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import pytest from ceph_deploy.cli import get_parser from ceph_deploy.tests.util import assert_too_few_arguments class TestParserRepo(object): def setup(self): self.parser = get_parser() def test_repo_help(self, capsys): with pytest.raises(SystemExit): self.parser.parse_args('re...
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import glob import os def _path(*args): return os.path.join(os.path.dirname(__file__), *args) # pyxbld for pyximport (from cython): pyxbld = open(_path('template.pyxbld')).read() # Sundials: sundials_templates_dir = _path('sundials_templates') sundials = { os.path.basename(pth): open(pth).read() for pth in ...
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import graphics as gfx import common import vector import apple as appleFuncs SPEED = 12 def testForAppleProjectileCollision(projectile, apples): for apple in apples[:]: appleCenter = apple.getCenter() projCenter = projectile.getCenter() if vector.distanceBetween(appleCenter, projCente...
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from django.urls import path from users import views as users_views from django.contrib.auth import views as auth_views from django.conf.urls import url urlpatterns = [ path('', users_views.profile, name='profile'), path('home/', users_views.home, name='home'), path('register/', users_views.register, name=...
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from utils_io_folder import get_immediate_childfile_paths from utils_json import read_json_from_file, write_json_to_file def merge_posetrack_jsons(): posetrack_annotation_folder = "../data/Data_2017/posetrack_data/annotations/train" save_json_path = "posetrack_merged_train.json" gt_json_paths = get_immedi...
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import os import glob from flask import Flask from flask import jsonify from flask import request, render_template from webapp import app #from model.util import * from SigNet import main1, getpredictions valid_mimetypes = ['image/jpeg', 'image/png', 'image/tiff'] global model # def get_predictions(img_name): # ...
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from pathlib import Path import pytest from sqlalchemy import Column, String from flask_filealchemy.loaders import ( BaseLoader, loader_for, MarkdownFrontmatterDirectoryLoader, YAMLDirectoryLoader, YAMLFileLoader, ) def test_base_loader_does_not_validate(): with pytest.raises(NotImplementedE...
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from __future__ import absolute_import from __future__ import division from __future__ import print_function import torch import torch.nn as nn import torch.nn.functional as F class SVDEmbedding(nn.Module): def __init__( self, num, rank, output_dim, padding_idx=None, ...
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class Winratio: def __init__(self, **kwargs): self.losses = kwargs.get("Losses", kwargs.get("losses", 0)) or 0 self.wins = kwargs.get("Wins", kwargs.get("wins", 0)) or 0 @property def winratio(self): _w = self.wins /(self.matches_played if self.matches_played > 1 else 1) * 100.0 return int(_w) if _w % 2 == 0...
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from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('validator', '0003_celery_task_20190402_1445'), ] operations = [ migrations.CreateModel( name='DatasetConfiguration', fields=[ ...
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data = ( 'Ruo ', # 0x00 'Bei ', # 0x01 'E ', # 0x02 'Yu ', # 0x03 'Juan ', # 0x04 'Yu ', # 0x05 'Yun ', # 0x06 'Hou ', # 0x07 'Kui ', # 0x08 'Xiang ', # 0x09 'Xiang ', # 0x0a 'Sou ', # 0x0b 'Tang ', # 0x0c 'Ming ', # 0x0d 'Xi ', # 0x0e 'Ru ', # 0x0f 'Chu ', # 0x10 'Zi ...
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import pkg_resources import warnings import matplotlib.pyplot as plt import networkx as nx import numpy as np import torch from .. import setting from . import activation from . import concatenator from . import array2diagmat from . import array2symmat from . import deepsets from . import gcn from . import grad_gcn f...
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import pytest from data.test_data import generate_unstructured_test_data from lofo import Dataset def test_dataset(): df = generate_unstructured_test_data(1000, text=True) features = ["A", "B", "C", "D", "D2", "E"] # Exception: feature group row count is not equal to the features' row count feature_g...
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from Utils import Attribute class View: def View(self,name): self.mName = name self.attributes = [] self.mChildren = [] @classmethod def fromELement(cls,element): mName = element.tag viewCls = cls(mName) attributeslist = [] mChildre...
