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# -*- coding: UTF-8 -*-
from random import randint
from math import sqrt
import random
'''
import numpy
import pylab
'''
def make_fair_dice(sides):
''' Creation of game dice with SIDES sides
>>> one_sided_dice = make_fair_dice(1)
>>> one_sided_dice()
1
'''
assert type(sides) == int and sides >=... |
from threading import Thread, Lock, Event
from curses import doupdate
from wingen import WinGen
import curses
class ConsoleScreen(object):
def __init__ (self):
self.screen = None
self.clsLock = Lock ()
self._execThread = None
self._Stop = Event ()
self.enabled = False
def __del__ (self):
if self.sc... |
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to us... |
#-------------------------------------------------------------------------------
# Copyright (c) 2020 DOIDO Technologies
#
# Author : Walter
# Version : 1.0.5
# Location : github
#-------------------------------------------------------------------------------
#-----------------------------------------------... |
#! /usr/bin/python3
#
# Copyright (c) 2017 Intel Corporation
#
# SPDX-License-Identifier: Apache-2.0
#
#
# FIXME:
#
# - command line method to discover installed capabiltiies; print
# each's __doc__
#
# - do not pass device--each function should gather it from target's
# tags
"""
.. _pos_multiroot:
Provisioning OS... |
# vim: tabstop=4 shiftwidth=4 softtabstop=4
# Copyright 2012 Nebula, Inc.
# Copyright 2013 IBM Corp.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org... |
import torch
import torch.nn as nn
# Discriminator Model
class CoDis28x28(nn.Module):
def __init__(self):
super(CoDis28x28, self).__init__()
# conv0
self.conv0_a = nn.Conv2d(3, 32, kernel_size=5, stride=2, padding=2)
self.conv0_b = nn.Conv2d(3, 32, kernel_size=5, stride=2, padding=... |
from __future__ import absolute_import
# Copyright (c) 2010-2016 openpyxl
# Simplified implementation of headers and footers: let worksheets have separate items
import re
from warnings import warn
from openpyxl.descriptors import (
Bool,
Strict,
String,
Integer,
MatchPattern,
Typed,
)
from op... |
# Copyright 2020 Kaggle Inc
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
# In this file, we extract the vision features as the keys in retrieval.
import argparse
import os
import pickle
import shutil
import sys
import h5py
import torch
from torchvision import transforms
from torchvision.datasets.folder import default_loader
import tqdm
from transformers import BertTokenizer
from PIL import... |
#!/usr/bin/env python
from __future__ import print_function
import os
import re
import sys
from datetime import datetime
import click
from send2trash import send2trash
# Verify that external dependencies are present first, so the user gets a
# more user-friendly error instead of an ImportError traceback.
from elodie... |
import math
import time
import torch
import torch.cuda.nvtx as nvtx
import numpy as np
import torch.nn.functional as F
import torch.optim as optim
import torch.utils.data
from tqdm import tqdm
from utils.initializers import args_initialize, env_initialize, log_initialize, model_initialize
from a2c.helper import call... |
# -*- coding: UTF-8 -*-
from flask import Flask, render_template, send_from_directory, send_file
from flask import request
import JsonWriter
import netifaces as ni
import sys
import signal
import wheaterData as wD
from _thread import start_new_thread
import time
from datetime import datetime
from flask import Markup
im... |
import types
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
def get_mask(in_features, out_features, in_flow_features, mask_type=None):
"""
mask_type: input | None | output
See Figure 1 for a better illustration:
https://arxiv.org/pdf/1502.03509.pdf
"""
... |
#!/usr/bin/env python
# coding=utf8
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
"""BFE 논문의 성능 비교를 위해 CUB BIRD200-2011 를 생성한다."""
import os
import random
import argparse
import sys
sys.path.append('./')
sys.path.append('../')
from datetime import datet... |
"""
Name: HumbleForwarder
Author: kjp
URL: https://github.com/kjpgit/HumbleForwarder
Humble SES email forwarder. Simple address mapping is supported. Feel free to
fork it if you want more configurability.
