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import torch from torch import nn as nn from basicsr.archs.arch_util import ResidualBlockNoBN, Upsample, make_layer from basicsr.utils.registry import ARCH_REGISTRY @ARCH_REGISTRY.register() class EDSR(nn.Module): """EDSR network structure. Paper: Enhanced Deep Residual Networks for Single Image Super-Resol...
[ "torch.Tensor", "basicsr.utils.registry.ARCH_REGISTRY.register", "basicsr.archs.arch_util.Upsample", "torch.nn.Conv2d", "basicsr.archs.arch_util.make_layer" ]
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# Copyright 2020 <NAME> # # 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 ...
[ "networkx.DiGraph", "decyclify.node_iterators.TasksIterator", "pytest.fail", "decyclify.functions.decyclify", "decyclify.node_iterators.CycleIterator", "pytest.raises" ]
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import json import xmltodict with open("data.xml") as xml_file: data_dict = xmltodict.parse(xml_file.read()) print(data_dict) xml_file.close() json_data = json.dumps(data_dict, indent=4) with open("xml_data.json", "w") as json_file: json_file.write(json_data) json_file.close()
[ "json.dumps" ]
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#!/usr/bin/env python # -*- coding: utf-8 -*- from distutils.core import setup setup(name='arpy', version='0.1.1', description='Library for accessing "ar" files', author=u'<NAME>', author_email='<EMAIL>', url='http://bitbucket.org/viraptor/arpy', py_modules=['arpy'], license="Simplified BSD", )
[ "distutils.core.setup" ]
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# ============================================================================= # PROJECT CHRONO - http://projectchrono.org # # Copyright (c) 2014 projectchrono.org # All rights reserved. # # Use of this source code is governed by a BSD-style license that can be found # in the LICENSE file at the top level of the distr...
[ "pychrono.fea.CastToChNodeFEAxyzD", "pychrono.ChVisualShapeFEA", "pychrono.ChTimestepperHHT", "pychrono.GetChronoDataFile", "pychrono.ChVectorD", "pychrono.fea.CastToChNodeFEAbase", "pychrono.fea.ChMaterialShellANCF", "pychrono.irrlicht.ChVisualSystemIrrlicht", "pychrono.ChSolverMINRES", "pychrono...
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# encoding: utf-8 import json import yaml import click import googleanalytics as ga from googleanalytics import utils from .common import cli # TODO: the blueprint stuff can probably be simplified so that # it's little more than just a call to ga.describe def from_blueprint(scope, src): description = yaml.load(...
[ "click.Choice", "click.argument", "googleanalytics.authenticate", "click.IntRange", "click.option", "click.File", "yaml.load", "click.echo", "googleanalytics.query.describe", "googleanalytics.Blueprint", "googleanalytics.utils.cut" ]
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from config import * from utils import make_bb from utils import sed_integ from mdwarf_interp import * def initialize(): global bb10k bb10k = make_bb(WAVELENGTH, 10000) global BBnorm BBnorm = 1 / sed_integ(WAVELENGTH[WMIN:WMAX], bb10k[WMIN:WMAX]) global MDarea mdinterp = mdwarf_interp(MDSPEC...
[ "utils.make_bb", "utils.sed_integ" ]
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from microbit import * import neopixel np = neopixel.NeoPixel(pin1 ,32) def np_rainbow(np, num, bright=32, offset = 0): rb = ((255,0,0), (255,127,0), (255,255,0), (0,255,0), (0,255,255),(0,0,255),(136,0,255), (255,0,0)) for i in range(num): t = 7*i/num t0 = int(t) r = round((rb[t0][0] ...
[ "neopixel.NeoPixel" ]
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# Created byMartin.cz # Copyright (c) <NAME>. All rights reserved. from pero.properties import * from pero import StraitAxis from pero import Scale, ContinuousScale, LinScale, LogScale, OrdinalScale from pero import Ticker, LinTicker, LogTicker, FixTicker, TimeTicker from pero import Formatter, IndexFormatter from ...