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import os dataset_path = r"D:\free_corpus\base" transformed_path = r"D:\free_corpus\processed" packed_path = r"D:\free_corpus\packed" # Containing metadata.csv and mels/, in dir of each dataset # and lang_to_id.json and spk_id.json in transformed_path and packed_path include_corpus = ['caito_de_de', 'caito_en_uk', 'c...
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import socket import threading import docker import time import iptc from enum import Enum from src.logger import logger from src.OneWayThread import OneWayThread class ContainerThread(threading.Thread): def __init__(self, source, connection, config): super().__init__() self.source = source ...
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from zipf import make_zipf, is_zipf generated = make_zipf(5) print('generated distribution: {}'.format(generated)) generated[-1] *= 2 print('passes test with default tolerance: {}'.format(is_zipf(generated))) print('passes test with tolerance of 1.0: {}'.format(is_zipf(generated, rel=1.0)))
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from numpy import arcsin, exp def _comp_point_coordinate(self): """Compute the point coordinates needed to plot the Slot. Parameters ---------- self : SlotW29 A SlotW29 object Returns ------- point_dict: dict A dict of the slot point coordinates """ Rbo = self.get...
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import torchvision.ops # noqa: F401 from torch2trt_dynamic.plugins import create_roipool_plugin from torch2trt_dynamic.torch2trt_dynamic import (get_arg, tensorrt_converter, trt_) @tensorrt_converter('torchvision.ops.roi_pool') def convert_roi_pool(ctx): input = g...
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import pyaudio import socket import select from pynput.keyboard import Key, Listener, Controller import threading FORMAT = pyaudio.paInt16 CHANNELS = 1 RATE = 44100 CHUNK = 4096 HOST = socket.gethostname() PORT = 8082 streaming = True audio = pyaudio.PyAudio() s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s...
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import re def get_errors(query: str, offset_field: str): errors = [] if not is_valid_timestamp(query, offset_field): errors.append(f'The query should have ascending ordering by {offset_field}') if not is_valid_offset(query): errors.append('Please use ${OFFSET} with a gt condition (not gte)...
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from .variables import get_variable, set_variable, delete_variable, Attributes from .variables import GLOBAL_NAMESPACE, DEFAULT_ATTRIBUTES from .privileges import privileges, patch_current_process_privileges from .boot import get_boot_order, get_boot_entry, set_boot_entry, set_boot_order from .boot import get_parsed_...
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import geoip2.database import geoip2.webservice import os from pydantic import BaseModel from tracardi.domain.named_entity import NamedEntity from tracardi.service.singleton import Singleton class PluginConfiguration(BaseModel): source: NamedEntity ip: str class GeoLiteCredentials(BaseModel): accountId...
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import os import sys from distutils.core import setup from pathlib import Path import numpy as np from transonic.dist import make_backend_files, init_transonic_extensions path_here = Path(__file__).parent.absolute() include_dirs = [np.get_include()] pack_name = "future" paths = tuple((path_here / pack_name).glob("...
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import dash_bootstrap_components as dbc from dash import html from .util import make_subheading badge = html.Div( [ dbc.Badge("Primary", color="primary", className="me-1"), dbc.Badge("Secondary", color="secondary", className="me-1"), dbc.Badge("Success", color="success", className="me-1"),...
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import random import asyncio import sc2 from sc2 import Race, Difficulty from sc2.constants import * from sc2.player import Bot, Computer from proxy_rax import ProxyRaxBot class SlowBot(ProxyRaxBot): async def on_step(self, iteration): await asyncio.sleep(random.random()) await super().on_step(it...
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import numpy as np import matplotlib.pyplot as plt RANDOM_SEED = 42 NUM_VIDEOS = 1000 MAX_NUM_BITRATES = 10 MIN_NUM_BITRATES = 3 MAX_NUM_CHUNKS = 100 MIN_NUM_CHUNKS = 20 # bit rate candidates # [200, 300, 450, 750, 1200, 1850, 2850, 4300, 6000, 8000] # Kbps MEAN_VIDEO_SIZE = [0.1, 0.15, 0.38, 0.6, 0.93, 1.43, 2.15, ...
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class UserModel(Tower): @model_property def inference(self): assert self.input_shape[0]==224, 'Input shape should be 224 pixels' assert self.input_shape[1]==224, 'Input shape should be 224 pixels' # Create some wrappers for simplicity def conv2d(x, W, b, s, padding='SAME'): ...
