content
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sequencelengths 1
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| ratio_char_token
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import json
colours = json.loads(open("theme/default.json").read()) | [
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# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
import multiprocessing
import os
import random
import time
from enum import Enum
import numpy as np
from PIL import Image
from settings import default_sim_settings, make_cfg
import habitat_sim
import habitat_sim.agent
import habitat_sim.bindings as hsim
from habitat_sim.physics import MotionType
from habitat_sim.utils.common import (
d3_40_colors_rgb,
download_and_unzip,
quat_from_angle_axis,
)
_barrier = None
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 17 15:05:43 2020
@author: lihaoyang03
"""
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import sys
import time
import random
from sync_utils import Thread, Semaphore, Barrier, watch
SANTA = Semaphore(0)
NUM_DEERS = 0
DEER_MUTEX = Semaphore(1)
SLEDGE = Semaphore(0)
SLEDGE_READY = Semaphore(0)
BARRIER = Barrier(9)
NUM_ELVES = 0
ELF_MUTEX = Semaphore(1)
ELF_MULTIPLEX = Semaphore(3)
HELP = Semaphore(0)
watch(main)
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import pandas as pd
import numpy as np
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#!/usr/bin/python
import argparse
import dns.resolver
import dns.query
import dns.zone
import os
import sys
from multiprocessing import Pool
INPUTFILE = sys.stdin
OUTPUTFILE = sys.stdout
LOGFILE = sys.stderr
PROCESSES = 20
if __name__ == '__main__':
main()
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"""Script to convert non-jpgs in a folder to jpg"""
import os
from pathlib import Path
from PIL import Image
from glob import glob
from tqdm import tqdm
from shutil import move
cwd = Path.cwd()
DATA_DIR = cwd.parent / 'data' / 'stanford-car-dataset-by-classes-folder' / 'car_data' / 'new_data'
if __name__ == '__main__':
convert_png_to_jpg() | [
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import learnable_histogram
import TauDataset
import data_processing as dp
import numpy as np
import tensorflow as tf
import losses
import histogram
import visualizer
import CubeDataset
from report import print_report, error_statistics
mode = 'rb'
# path = "/media/donik/Disk/intel_tau/paths_field.txt"
# imgs = load_image_names(path, base_path='/media/donik/Disk/intel_tau')
# count = len(imgs)
# imgs_test = imgs[int(count * 0.9):]
import CubeDataset
from sklearn.model_selection import train_test_split
path = "/media/donik/Slowpoke/fax/Cube+/paths.txt"
paths = load_image_names(path, base_path="/media/donik/Slowpoke/fax/Cube+")
_, paths = train_test_split(paths, train_size=0.8, random_state=69)
gts = np.loadtxt("/media/donik/Slowpoke/fax/Cube+/cube+_gt.txt")
indices = np.array(list(map(lambda x: int(x[x.rfind('/') + 1:-4]) - 1, paths)))
ds = CubeDataset.regression_dataset(paths, indices, type=CubeDataset.TEST, bs=1, cache=False,
uv=False,
gts=gts)
# ds = TauDataset.regression_dataset(imgs_test, dp.TEST, bs=1, uv=True)
ds = ds.map(map_fn)
model, hist = learnable_histogram.build_model(TauDataset.IMG_HEIGHT // 2, TauDataset.IMG_WIDTH // 2, 5, 256,
range_init=(0, 1), w_init=1 / 64, out=2, activation='relu')
# model, hist = learnable_histogram.build_simple_model(TauDataset.IMG_HEIGHT // 2, TauDataset.IMG_WIDTH // 2, 3, 64,
# range_init=(-5, 5), w_init=1 / 32)
checkpoint_path = f"/home/donik/Desktop/models/training_08_11/hist_simple_2_cube.ckpt"
# checkpoint_path = f"/home/donik/Desktop/models/training_06_11/hist_simple_tau.ckpt"
model.load_weights(checkpoint_path)
learnable_histogram.plot_histogram(hist)
coss = []
for img, mask in iter(ds):
pred = model.predict(img)
if mode == 'uv':
pred_rgb = histogram.from_uv(pred)
mask_rgb = histogram.from_uv(mask)
else:
pred_rgb = tf.stack([pred[..., 0], tf.ones_like(pred[..., 0]), pred[..., 1]], axis=-1)
mask_rgb = tf.stack([mask[..., 0], tf.ones_like(mask[..., 0]), mask[..., 1]], axis=-1)
mask_rgb = tf.cast(mask_rgb, dtype=float)
cos = losses.cosine_similarity(pred_rgb, mask_rgb) * 180 / 3.14
coss.append(cos)
print(cos)
p = visualizer.create_mask(pred_rgb[0], (10, 10))
m = visualizer.create_mask(mask_rgb[0], (10, 10))
visualizer.visualize([m,p])
report = error_statistics(coss)
print_report(report) | [
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] | 2.142017 | 1,190 |
from .rotation import * | [
6738,
764,
10599,
341,
1330,
1635
] | 3.833333 | 6 |
from output.models.nist_data.list_pkg.any_uri.schema_instance.nistschema_sv_iv_list_any_uri_max_length_3_xsd.nistschema_sv_iv_list_any_uri_max_length_3 import NistschemaSvIvListAnyUriMaxLength3
__all__ = [
"NistschemaSvIvListAnyUriMaxLength3",
]
| [
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] | 2.241071 | 112 |
# -*- coding: utf-8 -*-
import sys, time, random
#FLASK
from flask import Flask, request
from flaskJSONRPCServer import flaskJSONRPCServer
echo._alias='helloworld' #setting alias for method
app=Flask(__name__)
@app.route('/readpost', methods=['POST'])
app2=Flask(__name__)
@app2.route('/helloworld', methods=['GET'])
@app2.route('/readpost', methods=['POST'])
if __name__=='__main__':
print 'Running api..'
# Creating instance of server
# <blocking> switch server to one-request-per-time mode
# <cors> switch auto CORS support
# <gevent> switch to patching process with Gevent
# <debug> switch to logging connection's info from serv-backend
# <log> set logging level (0-critical, 1-errors, 2-warnings, 3-info, 4-debug)
# <fallback> switch auto fallback to JSONP on GET requests
# <allowCompress> switch auto compression
# <compressMinSize> set min limit for compression
# <tweakDescriptors> set file-descriptor's limit for server (useful on high-load servers)
# <jsonBackend> set JSON-backend. Auto fallback to native when problems
# <notifBackend> set exec-backend for Notify-requests
# <servBackend> set serving-backend ('pywsgi', 'werkzeug', 'wsgiex' or 'auto'). 'auto' is more preffered
# <experimental> switch using of experimental perfomance-patches
server=flaskJSONRPCServer(("0.0.0.0", 7001), blocking=False, cors=False, gevent=True, debug=False, log=3, fallback=True, allowCompress=False, jsonBackend='simplejson', notifBackend='simple', tweakDescriptors=[1000, 1000], servBackend='auto')
# Register dispatchers for single functions
server.registerFunction(echo, path='/api')
server.registerFunction(stats, path='/api')
# merge with Flask app
server.postprocessAdd_wsgi(app, status=404)
server.postprocessAdd_wsgi(fakeWSGI1, status=404)
server.postprocessAdd_wsgi(fakeWSGI2, status=404)
server.postprocessAdd_wsgi(app2, status=404)
server.postprocessAdd_cb(ppCB1, status=404)
# Run server
server.serveForever()
# Now you can access this api by path http://127.0.0.1:7001/api for JSON-RPC requests
# Or by path http://127.0.0.1:7001/api/<method>?jsonp=<callback>&(params) for JSONP requests
# For example by http://127.0.0.1:7001/api/echo?data=test_data&jsonp=jsonpCallback_129620
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28,
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79,
47258,
62,
1065,
4846,
1238,
198
] | 2.59806 | 928 |
# Copyright 2019 Pants project contributors (see CONTRIBUTORS.md).
# Licensed under the Apache License, Version 2.0 (see LICENSE).
from pathlib import Path
import pytest
from pants.core.util_rules.distdir import DistDir, InvalidDistDir, validate_distdir
| [
2,
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62,
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628
] | 3.685714 | 70 |
import numpy as np
import pickle
from .testutil import datadir
from brainstat.stats.SLM import SLM, f_test
from brainstat.stats.terms import Term
# test data *pkl consists of slm1* and slm2* keys
# slm1* variables will be assigned to slm1 dictionary, and slm2* to the slm2 dict.
| [
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13,
628,
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628,
198
] | 2.94 | 100 |
import os
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import pickle
from collections import OrderedDict
from fragresp.gaussian_tools import check_opt as _check_opt
from fragresp.gaussian_tools import check_esp as _check_esp
from fragresp.gaussian_tools import get_energy as _get_energy
from fragresp.constants import hartree_to_kcal
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] | 3.201681 | 119 |
from model.factor import RandomVar
from model.factor import CPD
from model.factor import Factor
from model.influence import InfluenceDiagram
from inference.exact import ExpectedUtility
if __name__ == '__main__':
main()
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] | 3.603175 | 63 |
#!/usr/bin/python
# Importing custom files
import sys
sys.path.insert(1, '../')
import utils
import instagram
from datetime import date
from PIL import Image, ImageDraw
from bs4 import BeautifulSoup
import urllib.request
import requests
import time
import wget
import json
import os
if __name__ == "__main__":
if "--debug" in sys.argv[1:]:
debug=True
elif "-d" in sys.argv[1:]:
debug=True
else:
debug=False
main(debug)
print("\nDONE") | [
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] | 2.526042 | 192 |
import os
| [
11748,
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628
] | 3.666667 | 3 |
import sys
import os
sys.path.append(os.path.abspath('.'))
sys.path.append(os.path.abspath('../'))
sys.path.append(os.path.abspath('../../'))
import matplotlib.pyplot as plt
import numpy as np
from fusion.scheduling import batch_size
from fusion.scheduling import Resource
from fusion.scheduling import LoopLowerBound
from fusion.scheduling import ScheduleGenerator
from fusion.scheduling import extract_arch_info, extract_dataflow_info
from fusion.scheduling import CostModel
from fusion.scheduling import res_parse
from fusion.nn_models import import_network
def do_scheduling():
"""
Get optimal scheduling for given problem. Return a result schedule.
"""
buffer = [128, 128, 256, 256, 512, 512, 512, 512]
pe_array = [16, 32, 16, 32, 16, 16, 32, 64]
# Network.
batch_size.init(4)
network = import_network("squeezenet")
dataflow_info = extract_dataflow_info('./fusion/dataflow/dataflow_Ow_Cout.json')
access_list = []
energy_list = []
for pe, bf in zip(pe_array, buffer):
arch_file = './fusion/arch/3_level_mem_{}KB.json'.format(bf)
arch_info = extract_arch_info(arch_file)
arch_info["parallel_count"][0] = pe ** 2
if pe == 8:
arch_info["parallel_cost"][0] = 0.05
resource = Resource.arch(arch_info)
# Unroll loop lower bound
dataflow_info["partitioning_size"] = [pe] * len(dataflow_info["partitioning_size"])
loop_lower_bound = LoopLowerBound.dataflow(dataflow_info)
print("\n===========================================================")
print('PE-array: {}x{}, buffer size: {}(KB)'.format(pe, pe, bf))
print("waiting...")
cost_model = CostModel(network, resource)
# optimal schedule
sg = ScheduleGenerator(network, resource, cost_model, loop_lower_bound)
schedule_info_list, _ = sg.schedule_search()
print("done!\n\n")
energy, access = res_parse(schedule_info_list, resource,
cost_model, sg, network,
loop_lower_bound,
'./result/pe_array', arch_info)
energy_list.append(energy)
access_list.append(access)
x = ["16x16,128", "32x32,128", "16x16,256", "32x32,256", "8x8,512", "16x16,512", "32x32,512", "64x64,512"]
energy_list = np.array(energy_list) / energy_list[0]
access_list = np.array(access_list) / access_list[0]
plt.figure(figsize=(8, 2))
plt.plot(x, energy_list, label="Normalized Energy")
plt.plot(x, access_list, label="Normalized DRAM Access")
plt.ylim(0.2, 1.2)
plt.legend()
plt.savefig('./result/pe_array/pe_array.png')
plt.show()
def main():
"""
Main function.
