id stringlengths 3 8 | content stringlengths 100 981k |
|---|---|
101659 | import argparse
parser = argparse.ArgumentParser()
parser.add_argument(
"--dataset_path",
default=None,
type=str,
required=True,
help="Path to the [dev, test] dataset",
)
parser.add_argument(
"--index_path",
default=None,
type=str,
required=True,
help="Path to the indexes of c... |
101665 | import numpy as np
import os
import matplotlib.pyplot as plt
import glob
import re
import torch
import torch.nn as nn
import torch
import cv2
import torchvision
from torch.utils.data import Dataset, DataLoader, ConcatDataset
from torchvision import transforms
import tqdm
from PIL import Image
import albumentations a... |
101750 | from pathlib import Path
from tempfile import TemporaryDirectory
from unittest import TestCase
from zkviz import zkviz
class TestListZettels(TestCase):
def test_list_zettels_with_md_extension(self):
# Create a temporary folder and write files in it
with TemporaryDirectory() as tmpdirname:
... |
101775 | import dataclasses
from types import MethodType
from typing import ( # type: ignore
Any,
Callable,
Dict,
List,
Optional,
Tuple,
Type,
_TypedDictMeta,
)
from dictdaora import DictDaora
from .decorator import jsondaora
from .exceptions import DeserializationError
class StringField(Dic... |
101827 | import numpy as np
a = np.arange(10) * 10
print(a)
# [ 0 10 20 30 40 50 60 70 80 90]
print(a[5])
# 50
print(a[8])
# 80
print(a[[5, 8]])
# [50 80]
print(a[[5, 4, 8, 0]])
# [50 40 80 0]
print(a[[5, 5, 5, 5]])
# [50 50 50 50]
idx = np.array([[5, 4], [8, 0]])
print(idx)
# [[5 4]
# [8 0]]
print(a[idx])
# [[50 40]
... |
101831 | import csv
import json
from collections import OrderedDict
csvfile = open('./pokedex.csv', 'r')
jsonfile = open('./pokedex.json', 'w')
jsonNames = ("orderID", "nDex", "name", "type1", "type2", "ability1", "ability2", "hiddenability", "hp", "atk", "def", "spatk", "spdef", "spe", "note", "tier", "image")
reader = csv.D... |
101834 | from __future__ import print_function
class Rule(object):
def __init__(self):
pass
def __repr__(self):
return self.name()
@classmethod
def name(cls):
return cls.__name__.split('.')[-1]
@classmethod
def explain(cls):
return cls.__doc__
def __cmp__(self, other)... |
101846 | import operator
from django.conf import settings
from django.contrib.auth.models import User
from rest_framework import serializers
from .models import Board, Column, Project, Tag, Todo, Type
REPORTER_ATTR = getattr(settings, 'BUDGET_REPORTER_ATTR', 'is_staff')
EDITOR_ATTR = getattr(settings, 'BUDGET_EDITOR_ATTR', '... |
101861 | from pathlib import Path
import pytest
import sys
import ssh2net
from ssh2net import SSH2Net
from ssh2net.exceptions import ValidationError, SetupTimeout
NET2_DIR = ssh2net.__file__
UNIT_TEST_DIR = f"{Path(NET2_DIR).parents[1]}/tests/unit/"
def test_init__shell():
test_host = {"setup_host": "my_device ", "aut... |
101870 | from __future__ import print_function, division
from argparse import ArgumentParser
import yaml
import logging
import os
import sys
import time
from subprocess import call
from marmot.experiment.import_utils import build_objects, build_object, call_for_each_element, import_class