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from tensorflow.keras.layers import Input, Dense, Conv2D, MaxPool2D, ZeroPadding2D, Flatten from tensorflow import keras import tensorflow as tf import numpy as np class BaseModel(): """ Base class used to implement a model. This class itself should not instantiated. """ def __init__(self, comm, ...
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from flask_socketio import SocketIO socketio = SocketIO(cors_allowed_origins='*') def initSocket(app): socketio.init_app(app)
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from __future__ import absolute_import import os from django.conf import settings from celery import Celery # set the default Django settings module for the 'celery' program. os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'troupon.settings') app = Celery('troupon') app.config_from_object('django.conf:settings') app....
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from ctypes import c_int, c_size_t, c_void_p from .dll import _bind, SDLFunc, AttributeDict from .stdinc import SDL_bool __all__ = [ # Defines "SDL_CACHELINE_SIZE", ] # Constants & enums SDL_CACHELINE_SIZE = 128 # Raw ctypes function definitions _funcdefs = [ SDLFunc("SDL_GetCPUCount", None, c_int), ...
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import argparse import os import math import ruamel.yaml as yaml import numpy as np import random import time import datetime import json from pathlib import Path import torch import torch.backends.cudnn as cudnn import torch.distributed as dist from models.model_captioning import XVLM import utils from utils.checkp...
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from .scp_policy_resource import ScpPolicyResource from .scp_attachment_resource import ScpAttachmentResource
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import numpy as np import pytest from pytest_lazyfixture import lazy_fixture # Fixtures must be visible for lazy_fixture() calls. from .fixtures import * # noqa @pytest.fixture( params=( lazy_fixture('cof1'), lazy_fixture('cof2'), lazy_fixture('cof3'), ), ) def case_data(request): ...
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import os import sys from typing import Dict, Set import setuptools is_py37_or_newer = sys.version_info >= (3, 7) package_metadata: dict = {} with open("./src/datahub_airflow_plugin/__init__.py") as fp: exec(fp.read(), package_metadata) def get_long_description(): root = os.path.dirname(__file__) with...
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from typing import TYPE_CHECKING from PySide2.QtGui import QKeySequence, Qt from .menu import Menu, MenuEntry, MenuSeparator if TYPE_CHECKING: from angrmanagement.ui.widgets.qlog_widget import QLogWidget class LogMenu(Menu): def __init__(self, log_widget: 'QLogWidget'): super().__init__("", parent=...
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from decimal import Decimal as D from django.test import TestCase from parameterized import parameterized from capone.api.actions import create_transaction from capone.api.actions import credit from capone.api.actions import debit from capone.models import LedgerEntry from capone.models import MatchType from capone.m...
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import pickle import numpy as np import pytest import tensorflow as tf from garage.envs import GymEnv from garage.tf.q_functions import ContinuousMLPQFunction from tests.fixtures import TfGraphTestCase from tests.fixtures.envs.dummy import DummyBoxEnv class TestContinuousMLPQFunction(TfGraphTestCase): @pytest...
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import pytest import torch from utils import seq_len_to_mask from module import DotAttention, MultiHeadAttention torch.manual_seed(1) q = torch.randn(4, 6, 20) # [B, L, H] k = v = torch.randn(4, 5, 20) # [B, S, H] key_padding_mask = seq_len_to_mask([5, 4, 3, 2], max_len=5) attention_mask = torch.tensor([1, 0, 0, 1, ...
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import torch class Net(torch.jit.ScriptModule): def __init__(self, n: int): super().__init__() self._conv1 = torch.nn.Conv2d( 1, 10, 4, stride=1, padding=0, dilation=1, groups=1, bias=True ) self._conv2 = torch.nn.Conv2d( 10, 10, 3, stride=1, padding=0, dilat...
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from abc import ABC, abstractmethod from typing import Dict, Callable, Any, Optional, List from dataclasses import dataclass @dataclass class BaseParams: cpus_per_worker: int = 1 use_gpu: bool = False gpus_per_worker: Optional[int] = None def __post_init__(self): if self.gpus_per_worker and not...