"""
do_scheduling()
return 0
if __name__ == '__main__':
sys.exit(main())
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220,
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62,
1416,
704,
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198,
220,
220,
220,
1441,
657,
628,
198,
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3672,
834,
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834,
12417,
834,
10354,
198,
220,
220,
220,
25064,
13,
37023,
7,
12417,
28955,
198
] | 2.328431 | 1,224 |
from libfuturize.fixes.fix_future_builtins import FixFutureBuiltins
| [
6738,
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62,
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1040,
1330,
13268,
29783,
39582,
1040,
198
] | 3.238095 | 21 |
"""This module does blah blah."""
import httplib2
resp, content = httplib2.Http().request("http://myip.dk")
#start = content.find("ipv4address")
#end = start + 100
print (content) #[start:end].strip()) | [
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] | 2.927536 | 69 |
from enum import Enum
import requests
from bbdata.config import output_api_url
from bbdata.util import handle_response
from bbdata.exceptions import ClientException
| [
6738,
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] | 3.772727 | 44 |
from collections import defaultdict
from lxml import html
import requests
from plumbum import colors
from dict_tiny.setting import TIME_OUT
def is_alphabet(word):
"""
return the word is English or Chinese
:param word:
:return:
"""
is_alphabet = defaultdict(int)
word = word.replace(' ', '')
for each_letter in word:
if each_letter >= '\u4e00' and each_letter <= '\u9fff':
is_alphabet['cn'] += 1
# elif word >= '\u0030' and word <= '\u0039':
# return 'num'
elif (each_letter >= '\u0041' and each_letter <= '\u005a') or (
each_letter >= '\u0061' and each_letter <= '\u007a'):
is_alphabet['en'] += 1
else:
is_alphabet['other'] += 1
is_alphabet['en'] /= 4
for len_type, num in is_alphabet.items():
if num >= sum(is_alphabet.values()) * 0.7:
return len_type
return 'other'
def downloader(url, header):
"""
:param url: url need to be downloaded
:param header: fake header
:return:
"""
try:
result = requests.get(url, headers=header, timeout=TIME_OUT)
result_selector = html.etree.HTML(result.text)
resp_code = result.status_code
except requests.exceptions.ConnectionError as e:
print(colors.red | "[Error!] Time out.")
print("<%s>" % e)
result_selector = None
resp_code = None
return result_selector, resp_code
def downloader_plain(url, header):
"""
plain download. Do not make the resp to selector
:param url:
:param header:
:return:
"""
try:
return requests.get(url, headers=header).text
except:
return None
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2845,
25,
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220,
220,
220,
220,
220,
220,
220,
1441,
6045,
198
] | 2.320652 | 736 |
#!/usr/bin/env python3
"""
Created on Thr Apr 8 18:00:00 2021
:Authors:
Mark Driver <mdd31>
Mark J. Williamson <mjw99>
"""
import logging
from cmlgenerator.test.cmlgeneratortests import run_tests
logging.basicConfig()
LOGGER = logging.getLogger(__name__)
LOGGER.setLevel(logging.WARN)
if __name__ == "__main__":
run_tests()
| [
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] | 2.544776 | 134 |
from math import cos, sin, pi
import bgl
import blf
import bpy
import gpu
from bpy.props import *
from bpy.types import Operator
from gpu_extras.batch import batch_for_shader
from .utils import dpifac, draw_tri_fan
from ...preferences import get_pref
class RSN_OT_DrawNodes(Operator):
"""Draw the active task's settings """
bl_idname = "rsn.draw_nodes"
bl_label = "Draw Nodes"
bl_options = {'REGISTER', 'UNDO'}
| [
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1391,
6,
31553,
41517,
3256,
705,
4944,
18227,
6,
92,
628,
198
] | 2.625 | 168 |
from internal.model import Node, Rule, ExistRule, ChildRule, Direction, RuleNode, ParentChildRule
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from marshmallow import fields, post_load
from portals.wwits.apis.rest import BaseSchemaExcludeFields as Schema
from .models import ParmModel, FunctionAuthorizeListModel, FunctionModel
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#!/usr/bin/env python3
# IB002 Domaci uloha 6.
#
# V nasledujicim textu pouzivame pojem "halda" ve vyznamu "binarni halda".
#
# Minimova halda je v kanonickem tvaru, pokud pro kazdy jeji prvek se dvema
# potomky plati, ze jeho levy potomek je mensi nez ten pravy nebo se oba
# rovnaji.
#
# Je v kanonickem tvaru | Neni v kanonickem tvaru
# |
# (1) | (1)
# / \ | / \
# (2) (3) | (3) (2)
# Trida representujici minimovou haldu. Pro praci s ni muzete s vyhodou pouzit
# funkce, ktere jste implementovali v zakladnim domacim ukolu.
# Ukol 1.
# Vasim prvnim ukolem je implementovat funkci is_canonical_min_heap(heap),
# ktera overi, zda je zadana halda 'heap' korektni minimovou haldou
# v kanonickem tvaru. Pokud ano, vrati True, v opacnem pripade vrati False.
#
# Prazdna nebo jednoprvkova halda je v kanonickem tvaru implicitne. Mejte na
# pameti, ze halda v kanonickem tvaru musi splnovat take pozadavky kladene na
# minimovou haldu.
def is_canonical_min_heap(heap):
"""
vstup: 'heap' typu MinHeap
(je zaruceno, ze heap.size je velikost pole heap.array;
neni zaruceno, ze prvky heap.array splnuji haldovou podminku
nebo podminku kanonickeho tvaru)
vystup: True, pokud je 'heap' minimova halda v kanonickem tvaru
False, jinak
casova slozitost: O(n), kde 'n' je pocet prvku 'heap'
"""
if heap is None:
return False
if heap.size == 1 or heap.size == 0:
return True
if not is_min_heap(heap.array, 0):
return False
i = 1
left = heap.array[1]
while i < heap.size:
if i % 2 == 1:
left = heap.array[i]
i += 1
continue
if left > heap.array[i]:
return False
i += 1
return True
# Ukol 2.
# Druhym ukolem je implementovat funkci canonise_min_heap(heap), ktera zadanou
# minimovou haldu 'heap' prevede na kanonicky tvar. Funkce bude menit primo
# haldu zadanou v argumentu, proto nebude vracet zadnou navratovou hodnotu.
#
# Napoveda:
# Pro algoritmus s linearni casovou slozitosti je potreba postupovat takto:
# - Rekurzivne resime od korene k listum haldy;
# - pro kazdy uzel haldy:
# + zkontrolujeme, jestli potomci splnuji vlastnost kanonickeho tvaru;
# pokud ne:
# * prohodime hodnoty leveho a praveho potomka;
# * tim se muze pokazit vlastnost haldy v pravem podstrome, proto
# probublame problematickou hodnotu z korene praveho podstromu
# tak hluboko, aby uz neporusovala vlastnost haldy (pri tomto bublani
# opravujeme pouze vlastnost haldy, kanonicky tvar neresime)
# + mame tedy korektni minimovou haldu, ktera navic splnuje kanonicky
# tvar od tohoto uzlu smerem nahoru;
# + pokracujeme v rekurzi vlevo a vpravo.
def canonise_min_heap(heap):
"""
vstup: 'heap' korektni minimova halda typu MinHeap
vystup: funkce nic nevraci, vstupni halda 'heap' je prevedena
do kanonickeho tvaru (pritom obsahuje stejne prvky jako na zacatku)
casova slozitost: O(n), kde 'n' je pocet prvku 'heap'
"""
if is_min_heap(heap.array, 0):
for i in range(heap.size // 2):
left, right = 2 * i + 1, 2 * i + 2
if left < heap.size and right < heap.size:
if heap.array[left] > heap.array[right]:
swap(heap.array, left, right)
check_subtree(heap, right)
heap = MinHeap()
heap.array = [1, 3, 2]
heap.size = 3
if is_canonical_min_heap(heap):
print(heap.array, " = IS canonical heap")
else:
print(heap.array, " = IS NOT canonical heap")
canonise_min_heap(heap)
print(heap.array, " = REPAIRED")
if is_canonical_min_heap(heap):
print(" = TEST OK")
else:
print(" = TEST NOK")
print("-----------------------------------------")
heap.array = [-1, 0, -1, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, -1]
heap.size = 14
if is_canonical_min_heap(heap):
print(heap.array, " = IS canonical heap")
else:
print(heap.array, " = IS NOT canonical heap")
canonise_min_heap(heap)
print(heap.array, " = REPAIRED")
if is_canonical_min_heap(heap):
print(" = TEST OK")
else:
print(" = TEST NOK")
print("-----------------------------------------")
heap.array = [-2, 0, -2, 0, 0, -1, -2]
heap.size = 7
if is_canonical_min_heap(heap):
print(heap.array, " = IS canonical heap")
else:
print(heap.array, " = IS NOT canonical heap")
canonise_min_heap(heap)
print(heap.array, " = REPAIRED")
if is_canonical_min_heap(heap):
print(" = TEST OK")
else:
print(" = TEST NOK")
print("-----------------------------------------")
heap.array = [-1, 0, -1, 0, 0, -1, 0, 0, 0, 0, 0, -1]
heap.size = 12
if is_canonical_min_heap(heap):
print(heap.array, " = IS canonical heap")
else:
print(heap.array, " = IS NOT canonical heap")
canonise_min_heap(heap)
print(heap.array, " = REPAIRED")
if is_canonical_min_heap(heap):
print(" = TEST OK")
else:
print(" = TEST NOK")
print("-----------------------------------------")
heap.array = [1, 3, 2, 4, 5, 9, 7, 6, 8]
heap.size = 9
if is_canonical_min_heap(heap):
print(heap.array, " = IS canonical heap")
else:
print(heap.array, " = IS NOT canonical heap")
canonise_min_heap(heap)
print(heap.array, " = REPAIRED")
if is_canonical_min_heap(heap):
print(" = TEST OK")
else:
print(" = TEST NOK")
print("-----------------------------------------")
heap.array = [0, 1, 0, 1, 1, 0]
heap.size = 6
if is_canonical_min_heap(heap):
print(heap.array, " = IS canonical heap")
else:
print(heap.array, " = IS NOT canonical heap")
canonise_min_heap(heap)
print(heap.array, " = REPAIRED")
if is_canonical_min_heap(heap):
print(" = TEST OK")
else:
print(" = TEST NOK")
print("-----------------------------------------")
heap.array = [0, 1, 0, 1, 1, 0, 0]
heap.size = 7
if is_canonical_min_heap(heap):
print(heap.array, " = IS canonical heap")
else:
print(heap.array, " = IS NOT canonical heap")
canonise_min_heap(heap)
print(heap.array, " = REPAIRED")
if is_canonical_min_heap(heap):
print(" = TEST OK")
else:
print(" = TEST NOK")
print("-----------------------------------------")
heap.array = [0, 1, 0, 1, 1, 0, 1]
heap.size = 7
if is_canonical_min_heap(heap):
print(heap.array, " = IS canonical heap")
else:
print(heap.array, " = IS NOT canonical heap")
canonise_min_heap(heap)
print(heap.array, " = REPAIRED")
if is_canonical_min_heap(heap):
print(" = TEST OK")
else:
print(" = TEST NOK")
print("-----------------------------------------") | [
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] | 2.14209 | 3,167 |
import os, glob
import json
from transformers import BertTokenizer
from tqdm import tqdm
from argparse import ArgumentParser
if __name__ == "__main__":
parser = ArgumentParser()
parser.add_argument('--file_path', type=str, required=True)
parser.add_argument('--output_path', type=str, required=True)
args = parser.parse_args()
if not os.path.exists(args.output_path):
os.makedirs(args.output_path)
# file_path = '../msmarco_passage_unicoil_encoded_TILDE_200'
# output_path = '../msmarco_passage_unicoil_encoded_TILDE_200_decoded'
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased', use_fast=True, cache_dir="../cache")
files = glob.glob(os.path.join(args.file_path, '*'))
for file in tqdm(files):
with open(file, 'r') as f, open(f"{args.output_path}/{file.split('/')[-1]}", 'w') as wf:
for line in f:
data = json.loads(line)
vector = {}
for tok_id in data['vector'].keys():
vector[tokenizer.decode([int(tok_id)])] = data['vector'][tok_id]
data['vector'] = vector
json.dump(data, wf)
wf.write('\n')
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] | 2.183636 | 550 |
from django.conf.urls import include, url
from django.contrib import admin
from chapter.view.createChapter import *
from chapter.view.getChapter import *
urlpatterns = [
# url('^login/$', login),
url('^createAChapter/$', createAChapter),
url('^getChapter/$', getChapter),
url('^bookChapter/$', bookChapter),
]
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] | 2.990909 | 110 |
"""
This module imports the configuration for yggdrasil.
.. todo::
Remove reference to environment variables for accessing config options.
"""
import os
import sys
import json
import shutil
import logging
import warnings
import subprocess
from yggdrasil.backwards import configparser
from yggdrasil import platform, tools
conda_prefix = os.environ.get('CONDA_PREFIX', '')
config_file = '.yggdrasil.cfg'
def_config_file = os.path.join(os.path.dirname(__file__), 'defaults.cfg')
if conda_prefix:
usr_dir = conda_prefix
else:
usr_dir = os.path.expanduser('~')
usr_config_file = os.path.join(usr_dir, config_file)
loc_config_file = os.path.join(os.getcwd(), config_file)
if not os.path.isfile(usr_config_file): # pragma: no cover
from yggdrasil.languages import install_languages
shutil.copy(def_config_file, usr_config_file)
install_languages.install_all_languages(from_setup=True)
logger = logging.getLogger(__name__)
class YggConfigParser(configparser.ConfigParser, object):
r"""Config parser that returns None if option not provided on get."""
def reload(self):
r"""Reload parameters from the original files."""
self._sections = self._dict()
if self.files is not None:
self.read(self.files)
@property
def file_to_update(self):
r"""str: Full path to file that should be updated if update_file is
called without an explicit file path."""
out = None
if self.files is not None:
out = self.files[-1]
return out
def update_file(self, fname=None):
r"""Write out updated contents to a file.