from marmot.experiment.preprocessing_u... |
101902 | from urllib.parse import urlparse
from logging import getLogger
from django.conf import settings
from django.db import transaction
from requests.auth import HTTPBasicAuth
from zipa import lattice # pylint: disable=no-name-in-module
from zinc import models
from zinc.utils.validation import is_ipv6
logger = getLogge... |
101908 | from using_extend import *
f = FooBar()
if f.blah(3) != 3:
raise RuntimeError, "blah(int)"
if f.blah(3.5) != 3.5:
raise RuntimeError, "blah(double)"
if f.blah("hello") != "hello":
raise RuntimeError, "blah(char *)"
if f.blah(3, 4) != 7:
raise RuntimeError, "blah(int,int)"
if f.blah(3.5, 7.5) != (3.... |
101930 | from savu.plugins.plugin_tools import PluginTools
class DezingerDeprecatedTools(PluginTools):
"""A plugin for cleaning x-ray strikes based on statistical evaluation of
the near neighbourhood
"""
def define_parameters(self):
"""
outlier_mu:
visibility: basic
dtype... |
101939 | import asyncio
import logging.config
from pathlib import Path
from symphony.bdk.core.config.loader import BdkConfigLoader
from symphony.bdk.core.symphony_bdk import SymphonyBdk
async def run():
config = BdkConfigLoader.load_from_symphony_dir("config.yaml")
async with SymphonyBdk(config) as bdk:
ext_a... |
101941 | import matplotlib
import matplotlib.pyplot as plt
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import pandas as pd
import os
import matplotlib.pyplot as plt
import sys
import itertools
mpl.rcParams['legend.fontsize'] = 12
DPI = 5000
input_dir = "/home/pablo/ws/log/trajectories"
print("Reading fr... |
101972 | from test_helper import run_common_tests, failed, passed, get_answer_placeholders, do_not_run_on_check
if __name__ == '__main__':
do_not_run_on_check()
run_common_tests()
|
101992 | from agents import *
from models import *
import numpy as np
import matplotlib
matplotlib.use('tkagg')
import matplotlib.pyplot as plt
import sys
import pickle
# end class world
def speed_profile(file_names):
"""
This function is to plot speed profiles for several evaluation results.
Args:
file_nam... |
101996 | import FWCore.ParameterSet.Config as cms
siStripGainESProducer = cms.ESProducer("SiStripGainESProducer",
appendToDataLabel = cms.string(''),
printDebug = cms.untracked.bool(False),
AutomaticNormalization = cms.bool(False),
APVGain = cms.VPSet(
cms.PSet(
Record = cms.string('SiStripA... |
101999 | from typing import Dict
import numpy as np
import pytorch_lightning as pl
import torch
from omegaconf import DictConfig
from src.utils.technical_utils import load_obj
class LitNER(pl.LightningModule):
def __init__(self, cfg: DictConfig, tag_to_idx: Dict):
super(LitNER, self).__init__()
self.cfg ... |
102015 | from .state import EOF
from .tokens import TokenEof
from .tokens_base import TOKEN_COMMAND_UNABBREVIATE
from .tokens_base import TokenOfCommand
from Vintageous import ex
@ex.command('unabbreviate', 'una')
class TokenUnabbreviate(TokenOfCommand):
def __init__(self, params, *args, **kwargs):
super().__init_... |
102051 | from typedpy import *
class Example1(Structure):
D = Map(items=[String(), Integer()], default=lambda: {'abc': 0})
_required = []