See README.md for full documentation
"""
import email.message
import email.parser
import email.policy
import js... |
import argparse
import time
import numpy as np
from ssn_dataset import SSNDataSet
from transforms import *
from ops.utils import temporal_nms
import pandas as pd
from multiprocessing import Pool
from terminaltables import *
import sys
sys.path.append('./anet_toolkit/Evaluation')
from anet_toolkit.Evaluation.eval_dete... |
from static.simulation.plot import create_plot, create_plot2
import numpy as np
from static.simulation.country import CountryCreator
from static.simulation.seir import seibqhr
from static.simulation.real_data import download
# TODO Add True Recovered
rc, rr, rd = download()
countries_arr, countries_keys = CountryCreat... |
from SkateUtils.NonHolonomicWorld import NHWorld, NHWorldV2
from SkateUtils.DartMotionEdit import DartSkelMotion
import numpy as np
from math import exp, pi, log
from PyCommon.modules.Math import mmMath as mm
from random import random, randrange
import gym
import gym.spaces
from gym.utils import seeding
import pydart2 ... |
from __future__ import division
from __future__ import print_function
import time
import argparse
import numpy as np
import torch
import torch.nn.functional as F
import torch.optim as optim
from pygcn.utils import load_data, accuracy
from pygcn.models import GCN, MLP
from sklearn.preprocessing import StandardScaler
... |
import tensorflow as tf
from tensorflow.keras import layers
from tensorflow.keras.layers import Input, Add, Dense, Activation, ZeroPadding2D, BatchNormalization, Flatten, Conv2D, AveragePooling2D, MaxPooling2D, GlobalMaxPooling2D
from tensorflow.keras.models import Model, load_model
def identity_block(input_ten... |
from Base.BaseType import *
CODE_PAGE = 'cp932'
SEPITH_CHI = 0
SEPITH_MIZU = 1
SEPITH_HONO = 3
SEPITH_KAZE = 2
SEPITH_TOKI = 4
SEPITH_SORA = 5
SEPITH_GEN = 6
CHIP_TYPE_CHAR = 7
CHIP_TYPE_APL = 8
CHIP_TYPE_MONSTER = 9
class ScenarioChipInfo:
# ULONG chipindex
def __init__(self, fs = None):
... |
"""Module for Regression Testing the InVEST GLOBIO model."""
import unittest
import tempfile
import shutil
import os
import pygeoprocessing.testing
from osgeo import ogr
from osgeo import gdal
import numpy
from natcap.invest import utils
SAMPLE_DATA = os.path.join(
os.path.dirname(__file__), '..', ... |
import pandas as pd
import numpy as np
import os
import datetime
# Helpers
# Identify Win/Loss Streaks if any.
def get_3game_ws(last_matches):
if hasattr(last_matches, "__len__"):
return 1 if len(last_matches) > 3 and last_matches[-3:] == 'WWW' else 0
return np.nan
def get_5game_ws(last_matches):
... |
import os
import json
import numpy
import math
from PIL import Image, ImageDraw, ImageFont
import copy
from tqdm import tqdm
type_dict = {0:(0,255,0),1:(255,0,0),2:(230,230,0),3:(230,0,233),4:(255,0,255),5:(125, 255, 233)}
def get_point(points, threshold):
count = 0
points_clean = []
for point in points:
... |
#!/usr/bin/env python3
import sys
import json
import argparse
from string import Template
try:
from html import escape # python 3.x
except ImportError:
from cgi import escape # python 2.x
class GCVAnnotation:
height = None
width = None
templates = {
'ocr_page': Template("""<?xml versi... |
from collections import namedtuple
from collections.abc import Iterable
from scipy.stats import rv_discrete, rv_continuous, multivariate_normal, norm
from scipy.stats._distn_infrastructure import rv_sample
from numpy import interp
from os.path import dirname
import numpy as np
import pickle
import os
__all__ = ['cum_... |
# cantest.py Tests of task cancellation
# The MIT License (MIT)
#
# Copyright (c) 2017-2018 <NAME>
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without li... |
import sys
from dataclasses import dataclass
import numpy as np
from scipy import spatial
from utils import MinHeap, Quadric, Plane
def quadric_error_function(src, tgt, halfedge):
# If this is a boundary edge, form the boundary condition quadric
if halfedge is not None:
if halfedge.is_boundary() or... |
# -*- coding: utf-8 -*-
# Copyright 2017 Vector Creations Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
from __future__ import unicode_literals