Args:
fname (str, optional): Full path to file where contents should be
saved. If None, file_to_update is used. Defaults to None.
Raises:
RuntimeError: If fname is None and file_to_update is None.
"""
if fname is None:
fname = self.file_to_update
if fname is None:
raise RuntimeError("No file provided or set at creation.")
with open(fname, 'w') as fd:
self.write(fd)
@classmethod
def from_files(cls, files, **kwargs):
r"""Construct a config parser from a set of files.
Args:
files (list): One or more files that options should be read from in
the order they should be loaded.
**kwargs: Additional keyword arguments are passed to the class
constructor.
Returns:
YggConfigParser: Config parser with information loaded from the
provided files.
"""
out = cls(files=files, **kwargs)
out.reload()
return out
def set(self, section, option, value=None):
"""Set an option."""
if not isinstance(value, str):
value = json.dumps(value)
super(YggConfigParser, self).set(section, option, value=value)
def get(self, section, option, default=None, **kwargs):
r"""Return None if the section/option does not exist.
Args:
section (str): Name of section.
option (str): Name of option in section.
default (obj, optional): Value that should be returned if the
section and/or option are not found or are an empty string.
Defaults to None.
**kwargs: Additional keyword arguments are passed to the parent
class's get.
Returns:
obj: String entry if the section & option exist, otherwise default.
"""
section = section.lower()
option = option.lower()
if self.has_section(section) and self.has_option(section, option):
# Super does not work for ConfigParser as not inherited from object
out = configparser.ConfigParser.get(self, section, option, **kwargs)
# Count empty strings as not provided
if not out:
return default
else:
return self.backwards_str2val(out)
else:
return default
# Initialize config
ygg_cfg_usr = YggConfigParser.from_files([usr_config_file])
ygg_cfg = YggConfigParser.from_files([def_config_file, usr_config_file,
loc_config_file])
def update_language_config(drv, skip_warnings=False,
disable_languages=None, enable_languages=None,
overwrite=False, verbose=False):
r"""Update configuration options for a language driver.
Args:
drv (list, class): One or more language drivers that should be
configured.
skip_warnings (bool, optional): If True, warnings about missing options
will not be raised. Defaults to False.
disable_languages (list, optional): List of languages that should be
disabled. Defaults to an empty list.
enable_languages (list, optional): List of languages that should be
enabled. Defaults to an empty list.
overwrite (bool, optional): If True, the existing file will be overwritten.
Defaults to False.
verbose (bool, optional): If True, information about the config file
will be displayed. Defaults to False.
"""
if verbose:
logger.info("Updating user configuration file for yggdrasil at:\n\t%s"
% usr_config_file)
miss = []
if not isinstance(drv, list):
drv = [drv]
if disable_languages is None:
disable_languages = []
if enable_languages is None:
enable_languages = []
if overwrite:
shutil.copy(def_config_file, usr_config_file)
ygg_cfg_usr.reload()
for idrv in drv:
if (((idrv.language in disable_languages)
and (idrv.language in enable_languages))):
logger.info(("%s language both enabled and disabled. "
"No action will be taken.") % idrv.language)
elif idrv.language in disable_languages:
ygg_cfg_usr.set(idrv.language, 'disable', 'True')
elif idrv.language in enable_languages:
ygg_cfg_usr.set(idrv.language, 'disable', 'False')
if ygg_cfg_usr.get(idrv.language, 'disable', 'False').lower() == 'true':
continue # pragma: no cover
miss += idrv.configure(ygg_cfg_usr)
ygg_cfg_usr.update_file()
ygg_cfg.reload()
if not skip_warnings:
for sect, opt, desc in miss: # pragma: windows
warnings.warn(("Could not set option %s in section %s. "
+ "Please set this in %s to: %s")
% (opt, sect, ygg_cfg_usr.file_to_update, desc),
RuntimeWarning)
def find_all(name, path):
r"""Find all instances of a file with a given name within the directory
tree starting at a given path.
Args:
name (str): Name of the file to be found (with the extension).
path (str, None): Directory where search should start. If set to
None on Windows, the current directory and PATH variable are
searched.
Returns:
list: All instances of the specified file.
"""
result = []
try:
if platform._is_win: # pragma: windows
if path is None:
out = subprocess.check_output(["where", name],
env=os.environ,
stderr=subprocess.STDOUT)
else:
out = subprocess.check_output(["where", "/r", path, name],
env=os.environ,
stderr=subprocess.STDOUT)
else:
args = ["find", "-L", path, "-type", "f", "-name", name]
pfind = subprocess.Popen(args, env=os.environ,
stderr=subprocess.PIPE,
stdout=subprocess.PIPE)
(stdoutdata, stderrdata) = pfind.communicate()
out = stdoutdata
for l in stderrdata.splitlines():
if b'Permission denied' not in l:
raise subprocess.CalledProcessError(pfind.returncode,
' '.join(args),
output=stderrdata)
except subprocess.CalledProcessError:
out = ''
if not out.isspace():
result = sorted(out.splitlines())
result = [os.path.normcase(os.path.normpath(m.decode('utf-8'))) for m in result]
return result
def locate_file(fname, environment_variable='PATH', directory_list=None):
r"""Locate a file within a set of paths defined by a list or environment
variable.
Args:
fname (str): Name of the file that should be located.
environment_variable (str): Environment variable containing the set of
paths that should be searched. Defaults to 'PATH'. If None, this
keyword argument will be ignored. If a list is provided, it is
assumed to be a list of environment variables that should be
searched in the specified order.
directory_list (list): List of paths that should be searched in addition
to those specified by environment_variable. Defaults to None and is
ignored. These directories will be searched be for those in the
specified environment variables.
Returns:
bool, str: Full path to the located file if it was located, False
otherwise.
"""
out = []
if ((platform._is_win and (environment_variable == 'PATH')
and (directory_list is None))): # pragma: windows
out += find_all(fname, None)
else:
if directory_list is None:
directory_list = []
if environment_variable is not None:
if not isinstance(environment_variable, list):
environment_variable = [environment_variable]
for x in environment_variable:
directory_list += os.environ.get(x, '').split(os.pathsep)
for path in directory_list:
if path:
out += find_all(fname, path)
if not out:
return False
first = out[0]
if len(out) > 1:
warnings.warn(("More than one (%d) match to %s. "
+ "Using first match (%s)") %
(len(out), fname, first), RuntimeWarning)
return first
# Set associated environment variables
env_map = [('debug', 'ygg', 'YGG_DEBUG'),
('debug', 'rmq', 'RMQ_DEBUG'),
('debug', 'client', 'YGG_CLIENT_DEBUG'),
('jsonschema', 'validate_components', 'YGG_SKIP_COMPONENT_VALIDATION'),
('jsonschema', 'validate_all_messages', 'YGG_VALIDATE_ALL_MESSAGES'),
('rmq', 'namespace', 'YGG_NAMESPACE'),
('rmq', 'host', 'YGG_MSG_HOST'),
('rmq', 'vhost', 'YGG_MSG_VHOST'),
('rmq', 'user', 'YGG_MSG_USER'),
('rmq', 'password', 'YGG_MSG_PW'),
('parallel', 'cluster', 'YGG_CLUSTER'),
]
def get_ygg_loglevel(cfg=None, default='DEBUG'):
r"""Get the current log level.
Args:
cfg (:class:`yggdrasil.config.YggConfigParser`, optional):
Config parser with options that should be used to determine the
log level. Defaults to :data:`yggdrasil.config.ygg_cfg`.
default (str, optional): Log level that should be returned if the log
level option is not set in cfg. Defaults to 'DEBUG'.
Returns:
str: Log level string.
"""
is_model = tools.is_subprocess()
if cfg is None:
cfg = ygg_cfg
if is_model:
opt = 'client'
else:
opt = 'ygg'
return cfg.get('debug', opt, default)
def set_ygg_loglevel(level, cfg=None):
r"""Set the current log level.
Args:
level (str): Level that the log should be set to.
cfg (:class:`yggdrasil.config.YggConfigParser`, optional):
Config parser with options that should be used to update the
environment. Defaults to :data:`yggdrasil.config.ygg_cfg`.
"""
is_model = tools.is_subprocess()
if cfg is None:
cfg = ygg_cfg
if is_model:
opt = 'client'
else:
opt = 'ygg'
cfg.set('debug', opt, level)
logLevelYGG = eval('logging.%s' % level)
ygg_logger = logging.getLogger("yggdrasil")
ygg_logger.setLevel(level=logLevelYGG)
def cfg_logging(cfg=None):
r"""Set logging levels from config options.
Args:
cfg (:class:`yggdrasil.config.YggConfigParser`, optional):
Config parser with options that should be used to update the
environment. Defaults to :data:`yggdrasil.config.ygg_cfg`.
"""
is_model = tools.is_subprocess()
if cfg is None:
cfg = ygg_cfg
_LOG_FORMAT = "%(levelname)s:%(module)s.%(funcName)s[%(lineno)d]:%(message)s"
logging.basicConfig(level=logging.INFO, format=_LOG_FORMAT)
logLevelYGG = eval('logging.%s' % cfg.get('debug', 'ygg', 'NOTSET'))
logLevelRMQ = eval('logging.%s' % cfg.get('debug', 'rmq', 'INFO'))
logLevelCLI = eval('logging.%s' % cfg.get('debug', 'client', 'INFO'))
ygg_logger = logging.getLogger("yggdrasil")
rmq_logger = logging.getLogger("pika")
if is_model:
ygg_logger.setLevel(level=logLevelCLI)
else:
ygg_logger.setLevel(level=logLevelYGG)
rmq_logger.setLevel(level=logLevelRMQ)
# For models, route the loggs to stdout so that they are displayed by the
# model driver.
if is_model:
handler = logging.StreamHandler(sys.stdout)
handler.setLevel(logLevelCLI)
ygg_logger.addHandler(handler)
rmq_logger.addHandler(handler)
def cfg_environment(env=None, cfg=None):
r"""Set environment variables based on config options.
Args:
env (dict, optional): Dictionary of environment variables that should
be updated. Defaults to `os.environ`.
cfg (:class:`yggdrasil.config.YggConfigParser`, optional):
Config parser with options that should be used to update the
environment. Defaults to :data:`yggdrasil.config.ygg_cfg`.
"""
if env is None:
env = os.environ
if cfg is None:
cfg = ygg_cfg
for s, o, e in env_map:
v = cfg.get(s, o)
if v:
env[e] = v
# Do initial update of logging & environment (legacy)
cfg_logging()
cfg_environment()
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220,
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17365,
58,
68,
60,
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410,
628,
220,
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220,
220,
220,
220,
220,
220,
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2,
2141,
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4296,
286,
18931,
1222,
2858,
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8,
198,
37581,
62,
6404,
2667,
3419,
198,
37581,
62,
38986,
3419,
198
] | 2.236475 | 6,525 |
# -*- coding:utf-8; -*-
class Solution:
"""
解题思路：递归
"""
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import requests_unixsocket
import json
from errors import NoSuchContainerError, ServerErrorError
from utils.utils import Utils
u = Utils()
#https://docs.docker.com/engine/reference/api/docker_remote_api_v1.24/
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quant_de_testes = int(input())
soma_de_impares_consecutivos(quant_de_testes)
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# Copyright 2018 Google LLC
#
# 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, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import argparse
import json
import logging
from google.cloud import bigquery
def parse_arguments():
"""Parse command line arguments."""
parser = argparse.ArgumentParser()
parser.add_argument(
'--output',
type=str,
required=False,
help='GCS URL where results will be saved as a CSV.')
parser.add_argument(
'--query',
type=str,
required=True,
help='The SQL query to be run in BigQuery')
parser.add_argument(
'--dataset_id',
type=str,
required=True,
help='Dataset of the destination table.')
parser.add_argument(
'--table_id',
type=str,
required=True,
help='Name of the destination table.')
parser.add_argument(
'--project',
type=str,
required=True,
help='The GCP project to run the query.')
args = parser.parse_args()
return args
if __name__ == '__main__':
main()
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3672,
834,
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705,
834,
12417,
834,
10354,
198,
220,
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3419,
198
] | 2.88932 | 515 |
import os
import subprocess
import sys
import shutil
import logging
from typing import Optional, List
import click
from google.cloud import storage
@click.command()
@click.option('-b', "--bucket_name", help="(str) Name of GCS bucket")
@click.option(
'-r',
"--requirement",
help="(str) Name of Python package or requirements file",
)
@click.option(
'-d',
"--download_dir",
default="gcs_packages",
help="(optional, str) File download destination",
)
@click.option("-t", "--target", default="", help="(str) Package install destination")
def main(bucket_name, requirement, download_dir, target):
"""Pip install {pkg_name}/{pkg_name_versioned}.tar.gz to
current enviroment or a target directory
(1) Copy package_name.tar.gz from Google Cloud bucket
(2) Pip Install package_name.tar.gz into staging directory
(3) Remove the package_name.tar.gz
"""
try:
packages = []
if os.path.isfile(requirement):
with open(requirement) as gs_requirements:
for package_name in gs_requirements.readlines():
packages.append(package_name.strip())
else:
packages.append(requirement)
download_packages(
bucket_name=bucket_name,
package_list=packages,
packages_download_dir=download_dir,
)
logging.info('download done')
install_packages(download_dir, target)
finally:
if os.path.exists(download_dir):
shutil.rmtree(download_dir)
def install_packages(packages_download_dir: str, target_dir: Optional[str] = None):
"""Install packages found in local directory. Do not install dependencies if
target directory is specified.