|
102055 | from django.shortcuts import render, redirect
# Create your views here.
from django.http import Http404
from homework_app.models import Homework, Comment
from django.views.generic.list import ListView
from homework_app.forms import CommentForm
def homework(request, homework_id):
p = Homework.objects.get(pk=homew... |
102057 | import httpx
from statuscheck.services.bases._base import BaseServiceAPI
from statuscheck.services.models.generic import (
COMPONENT_TYPE_DEGRADED,
COMPONENT_TYPE_GOOD,
COMPONENT_TYPE_MAINTENANCE,
COMPONENT_TYPE_MAJOR_OUTAGE,
COMPONENT_TYPE_PARTIAL_OUTAGE,
COMPONENT_TYPE_SECURITY,
COMPONENT... |
102059 | import numpy as np
import tensorflow as tf
from tensorflow.keras.layers import Layer
class MultiMaskedConv2D(Layer):
"""
Masked multitask 2-dimensional convolutional layer. This layer implements
multiple stacks of the convolutional architecture and implements masking consistent
with the MANN API to sup... |
102094 | import logging
import time, datetime
from thespian.actors import *
from thespian.test import *
import signal
import os
class KillMeActor(Actor):
def receiveMessage(self, msg, sender):
logging.info('EchoActor got %s (%s) from %s', msg, type(msg), sender)
self.send(sender, os.getpid())
class Paren... |
102208 | import numpy as np
from .layer_base import LayerBase
class ReluLayer(LayerBase):
def __init__(self):
super().__init__()
self.cache = {}
def id(self):
return "Relu"
def forward(self, x):
y = np.maximum(x, 0)
self.cache["is_negative"] = (x < 0)
return y
... |
102260 | from atcodertools.fmtprediction.models.calculator import CalcNode
class Index:
"""
The model to store index information of a variable, which has a likely the minimal / maximal value and for each dimension.
Up to 2 indices are now supported.
In most cases, the minimal value is 1 and the m... |
102290 | import types
import datetime
from nose.tools import eq_ as orig_eq_
from unittest import skip
from allmychanges.utils import first, html_document_fromstring
from allmychanges.parsing.pipeline import (
get_markup,
extract_metadata,
group_by_path,
strip_outer_tag,
prerender_items,
highlight_keywo... |
102299 | import random
from django.core import serializers
from django.shortcuts import HttpResponse
from .models import DemoData
TEMP = "1234567890abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ!@#$%^&*()_+=-"
# Create your views here.
def demo_views(request):
result = DemoData.objects.filter(
name="".joi... |
102302 | from werkzeug.utils import find_modules, import_string
def import_all(import_name):
for module in find_modules(import_name, include_packages=True, recursive=True):
import_string(module)
|
102400 | import pytest
def test_ec2user_user_group(host):
"""Check if the ec2-user user created in a ec2-user group and its UID and GUID values is 1000"""
assert host.user("ec2-user").exists
assert host.group("ec2-user").exists
assert host.user("ec2-user").uid == 1000
assert host.user("ec2-user").gid == 10... |
102413 | import pandas as pd
import numpy as np
np.random.seed(163)
from sklearn.svm import SVC
from sklearn.cross_validation import StratifiedKFold
# Load the precomputed X mutag feature matrix.
print "Loading Feature Matrix..."
df=pd.read_csv('X_mutag.csv',header=None)
X=np.array(df)
# Load the precomputed Y mutag feature... |
102435 | import datetime, calendar
from dateutil.relativedelta import relativedelta
from freezegun import freeze_time
from doajtest.helpers import DoajTestCase
from portality.scripts.prune_marvel import generate_delete_pattern
class TestPruneMarvel(DoajTestCase):
@classmethod
def setUpClass(cls):
cls.runs = ... |
102460 | import time
import copy
import gobject
from phony.base.log import ClassLogger
from RPi import GPIO
from types import MethodType
class Inputs(ClassLogger):
_layout = {}