[ "pero.LogScale", "pero.LinTicker", "pero.LinScale", "pero.OrdinalScale", "pero.StraitAxis", "pero.LogTicker", "pero.TimeTicker", "pero.IndexFormatter" ]
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__path__ = __import__("pkgutil").extend_path(__path__, __name__) from collections.abc import Sequence from types import ModuleType from typing import Any, Optional from arti.formats import Format from arti.internal.utils import dispatch, import_submodules from arti.storage import StoragePartition, _StoragePartition f...
[ "arti.internal.utils.import_submodules" ]
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import binascii import os from typing import Any, Callable, Generator, Iterator, NewType, Optional import requests from apk_patcher.lib.progress import ProgressCallback, ProgressCancelled, ProgressData, ProgressStage, ProgressType DownloadMiddleware = NewType('DownloadMiddleware', Callable[[Iterator], Genera...
[ "apk_patcher.lib.progress.ProgressData", "requests.get", "typing.NewType", "os.path.dirname", "apk_patcher.lib.progress.ProgressCancelled", "os.path.basename", "binascii.a2b_base64" ]
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#%% Import modules import numpy as np import torch def train(A, ss, epoch, single_model, single_optim, loss_MSE): device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') FR_ORDER_TRAIN = A["FR_ORDER_TRAIN"] POS_NOR_ORDER_TRAIN = A["POS_NOR_ORDER_TRAIN"] VEL_NOR_ORDER_TRAIN = A["VEL_NOR_OR...
[ "torch.utils.data.DataLoader", "torch.utils.data.TensorDataset", "torch.from_numpy", "torch.cuda.is_available", "torch.save", "numpy.concatenate", "torch.no_grad" ]
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# -*- coding: utf-8 -*- # Generated by Django 1.11.2 on 2018-08-18 22:32 from __future__ import unicode_literals from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ migratio...
[ "django.db.models.ForeignKey", "django.db.models.ManyToManyField", "django.db.models.AutoField", "django.db.migrations.swappable_dependency", "django.db.models.CharField" ]
[((312, 369), 'django.db.migrations.swappable_dependency', 'migrations.swappable_dependency', (['settings.AUTH_USER_MODEL'], {}), '(settings.AUTH_USER_MODEL)\n', (343, 369), False, 'from django.db import migrations, models\n'), ((1550, 1604), 'django.db.models.ManyToManyField', 'models.ManyToManyField', ([], {'blank': ...
import torch import math import gpytorch from torch import nn from gpytorch.random_variables import GaussianRandomVariable from .likelihood import Likelihood class GaussianLikelihood(Likelihood): def __init__(self, log_noise_bounds=(-1000, 1000)): super(GaussianLikelihood, self).__init__() self.re...
[ "gpytorch.random_variables.GaussianRandomVariable", "torch.zeros", "math.log" ]
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import sys import math from collections import defaultdict, deque sys.setrecursionlimit(10 ** 6) stdin = sys.stdin INF = float('inf') ni = lambda: int(ns()) na = lambda: list(map(int, stdin.readline().split())) ns = lambda: stdin.readline().strip() sx, sy, gx, gy, T, V = na() N = ni() for _ in range(N): x, y = ...
[ "sys.setrecursionlimit", "math.sqrt" ]
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from comment.models import Comment from django.contrib.contenttypes.fields import GenericRelation from django.db.models.signals import post_save from django.conf import settings from django.db import models from django.db.models import Sum from django.shortcuts import reverse from django_countries.fields import Country...
[ "django.db.models.OneToOneField", "django.db.models.FloatField", "django.db.models.TextField", "django.db.models.IntegerField", "django.db.models.ForeignKey", "django.db.models.FileField", "django.db.models.BooleanField", "django.shortcuts.reverse", "django.db.models.ImageField", "django.db.models...