Args:
packages_download_dir (str): Directory containing packages
target_dir (str): Destination to install packages
"""
for gs_package_zip_file in os.listdir(packages_download_dir):
if not target_dir:
install_command = [
sys.executable,
"-m",
"pip",
"install",
"--quiet",
"--upgrade",
f"{packages_download_dir}/{gs_package_zip_file}",
]
else:
install_command = [
sys.executable,
"-m",
"pip",
"install",
"--quiet",
"--no-deps",
"--upgrade",
"-t",
target_dir,
f"{packages_download_dir}/{gs_package_zip_file}",
]
try:
subprocess.check_output(install_command)
except Exception:
logging.warning("Attempting pip install with pyenv python")
install_command[0] = f"{os.environ['HOME']}/.pyenv/shims/python"
subprocess.check_output(install_command)
def download_packages(
packages_download_dir: str,
bucket_name: str,
package_list: List[str],
):
"""Download Python packages from GCS into a local directory.
Args:
packages_download_dir (str): Local directory to download packages into
bucket_name (str): Name of GCS bucket to download packages from
packages list(str): Names of packages found in bucket
"""
os.mkdir(packages_download_dir)
storage_client = storage.Client()
bucket = storage_client.bucket(bucket_name)
for package_name in package_list:
name_no_version = package_name.split("==")[0]
name_versioned = package_name.replace("==", "-")
package_filepath = f"{name_versioned}.tar.gz"
gs_package_path = f"{name_no_version}/{package_filepath}"
blob_package = bucket.blob(gs_package_path)
blob_package.download_to_filename(
os.path.join(packages_download_dir, package_filepath)
)
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220,
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8,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
198
] | 2.27459 | 1,708 |
#!/usr/bin/env python
from django.core.management.utils import get_random_secret_key
print(get_random_secret_key())
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2,
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] | 2.95 | 40 |
import json
import os
| [
11748,
33918,
198,
11748,
28686,
628,
198
] | 3.428571 | 7 |
from .locate import (
this_dir,
allow_relative_location_imports,
force_relative_location_imports,
append_sys_path,
prepend_sys_path,
)
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] | 2.421875 | 64 |
from .basecontainer import inflateChildren
from .. import LabeledContainer
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26829,
198,
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] | 4.6875 | 16 |
from functools import wraps
import re
from urllib.parse import unquote
from twilio.base.exceptions import TwilioRestException
from flask import (
current_app as app,
render_template,
request,
Response,
url_for,
)
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8,
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628,
198
] | 2.802326 | 86 |
"""
.. module:: ldtui
:synopsis: Main tools UI.
.. moduleauthor:: Ezequiel Mastrasso
"""
from Qt import QtGui, QtWidgets, QtCore
from Qt.QtWidgets import QApplication, QWidget, QLabel, QMainWindow
import sys
import imp
import os
import logging
from functools import partial
from ldtui import qtutils
import ldt
logger = logging.getLogger(__name__)
class LDTWindow(QMainWindow):
'''Main Tools UI Window. Loads the plugInfo.plugin_object.plugin_layout
QWidget from all loaded plugins as tabs'''
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220,
220,
220,
1195,
38300,
422,
477,
9639,
20652,
355,
22524,
7061,
6,
198
] | 2.976744 | 172 |
import unittest
from poker import best_hands
if __name__ == "__main__":
unittest.main()
| [
11748,
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395,
198,
198,
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1298,
198,
220,
220,
220,
555,
715,
395,
13,
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3419,
198
] | 2.714286 | 35 |
from lib.actions import BaseAction
| [
6738,
9195,
13,
4658,
1330,
7308,
12502,
628
] | 4.5 | 8 |
from rest_framework import serializers
from .models import Exchange
| [
6738,
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62,
30604,
1330,
11389,
11341,
198,
198,
6738,
764,
27530,
1330,
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198
] | 4.6 | 15 |
from dataclasses import field
from enum import Enum
from typing import Dict, List, Optional, Union
from . import is_pydantic_available
from .doc import generate_doc_dataclass
if is_pydantic_available():
from pydantic.dataclasses import dataclass
else:
from dataclasses import dataclass
@generate_doc_dataclass
@dataclass
class Calibration:
"""Parameters for post-training calibration with static quantization."""
method: CalibrationMethods = field(
metadata={"description": 'Calibration method used, either "minmax", "entropy" or "percentile".'}
)
num_calibration_samples: int = field(
metadata={
"description": "Number of examples to use for the calibration step resulting from static quantization."
}
)
calibration_histogram_percentile: Optional[float] = field(
default=None, metadata={"description": "The percentile used for the percentile calibration method."}
)
calibration_moving_average: Optional[bool] = field(
default=None,
metadata={
"description": "Whether to compute the moving average of the minimum and maximum values for the minmax calibration method."
},
)
calibration_moving_average_constant: Optional[float] = field(
default=None,
metadata={
"description": "Constant smoothing factor to use when computing the moving average of the minimum and maximum values. Effective only when the selected calibration method is minmax and `calibration_moving_average` is set to True."
},
)
@generate_doc_dataclass
@dataclass
@generate_doc_dataclass
@dataclass
@generate_doc_dataclass
@dataclass
@generate_doc_dataclass
@dataclass
class DatasetArgs:
"""Parameters related to the dataset."""
path: str = field(metadata={"description": "Path to the dataset, as in `datasets.load_dataset(path)`."})
eval_split: str = field(metadata={"description": 'Dataset split used for evaluation (e.g. "test").'})
data_keys: Dict[str, Union[None, str]] = field(
metadata={
"description": 'Dataset columns used as input data. At most two, indicated with "primary" and "secondary".'
}
)
ref_keys: List[str] = field(metadata={"description": "Dataset column used for references during evaluation."})
name: Optional[str] = field(
default=None, metadata={"description": "Name of the dataset, as in `datasets.load_dataset(path, name)`."}
)
calibration_split: Optional[str] = field(
default=None, metadata={"description": 'Dataset split used for calibration (e.g. "train").'}
)
@generate_doc_dataclass
@dataclass
class TaskArgs:
"""Task-specific parameters."""
is_regression: Optional[bool] = field(
default=None,
metadata={
"description": "Text classification specific. Set whether the task is regression (output = one float)."
},
)
@dataclass
@dataclass
@dataclass
class _RunConfigBase:
"""Parameters defining a run. A run is an evaluation of a triplet (model, dataset, metric) coupled with optimization parameters, allowing to compare a transformers baseline and a model optimized with Optimum."""
metrics: List[str] = field(metadata={"description": "List of metrics to evaluate on."})
@dataclass
@dataclass
@generate_doc_dataclass
@dataclass
class RunConfig(Run, _RunConfigDefaults, _RunConfigBase):
"""Class holding the parameters to launch a run."""
pass
| [
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] | 2.947679 | 1,185 |
"""
===========================================================
Plot single trial activity, grouped by ROI and sorted by RT
===========================================================
This will produce what is sometimes called an event related
potential / field (ERP/ERF) image.
The EEGLAB example file, which contains an experiment with button press
responses to simple visual stimuli, is read in and response times are
calculated.
Regions of Interest are determined by the channel types (in 10/20 channel
notation, even channels are right, odd are left, and 'z' are central). The
median and the Global Field Power within each channel group is calculated,
and the trials are plotted, sorting by response time.
"""
# Authors: Jona Sassenhagen <[email protected]>
#
# License: BSD-3-Clause
# %%
import mne
from mne.event import define_target_events
from mne.channels import make_1020_channel_selections
print(__doc__)
# %%
# Load EEGLAB example data (a small EEG dataset)
data_path = mne.datasets.testing.data_path()
fname = data_path / 'EEGLAB' / 'test_raw.set'
event_id = {"rt": 1, "square": 2} # must be specified for str events
raw = mne.io.read_raw_eeglab(fname)
mapping = {
'EEG 000': 'Fpz', 'EEG 001': 'EOG1', 'EEG 002': 'F3', 'EEG 003': 'Fz',
'EEG 004': 'F4', 'EEG 005': 'EOG2', 'EEG 006': 'FC5', 'EEG 007': 'FC1',
'EEG 008': 'FC2', 'EEG 009': 'FC6', 'EEG 010': 'T7', 'EEG 011': 'C3',
'EEG 012': 'C4', 'EEG 013': 'Cz', 'EEG 014': 'T8', 'EEG 015': 'CP5',
'EEG 016': 'CP1', 'EEG 017': 'CP2', 'EEG 018': 'CP6', 'EEG 019': 'P7',
'EEG 020': 'P3', 'EEG 021': 'Pz', 'EEG 022': 'P4', 'EEG 023': 'P8',
'EEG 024': 'PO7', 'EEG 025': 'PO3', 'EEG 026': 'POz', 'EEG 027': 'PO4',
'EEG 028': 'PO8', 'EEG 029': 'O1', 'EEG 030': 'Oz', 'EEG 031': 'O2'
}
raw.rename_channels(mapping)
raw.set_channel_types({"EOG1": 'eog', "EOG2": 'eog'})
raw.set_montage('standard_1020')
events = mne.events_from_annotations(raw, event_id)[0]
# %%
# Create Epochs
# define target events:
# 1. find response times: distance between "square" and "rt" events
# 2. extract A. "square" events B. followed by a button press within 700 msec
tmax = 0.7
sfreq = raw.info["sfreq"]
reference_id, target_id = 2, 1
new_events, rts = define_target_events(events, reference_id, target_id, sfreq,
tmin=0., tmax=tmax, new_id=2)
epochs = mne.Epochs(raw, events=new_events, tmax=tmax + 0.1,
event_id={"square": 2})
# %%
# Plot using :term:`global field power`
# Parameters for plotting
order = rts.argsort() # sorting from fast to slow trials
selections = make_1020_channel_selections(epochs.info, midline="12z")
# The actual plots (GFP)
epochs.plot_image(group_by=selections, order=order, sigma=1.5,
overlay_times=rts / 1000., combine='gfp',
ts_args=dict(vlines=[0, rts.mean() / 1000.]))
# %%
# Plot using median
epochs.plot_image(group_by=selections, order=order, sigma=1.5,
overlay_times=rts / 1000., combine='median',
ts_args=dict(vlines=[0, rts.mean() / 1000.]))
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] | 2.432369 | 1,279 |
# This file is intended for local testing when contributing to this repository
# Do not commit any changes
# You will need to generate a GitLab Personal Access Token to use this
from os import environ as env
import gitlab
from gitlabchangelog.changelog import Changelog
env["GITLAB_URL"] = "https://gitlab.invenia.ca"
env["GITLAB_API_TOKEN"] = "<the-personal-access-token-you-created>"
client = gitlab.Gitlab(env["GITLAB_URL"], private_token=env["GITLAB_API_TOKEN"])
repo = "invenia/Example.jl"
p = client.projects.get(repo, lazy=True)
template = """
This is release {{ version }} of {{ package }}.