_inputs_by_channel = {}
_rising_callback_by_channel_name = {}
_falling_callback_by_channel_name = {}
_pulse_callback_by_channel_name = {}
... |
102466 | from .transformer import *
from .common import *
#tf.compat.v1.disable_eager_execution()
#
#batch_size = 40
#seq_length = 200
#hidden_size = 768
#num_attention_heads =12
#size_per_head = int(hidden_size / num_attention_heads)
#
#layer_input = tf.compat.v1.placeholder(tf.float32, shape=(batch_size*seq_length, hidden_si... |
102475 | from copy import deepcopy
from pymaclab.dsge.translators import pml_to_dynarepp
from pymaclab.dsge.translators import dynarepp_to_pml
from pymaclab.dsge.translators import pml_to_pml
from pymaclab.dsge.parsers._dsgeparser import ff_chron_str, bb_chron_str
class Translators(object):
def __init__(self,other=None):
... |
102492 | import unittest
from unittest import mock
from apiserver.search import parse_query
from apiserver.search import join
from apiserver.search.union import name_similarity
from .utils import DataTestCase
class TestSearch(unittest.TestCase):
def test_simple(self):
"""Test the query generation for a simple se... |
102547 | import py
class TestJitTraceInteraction(object):
def test_trace_while_blackholing(self):
import sys
l = []
printed = []
def trace(frame, event, arg):
l.append((frame.f_code.co_name, event))
return trace
def g(i, x):
if i > x - 10:
... |
102551 | r=open('all.protein.faa','r')
w=open('context.processed.all.protein.faa','w')
start = True
mem = ""
for line in r:
if '>' in line and not start:
list_char = list(mem.replace('\n',''))
list_context = []
list_context_length_before = 1
list_context_length_after = 1
for i in range(len(list_char)):
tmp=""
... |
102575 | import os
from pathlib import Path
from appdirs import user_data_dir
class EnvManager:
"""Stashes environment variables in a file and
retrieves them in (a different process) with get_environ
with failover to os.environ
"""
app_env_dir = Path(user_data_dir("NEBULO"))
app_env = app_env_dir / ... |
102585 | import re
import click
from matrix_connection import matrix_client
from tabulate import tabulate
@click.command()
@click.argument('pattern', required=False, type=str)
def list_rooms(pattern):
"""List room ids and keys."""
rooms = matrix_client().get_rooms()
data = [(rid, room.display_name)
f... |
102607 | import os
import unittest
from scrapy.http import TextResponse, Request
from pdl_scraper.spiders.pdfurl_spider import PdfUrlSpider
class TestPdfUrlSpider(unittest.TestCase):
def setUp(self):
self.spider = PdfUrlSpider()
def test_find_pdfurl(self):
codigos = (
'00001',
... |
102629 | from enum import Enum
from deprecation import deprecated
@deprecated(details="""Enum-value statuses are deprecated since SLIMS 6.4.
Unless your SLIMS system still uses them (see Lab Settings),
you should use the Status table and cntn_fk_status for status queries.""")
class Status(Enum):
"... |
102645 | from mongoengine import *
class VersionModel(Document):
"""
각 클라이언트의 버전 관리를 위한 collection
"""
meta = {
'collection': 'versions'
}
platform = IntField(
required=True,
primary_key=True
)
# 1: Web
# 2: Android
# 3: IOS
version = StringField(
r... |
102718 | import requests
import json
from bs4 import BeautifulSoup
def scrape_creatures():
print 'scraping creatures'
url = 'http://ark.gamepedia.com/Entity_IDs'
r = requests.get(url)
soup = BeautifulSoup(r.text, 'html.parser')
tables = soup.find_all('table')
creature_table = tables[2]
container =... |
102721 | import os
import datetime
import pytest
import pandas as pd
import geopandas as gpd
from shapely.geometry import Point
import trackintel as ti
@pytest.fixture
def testdata_sp_tpls_geolife_long():
"""Generate sp and tpls sequences of the original pfs for subsequent testing."""
pfs, _ = ti.io.dataset_reader.r... |
102730 | import os
print "UPDATING..."
