, self).__init__(*args, **kwargs)
@staticmethod
def ... |
11568474 | import os
import sys
import shutil
import json
import time
import random
import datetime
import argparse
import torch
import numpy as np
import tensorboardX
import utils
from data import Tree, PartGraphShapesDataset
import trainer as trainer_def
import model_gen as gen_model_def
import model_dis as dis_model_def
### p... |
11568517 | from typing import Optional
from ground.hints import (Maybe,
Scalar)
from reprit.base import generate_repr
from .angle import Angle
from .compound import (Compound,
Indexable,
Linear,
Location,
Relati... |
11568548 | from setuptools import setup, find_packages
import sys
import pathlib
import platform
parent = pathlib.Path(__file__).parent
# get the readme for use in our long description
readme = (parent / "README.md").read_text()
python_version = platform.python_version().rsplit('.', maxsplit=1)[0]
mac_v, _, _ = platform.mac_ve... |
11568560 | import subprocess
import sys
import os
import configparser
from utils import sync_process, get_machine_list
if __name__ == "__main__":
pool = list()
if len(sys.argv) < 2:
print("Usage: python cleanup.py <bin>")
sys.exit(-1)
binName = sys.argv[1]
print("Clean up " + binName)
confi... |
11568564 | import unittest
import feed
import entities
import util
class TestStopTime(unittest.TestCase):
def test_point(self):
pass
def test_stops(self):
pass
|
11568568 | from swissdutch.constants import FloatStatus, Colour, ColourPref
class Player:
def __init__(self, name, rating, title=None, pairing_no=None,
score=0, float_status=FloatStatus.none, opponents=(),
colour_hist=()):
self._name = name
self._rating = rating... |
11568633 | import os
import random
from lft.app.vote import DefaultVote
from lft.consensus.round import RoundMessages
def test_vote():
round_messages = RoundMessages()
assert not round_messages.votes
vote = _random_vote()
round_messages.add_vote(vote)
assert round_messages.votes
assert vote.id in round... |
11568649 | TIMEOPT_CONFIG_FILE = "cfg_softConstraints_talos.yaml"
from .common_talos import *
SCRIPT_PATH = "memmo"
ENV_NAME = "multicontact/ground"
kp_am = 1.
w_am = 0.5
DURATION_SS = 1.2
EFF_T_PREDEF = 0.2
EFF_T_DELAY = 0.05
p_max = 0.07
FEET_MAX_VEL = 100.
FEET_MAX_ANG_VEL = 100.
|
11568659 | from sightseer import Sightseer
from sightseer.zoo import YOLOv3Client
yolo = YOLOv3Client()
yolo.load_model()
ss = Sightseer()
frames = ss.load_vidsource("./test_data/img/london.mp4")
print (frames.shape)
preds, det_frames = yolo.framewise_predict(frames, stride=10, verbose=False)
ss.render_footage(det_frames) |
11568662 | import unittest
import os
from pymongo import MongoClient, GEO2D, DESCENDING
from bson import json_util
from conversiontools.csv2geojson import *
from conversiontools.kml2geojson import *
from conversiontools.shp2geojson import *
from conversiontools.validategeojson import *
from conversiontools.geojson2mongo import *
... |
11568674 | from __future__ import absolute_import
import unittest
import numpy as np
from sklearn.datasets import load_iris as load_data
from sklearn.cluster import KMeans
import matplotlib.pyplot as plt
from scikitplot.cluster import plot_elbow_curve
class TestPlotElbow(unittest.TestCase):
def setUp(self):
np.rand... |
11568675 | from __future__ import print_function
import sys
import glob
from vispy import app, visuals, scene
from vispy.scene import ViewBox
from vispy.scene.visuals import Markers, Line, XYZAxis
import vispy
vispy.app.use_app(backend_name="PyQt5", call_reuse=True)
import numpy as np
import mesh_lib
class canvasCreater:
... |
11568684 | from pagarme.resources import handler_request
from pagarme.resources.routes import bulk_anticipation_routes
def cancel(recipient_id, bulk_anticipation_id):
return \