{% if merge_requests %}
**Summary:**
{% for merge_request in merge_requests %}
- {{ merge_request.labels }} {{ merge_request.title }} (!{{ merge_request.number }})
{% endfor %}
{% endif %}
{% if previous_release %}
**Changeset:** {{ compare_url }})
{% endif %}
"""
changelog = Changelog(p, template)
tags = p.tags.list(all=False)
for tag in tags:
commit = tag.commit["id"]
version = tag.name
release_notes = changelog.get(version, commit)
print(release_notes)
print("\n-----------------------------------------------------------------------\n")
# Note the line below will actually set the release notes in the repository used
# Should only be used if that is the intended behaviour
# tag.set_release_description(release_notes)
| [
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] | 3 | 469 |
import os
from pathlib import Path
from colorama import Fore, init
if __name__ == '__main__':
Tree().main()
| [
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] | 2.688889 | 45 |
import uuid
from django.core.exceptions import ValidationError
from django.db import models
from sagepaypi.constants import COUNTRY_CHOICES, US_STATE_CHOICES
from sagepaypi.models import CardIdentifier
from tests.test_case import AppTestCase
# fields
# properties
# validation
| [
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] | 3.288889 | 90 |
"""Setup for Axis."""
from setuptools import setup
setup(
name="axis",
packages=["axis"],
version="33",
description="A Python library for communicating with devices from Axis Communications",
author="Robert Svensson",
author_email="[email protected]",
license="MIT",
url="https://github.com/Kane610/axis",
download_url="https://github.com/Kane610/axis/archive/v33.tar.gz",
install_requires=["attrs", "requests", "xmltodict"],
keywords=["axis", "vapix", "onvif", "event stream", "homeassistant"],
classifiers=["Natural Language :: English", "Programming Language :: Python :: 3"],
)
| [
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7904,
11361,
7904,
513,
33116,
198,
8,
198
] | 2.901345 | 223 |
from keras import backend as K
from keras.layers import Input, Convolution2D, MaxPooling2D, Activation, concatenate, Dense, add, GaussianNoise
from keras.layers import GlobalAveragePooling2D
from keras.models import Model
from keras.regularizers import l2
sq1x1 = "squeeze1x1"
exp1x1 = "expand1x1"
exp3x3 = "expand3x3"
selu = "selu_"
# Modular function for Fire Node
# Original SqueezeNet from paper.
def SqueezeNet(
input_shape=None,
filters=8,
weight_decay=0.,
classes=2):
"""Instantiates the SqueezeNet architecture.
"""
assert filters % 2 == 0, 'Number of filters must be 2*n, n > 1'
img_input = Input(shape=input_shape)
x = Convolution2D(filters, (3, 3), padding='valid',
use_bias=True,
kernel_regularizer=l2(weight_decay),
name='conv1')(img_input)
x = Activation('selu', name='selu_conv1')(x)
x = fire_module(x, fire_id=2, squeeze=filters // 2, expand=filters, weight_decay=weight_decay)
residual = x
x = fire_module(x, fire_id=3, squeeze=filters // 2, expand=filters, weight_decay=weight_decay)
x = add([x, residual])
filters *= 2
x = fire_module(x, fire_id=4, squeeze=filters // 2, expand=filters, weight_decay=weight_decay)
x = MaxPooling2D(pool_size=(3, 3), strides=(2, 2), name='pool1')(x)
residual = x
x = fire_module(x, fire_id=5, squeeze=filters // 2, expand=filters, weight_decay=weight_decay)
x = add([x, residual])
filters *=2
x = fire_module(x, fire_id=6, squeeze=filters // 2, expand=filters, weight_decay=weight_decay)
residual = x
x = fire_module(x, fire_id=7, squeeze=filters // 2, expand=filters, weight_decay=weight_decay)
x = add([x, residual])
filters *= 2
x = fire_module(x, fire_id=8, squeeze=filters // 2, expand=filters, weight_decay=weight_decay)
x = MaxPooling2D(pool_size=(3, 3), strides=(2, 2), name='pool2')(x)
residual = x
x = fire_module(x, fire_id=9, squeeze=filters // 2, expand=filters, weight_decay=weight_decay)
x = add([x, residual])
x = Convolution2D(filters, (1, 1), padding='valid',
use_bias=True,
kernel_regularizer=l2(weight_decay),
name='conv10')(x)
x = Activation('selu', name='selu_conv10')(x)
x = GlobalAveragePooling2D()(x)
x = Dense(classes, activation='softmax', name='predictions')(x)
# Ensure that the model takes into account
# any potential predecessors of `input_tensor`.
inputs = img_input
model = Model(inputs, x, name='squeezenet')
return model
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] | 2.305872 | 1,141 |
co = float(input('Medida do cateto oposto: '))
ca = float(input('Medida do cateto adjacente:'))
hi = ((co**2) + (ca**2)) ** (1/2)
print('A hipotenusa mede {:.2f}.'.format(hi))
| [
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] | 2.311688 | 77 |
from typing import Optional
from pydantic import BaseModel, Field, validator
from app.airtable.response import AirtableResponse, ListAirtableResponse
from app.airtable.validators import get_first_or_default_none
| [
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'''
import boto3
from boto.mturk.connection import MTurkConnection
from boto.mturk.question import HTMLQuestion
from boto.mturk.layoutparam import LayoutParameter
from boto.mturk.layoutparam import LayoutParameters
import json
# Create your connection to MTurk
mtc = MTurkConnection(aws_access_key_id='AKIAIBPHQKOJQZULHJSA',
aws_secret_access_key='2EDgdoD4lFrAUd4NHqWnF9qoQBYp1ekV6CVlhUTS',
host='mechanicalturk.sandbox.amazonaws.com') #host='mechanicalturk.amazonaws.com')
account_balance = mtc.get_account_balance()[0]
print("You have a balance of: {}".format(account_balance))
'''
import boto3
import json
region_name = 'us-east-1'
aws_access_key_id = 'AKIAIBPHQKOJQZULHJSA'
aws_secret_access_key = '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'
endpoint_url = 'https://mturk-requester-sandbox.us-east-1.amazonaws.com'
# Uncomment this line to use in production
# endpoint_url = 'https://mturk-requester.us-east-1.amazonaws.com'
mtc = boto3.client(
'mturk',
endpoint_url=endpoint_url,
region_name=region_name,
aws_access_key_id=aws_access_key_id,
aws_secret_access_key=aws_secret_access_key,
)
# This will return $10,000.00 in the MTurk Developer Sandbox
print(mtc.get_account_balance()['AvailableBalance'])
# This is the value you received when you created the HIT
# You can also retrieve HIT IDs by calling GetReviewableHITs
# and SearchHITs. See the links to read more about these APIs.
hit_id = "386T3MLZLNVRU564VQVZSIKA8D580B"
result = mtc.get_assignments(hit_id)
assignment = result[0]
worker_id = assignment.WorkerId
for answer in assignment.answers[0]:
if answer.qid == 'annotation_data':
worker_answer = json.loads(answer.fields[0])
print("The Worker with ID {} gave the answer {}".format(worker_id, worker_answer))
left = worker_answer[0]['left']
top = worker_answer[0]['top']
print("The top and left coordinates are {} and {}".format(top, left)) | [
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389,
23884,
290,
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18982,
7,
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11,
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4008
] | 2.624133 | 721 |
import torch
import torch.nn as nn
# import torch.onnx
# import onnx
# import onnx_caffe2.backend
# from onnx import checker, helper
import torch.optim as optim
import numpy as np
import cv2
from PIL import Image
import torch.utils.model_zoo as model_zoo
import torch.onnx
# print(make_prediction("test/Prairie.jpg"))
# print(make_prediction("test/He_was_happy..png"))
# print(make_prediction("test/the_little.png"))
# print(make_prediction("test/with_his_family.png"))
# print(make_prediction("test/with_his_mouth..png"))
# print(make_prediction("test/would_run_and_get_it.png")) | [
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] | 2.77619 | 210 |
## SPDX-License-Identifier: MIT
## The content of this file has been developed in the context of the MOSIM research project.
## Original author(s): Jannes Lehwald
# -*- coding: utf-8 -*-
"""
"""
from MOSIM.mmi.register import MMIAdapter
#from MMIStandard import MMIAdapter
from MOSIM.abstraction.access.interface.adapter_client import IAdapterClient
class LocalAdapterClient(IAdapterClient):
"""
A wrapper for an adapter client connection
Attributes
----------
_acces : MMIAdapter.Iface
The actual access
"""
def __init__(self, instance):
"""
Constructor which needs an address, a port and an access_type.
Parameters
----------
instance : MMIAdapter.Iface
The local instance
"""
assert(isinstance(instance, MMIAdapter.Iface)), "The instance is no MMIAdapter"
super(LocalAdapterClient, self).__init__()
self._access = instance | [
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220,
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220,
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2116,
13557,
15526,
796,
4554
] | 2.53944 | 393 |
from argparse import ArgumentParser
from getpass import getpass
from os.path import isfile, expanduser
from sys import exit | [
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#!/usr/bin/env python
# -*- coding: utf-8
"""
Taxonomy Resolver
:copyright: (c) 2020-2021.
:license: Apache 2.0, see LICENSE for more details.
"""
import os
import pytest
from taxonresolver import TaxonResolver
from taxonresolver.utils import load_logging
@pytest.fixture
@pytest.fixture
| [
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
from pyspark.mllib.tree import DecisionTree
from functions_MLlib import spark_context, training_set, test_set, write_result, brexit_labeled_data, mode_predict
if __name__ == "__main__" :
sc = spark_context()
numFeatures = 10000
print("Training...\n")
(training, idf) = training_set(sc, numFeatures = numFeatures)
model = DecisionTree.trainClassifier(training, categoricalFeaturesInfo={}, impurity="entropy", maxDepth=5, numClasses=2)
print("Test... \n")
test = test_set(sc, numFeatures = numFeatures, idf = idf)
(num_pos, num_neg) = mode_predict(model, test)
print("Test on Brexit labeled data...\n")
(accuracy, f1) = brexit_labeled_data(sc, model = model, numFeatures = numFeatures, idf = idf)
print("Saving results...")
write_result(num_pos, num_neg, accuracy = accuracy, f1 = f1, name = "Decision Tree (Entropy)") | [
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62,
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11,
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62,
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11,
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11,
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11,
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12200,
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14539,
28338,
8,
4943
] | 2.528947 | 380 |
# SPDX-FileCopyrightText: 2021 Sandy Macdonald
#
# SPDX-License-Identifier: MIT
"""
`Keybow 2040 CircuitPython library`
====================================================
CircuitPython driver for the Pimoroni Keybow 2040 and Pico RGB Keypad Base.
Drop the `lib` contents (`keybow2040.py` file and `keybow_hardware` folder)
into your `lib` folder on your `CIRCUITPY` drive.
* Authors: Sandy Macdonald, Maciej Sokolowski
Notes
--------------------
**Hardware:**
One of:
* Pimoroni Keybow 2040
<https://shop.pimoroni.com/products/keybow-2040>_
* Pimoroni Pico RGB Keypad Base
<https://shop.pimoroni.com/products/pico-rgb-keypad-base>_
**Software and Dependencies:**
For Keybow 2040:
* Adafruit CircuitPython firmware for Keybow 2040:
<https://circuitpython.org/board/pimoroni_keybow2040/>_
* Adafruit CircuitPython IS31FL3731 library:
<https://github.com/adafruit/Adafruit_CircuitPython_IS31FL3731>_
For Pico RGB Keypad Base:
* Adafruit CircuitPython firmware for Raspberry Pi Pico:
<https://circuitpython.org/board/raspberry_pi_pico/>_
* Adafruit CircuitPython DotStar library:
<https://github.com/adafruit/Adafruit_CircuitPython_DotStar>_
"""
import time
class Keybow2040(object):
"""
Represents a Keybow 2040 and hence a set of Key instances with
associated LEDs and key behaviours.
:param hardware: object representing a board hardware
"""
# def rotate(self, degrees):
# # Rotates all of Keybow's keys by a number of degrees, clamped to
# # the closest multiple of 90 degrees. Because it shuffles the order
# # of the Key instances, all of the associated attributes of the key
# # are retained. The x/y coordinate of the keys are rotated also. It
# # also handles negative degrees, e.g. -90 to rotate 90 degrees anti-
# # clockwise.
# # Rotate as follows: `keybow.rotate(270)`
# self.rotation = degrees
# num_rotations = degrees // 90
# if num_rotations == 0:
# return
# if num_rotations < 1:
# num_rotations = 4 + num_rotations
# matrix = [[(x * 4) + y for y in range(4)] for x in range(4)]
# for r in range(num_rotations):
# matrix = zip(*matrix[::-1])
# matrix = [list(x) for x in list(matrix)]
# flat_matrix = [x for y in matrix for x in y]
# for i in range(len(self.keys)):
# self.keys[i].number = flat_matrix[i]
# self.keys = sorted(self.keys, key=lambda x:x.number)
class Key:
"""
Represents a key on Keybow 2040, with associated switch and
LED behaviours.