os.system("cd")
os.system('cd /root/ && rm -fr hackers-tool-kit && git clone https://github.com/unkn0wnh4ckr/hackers-tool-kit && echo "[UPDATED]: Restart Your Terminal"') |
102731 | from django.apps import AppConfig
from django.utils.translation import gettext_lazy as _
class PatreonManagerConfig(AppConfig):
name = 'patreonmanager'
verbose_name = _("Patreon Manager")
|
102732 | from yaml import load, dump, FullLoader
import sys, os
class QuietLoaders:
def resource_path(self, relative):
if hasattr(sys, "_MEIPASS"):
return os.path.join(sys._MEIPASS, relative)
return os.path.join(relative)
def __init__(self):
self.settings_path = self.resource_path(os.path.join('data', 'config/sett... |
102763 | from __future__ import absolute_import, division, print_function
import codecs
try:
from collections import OrderedDict
except ImportError:
from ordereddict import OrderedDict
import copy
import os
import os.path as path
import sys
import toml
import nfldb
import nflfan.provider as provider
import nflfan.sco... |
102809 | import numpy as np
from model import generate_recommendations
user_address = '0x8c373ed467f3eabefd8633b52f4e1b2df00c9fe8'
already_rated = ['0x006bea43baa3f7a6f765f14f10a1a1b08334ef45','0x5102791ca02fc3595398400bfe0e33d7b6c82267','0x68d57c9a1c35f63e2c83ee8e49a64e9d70528d25','0xc528c28fec0a90c083328bc45f587ee215760a0f']... |
102831 | from setuptools import setup, find_packages
setup(
name="Segy2Segy",
version="0.2",
packages=find_packages(exclude=["tests*"]),
scripts=['core/segy2segy.py'],
install_requires=['gdal', 'obspy'],
author="<NAME>",
author_email="<EMAIL>",
description="A command line tool for projecting an... |
102866 | import torch
from torch import nn
from torch.nn import functional as F
def masked_normalization(logits, mask):
scores = F.softmax(logits, dim=-1)
# apply the mask - zero out masked timesteps
masked_scores = scores * mask.float()
# re-normalize the masked scores
normed_scores = masked_scores.div(... |
102867 | from .utils.suite_writer import Suite
from contextlib import contextmanager
import pytest
# pylint: disable=redefined-outer-name
def test_expect_failure_not_met(suite, test):
test.expect_failure()
with _raises_assertion('Test did not fail as expected'):
suite.run()
def test_expect_error_not_met(su... |
102902 | from baserow.contrib.database.formula.exceptions import BaserowFormulaException
class InvalidNumberOfArguments(BaserowFormulaException):
def __init__(self, function_def, num_args):
if num_args == 1:
error_prefix = "1 argument was"
else:
error_prefix = f"{num_args} arguments... |
102903 | from time import time
from functools import wraps
import matplotlib.pyplot as plt
from mandelbrot.python_mandel import compute_mandel as compute_mandel_py
from mandelbrot.hybrid_mandel import compute_mandel as compute_mandel_hy
from mandelbrot.cython_mandel import compute_mandel as compute_mandel_cy
def timer(func, n... |
102932 | from invitations.adapters import BaseInvitationsAdapter
from registration.signals import user_registered
class DepartmentInvitationsAdapter(BaseInvitationsAdapter):
def get_user_signed_up_signal(self):
return user_registered
|
102985 | import numpy
from gensim.summarization.bm25 import BM25
class WrappedBM25(BM25):
def __init__(self, docs, tokenizer='spacy'):
self.docs = docs
if tokenizer == 'spacy':
try:
import spacy
except ImportError:
raise ImportError('Please install sp... |
102997 | from torch_rgcn.utils import *
from torch.nn.modules.module import Module
from torch.nn.parameter import Parameter
from torch import nn
import math
import torch
class DistMult(Module):
""" DistMult scoring function (from https://arxiv.org/pdf/1412.6575.pdf) """
def __init__(self,
indim,
... |
103010 | norm_cfg = dict(type='GN', num_groups=32, requires_grad=True)
model = dict(
type='PoseDetDetector',
pretrained='pretrained/dla34-ba72cf86.pth',
# pretrained='open-mmlab://msra/hrnetv2_w32',
backbone=dict(
type='DLA',
return_levels=True,
levels=[1, 1, 1, 2, 2, 1],
channel... |
103066 | from bson import ObjectId
from odmantic import Model
class Player(Model):
name: str
level: int = 1
document = {"name": "Leeroy", "_id": ObjectId("5f8352a87a733b8b18b0cb27")}
user = Player.parse_doc(document)
print(repr(user))
#> Player(
#> id=ObjectId("5f8352a87a733b8b18b0cb27"),
#> name="Leeroy",... |
103078 | from autogluon.core.utils.feature_selection import *
from autogluon.core.utils.utils import unevaluated_fi_df_template
import numpy as np