handler_request.post(bulk_anticipation_routes.CANCEL_ANTICIPATION.format(recipient_id, bulk_anticipation_id))
def confirm(recipient_id, bul... |
11568810 | from ipaddress import ip_address
import pytest
from ocflib.infra.net import ipv4_to_ipv6
from ocflib.infra.net import ipv6_to_ipv4
from ocflib.infra.net import is_ocf_ip
from ocflib.infra.net import OCF_DNS_RESOLVER
from ocflib.infra.net import OCF_GATEWAY_V4
from ocflib.infra.net import OCF_GATEWAY_V6
from ocflib.in... |
11568818 | from .lang_identifier import LangIdentifier, identify_lang, identify_topn_langs
from . import models
|
11568826 | import MQTTConst as mqttConst
from machine import Timer
import json
import os
import _thread
class _basicJSONParser:
def setString(self, srcString):
self._rawString = srcString
self._dictionObject = None
def regenerateString(self):
return json.dumps(self._dictionaryObject)
def ge... |
11568834 | import azure.functions as func
from .globals import getLogger, EXTERNAL_DEPENDENCY_URL
from .utils import call_internal_api, call_external_api
logger = getLogger(__name__)
class FunctionLogic:
@classmethod
def run(cls, req: func.HttpRequest) -> func.HttpResponse:
"""Azure Function business logic
... |
11568851 | from classicML.api.models import BaseModel
from classicML.api.models import AveragedOneDependentEstimator
from classicML.api.models import AODE
from classicML.api.models import BackPropagationNeuralNetwork
from classicML.api.models import BPNN
from classicML.api.models import DecisionTreeClassifier
from classicML.api.m... |
11568916 | from typing import Union, Tuple, List
import torch
from skrl.memories.torch import Memory # from .base import Memory
class CustomMemory(Memory):
def __init__(self, memory_size: int, num_envs: int = 1, device: Union[str, torch.device] = "cuda:0") -> None:
"""
:param memory_size: Maximum number... |
11568945 | from pyspark.sql.dataframe import DataFrame
from pyspark.sql.types import TimestampType
from visions.types.date_time import DateTime
@DateTime.contains_op.register
def datetime_contains(sequence: DataFrame, state: dict) -> bool:
if len(sequence.schema) != 1:
return False
dtype = sequence.schema[0].d... |
11568966 | from invariances.model.cinn import ConditionalTransformer
def get_model(name):
# TODO: add the other models
_models = {
"alexnet_conv5_animals": lambda: ConditionalTransformer.from_pretrained("animals"),
}
return _models[name]()
|
11568968 | from .prop import prop
from ramda.private.asserts import assert_equal
class TestObject:
def __init__(self, val):
self.val = val
test_object = TestObject("foo")
def prop_nocurry_test():
assert_equal(prop("val", test_object), "foo")
def prop_curry_test():
assert_equal(prop("val")(test_object),... |
11569008 | import os
from pathlib import Path
import requests
from picktrue.meta import UA, ImageItem
from picktrue.utils import retry
def normalize_proxy_string(proxy):
if 'socks5' in proxy:
if 'socks5h' not in proxy:
proxy = proxy.replace('socks5', 'socks5h')
return proxy
def get_proxy(proxy_st... |
11569054 | import logging
import string
from collections import Counter
from typing import Dict, List, Any
import numpy as np
import pandas as pd
import torch
from transfer_nlp.common.tokenizers import CustomTokenizer
from transfer_nlp.embeddings.embeddings import Embedding
from transfer_nlp.loaders.loaders import DatasetSplits... |
11569101 | DEBUG = True
SECRET_KEY = 'insecurekeyfordev'
# Change localhost to your Docker Machine IP if you're using Docker Toolbox.
SERVER_NAME = 'localhost:8000'
|
11569115 | from django.urls import path
from .apps import LibiAccountConfig
from .views import (
AccountView,
TokenView,
)
app_name = LibiAccountConfig.name
urlpatterns = [
path('', AccountView.as_view(), name='account'),
path('token', TokenView.as_view(), name='token'),
]
|
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