:param number: the key number (0-15) to associate with the key
:param hardware: object representing a board hardware
""" | [
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25,
220,
2134,
10200,
257,
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6890,
198,
220,
220,
220,
37227
] | 2.680542 | 1,033 |
import urequests
from simp_py import lcd, mon
while 1:
try:
response = urequests.get('http://api.coindesk.com/v1/bpi/currentprice.json')
if response.reason==b'OK':
data= response.json()
updated=data['time']['updatedISO']
btc = data['bpi']['USD']['rate_float']
lcd.text(0,140,updated)
lcd.text(0,160,'btc:%.04f ' % btc)
else:
lcd.text(0,140,'err:%s' % response.reason)
except Exception as e:
mon.log_exc(e)
time.sleep(10)
| [
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] | 2.067227 | 238 |
# mapGenerator.py
import os, os.path, sys, tempfile
# NOTE: The following needs to be added to fix a problem with my path and
# Python3. Remove to make this work generally.
sys.path.insert(0, "/usr/local/lib/python3.3/site-packages")
# End of fix.
import mapnik
| [
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""" The Code is under Tencent Youtu Public Rule
builder for transforms
transforms from torch or home-made
"""
import copy
from torchvision import transforms
from .randaugment import RandAugmentMC
from .gaussian_blur import GaussianBlur
other_func = {"RandAugmentMC": RandAugmentMC,"GaussianBlur":GaussianBlur}
class BaseTransform(object):
""" For torch transform or self write
"""
def __init__(self, pipeline):
""" transforms for data
Args:
pipelines (list): list of dict, each dict is a transform
"""
self.pipeline = pipeline
self.transform = self.init_trans(pipeline)
class ListTransform(BaseTransform):
""" For torch transform or self write
"""
def __init__(self, pipelines):
""" transforms for data
Args:
pipelines (list): list of dict, each dict is a transform
"""
self.pipelines = pipelines
self.transforms = []
for trans_dict in self.pipelines:
self.transforms.append(self.init_trans(trans_dict))
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329,
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62,
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7,
944,
13,
15003,
62,
7645,
7,
7645,
62,
11600,
4008,
198
] | 2.691139 | 395 |
from django.contrib import admin
from .models.fakeauth import FakeAuthMail
@admin.register(FakeAuthMail)
| [
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#!/usr/bin/python3
"""
ssh [email protected]
cd compData
python startServer.py
"""
from http.server import HTTPServer, SimpleHTTPRequestHandler
from os import curdir
import json
from copy import deepcopy
if __name__ == '__main__':
# i.e. if this file is being run directly, not as imported module
main()
| [
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from extractor.models import Extractor
from rest_framework import serializers
from datetime import datetime
from .tasks import extractor_job
from .models import Extractor
from django.utils import timezone
import pytz | [
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"""
LeetCode Problem: 392. Is Subsequence
Link: https://leetcode.com/problems/is-subsequence/
Written by: Mostofa Adib Shakib
Language: Python
"""
"""
Recursion + Memoization[Built-in function]
Time Complexity: O(n*m)
Space Complexity: O(n*m)
"""
from functools import lru_cache
"""
Dynamic Programming
Time Complexity: O(n*m)
Space Complexity: O(n*m)
"""
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# Licensed under the BSD 3-Clause License
# Copyright (C) 2021 GeospaceLab (geospacelab)
# Author: Lei Cai, Space Physics and Astronomy, University of Oulu
import netCDF4
import datetime
import numpy as np
import geospacelab.toolbox.utilities.pydatetime as dttool
if __name__ == "__main__":
import pathlib
fp = pathlib.Path('/Users/lcai/Geospacelab/Data/JHUAPL/DMSP/SSUSI/f17/20151205/' +
'PS.APL_V0105S027CE0008_SC.U_DI.A_GP.F17-SSUSI_PA.APL-EDR-AURORA_DD.20151205_SN.46863-00_DF.NC')
loader = Loader(file_path=fp)
# if hasattr(readObj, 'pole'):
# readObj.filter_data_pole(boundinglat = 25) | [
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] | 2.19863 | 292 |
""" My init to load all main process around my ML project """
from .spark_manage import spark_start
from .data_processing import dataset_train_transpose | [
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# coding=utf-8
import os
import unittest
import six
from conans.errors import ConanException
from conans.model.build_info import CppInfo, DepsCppInfo, DepCppInfo
from conans.test.utils.test_files import temp_folder
from conans.util.files import save
| [
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# encoding: utf-8
# module Wms.RemotingImplementation.Activities.Renderers calls itself Renderers
# from Wms.RemotingImplementation,Version=1.23.1.0,Culture=neutral,PublicKeyToken=null
# by generator 1.145
# no doc
# no important
from __init__ import *
# no functions
# classes
class MobileProgressBarRenderer(object):
""" MobileProgressBarRenderer(current: Decimal,total: Decimal,title: str,enableDetails: bool,progressColor: str) """
def ZZZ(self):
"""hardcoded/mock instance of the class"""
return MobileProgressBarRenderer()
instance=ZZZ()
"""hardcoded/returns an instance of the class"""
def Dispose(self):
""" Dispose(self: MobileProgressBarRenderer) """
pass
def Render(self):
""" Render(self: MobileProgressBarRenderer) -> Array[Byte] """
pass
def __enter__(self,*args):
""" __enter__(self: IDisposable) -> object """
pass
def __exit__(self,*args):
""" __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """
pass
def __init__(self,*args):
""" x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """
pass
@staticmethod
def __new__(self,current,total,title,enableDetails,progressColor):
""" __new__(cls: type,current: Decimal,total: Decimal,title: str,enableDetails: bool,progressColor: str) """
pass
def __repr__(self,*args):
""" __repr__(self: object) -> str """
pass
Current=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Get: Current(self: MobileProgressBarRenderer) -> Decimal
Set: Current(self: MobileProgressBarRenderer)=value
"""
EnableDetails=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Get: EnableDetails(self: MobileProgressBarRenderer) -> bool
Set: EnableDetails(self: MobileProgressBarRenderer)=value
"""
ProgressColor=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Get: ProgressColor(self: MobileProgressBarRenderer) -> str
Set: ProgressColor(self: MobileProgressBarRenderer)=value
"""
Title=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Get: Title(self: MobileProgressBarRenderer) -> str
Set: Title(self: MobileProgressBarRenderer)=value
"""
Total=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Get: Total(self: MobileProgressBarRenderer) -> Decimal
Set: Total(self: MobileProgressBarRenderer)=value
"""
| [
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] | 2.930023 | 886 |
# Copyright 2015 The Emscripten Authors. All rights reserved.
# Emscripten is available under two separate licenses, the MIT license and the
# University of Illinois/NCSA Open Source License. Both these licenses can be
# found in the LICENSE file.
import os, shutil, logging, subprocess, sys, stat
TAG = 'version_4'
| [
2,
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796,
705,
9641,
62,
19,
6,
628,
628,
198
] | 3.681818 | 88 |
from requests import Session
from models.vendor import Vendor
from bs4 import BeautifulSoup
from io_utils.csv_exporter import save_scraped_vendor
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] | 3.609756 | 41 |
"""
Common test tools.
"""
from os import environ
from semver import compare
from unittest import skipIf
import requests
import subprocess
import time
TEST_GOLANG_VERSION = environ.get("TEST_GOLANG_VERSION", False)
DOCKER_VERSION = environ.get("DOCKER_VERSION", "")
skip_if_go_version = skipIf(
TEST_GOLANG_VERSION,
"Not expected to work in go version"
)
skip_if_python_version = skipIf(
not TEST_GOLANG_VERSION,
"Not expected to work in Python version"
)
skip_if_docker_version_less_than = lambda ver: skipIf(
_skip_max_docker_ver(ver),
"Not expected to work in this Docker version")
def try_until(f, attempts=5, backoff=0.1, attempt=1):
"""
Synchronously, retry ``f`` every ``backoff`` * (2 ^ ``attempt``) seconds
until it doesn't raise an exception, or we've tried ``attempts`` many
times. Return the result of running ``f`` successfully, or raise the last
exception it raised when attempted.
"""
try:
return f()
except:
if attempt > attempts:
raise
time.sleep(backoff * (2 ** attempt))
return try_until(
f, attempts=attempts, backoff=backoff, attempt=attempt + 1)
def run(cmd):
"""
Run cmd (list of bytes), e.g. ["ls", "/"] and return the result, raising
CalledProcessErrorWithOutput if return code is non-zero.
"""
try:
result = subprocess.check_output(
cmd,
stderr=subprocess.STDOUT
)
except subprocess.CalledProcessError, error:
exc = CalledProcessErrorWithOutput(
"\n>> command:\n%(command)s"
"\n>> returncode\n%(returncode)d"
"\n>> output:\n%(output)s" %
dict(command=" ".join(cmd),
returncode=error.returncode,
output=error.output))
exc.original = error
raise exc
return result
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13,
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220,
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220,
5298,
2859,
198,
220,
220,
220,
1441,
1255,
198
] | 2.419231 | 780 |
#!/bin/py
#
# interpolate over data field with 2d polynomial fit
#
# fit a 2D, 3rd order polynomial to data
# estimate the 16 coefficients using all of your data points.
#
# http://stackoverflow.com/questions/18832763/drawing-directions-fields
#
#
import numpy as np
import matplotlib
matplotlib.use('Agg')
import itertools
import matplotlib.pyplot as plt
from scipy import integrate
from scipy.integrate import ode
hprime = -4.5
#
#
#
#
#
#
#
#
#
#
# main function: execute
#
#
# EXECUTE
#
main()
#
# nick
# 1/30/16
#
# http://stackoverflow.com/questions/7997152/python-3d-polynomial-surface-fit-order-dependent
#
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498,
12,
42029,
12,
11147,
12,
2875,
12,
21186,
198,
2,
198
] | 2.567347 | 245 |
import cv2
from matplotlib import pyplot as plt
img = cv2.imread('galaxy.jpg', 0)
img = cv2.resize(img, (int(img.shape[1]/2), int(img.shape[0]/2)))
cv2.imwrite('GlaxyResized.jpg', img)
plt.imshow(img)
plt.show()
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] | 2.118812 | 101 |
import os
import re
from pathlib import Path
from typing import Dict
from typing import Optional
from typing import Union
from urllib.request import urlopen
from xsdata.codegen.parsers import DefinitionsParser
from xsdata.codegen.parsers import SchemaParser
from xsdata.logger import logger
from xsdata.models.wsdl import Definitions
from xsdata.models.xsd import Schema
class Downloader:
"""
Helper class to download a schema or a definitions with all their imports
locally. The imports paths will be adjusted if necessary.
:param output: Output path
"""
__slots__ = ("output", "base_path", "downloaded")
def wget(self, uri: str, location: Optional[str] = None):
"""Download handler for any uri input with circular protection."""
if not (uri in self.downloaded or (location and location in self.downloaded)):
self.downloaded[uri] = None
self.downloaded[location] = None
self.adjust_base_path(uri)
logger.info("Fetching %s", uri)
input_stream = urlopen(uri).read() # nosec
if uri.endswith("wsdl"):
self.parse_definitions(uri, input_stream)
else:
self.parse_schema(uri, input_stream)
self.write_file(uri, location, input_stream.decode())
def parse_schema(self, uri: str, content: bytes):
"""Convert content to a schema instance and process all sub imports."""
parser = SchemaParser(location=uri)
schema = parser.from_bytes(content, Schema)
self.wget_included(schema)
def parse_definitions(self, uri: str, content: bytes):
"""Convert content to a definitions instance and process all sub
imports."""
parser = DefinitionsParser(location=uri)
definitions = parser.from_bytes(content, Definitions)
self.wget_included(definitions)
for schema in definitions.schemas:
self.wget_included(schema)
def adjust_base_path(self, uri: str):
"""
Adjust base path for every new uri loaded.
Example runs:
- file:///schemas/air_v48_0/Air.wsdl -> file:///schemas/air_v48_0
- file:///schemas/common_v48_0/CommonReqRsp.xsd -> file:///schemas
"""
if not self.base_path:
self.base_path = Path(uri).parent
logger.info("Setting base path to %s", self.base_path)
else:
common_path = os.path.commonpath((self.base_path or "", uri))
if common_path:
common_path_path = Path(common_path)
if common_path_path < self.base_path:
self.base_path = Path(common_path)
logger.info("Adjusting base path to %s", self.base_path)
def adjust_imports(self, path: Path, content: str) -> str:
"""Try to adjust the import locations for external locations that are
not relative to the first requested uri."""
matches = re.findall(r"ocation=\"(.*)\"", content)
for match in matches:
if isinstance(self.downloaded.get(match), Path):
location = os.path.relpath(self.downloaded[match], path)
replace = str(location).replace("\\", "/")
content = content.replace(f'ocation="{match}"', f'ocation="{replace}"')
return content
def write_file(self, uri: str, location: Optional[str], content: str):
"""
Write the given uri and it's content according to the base path and if
the uri is relative to first requested uri.
Keep track of all the written file paths, in case we have to
modify the location attribute in an upcoming schema/definition
import.