from numpy.core.fromnumeric import sort
import pandas as pd
import pytest
def evaluated_fi_df_template(features, importance=None, n=None):
rng = np.random.default_rng(0)
im... |
103083 | from unittest import mock
from unittest.mock import call
from django.test import override_settings
from lego.apps.external_sync.external import ldap
from lego.apps.users.constants import GROUP_COMMITTEE
from lego.apps.users.models import AbakusGroup, User
from lego.utils.test_utils import BaseTestCase
class LDAPTes... |
103094 | DOMAIN = "audiconnect"
CONF_VIN = "vin"
CONF_CARNAME = "carname"
CONF_ACTION = "action"
MIN_UPDATE_INTERVAL = 5
DEFAULT_UPDATE_INTERVAL = 10
CONF_SPIN = "spin"
CONF_REGION = "region"
CONF_SERVICE_URL = "service_url"
CONF_MUTABLE = "mutable"
SIGNAL_STATE_UPDATED = "{}.updated".format(DOMAIN)
TRACKER_UPDATE = f"{DOMA... |
103105 | from soccer_geometry.transformation import Transformation
from soccer_geometry.camera import Camera
|
103110 | import os
import json
import time
import torch
import itertools
import detectron2.utils.comm as comm
from fvcore.common.file_io import PathManager
from detectron2.config import global_cfg
from detectron2.engine.train_loop import HookBase
from detectron2.evaluation.testing import flatten_results_dict
__all__ = ["EvalHo... |
103146 | from imghdr import what
from os import getenv
from json import loads, dumps
import flask
from rockset import Client, Q
from flask_cors import CORS
from sys import argv
app = flask.Flask(__name__, static_folder='compendium/images')
CORS(app)
rs = Client(api_key=getenv('RS2_TOKEN') or argv[1], api_server='api.rs2.usw2.r... |
103169 | from abc import ABC, abstractmethod
class Verb(ABC):
"""
This docstring is used in the help message when doing
`htcondor noun verb --help`
"""
# The options class dict is a nested dict containing kwargs
# per option for the add_argument method of ArgumentParser,
# see COMMON_OPTIONS in __... |
103181 | class YamboSpectra():
"""
Class to show optical absorption spectra
"""
def __init__(self,energies,data):
self.energies = energies
self.data = data
|
103292 | import sys
import os
import logging
import datetime
import datetime
import json
import traceback
import copy
import random
import string
import gzip
import asyncio
from pathlib import Path
from collections.abc import Iterable
import discord
from tqdm import tqdm
__version__ = "0.3.3"
PBAR_UPDATE_INTERVAL = 100
PBAR_... |
103357 | from django.apps import AppConfig
class OfficialDocumentsCollectionConfig(AppConfig):
name = 'official_documents_collection'
|
103385 | import unittest
import numpy as np
import scipy.sparse
from injector import Injector
from decai.simulation.data.featuremapping.feature_index_mapper import FeatureIndexMapper
from decai.simulation.logging_module import LoggingModule
class TestFeatureIndexMapper(unittest.TestCase):
@classmethod
def setUpClass... |
103387 | from pyNastran.dev.bdf_vectorized.test.test_coords import *
from pyNastran.dev.bdf_vectorized.test.test_mass import *
from pyNastran.dev.bdf_vectorized.cards.elements.solid.test_solids import *
from pyNastran.dev.bdf_vectorized.cards.elements.shell.test_shell import *
from pyNastran.dev.bdf_vectorized.cards.elements.r... |
103394 | import abc
class Metrics(abc.ABC):
def __init__(self):
raise NotImplementedError
@abc.abstractmethod
def calculate(self) -> float:
raise NotImplementedError
class Accuracy(Metrics):
def __init__(self):
super().__init__()
self._num_correct = 0
self._num_sample... |
103404 | def f(*, b):
return b
def f(a, *, b):
return a + b
def f(a, *, b, c):
return a + b + c
def f(a, *, b=c):
return a + b
def f(a, *, b=c, c):
return a + b + c
def f(a, *, b=c, c=d):
return a + b + c
def f(a, *, b=c, c, d=e):
return a + b + c + d
def f(a=None, *, b=None):
return a + b... |
103416 | from .Dataset import Dataset
from .constants import *
from .DataLoader import DataLoader, create_datasets
from .Dict import Dict |
103438 | import json
from collections import Iterator
from os.path import join
from elasticsearch import Elasticsearch
from examples.imdb.conf import ES_HOST, ES_USE_AUTH, ES_PASSWORD, ES_USER, DATA_DIR
from pandagg.index import DeclarativeIndex, Action
from pandagg.mappings import Keyword, Text, Float, Nested, Integer
class... |
103464 | import random
import time
from agora.retry.backoff import Backoff
class Strategy:
"""Determines whether or not an action should be retried. Strategies are allowed to delay or cause other side
effects.