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from __future__ import unicode_literals import six import abc import logging from jsonpointer import resolve_pointer, JsonPointerException logger = logging.getLogger(__name__) @six.add_metaclass(abc.ABCMeta) class BaseTransformer(object): @abc.abstractmethod def _transform_string(self, string, doc): ...
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import time from datetime import datetime from smtplib import SMTPRecipientsRefused from django.contrib import messages from django.contrib.auth import authenticate, login from django.contrib.auth.decorators import login_required from django.contrib.auth.views import password_reset, password_reset_confirm from django....
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import numpy as np import argparse import json import os # Function copy from video2tfrecords.py def split_equal(ids: list, duration: list, num: int, min_duration: int = 256): sort = sorted(zip(duration, ids))[::-1] ids_split = [[] for i in range(num)] duration_spit = [[] for i in range(num)] durati...
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import sj import sys status = 0 def test(prefix, file, rest): sj.create_and_cd_jalangi_tmp() ana = sj.execute_return_np(sj.JALANGI_SCRIPT+' --inlineIID --inlineSource --analysis ../src/js/sample_analyses/ChainedAnalyses.js --analysis ../src/js/runtime/SMemory.js --analysis ../src/js/sample_analyses/pldi16/Tra...
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from tests.utils import W3CTestCase class TestFlexbox_Inline(W3CTestCase): vars().update(W3CTestCase.find_tests(__file__, 'flexbox_inline'))
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def omp_sections_private(): sum = 7 sum0 = 0 if 'omp parallel': if 'omp sections private(sum0)': if 'omp section': sum0 = 0 for i in range(0, 400): sum0 += i if 'omp critical': sum += sum0 ...
476903
import logging import unittest from clarifai.rest import ApiError, ClarifaiApp class TestAuth(unittest.TestCase): """ unit test for api auth """ def test_auth_with_invalid_key(self): """ instantiate with key """ api_preset_key = 'abc' with self.assertRaises(ApiError): ClarifaiApp(api_key=...
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import numpy as np import matplotlib.pyplot as plt # For plotting import pdb import pandas as pd import seaborn as sns from scipy import stats data1 = np.load("train_nu.npz") #data1 = np.load('pipe_test_1dnu.npz') nu = data1['nu_1d'] #nu = np.sort(nu) print('nu is',nu) ############################ #profile viscosity ...
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class StorageNotFound(Exception): pass class StorageSettedError(Exception): pass class MismatchedVersionError(Exception): pass class InvalidPassword(Exception): pass
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from pymtl import * from lizard.util.rtl.interface import UseInterface from lizard.util.rtl.method import MethodSpec from lizard.util.rtl.drop_unit import DropUnit, DropUnitInterface from lizard.util.rtl.register import Register, RegisterInterface from lizard.mem.rtl.memory_bus import MemMsgType, MemMsgStatus from liza...
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import FWCore.ParameterSet.Config as cms source = cms.Source("EmptySource") from GeneratorInterface.Hydjet2Interface.hydjet2DefaultParameters_cff import * generator = cms.EDFilter("Hydjet2GeneratorFilter", collisionParameters5020GeV, qgpParameters, hydjet2Parameters, fNhsel = cms.int32(2), # Flag to include je...
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import urllib.request as request import os, datetime, json url = 'https://ladsweb.modaps.eosdis.nasa.gov/archive/allData' def get_lev_pro_year(level, product, year): ref = url + '/%s/%s/%s.json'%(level, product, year) req = request.Request(ref) response = request.urlopen(req) return json.loads(respons...
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from followthemoney.rdf import URIRef, Identifier from followthemoney.types.common import PropertyType from followthemoney.util import defer as _ class ChecksumType(PropertyType): """Content hashes calculated using SHA1. Checksum references are used by document-typed entities in Aleph to refer to raw data in ...
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def palin_perm(str): bitvec = [0] * 26 str = str.lower() for char in str: charCode = ord(char) - ord("a") if charCode >= 0 and charCode < 26: if bitvec[charCode] == 0: bitvec[charCode] = 1 else: bitvec[charCode] = 0 one = False ...
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class RhinoDeselectAllObjectsEventArgs(EventArgs): # no doc Document=property(lambda self: object(),lambda self,v: None,lambda self: None) """Get: Document(self: RhinoDeselectAllObjectsEventArgs) -> RhinoDoc """ ObjectCount=property(lambda self: object(),lambda self,v: None,lambda self: None) """Get:...