from flask import Flask, render_template_string, Markup
from unittest import TestCase
from textwrap import dedent
try:
from unittest import mock
except ImportError:
import mock
import misaka
from misaka import (EXT_AUTOLINK, EXT_FENCED_CODE, # pyflakes.ignore
... |
#!/usr/bin/python
# pylint: disable=missing-module-docstring
# pylint: disable=missing-function-docstring
# pylint: disable=missing-class-docstring
import os
import shutil
import sys
from argparse import ArgumentParser
import python_hosts
from dotenv import load_dotenv
from mininet.cli import CLI
# from mininet.link... |
import torch
from torch import nn, optim
import torch.nn.functional as F
import random
__all__ = ['ImgVAE', 'ImgDiscriminator', 'ReplayBuffer']
class ResizeConv2d(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, scale_factor, mode='nearest'):
super().__init__()
self.scale_fa... |
# Copyright (C) 2018-2021 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import logging as log
import numpy as np
from openvino.tools.mo.front.common.partial_infer.utils import assign_dims_to_weights, int64_array, compatible_dims, compatible_shapes, \
shape_array, is_fully_defined, shape_delete, shape_i... |
import datetime
import getpass
import json
import logging
from copy import deepcopy
from hashlib import sha1
from botocore.credentials import (CachedCredentialFetcher,
CanonicalNameCredentialSourcer,
CredentialProvider, Credentials,
... |
from __future__ import with_statement
import random
import re
import socket
import mock
from nose.tools import eq_
from statsd import StatsClient
ADDR = (socket.gethostbyname('localhost'), 8125)
def _client(prefix=None):
sc = StatsClient(host=ADDR[0], port=ADDR[1], prefix=prefix)
sc._sock = mock.Mock()
... |
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import os
import pytest
import numpy as np
import astropy.units as u
from astropy.io import ascii
from astropy.utils.data import get_pkg_data_filename
import synphot
from .. import core
from ..core import *
from ...photometry import bandpass
from ...calib... |
# coding=utf-8
# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... |
from math import sqrt
import einops
import torch
import torch.nn as nn
import torch.nn.functional as F
from modeling.ops import PositionalEncodingFourier, DropPath
class MultiHeadXCITAttention(torch.nn.Module):
def __init__(self, embed_size, num_heads, attention_dropout_rate, projection_dropout_rate, attention_... |
# py--lint: disable=import-error
def send_email(sender:str, receivers:list, msg_title, msg_body, smtp_server:str, password:str,
cc_emails:list=None, sender_name:str='',
attachment_filepath=None, attachment_name=None,
receivers_can_see_eachother=False, print_ret=False) -> bool:
... |
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... |
# vim: tabstop=4 shiftwidth=4 softtabstop=4
# OpenCenter(TM) is Copyright 2013 by Rackspace US, Inc.
##############################################################################
#
# OpenCenter is licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compli... |
'''
STEP1: load data -->
STEP2: prepare data -->
STEP3: learn node embeddings -->
STEP4: downstream evaluations
python src/main.py --method abrw
by <NAME> 2018 <<EMAIL>>
'''
import time
import random
import numpy as np
from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
from sklearn.linear_model impor... |
import os
import time
from data_util.log import logger
import torch as T
import rouge
from model import Model
from data_util import config, data
from data_util.batcher import Batcher, Example, Batch
from data_util.data import Vocab
from beam_search import beam_search
from train_util import get_enc_data
from rouge impor... |
"""
Ray factory
classes that provide vertex and triangle information for rays on spheres
Example:
rays = Rays_Tetra(n_level = 4)
print(rays.vertices)
print(rays.faces)
"""
from __future__ import print_function, unicode_literals, absolute_import, division
import numpy as np
from scipy.spatial import Con... |
"""
Morphology module
=================
:synopsis: Create foam morphology in CAD format.