"""
def should_retry(self, attempts: int, e: Exception) -> bool:
"""Returns whether or not... |
103467 | import torch
import torch.nn as nn
import os
from .models import Darknet
from .utils.utils import non_max_suppression, rescale_boxes
class YoLov3HumanDetector(nn.Module):
def __init__(self, weights_path="weights/yolov3.weights",
conf_thres=0.8, nms_thres=0.4, img_size=416, device=torch.device("c... |
103484 | import EchelleJSON as ej
import numpy as np
# Read all of the file names and convert the strings to UT and JD
f = open("files.txt")
files = ["{}.json".format(ff[:-6]) for ff in f.readlines()]
# Read the HJDN field
f = open("HJD.txt", "w")
for ff in files:
edict = ej.read("jsons_BCV/{}".format(ff))
HJD = edic... |
103515 | import torch
import torch.nn.functional as F
def aggregate_sbg(prob, keep_bg=False, hard=False):
device = prob.device
k, _, h, w = prob.shape
ex_prob = torch.zeros((k+1, 1, h, w), device=device)
ex_prob[0] = 0.5
ex_prob[1:] = prob
ex_prob = torch.clamp(ex_prob, 1e-7, 1-1e-7)
logits = torch.... |
103524 | from fastapi import APIRouter
from .api.v1.job import router as job_router
from .api.v1.record import router as record_router
router = APIRouter()
router.include_router(job_router)
router.include_router(record_router) |
103544 | import dash_html_components as html
import dash_vtk
from dash_docs import tools
from dash_docs import styles
from dash_docs import reusable_components as rc
examples = tools.load_examples(__file__)
layout = html.Div([
rc.Markdown('''
# Click and Hover Callbacks
It's possible to create callbacks based on ... |
103604 | import argparse, time, sys, os, subprocess
class snmpRecon(object):
def __init__(self):
self.parseArgs()
self.paramStrings=['1.3.6.1.2.1.25.1.6.0', '1.3.6.1.2.1.25.4.2.1.2', '1.3.6.1.2.1.25.4.2.1.4', '1.3.6.1.2.1.25.2.3.1.4', '1.3.6.1.2.1.25.6.3.1.2', '1.3.6.1.4.1.77.1.2.25', '1.3.6.1.2.1.6.13.1.3'... |
103615 | import asyncio
import elasticsearch
import json
import logging
import requests
import time
from urllib.parse import urlencode
from datamart_core import Discoverer
from datamart_core.common import setup_logging
logger = logging.getLogger(__name__)
class ZenodoDiscoverer(Discoverer):
EXTENSIONS = ('.xls', '.xlsx... |
103626 | import torch
from torch import Tensor
from torch.nn import Module
class ExponentialMovingAverage(Module):
def __init__(self, *size: int, momentum: float = 0.995):
super(ExponentialMovingAverage, self).__init__()
self.register_buffer("average", torch.ones(*size))
self.register_buffer("init... |
103645 | from django.conf.urls import url
from dojo.engagement import views
urlpatterns = [
# engagements and calendar
url(r'^calendar$', views.engagement_calendar, name='calendar'),
url(r'^calendar/engagements$', views.engagement_calendar, name='engagement_calendar'),
url(r'^engagement$', views.engagement, n... |
103646 | import numpy as np
import tensorflow as tf
from deep_da.model.util import util_tf
"""
Models used in DANN paper
"""
class Model:
__base_n_hidden = [3072, 2048]
def __init__(self,
output_size: int=10,
n_hidden: list=None):
__n_hidden = n_hidden or self.__base_n_hid... |
103651 | import os
from setuptools import setup