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from __future__ import print_function,division import torch import torch.nn as nn from torch.utils.data import DataLoader class Evaluator(object): def __init__(self,loss=nn.MSELoss(),batch_size=64,delay=36): self.loss=loss self.batch_size=batch_size self.delay=delay def evaluate(self,m...
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import string # forced import by CodeWars kata from string import ascii_uppercase as up, ascii_lowercase as low, \ ascii_letters as az, maketrans ROT13 = maketrans(low[13:] + low[:13] + up[13:] + up[:13], az) def rot13(message): return message.translate(ROT13)
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class TestCRUD: def test_add_one(self, db): result = db.add_one( {'name': 'alice', 'url': 'alice.com', 'method': 'get'}) errors = result.get('errors') success = result.get('success') assert errors is None assert success is True def test_fetch_one(self, db, ...
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import json import unittest import mock from src.access_token_common import AccessTokenCommon class AccessTokenCommonTest(unittest.TestCase): mock_os_environ_access_token = {"ACCESS_TOKEN_FROM_ENV": "access token 42"} @mock.patch.dict("os.environ", mock_os_environ_access_token, clear=True) def test_ac...
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from __future__ import (absolute_import, division, print_function, unicode_literals) import numpy as np import pandas as pd import statsmodels.api as sm from statsmodels.nonparametric.smoothers_lowess import lowess as smlowess from statsmodels.sandbox.regression.predstd import wls_prediction_std...
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import torch from torch import nn class LiteConv3x3(nn.Module): """Lite 3x3 convolution""" def __init__(self): super(LiteConv3x3, self).__init__() def forward(self, input): return input class AG(nn.Module): """Aggregation gate""" def __init__(self): super(AG, self).__i...
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import os import copy import click import uuid from zipfile import ZipFile, ZIP_DEFLATED from io import BytesIO from tcfcli.libs.utils.yaml_parser import yaml_dump from tcfcli.common.template import Template from tcfcli.libs.utils.cos_client import CosClient from tcfcli.common.user_exceptions import TemplateNotFoundExc...
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import pytest import time from common.exceptions import PlenumTypeError, PlenumValueError from stp_core.ratchet import Ratchet from plenum.common.throttler import Throttler def test_throttler_init_invalid_args(): for windowSize in (None, '5', [4]): with pytest.raises(PlenumTypeError): Throttl...
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import sys from bisect import bisect_left def bin_number(n, size=4): return bin(n)[2:].zfill(size) def iar(): return list(map(int, input().split())) def ini(): return int(input()) def isp(): return map(int, input().split()) def sti(): return str(input()) def par(a): print(" ".join(li...
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import os from abc import ABC import datetime import logging from typing import Callable, Iterator, Union, Optional, List, Type from enum import Enum, IntEnum import numpy import h5py from s100py.s1xx import s1xx_sequence, S1xxObject, S1xxCollection, S1xxDatasetBase, S1xxGridsBase, S1XXFile, h5py_string_dtype...
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import torch import torch.nn as nn from torch.nn import init from torch.optim import lr_scheduler import torchvision.models as torch_models ''' Helper functions for model Borrow tons of code from https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/blob/master/models/networks.py ''' def get_scheduler(optimizer, ...
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import torch import os import sys import numpy as np from pycocotools.coco import COCO from pycocotools.cocoeval import COCOeval from ..utils import tqdm, HiddenPrints class Evaluator(): """ Evaluation class. Performs evalution on a given model and DataHandler. Two main functions can be used:...
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import numpy as np import cv2 import string import math import os import uuid wd, _ = os.path.split(os.path.abspath(__file__)) class Captcha: def __init__(self, width, high, ls=None, lc=4, fs=None, folder=os.path.join(wd, 'samples'), debug=False): """ :param ls: letter set, all ...
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class Solution: def canConvert(self, s1: str, s2: str) -> bool: if s1 == s2: return True dp = {} for i, j in zip(s1, s2): if dp.setdefault(i, j) != j: return False return len(set(s2)) < 26
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import json import seaborn as sns import re import sys import os import os.path import pandas as pd import tinydb from matplotlib import pyplot as plt import pprint DEFAULT_STYLE = { 'secondary': 'style' } pp = pprint.PrettyPrinter() class ExperimentPlotter(object): def __init__(self, base_path, data, confi...