.. moduleauthor:: <NAME> <<EMAIL>>
"""
from __future__ import print_function
import os
import numpy as np
from blessings import Terminal
from OCC.Core.gp import gp_Pnt, gp_Vec, gp_Trsf
from OCC.Core.BRep import BRep_Builder
from O... |
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import sys
#from __future__ import unicode_literals
from pytoxr.mathfunctions import sine, sine_perfect_helix, residuals
import scipy.optimize
import os
#from thoipapy.sine_curve.tlabtools import tools
#import tlabtools as tools
#from thoipapy.utils... |
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See LICENSE in the project root
# for license information.
from __future__ import absolute_import, division, print_function, unicode_literals
import pytest
import sys
import debugpy
import tests
from tests import debug
from... |
'''Check files for broken links.'''
import os
import re
import sys
import yaml
import logging
import requests
import time
from multiprocessing.dummy import Pool as ThreadPool
from multiprocessing.dummy import Lock
# This isn't a perfect URL matcher, but should catch the large majority of URLs.
# This now matches URLs... |
import datetime as dt
import discord
generated_ids = 0
def make_id():
global generated_ids
# timestamp
discord_epoch = str(bin(int(dt.datetime.now().timestamp() * 1000) - 1420070400000))[2:]
discord_epoch = "0" * (42 - len(discord_epoch)) + discord_epoch
# internal worker id
worker = "00001"... |
# coding: utf-8
'''
Module to be used for static analysis
'''
import numpy as np
import sympy as sp
import scipy
import matplotlib.pyplot as plt
from matplotlib import patches
from mpl_toolkits.mplot3d import Axes3D
def simple_support():
L = 15
P = 5
Ploc = 5
plt.rcParams['figure.figsize'] = (10, 8)... |
import time
from typing import Any, Iterable, List, Optional, Set, Union
import numpy as np
import wrapt
def subsample_sequence(old_len, new_len):
if new_len == old_len:
return 0, old_len
assert new_len < old_len
max_start = old_len - new_len
start = np.random.randint(0, max_start)
return... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import collections
import json
from crypto import (PublicKey, PrivateKey, seed_from_mnemonic, root_from_seed, decode_xkey,
xpub_from_xprv, private_derivation, public_derivation)
from address import Address
from mnemonic import generate_mnemonic
from ... |
import tensorflow as tf
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
import re
import sys
import time
import pickle
import I2S_Model
from datetime import datetime
np.set_printoptions(threshold=sys.maxsize)
tpu = tf.distribute.cluster_resolver.TPUClusterResolver(tpu='node-3')
print('Runni... |
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
from sklearn.model_selection import GridSearchCV
from sklearn.linear_model import LogisticRegression
from sklearn.svm import SVC
from sklearn.linear_model import LinearRegression
from sklearn.ensemble import RandomForestRegres... |
import logging
import numpy
import chaospy
def approximate_inverse(
distribution,
idx,
qloc,
bounds=None,
cache=None,
parameters=None,
xloc0=None,
iterations=300,
tolerance=1e-12,
):
"""
Calculate the approximation of the inverse Rosenbl... |
import numpy as np
import tensorflow as tf
import cv2
import tqdm
from network_sn import Network
import load
import random
IMAGE_SIZE = 128
LOCAL_SIZE = 64
HOLE_MIN = 24
HOLE_MAX = 48
LEARNING_RATE = 5e-4
BATCH_SIZE = 16
PRETRAIN_EPOCH = 100
HOGO = 100
BETA1 = 0.9
BETA2 = 0.999
RETAIN = True
def train():