"""
common_path = os.path.commonpath((self.base_path or "", uri))
if common_path:
file_path = self.output.joinpath(Path(uri).relative_to(common_path))
else:
file_path = self.output.joinpath(Path(uri).name)
content = self.adjust_imports(file_path.parent, content)
file_path.parent.mkdir(parents=True, exist_ok=True)
file_path.write_text(content, encoding="utf-8")
logger.info("Writing %s", file_path)
self.downloaded[uri] = file_path
if location:
self.downloaded[location] = file_path
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628,
220,
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611,
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220,
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220,
220,
2116,
13,
2902,
14578,
58,
24886,
60,
796,
2393,
62,
6978,
198
] | 2.413237 | 1,798 |
from setuptools import setup, find_packages
import sys, os
version = '0.2.2'
setup(name = 'eclipseprofileselector',
version = version,
description = 'Manage separate Eclipse profiles and workspaces with a nice graphical user interface.',
long_description = open('README.rst', 'r').read(),
keywords = 'eclipse profile',
classifiers = [
'Development Status :: 4 - Beta',
'Environment :: X11 Applications :: GTK',
'Intended Audience :: Developers',
'License :: OSI Approved :: MIT License',
'Natural Language :: English',
'Operating System :: POSIX',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
'Topic :: Utilities'
],
author = 'Stephan Klein',
url = 'https://github.com/privatwolke/eclipseprofileselector',
license = 'MIT',
packages = ['eclipseprofileselector'],
package_data = {
'eclipseprofileselector': ['ui.glade']
},
include_package_data = True,
zip_safe = True,
entry_points = {
'gui_scripts': [
'eclipse-profile-selector = eclipseprofileselector.profile:main'
]
}
)
| [
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12417,
6,
198,
197,
197,
60,
198,
197,
92,
198,
8,
198
] | 2.922222 | 360 |
from django.contrib import admin
from .models import Contributor
admin.site.register(Contributor)
| [
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] | 3.571429 | 28 |
# -*- coding: utf-8 -*-
import datetime
from south.db import db
from south.v2 import SchemaMigration
from django.db import models
| [
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] | 2.977273 | 44 |
from sqlalchemy.orm.exc import NoResultFound
from porthole.app import Session
from .logger import PortholeLogger
from porthole.models import AutomatedReport, AutomatedReportContact, AutomatedReportRecipient
| [
6738,
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] | 3.781818 | 55 |
from __future__ import print_function
import kwfile_dict
import glob, os, sys
import numpy as N
from astropy.io import fits as pyfits
import pylab as P
import matplotlib
from pysynphot.compat import ASTROPY_LT_1_3
def reverse(d):
"""Return a reverse lookup dictionary for the input dictionary"""
r={}
for k in d:
r[d[k]]=k
return r
if __name__ == '__main__':
#dirpath, fieldname, instr=sys.argv[1:]
try:
run(*sys.argv[1:])
except TypeError as e:
print("sys.argv[1:] = ",sys.argv[1:])
raise e
| [
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] | 2.355932 | 236 |
"""
Usage
-----
CUDA_VISIBLE_DEVICES=0 python app.py
"""
import os
from time import time
# from neuspell import AspellChecker, JamspellChecker
from neuspell import BertsclstmChecker, CnnlstmChecker, ElmosclstmChecker, NestedlstmChecker
from neuspell import SclstmChecker, SclstmbertChecker, SclstmelmoChecker, BertChecker
from flask import Flask, render_template, url_for, request
from flask_cors import CORS
TOKENIZE = True
PRELOADED_MODELS = {}
CURR_MODEL_KEYWORD = "elmosc-rnn"
CURR_MODEL = None
TOPK = 1
LOGS_PATH = "./logs"
if not os.path.exists(LOGS_PATH):
os.makedirs(LOGS_PATH)
opfile = open(os.path.join(LOGS_PATH, str(time()) + ".logs.txt"), "w")
# Define the app
app = Flask(__name__)
CORS(app) # needed for cross-domain requests, allow everything by default
@app.route('/')
@app.route('/home', methods=['POST'])
@app.route('/loaded', methods=['POST'])
@app.route('/reset', methods=['POST'])
@app.route('/predict', methods=['POST'])
if __name__ == "__main__":
print("*** Flask Server ***")
preload_models()
app.run(debug=True, host='0.0.0.0', port=5000)
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220,
220,
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17202,
4943,
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198,
220,
220,
220,
662,
2220,
62,
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3419,
201,
198,
220,
220,
220,
598,
13,
5143,
7,
24442,
28,
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11,
2583,
11639,
15,
13,
15,
13,
15,
13,
15,
3256,
2493,
28,
27641,
8,
201,
198
] | 2.359343 | 487 |
# Released under the MIT License. See LICENSE for details.
#
"""Provides help related ui."""
from __future__ import annotations
from typing import TYPE_CHECKING
import _ba
import ba
if TYPE_CHECKING:
from typing import Optional
class HelpWindow(ba.Window):
"""A window providing help on how to play."""
| [
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] | 3.445652 | 92 |
# -*- coding: utf-8 -*-
#
# Copyright © Spyder Project Contributors
# Licensed under the terms of the MIT License
# (see spyder/__init__.py for details)
"""
Utils to handle Switcher elements.
"""
# Standard library imports
import os
import os.path as osp
import sys
# Local imports
from spyder.config.base import _
from spyder.py3compat import iteritems, PY2
from spyder.utils import icon_manager as ima
if PY2:
from itertools import izip as zip
def shorten_paths(path_list, is_unsaved):
"""
Takes a list of paths and tries to "intelligently" shorten them all. The
aim is to make it clear to the user where the paths differ, as that is
likely what they care about. Note that this operates on a list of paths
not on individual paths.
If the path ends in an actual file name, it will be trimmed off.
"""
# TODO: at the end, if the path is too long, should do a more dumb kind of
# shortening, but not completely dumb.
# Convert the path strings to a list of tokens and start building the
# new_path using the drive
path_list = path_list[:] # Make a local copy
new_path_list = []
common_prefix = osp.dirname(osp.commonprefix(path_list))
for ii, (path, is_unsav) in enumerate(zip(path_list, is_unsaved)):
if is_unsav:
new_path_list.append(_('unsaved file'))
path_list[ii] = None
else:
drive, path = osp.splitdrive(osp.dirname(path))
new_path_list.append(drive + osp.sep)
path_list[ii] = [part for part in path.split(osp.sep) if part]
recurse_level({i: pl for i, pl in enumerate(path_list) if pl})
if common_prefix:
result_paths = []
for path in new_path_list:
path_elements = path.rstrip(os.sep).split(common_prefix)
if len(path_elements) > 1:
result_paths.append("...{}".format(path_elements[-1]))
else:
result_paths.append(path)
else:
result_paths = [path.rstrip(os.sep) for path in new_path_list]
return result_paths
def get_file_icon(path):
"""Get icon for file by extension."""
if sys.platform == 'darwin':
scale_factor = 0.9
elif os.name == 'nt':
scale_factor = 0.8
else:
scale_factor = 0.6
return ima.get_icon_by_extension_or_type(path, scale_factor)
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62,
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7,
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11,
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] | 2.466597 | 958 |
import os
import logging
from src.trainer import train_by_config
logging.basicConfig(format='%(asctime)s - %(message)s', level=logging.INFO)
directory = 'train_settings/'
for filename in os.listdir(directory):
config_path = os.path.join(directory, filename)
logging.info(f'Training model in accordance with {config_path} config')
try:
train_by_config(config_path)
except Exception as err:
print(err)
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] | 2.650888 | 169 |
"""
Simple utility to get random names. I think it uses data from a US census, located in the words folder.
"""
import random
import os.path
__author__ = "Matt Fister"
maleFirsts = [line.rstrip('\n').title() for line in open(os.path.join(os.path.dirname(__file__), (os.path.join('words', 'maleFirstNames.txt'))))]
femaleFirsts = [line.rstrip('\n').title() for line in open(os.path.join(os.path.dirname(__file__), (os.path.join('words', 'femaleFirstNames.txt'))))]
lasts = [line.rstrip('\n').title() for line in open(os.path.join(os.path.dirname(__file__), (os.path.join('words', 'lastNames.txt'))))]
if __name__ == "__main__":
print(get_name(random.choice(['male', 'female'])))
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13,
25541,
7,
17816,
22606,
3256,
705,
24724,
20520,
22305,
198
] | 2.767068 | 249 |
from django.conf import settings
from core.utils import ensure_user_group_membership
from .models import SlackAccess
def invite_to_slack(privilege, person):
"""
Invites the user to Slack.
"""
privilege.slack_access.grant(person)
def add_to_group(privilege, person):
"""
Generic "add person to group" privilege. The group to add is taken from the privilege slug.
"""
group = Group.objects.get(name=privilege.slug)
ensure_user_group_membership(person.user, groups_to_add=[group])
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11,
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62,
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62,
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41888,
8094,
12962,
198
] | 2.949153 | 177 |
from django.contrib import admin
from .models import Transaction, Header, Ticker
# Register your models here.
admin.site.register(Transaction)
admin.site.register(Header)
admin.site.register(Ticker)
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13,
15654,
13,
30238,
7,
48720,
8,
198,
28482,
13,
15654,
13,
30238,
7,
39681,
8,
198,
28482,
13,
15654,
13,
30238,
7,
51,
15799,
8,
198
] | 3.526316 | 57 |
# Copyright 2019 Huawei Technologies Co., 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 applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
################################################
Testcase_PrepareCondition:
Testcase_TestSteps:
Testcase_ExpectedResult:
"""
import datetime
import os
from base import TestBase
import pytest
from test_run.focal_loss_run import focal_loss_run
from test_run.focalloss_ad_run import focalloss_grad_run
from test_run.smooth_l1_loss_run import smooth_l1_loss_run
from test_run.smooth_l1_loss_grad_run import smooth_l1_loss_grad_run
############################################################
# TestCase= class: put to tests/*/
############################################################
if __name__ == "__main__":
c = TestFocalLoss()
c.setup()
c.test_ci_run()
c.teardown()
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220,
220,
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269,
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220,
220,
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201,
198,
220,
220,
220,
269,
13,
660,
446,
593,
3419,
201,
198
] | 3.175772 | 421 |
import cfnresponse, logging, traceback, boto3
from random import choice
from string import ascii_uppercase, ascii_lowercase, digits
| [
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269,
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11,
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] | 3.35 | 40 |
from django.urls import path, include
from rest_framework.routers import DefaultRouter
from rest_framework_bulk.routes import BulkRouter
from supplier import views
router = DefaultRouter()
bulk_router = BulkRouter()
bulk_router.register("receives", views.ReceiveViewSet)
bulk_router.register("suppliers", views.SupplierViewSet)
bulk_router.register("purchase_orders", views.PurchaseOrderViewSet)
app_name = "supplier"
urlpatterns = [
path("", include(router.urls)),
path("", include(bulk_router.urls)),
]
| [
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8,
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7,
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82,
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7,
65,
12171,
62,
472,
353,
13,
6371,
82,
36911,
198,
60,
198
] | 2.899441 | 179 |
'''
A pangram is a sentence where every letter of the English alphabet appears at least once.
Given a string sentence containing only lowercase English letters, return true if sentence is a pangram, or false otherwise.
Example 1:
Input: sentence = "thequickbrownfoxjumpsoverthelazydog"
Output: true
Explanation: sentence contains at least one of every letter of the English alphabet.
Example 2:
Input: sentence = "leetcode"
Output: false
'''
| [
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import matplotlib.pyplot as plt
import numpy as np
from PyQt5.QtCore import Qt
from PyQt5.QtGui import QCursor
from PyQt5.QtWidgets import QApplication
from draw_binary_image import plot_binary_image
if __name__ == "__main__":
main() | [
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834,
1298,
198,
220,
220,
220,
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3419
] | 2.7 | 90 |
from PolyAModel import *
import re
import os, sys, copy, getopt, re, argparse
import random
import pandas as pd
import numpy as np
from Bio.Seq import Seq
from TrimmedMean import TrimmedMean
import gc
#from extract_coverage_from_scanGenome import check
#def dataProcessing(scan_file,window,rst):
if __name__ == "__main__":
Evaluate(*args())
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220,
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201,
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] | 2.386503 | 163 |
import sys
import os
from jinja2 import Template
# Apply environment variables to a Jinga2 Template file
# Save the results into an output file specified by the caller
if __name__ == "__main__":
if len(sys.argv) != 3:
print("usage: python apply_env.py input_file output_file")
sys.exit(1)
with open(sys.argv[1], "r") as f:
data = f.read()
t = Template(data)
with open(sys.argv[2], "w") as f:
f.write(t.render(os.environ))
| [
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277,
25,
198,
220,
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277,
13,
13564,
7,
83,
13,
13287,
7,
418,
13,
268,
2268,
4008,
198
] | 2.489474 | 190 |
#!/usr/bin/env python
import os
import argparse
import PIL.Image
import PIL.ExifTags
if __name__ == '__main__':
main()
| [
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220,
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198
] | 2.529412 | 51 |
###
# Copyright (c) 2004-2005, Jeremiah Fincher
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice,
# this list of conditions, and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions, and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of the author of this software nor the name of
# contributors to this software may be used to endorse or promote products
# derived from this software without specific prior written consent.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