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import sys import decouple try: from .base import * # noqa except decouple.UndefinedValueError as exp: print('ERROR:', exp.message) sys.exit(1)
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import torch from torch import nn import math from typing import Optional from torch import Tensor eps=1e-5 ################################################################ # DGL's implementation of FeedForwardNet (MLP) for SIGN class FeedForwardNet(nn.Module): def __init__(self, in_feats, hidden, out_feats, n_la...
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from pymclevel.infiniteworld import MCInfdevOldLevel from pymclevel import mclevel from timeit import timeit import templevel #import logging #logging.basicConfig(level=logging.INFO) def natural_relight(): world = mclevel.fromFile("testfiles/AnvilWorld") t = timeit(lambda: world.generateLights(world.allChunk...
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import re from core.msfActionModule import msfActionModule from core.keystore import KeyStore as kb from core.utils import Utils class scan_msf_jboss_vulnscan(msfActionModule): def __init__(self, config, display, lock): super(scan_msf_jboss_vulnscan, self).__init__(config, display, lock) self.tri...
477500
import threading from lemoncheesecake.helpers.threading import ThreadedFactory def test_threaded_factory(): class TestFactory(ThreadedFactory): def setup_object(self): return object() factory = TestFactory() objects = [] class TestThread(threading.Thread): def run(self):...
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from collections import defaultdict from data_util.global_var import * class UnimorphSchema: # schema in unimorph-schema.tsv automatically extracted from https://unimorph.github.io/doc/unimorph-schema.pdf # using tabula https://github.com/tabulapdf/tabula def __init__(self, src=UNIMORPH_SCHEMA_SRC, ignor...
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import deep_architect.search_logging as sl import deep_architect.visualization as vi import deep_architect.utils as ut from deep_architect.searchers.random import RandomSearcher import deep_architect.modules as mo import deep_architect.contrib.misc.search_spaces.tensorflow.dnn as css_dnn import search_space as ss de...
477512
import math import bisect import copy import os.path as osp import json from functools import partial import numpy as np from PIL import Image import cv2 import torch from torch.utils.data import Dataset, DataLoader from torchvision.transforms.functional import normalize as tf_norm, to_tensor from .. import cfg as g...
477633
import os matlab_src_dir = os.path.abspath('.') extensions = ['sphinx.ext.autodoc', 'sphinxcontrib.matlab'] primary_domain = 'mat' master_doc = 'contents' # The suffix of source filenames. source_suffix = '.rst' nitpicky = True
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import json import mongodb_consistent_backup import sys from datetime import datetime from argparse import Action from pkgutil import walk_packages from yconf import BaseConfiguration from yconf.util import NestedDict def parse_config_bool(item): try: if isinstance(item, bool): return item ...
477662
from joblib import load as jl_load from pathlib import Path from os.path import dirname def load_model(model_name: str): pipeline = jl_load(Path(dirname(__file__)) / 'model' / f"{model_name}.joblib") pipeline.steps[0][1].init() return pipeline
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import dramatiq from account.models import User from submission.models import Submission from judge.dispatcher import JudgeDispatcher from judge.ide import IDEDispatcher from utils.shortcuts import DRAMATIQ_WORKER_ARGS @dramatiq.actor(**DRAMATIQ_WORKER_ARGS()) def judge_task(submission_id, problem_id): uid = Sub...
477713
import random import os import shutil from bench import resources from audiomate.corpus import io def run(corpus, base_path): target_path = os.path.join(base_path, 'out') shutil.rmtree(target_path, ignore_errors=True) os.makedirs(target_path) writer = io.KaldiWriter() writer.save(corpus, target...
477717
from gi.repository import Gtk, GObject, Gio from core.engine import GameEngine from gui.controllers.main_window_controller import MainWindowController from gui.controllers.theme_selection_controller import ThemeSelectionController from os import path from gui.controllers import gmenu_controller, about_controller from g...