val_g =... |
from scipy.stats.stats import pearsonr, spearmanr
from plotly import tools
from plotly.graph_objs import *
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
import plotly.graph_objs as go
import matplotlib.pyplot as plt
import seaborn as sns
import itertools
import numpy as np
import pandas ... |
# Copyright (c) 2019, Myrtle Software Limited. All rights reserved.
# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# ... |
from downloader import Downloader
from descriptive_analysis import *
from export_collection_data import *
from pymongo import MongoClient
from pymongo.errors import PyMongoError
from bs4 import BeautifulSoup
from datetime import datetime
import ssl
import re
ssl._create_default_https_context = ssl._create_un... |
import asyncio
import datetime
import json
import asyncpg
import discord
from discord.ext import commands, tasks
from discord.ext.commands.cooldowns import BucketType
class Stats(commands.Cog):
def __init__(self, bot):
self.bot = bot
# Track command count
self.command_count = 0
s... |
"""Datadog monitor to OSC messages
This program reads the query from a Datadog monitor, calls their query API and normalizes
the resultant values against the threshold to send out as an OSC message
"""
import argparse
import os
import time
import sys
from pprint import pprint
from pythonosc import udp_client
from ... |
#!/usr/bin/env python
######################################################################
# Software License Agreement (BSD License)
#
# Copyright (c) 2012, Rice University
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that t... |
# coding=utf-8
"""API to most common queries to the dataset."""
import collections
import os
import sqlite3
from typing import AnyStr
import tqdm
def main():
db_path = os.path.normpath(os.path.join(os.path.dirname(__file__), '../data/dataset/evalution2.db'))
# use verbose=1 for debugging.
db = EvaldDB(d... |
import json
import logging
import os
from pathlib import Path
from typing import Tuple
import hydra
import numpy as np
import torch
from apex.parallel.LARC import LARC
from omegaconf import OmegaConf
from torch.utils.data import DataLoader
from src.data.ag_news import (CollateSupervised, collate_eval_batch,
... |
import auth, os, random, re, socket, sys, time
import sqlite3 as sql
from markov import Markov
DIR = os.path.dirname(os.path.realpath(__file__))
print(DIR)
"""
Helper functions.
"""
# Initiation.
def init ():
init_ops()
# Average output generator
def avg (list_):
x = 0
for i in list_:
x += i
return int(x / l... |
import os, time
import unittest
import pandas as pd
import numpy as np
from pathlib import Path
from pyrolite.util.synthetic import test_df, test_ser
from pyrolite.util.general import temp_path, remove_tempdir
from pyrolite.util.meta import subkwargs
from pyrolite.util.pd import *
class TestColumnOrderedAppend(unitte... |
'''
###############################################################################
FIT POLYNOMIAL MODULE
###############################################################################
This module contains the following functions:
Polynomial fits
---------------
> fit_poly(x,y)
> fit_polynomial(data)
> polyfit2d(x, ... |
# -*- coding: utf-8 -*-
"""
@created on: 9/21/19,
@author: <NAME>,
@version: v0.0.1
@system name: badgod
Description:
..todo::
"""
import numpy as np
import random
from collections import defaultdict
"""
Monte-Carlo
In this problem, we will implememnt an AI player for Blackjack.
The main goal of thi... |
## @package optimizer_test_util
# Module caffe2.python.optimizer_test_util
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import unittest
import numpy as np
from caffe2.python import brew, core, workspace, cnn, optimi... |
import os
import sys
DEBUG = False
COMPRESS = True
OVERWRITE = True
sys.path.insert(0, '../..')
import tabixpy
def runTest(testName, infile, expects, indexType):
tb = tabixpy.Tabix(infile, indexType=indexType)
gzfile = tb.bgz
indexFile = tb.indexFile
sourceFile = tb.sourceFile
... |
# Original Link: https://github.com/kuangliu/pytorch-cifar/
# Original Author: <NAME>
# Original License: MIT
# Adapted to support Model quantization
'''MobileNetV2 in PyTorch.
See the paper "Inverted Residuals and Linear Bottlenecks:
Mobile Networks for Classification, Detection and Segmentation" for more details.