PROJECT_NAME = 'actionslog'
ROOT = os.path.abspath(os.path.dirname(__file__))
VENV = os.path.join(ROOT, '.venv')
VENV_LINK = os.path.join(VENV, 'local')
install_requires = [
'Django>=1.11.20',
'django-jsonfield>=0.9.15',
'pytz>=2015.7',
]
project = __import__(PROJEC... |
103672 | from core.run.event_dispatcher.register import EventRegister
def build_runner(model, runner_config, data_source_context, config, event_register: EventRegister):
if runner_config['type'] == 'default':
from .training.default.builder import build_default_training_runner
return build_default_training_... |
103692 | import socket
import asyncio
import time
import random
import json
import requests
from walkoff_app_sdk.app_base import AppBase
class BreachSense(AppBase):
__version__ = "1.0.0"
app_name = "Breachsense" # this needs to match "name" in api.yaml
def __init__(self, redis, logger, console_logger=None):
... |
103698 | import setuptools
setup_args = dict(
name="grr-grafanalib-dashboards",
description="GRR grafanalib Monitoring Dashboards",
license="Apache License, Version 2.0",
url="https://github.com/google/grr/tree/master/monitoring/grafana",
maintainer="GRR Development Team",
maintainer_email="<EMAIL>",
packages=set... |
103702 | from .box import Box
from .cylinder import Cylinder
from .sphere import Sphere
from .random_primitive import RandomPrimitive
from .plane import Plane |
103710 | from __future__ import print_function
import click
from click.testing import CliRunner
from kcleaner import cli
runner = CliRunner()
|
103712 | from crypt import mksalt
from datetime import datetime, timedelta
from typing import List, Optional
from arrow.arrow import Arrow
from fastapi.encoders import jsonable_encoder
import sqlalchemy
from sqlalchemy import or_
from sqlalchemy.orm import Session
from sqlalchemy.sql.functions import func
from app import crud... |
103715 | import sys
import os
pattern = sys.argv[1]
print(pattern)
def get_result_line(i, pattern):
filename = pattern.format(i)
if os.path.exists(filename):
lines = open(filename, 'r').readlines()[-3:]
return str(i) + "\t" + '\t'.join([line.split(':')[1].strip() for line in lines])
return None
re... |
103755 | import numpy as np
# projection mask of NYUv2
PMASK = np.zeros([480, 640], dtype=np.float64)
PMASK[44:471, 40:601] = 1.0
# sorted names
METRIC_NAMES = [
'RMSE',
'Mean RMSE',
'Mean Log10',
'Abs Rel Diff',
'Squa Rel Diff',
'delta < 1.25',
'delta < 1.25^2',
'delta < 1.25^3',
]
def get_m... |
103779 | import torch
import torch.nn as nn
from loss_functions import AngularPenaltySMLoss
class Stem_layer(nn.Module):
def __init__(self, in_ch, out_ch, kernel_size, drop_rate, pool_size):
super().__init__()
dilation = 1
self.conv = nn.Conv1d(
in_ch,
out_ch,
ke... |
103801 | class Solution:
def uniqueOccurrences(self, arr: List[int]) -> bool:
dict = {}
for i in arr :
if i in dict :
dict[i] += 1
else :
dict[i] = 1
count = 0
s = set(dict.values())
ns = len(s)
nl = len(... |
103803 | import pytest
from testfixtures import LogCapture
@pytest.fixture(autouse=True)
def log_capture():
with LogCapture() as capture:
yield capture
|
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