477741
from django.contrib import admin from reversion.admin import VersionAdmin from .models import Municipality, Suministro, Tag @admin.register(Tag) class TagAdmin(VersionAdmin): list_display = ["name", "slug"] @admin.register(Municipality) class MunicipalityAdmin(VersionAdmin): list_display = ["get_name", "sl...
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import collections def jewels(J,S): c=collections.Counter(S) count =0 for js in J: count+=c[js] return count J='aA' S='aAAd' print(jewels(J, S ))
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import os from openl3.cli import run import tempfile import numpy as np import shutil import pytest TEST_DIR = os.path.dirname(__file__) TEST_AUDIO_DIR = os.path.join(TEST_DIR, 'data', 'audio') TEST_IMAGE_DIR = os.path.join(TEST_DIR, 'data', 'image') TEST_VIDEO_DIR = os.path.join(TEST_DIR, 'data', 'video') # Test au...
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import pytest import leaguepedia_parser @pytest.mark.parametrize("team_tuple", [("tsm", "TSM"), ("IG", "Invictus Gaming")]) def test_get_long_team_name(team_tuple): assert ( leaguepedia_parser.get_long_team_name_from_trigram(team_tuple[0]) == team_tuple[1] ) @pytest.mark.parametrize( "te...
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from __future__ import unicode_literals from django.db import migrations from django.utils import translation from django.utils.translation import gettext_lazy as _ def insert_modules(apps, schema): from django.conf import settings translation.activate(settings.LANGUAGE_CODE) ModuleGroup = apps.get_mode...
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import random """ A helper module for making rolls. """ def d20_check_roll(difficulty_class, modifiers=0, advantage=None): """ :param difficulty_class: Target for Success :param modifiers: Total amount of modifiers :param advantage: If is applicable, True if advantage, False if disadvantage. :retu...
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import altair as alt def rapids_theme(): font = "Open Sans" text_color = "#666666" main_palette = ["#7400ff", "#36c9dd", "#d216d2", "#ffb500"] secondary_palette = ["#bababc", "#666666", "#8824ff", "#9942ff", "#a785e7"] return { "config": { "axis": { "labelFontS...
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from .import_ai import * class TimedPickle: def __init__(self, data, name, enabled=True): self.data = data self.name = name self.enabled = enabled def __getstate__(self): return (time.time(), self.data, self.name, self.enabled) def __setstate__(self, s): tstart, se...
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from __future__ import division import math import collections import six import tensorflow as tf from neupy import init from neupy.utils import as_tuple from neupy.exceptions import LayerConnectionError from neupy.core.properties import ( TypedListProperty, Property, ParameterProperty, ) from .base import B...
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from .converters import ( BIGINTEGER, BINARY, BOOLEAN, BOOLEAN_ARRAY, BYTES, Binary, CHAR, CHAR_ARRAY, DATE, DATETIME, DECIMAL, DECIMAL_ARRAY, Date, DateFromTicks, FLOAT, FLOAT_ARRAY, INET, INT2VECTOR, INTEGER, INTEGER_ARRAY, INTERVAL, JSON, JSONB, MACADDR, NAME, NAME_ARRAY, NULLTYPE, NUMBER, OID, PGEnu...
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from base import pipeline, clean_db import random def test_null_groups(pipeline, clean_db): """ Verify that null group columns are considered equal """ pipeline.create_stream('s', x='int', y='int', z='int') q = """ SELECT x::integer, y::integer, z::integer, COUNT(*) FROM s GROUP BY x, y, z; """ desc...
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import os import numpy as np import pandas as pd import torch.utils.data as td from csl_common.vis import vis from csl_common.utils import geometry from datasets import facedataset class AFLW(facedataset.FaceDataset): NUM_LANDMARKS = 19 ALL_LANDMARKS = list(range(NUM_LANDMARKS)) LANDMARKS_NO_OUTLINE = AL...
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import unittest from nlpmodels.utils.elt import dataset class TestAbstractDataset(unittest.TestCase): def test_cannot_instantiate_abstract_class(self): with self.assertRaises(TypeError): dataset.AbstractNLPDataset()
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import pygame, sys import numpy as np from random import randint ON = 1 OFF = 0 class GameOfLife: def __init__(self, width=100, height=100): self.width = width self.height = height self.state_new = np.zeros((height, width)) self.state_old = np.zeros((height, width)) def get_wi...