'... |
"""Testing utilities
"""
from textwrap import dedent
from xml.etree import ElementTree
import time
import datetime
import calendar
def to_utc(a_datetime):
timestamp = time.mktime(a_datetime.timetuple())
return datetime.datetime.utcfromtimestamp(timestamp)
def to_rfc3339(a_datetime):
utc_dt = to_utc(a_d... |
import math
import numpy as np
import os
import pandas as pd
import torch
from tqdm import tqdm as tqdm
from spacy import displacy
from spacy.util import is_in_jupyter
from transformers import AutoTokenizer
from typing import Dict
from thermostat.data import get_local_explanations
from thermostat.utils import delistif... |
"""watch a given directory for file changes using the command line, useful for demos"""
import os, platform, sys, time, argparse, math, logging
from colour import Colour
def normalised_path(input_path:str) -> str:
"""returns a normalised "real"/"full" filepath for a given directory then checks its a valid dir... |
import importlib
import inspect
import os
import re
import sys
import traceback
from types import FunctionType, MethodType
from devtool.utils.getModules import get_modules_location
from graphviz import Digraph
from entity2uml import FakeClass, __default_methods__
from entity2uml.drawer import (Diagram, __engines__, _... |
import ast
from unittest import TestCase
from darglint.lex import (
condense,
lex,
)
from darglint.parse.sphinx import (
parse,
)
from .sphinx_docstrings import docstrings
from darglint.utils import (
CykNodeUtils,
)
class SphinxParserTest(TestCase):
def test_parse_short_description_is_line_cyk(... |
import math
import numpy as np
from numpy import linalg as LA
import numpy as np
import scipy
from scipy.sparse import *
from scipy.sparse.linalg import norm
import time
import nonnegfac
import importlib
importlib.reload(nonnegfac)
def claculate_norm(X, A, K, PARFOR_FLAG):
# UNTITLED3 Summary of this function go... |
from __future__ import division
from __future__ import print_function
from __future__ import absolute_import
from builtins import zip
from builtins import range
from builtins import object
from past.utils import old_div
import numpy as np
import pandas as pd
import os
import collections
from ..serialize import Seriali... |
# MIT License
#
# Copyright (C) 2021. Huawei Technologies Co., Ltd. All rights reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation th... |
import os.path as path
import logging
import sqlite3
import pickle
from collections import deque
from ipaddress import ip_address
from threading import Lock
from time import time, sleep
from urllib.parse import urlparse
from tracker import Tracker
max_input_length = 20000
submitted_trackers = deque(maxlen=10000)
if p... |
# Required to upload files
from rest_framework.parsers import FileUploadParser
from rest_framework.response import Response
from rest_framework.views import APIView
from rest_framework import status
from rest_framework import generics
from .serializers import AmenitiesSerializer, MmuSerializer
from .models import Ameni... |
"""This file contains some sample functions for the domain operations.
Since Union/Cut/Intersection follow the same idea for sampling for a given number of points.
"""
import torch
import warnings
from torchphysics.problem.spaces.points import Points
def _inside_random_with_n(main_domain, domain_a, domain_b, n, para... |
"""
The MIT License (MIT)
Copyright © 2015 RealDolos
Copyright © 2018 Szero
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the “Software”), to deal
in the Software without restriction, including without limitation the rights
to use, cop... |
import unittest
from pathlib import Path
from bridgebots.board_record import BidMetadata
from bridgebots.deal_enums import Direction, Rank, Suit
from bridgebots.pbn import _build_record_dict, _parse_bidding_record, _sort_play_record, parse_pbn
class TestParsePbnFile(unittest.TestCase):
def test_parse_file(self):... |
import numpy as np
import gym
import matplotlib.pyplot as plt
SHOW_ENV_DISPLAY_FREQUENCY = 100
DEFAULT_ITERATION_COUNT = 100000
Observation = [30, 30, 50, 50]
np_array_win_size = np.array([0.25, 0.25, 0.01, 0.1])
# Creates a table of Q_values (state-action) initialized with zeros
# Initialize Q(s, a), for all s ∈ S,... |
#!/usr/bin/env python
"""***************************************************************************
**
** Copyright (C) 2005-2005 Trolltech AS. All rights reserved.
**
** This file is part of the example classes of the Qt Toolkit.
**
** This file may be used under the terms of the GNU General Public
** License versio... |
#!/usr/bin/env python
# coding=utf-8
"""Module Description
Copyright (c) 2018 <NAME> <<EMAIL>>
This code is free software; you can redistribute it and/or modify it
under the terms of the MIT License.