###
import supybot.utils as utils
from supybot.commands import *
import supybot.ircutils as ircutils
import supybot.schedule as schedule
import supybot.callbacks as callbacks
import commands
Class = Tail
# vim:set shiftwidth=4 softtabstop=4 expandtab textwidth=79:
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] | 3.449814 | 538 |
#
# Fusion Pickles Probability 3 Parts
#
# Peter Turney, July 14, 2021
#
# From the 20 runs, extract all of the pickled three-part seeds
# that are stored in the 20 "fusion_storage.bin" pickle files.
# Read the pickles and run each pickle, recording the results in
# a numpy tensor:
#
# tensor = num_seeds x num_steps x num_colours x num_parts
#
# num_seeds = to be determined
# num_steps = 1001
# num_colours = 5 (white, red, orange, blue, green)
# num_parts = 3
#
# After this tensor has been filled with values, generate
# a table of the form:
#
# <prob N M> = <probability for N managers and M workers>
#
# row in table = <step number> <prob 3 0> <prob 2 1> <prob 1 2> <prob 0 3>
#
import golly as g
import model_classes as mclass
import model_functions as mfunc
import model_parameters as mparam
import numpy as np
import copy
import time
import pickle
import os
import re
import sys
#
# Parameter values for making the graphs.
#
max_seeds = 2000 # probably won't need more seeds than this
num_steps = 1001 # number of time steps in the game
num_colours = 5 # 5 colours [white, red, blue, orange, green]
num_parts = 3 # number of parts
num_files = 20 # number of fusion pickle files
step_size = 20 # number of time steps between each plot point
#
# Location of fusion_storage.bin files -- the input pickles.
#
fusion_dir = "C:/Users/peter/Peter's Projects" + \
"/management-theory-revised/Experiments"
# list of pickle files
fusion_files = []
# loop through the fusion files and record the file paths
# -- we assume the folders have the form "run1", "run2", ...
for i in range(num_files):
fusion_files.append(fusion_dir + "/run" + str(i + 1) + \
"/fusion_storage.bin")
#
# Loop through the pickles, loading them into fusion_list.
# Each fusion file will contain several pickles.
#
seed_list = mfunc.read_fusion_pickles(fusion_files)
#
# Given a list of seeds, fill a tensor with counts of the growth of colours
# generated by running the Management Game.
#
[tensor, num_seeds] = mfunc.growth_tensor(g, seed_list, step_size,
max_seeds, num_steps, num_colours, num_parts)
#
# now the tensor is full, so let's make the graph for 3 parts
#
graph_file = fusion_dir + "/fusion_pickles_probability_3.txt"
graph_handle = open(graph_file, "w")
graph_handle.write("\n\nNOTE: {} Seeds -- {} Parts per seed\n\n".format(
num_seeds, num_parts))
header = ["step num", \
"3 managers and 0 workers", \
"2 managers and 1 worker", \
"1 manager and 2 workers", \
"0 managers and 3 workers"]
graph_handle.write("\t".join(header) + "\n")
#
for step_num in range(0, num_steps, step_size):
# initialize counts
count_3m0w = 0 # 3 managers, 0 workers
count_2m1w = 0 # 2 managers, 1 worker
count_1m2w = 0 # 1 manager, 2 workers
count_0m3w = 0 # 0 managers, 3 workers
# iterate over seed_num
for seed_num in range(num_seeds):
# iterate over parts
manager_count = 0
for part_num in range(num_parts):
# extract colours
red = tensor[seed_num, step_num, 1, part_num]
blue = tensor[seed_num, step_num, 2, part_num]
orange = tensor[seed_num, step_num, 3, part_num]
green = tensor[seed_num, step_num, 4, part_num]
# we focus on the current part (part_num) only
# -- the current part is always red, by convention
red_manager = (orange > green) # true or false
manager_count += red_manager # will increment by 0 or 1
# increment counts
if (manager_count == 3):
count_3m0w += 1
elif (manager_count == 2):
count_2m1w += 1
elif (manager_count == 1):
count_1m2w += 1
else:
count_0m3w += 1
#
assert count_3m0w + count_2m1w + count_1m2w + count_0m3w == num_seeds
#
probability_3m0w = count_3m0w / num_seeds
probability_2m1w = count_2m1w / num_seeds
probability_1m2w = count_1m2w / num_seeds
probability_0m3w = count_0m3w / num_seeds
#
graph_handle.write("{}\t{:.3f}\t{:.3f}\t{:.3f}\t{:.3f}\n".format(step_num,
probability_3m0w, probability_2m1w, probability_1m2w, probability_0m3w))
#
#
graph_handle.close()
#
# | [
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] | 2.514269 | 1,682 |
#!/usr/bin/env python3
# Copyright 2022 Amazon.com, Inc. or its affiliates. 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 applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import logging
import os
import re
import sys
from typing import Optional, Tuple
import click
from aws_ddk.__metadata__ import __version__
from aws_ddk.commands.bootstrap import bootstrap_account
from aws_ddk.commands.create import create_code_repository
from aws_ddk.commands.deploy import cdk_deploy
from aws_ddk.commands.init import init_project
from aws_ddk.utils import get_package_root
from boto3 import Session, _get_default_session, setup_default_session
DEBUG_LOGGING_FORMAT = "[%(asctime)s][%(filename)-13s:%(lineno)3d] %(message)s"
DEBUG_LOGGING_FORMAT_REMOTE = "[%(filename)-13s:%(lineno)3d] %(message)s"
DEFAULT_PROJECT_TEMPLATE = "data/project_templates/ddk_app/"
_logger: logging.Logger = logging.getLogger(__name__)
@click.group()
@click.version_option(__version__)
@click.option(
"--debug/--no-debug",
default=False,
help="Turn debug logging on/off.",
show_default=True,
)
def cli(
debug: bool,
) -> None:
"""AWS DDK CLI."""
click.echo(f"AWS DDK CLI {__version__} (Python {sys.version})")
if debug:
enable_debug(format=DEBUG_LOGGING_FORMAT)
_logger.debug(f"debug: {debug}")
@cli.command(name="init")
@click.argument(
"name",
type=str,
required=True,
)
@click.option(
"--environment",
"-e",
type=str,
help="The id of the environment.",
required=True,
default="dev",
show_default=True,
)
@click.option(
"--template",
"-t",
type=str,
help="A directory containing a project template directory, or a URL to a git repository",
)
def init(name: str, environment: str, template: Optional[str] = None) -> None:
"""
Create the local structure for a new AWS DDK Python project.
NAME is the name of the project.
"""
# Use default Cookiecutter project template
if not template:
template = os.path.join(get_package_root(), DEFAULT_PROJECT_TEMPLATE)
return init_project(name=name, environment=environment, template=template)
@cli.command(name="bootstrap")
@click.option(
"--environment",
"-e",
type=RegexString(regex=r"^[A-Za-z0-9_-]{1,4}$"),
help="The id of the environment.",
required=True,
default="dev",
show_default=True,
)
@click.option(
"--profile",
"-p",
type=str,
default="default",
help="Use a specific profile from your AWS credentials file.",
show_default=True,
required=False,
)
@click.option(
"--region",
"-r",
type=str,
default=None,
help="AWS Region name (e.g. us-east-1). If None, it will be inferred.",
show_default=False,
required=False,
)
@click.option(
"--prefix",
type=RegexString(regex=r"^[A-Za-z0-9_-]{1,5}$"),
help="The prefix to resource names.",
required=False,
default="ddk",
show_default=True,
)
@click.option(
"--qualifier",
type=RegexString(regex=r"^[A-Za-z0-9_-]{1,10}$"),
help="The CDK bootstrap qualifier.",
required=False,
)
@click.option(
"--trusted-accounts",
"-a",
type=str,
help="List of trusted AWS accounts to perform deployments (e.g. -a 111111111111 -a 222222222222).",
multiple=True,
required=False,
)
@click.option(
"--iam-policies",
"-i",
type=str,
help="""List of IAM managed policy ARNs that should be attached to the role performing deployments.
(e.g. -i arn1 -i arn2)""",
multiple=True,
required=False,
)
@click.option(
"--permissions-boundary",
type=str,
help="IAM managed permissions boundary policy ARN that should be attached to the role performing deployments.",
required=False,
)
@click.option(
"--tags",
"-t",
type=(str, str),
help="List of tags to apply to the stack (e.g -t CostCenter 1984 -t Framework DDK).",
multiple=True,
required=False,
)
def bootstrap(
environment: str,
profile: str,
region: Optional[str] = None,
prefix: Optional[str] = None,
qualifier: Optional[str] = None,
trusted_accounts: Optional[Tuple[str]] = None,
iam_policies: Optional[Tuple[str]] = None,
permissions_boundary: Optional[str] = None,
tags: Optional[Tuple[Tuple[str, str]]] = None,
) -> None:
"""Bootstrap the AWS account with DDK resources."""
setup_boto_session(profile, region)
bootstrap_account(
environment=environment,
prefix=prefix,
qualifier=qualifier,
trusted_accounts=trusted_accounts,
iam_policies=iam_policies,
permissions_boundary=permissions_boundary,
tags=tags,
)
@cli.command(name="create-repository")
@click.argument(
"name",
type=str,
required=True,
)
@click.option(
"--profile",
"-p",
type=str,
default="default",
help="Use a specific profile from your AWS credentials file.",
show_default=True,
required=False,
)
@click.option(
"--region",
"-r",
type=str,
default=None,
help="AWS Region name (e.g. us-east-1). If None, it will be inferred.",
show_default=False,
required=False,
)
@click.option(
"--description",
"-d",
type=str,
help="The description of the repository.",
required=False,
)
@click.option(
"--tags",
"-t",
type=(str, str),
help="List of tags to apply to the repository (e.g -t CostCenter 1984 -t Framework DDK).",
multiple=True,
required=False,
)
def create_repository(
name: str,
profile: str,
region: Optional[str] = None,
description: Optional[str] = None,
tags: Optional[Tuple[Tuple[str, str]]] = None,
) -> None:
"""
Create a code repository from the source system provider.
NAME is the name of the repository.
"""
setup_boto_session(profile, region)
create_code_repository(
name=name,
description=description,
tags=tags,
)
@cli.command(name="deploy")
@click.option(
"--profile",
"-p",
type=str,
default="default",
help="Use a specific profile from your AWS credentials file.",
show_default=True,
required=False,
)
@click.option(
"--require-approval",
type=click.Choice(["never", "any-change", "broadening"], case_sensitive=False),
default="never",
help="What security-sensitive changes need manual approval.",
required=False,
)
@click.option(
"--force",
"-f",
is_flag=True,
default=False,
help="Always deploy stack even if templates are identical.",
required=False,
)
@click.option(
"--output-dir",
"-o",
type=str,
help="Directory where cloud assembly is synthesized.",
required=False,
)
def deploy(
profile: str,
require_approval: Optional[str] = None,
force: Optional[bool] = None,
output_dir: Optional[str] = None,
) -> None:
"""Deploy DDK stacks to AWS account."""
setup_boto_session(profile)
cdk_deploy(
profile=profile,
require_approval=require_approval,
force=force,
output_dir=output_dir,
)
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24019,
389,
10411,
33283,
198,
220,
220,
220,
2672,
28,
25101,
11,
198,
8,
198,
31,
12976,
13,
18076,
7,
198,
220,
220,
220,
366,
438,
22915,
12,
15908,
1600,
198,
220,
220,
220,
27444,
78,
1600,
198,
220,
220,
220,
2099,
28,
2536,
11,
198,
220,
220,
220,
1037,
2625,
43055,
810,
6279,
10474,
318,
24983,
1143,
33283,
198,
220,
220,
220,
2672,
28,
25101,
11,
198,
8,
198,
4299,
6061,
7,
198,
220,
220,
220,
7034,
25,
965,
11,
198,
220,
220,
220,
2421,
62,
21064,
2100,
25,
32233,
58,
2536,
60,
796,
6045,
11,
198,
220,
220,
220,
2700,
25,
32233,
58,
30388,
60,
796,
6045,
11,
198,
220,
220,
220,
5072,
62,
15908,
25,
32233,
58,
2536,
60,
796,
6045,
11,
198,
8,
4613,
6045,
25,
198,
220,
220,
220,
37227,
49322,
20084,
42,
24285,
284,
30865,
1848,
526,
15931,
198,
220,
220,
220,
9058,
62,
65,
2069,
62,
29891,
7,
13317,
8,
198,
220,
220,
220,
22927,
74,
62,
2934,
1420,
7,
198,
220,
220,
220,
220,
220,
220,
220,
7034,
28,
13317,
11,
198,
220,
220,
220,
220,
220,
220,
220,
2421,
62,
21064,
2100,
28,
46115,
62,
21064,
2100,
11,
198,
220,
220,
220,
220,
220,
220,
220,
2700,
28,
3174,
11,
198,
220,
220,
220,
220,
220,
220,
220,
5072,
62,
15908,
28,
22915,
62,
15908,
11,
198,
220,
220,
220,
1267,
628
] | 2.578066 | 2,927 |
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