@Gene-panel sequencing analysis pipeline in somatic mode
@status: experimental
@version: 1.0
@author: <NAME>
@contact... |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
from collections import namedtuple
from typing import Union
import torch
from pytorch3d import _C
from torch.a... |
# -*- coding: utf-8 -*-
import torch
import torch.nn as nn
from supar.modules.dropout import SharedDropout
from torch.nn.modules.rnn import apply_permutation
from torch.nn.utils.rnn import PackedSequence, pack_padded_sequence
class CharLSTM(nn.Module):
r"""
CharLSTM aims to generate character-level embedding... |
from nltk.stem.snowball import SnowballStemmer
from nltk.corpus import stopwords
from summariser.rouge.rouge import Rouge
import summariser.utils.data_helpers as util
import numpy as np
import operator as op
import functools
from sklearn.metrics.pairwise import cosine_similarity
from sklearn.feature_extraction.text im... |
from __future__ import print_function
from copy import copy, deepcopy
import datetime
import inspect
import sys
import traceback
from django.core.management import call_command
from django.core.management.commands import loaddata
from django.db import models
from django import VERSION as DJANGO_VERSION
import south.... |
from pynq import Overlay
from pynq.lib import AxiGPIO
ol = Overlay("./overlays/CICADA_N_CLAIRE.bit")
import numpy as np
import time
trig_ldo_dut_ip = ol.ip_dict['gpio_spi_trig_ldo_dut']
dut_tx_rx_data_ip = ol.ip_dict['gpio_spi_dut_tx_rx_data']
ts_rst_dut_rst_ip = ol.ip_dict['gpio_spi_ts_rst_dut_rst']
trig_dut = AxiG... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import pandas as pd
from numpy import float64 as npfloat64
from scipy.sparse import coo_matrix, csr_matrix
from sklearn.model_selection import ParameterGrid
from implicit.als import AlternatingLeastSquares
from implicit.evaluation import train_test_split
from imp... |
#!/usr/bin/env python
import sys
import multiprocessing
import gzip
import os
from subprocess import check_call as cc, CalledProcessError
from enum import IntEnum
argv = sys.argv
if sys.version_info[0] != 3:
raise Exception("Python 3 required")
class ExitCodes(IntEnum):
EXIT_SUCCESS = 0
EXIT_FAILURE = 1... |
#! /usr/bin/env python
# encoding: utf-8
# <NAME>, 2011 (ita)
"""
A client for the network cache (playground/netcache/). Launch the server with:
./netcache_server, then use it for the builds by adding the following:
def options(opt):
opt.load('netcache_client')
The parameters should be present in the environment ... |
'''ResNet in PyTorch.
For Pre-activation ResNet, see 'preact_resnet.py'.
Reference:
[1] <NAME>, <NAME>, <NAME>, <NAME>
Deep Residual Learning for Image Recognition. arXiv:1512.03385
'''
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import numpy as np
cla... |
import numpy as np
from rsrespic.utilities import constants
from numpy import exp, sin, einsum
import numba
pi = np.pi
q = constants.cgs_constants['q']
c = constants.cgs_constants['c']
## Convert units to cgs from mks
class sine_transform_2D(object):
def __init__(self):
self.name = '2-d electrostatic solv... |
# -*- coding: utf-8 -*-
# Copyright 2020 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law ... |
#!/usr/bin/env python
import argparse
import contextlib
from collections import defaultdict
import string
import sys
import os
def main():
script_path = os.path.realpath(__file__)
script_dir = os.path.dirname(script_path)
default_input = os.path.join(
script_dir, "UnitTests", "TestData", "gen", "... |
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