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#!/usr/bin/env python # Copyright 2018 Kubos Corporation # Licensed under the Apache License, Version 2.0 # See LICENSE file for details. """ Wrapper for creating a UDP based Kubos service """ import socket import json import logging def start(logger, config, schema, context={}): logger.info("{} starting on {...
[ "json.dumps", "socket.socket" ]
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from __future__ import annotations import ast from typing import ( TYPE_CHECKING, Any, Awaitable, Callable, List, Optional, Type, Union, cast, ) from ....utils.logging import LoggingDescriptor from ....utils.uri import Uri from ...common.language import language_id from ...common.t...
[ "typing.cast" ]
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from decimal import Decimal from django.test import TestCase from django.test.utils import override_settings from django.urls import reverse from hordak.models import Account, StatementImport, StatementLine, Transaction from hordak.tests.utils import DataProvider from moneyed import Money from hordak.utilities.curren...
[ "hordak.models.Transaction.objects.count", "hordak.models.Transaction.objects.get", "hordak.models.StatementLine.objects.get", "hordak.models.StatementImport.objects.create", "hordak.utilities.currency.Balance", "moneyed.Money", "django.urls.reverse", "django.test.utils.override_settings", "decimal....
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#!flask/bin/python from flask import Flask, jsonify, abort, make_response, request, send_from_directory import sqlite3, json, logging, re from flask_httpauth import HTTPBasicAuth app = Flask(__name__) db = sqlite3.connect("booksdb",check_same_thread = False) cursor = db.cursor() date_format = "%Y-%m-%d" timestamp_form...
[ "flask_httpauth.HTTPBasicAuth", "sqlite3.connect", "re.compile", "flask.Flask", "logging.Formatter", "json.dumps", "flask.request.get_json", "logging.FileHandler", "flask.abort", "flask.jsonify" ]
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import tensorflow as tf def saturation(img): mean = tf.keras.backend.mean(img, axis=-1, keepdims = True) mul = tf.constant([1,1,1,3], tf.int32) mean = tf.tile(mean, mul) img = tf.math.subtract(img, mean) sat = tf.einsum('aijk,aijk->aij', img, img) sat = tf.math.scalar_mul((1.0/3.0),sat) sat = tf.math.add(sat, t...
[ "tensorflow.expand_dims", "tensorflow.tile", "tensorflow.math.abs", "tensorflow.math.pow", "tensorflow.keras.backend.mean", "tensorflow.math.subtract", "tensorflow.nn.convolution", "tensorflow.math.sqrt", "tensorflow.split", "tensorflow.einsum", "tensorflow.math.multiply", "tensorflow.constant...
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# -*- coding: utf-8 -*- # <nbformat>3.0</nbformat> # <codecell> from __future__ import division import csv import numpy as np import random import pickle import datetime from NonSpatialFns import * # <codecell> #Script #Number of state transitions to observe M = int(2e7) # time vector time = np.zeros(M) #Define par...
[ "numpy.random.random", "datetime.datetime.now", "numpy.zeros", "numpy.log10" ]
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from mudes.app.mudes_app import MUDESApp # app = HateSpansApp("multilingual-large", use_cuda=False) # print(app.predict_hate_spans("ගෝඨාභය පොන්නයා විවාදෙට එන්නේ නැත්තේ ඇයි දන්නවා ද?", spans=True, language="xx")) # # tokens = app.predict_tokens("ගෝඨාභය පොන්නයා විවාදෙට එන්නේ නැත්තේ ඇයි දන්නවා ද?", language="xx") # for t...
[ "mudes.app.mudes_app.MUDESApp" ]
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# Generated by Django 2.1.5 on 2019-01-16 15:45 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('travels', '0025_flight_time'), ] operations = [ migrations.AddField( model_name='flight', name='date2', ...
[ "django.db.models.DateField" ]
[((326, 365), 'django.db.models.DateField', 'models.DateField', ([], {'blank': '(True)', 'null': '(True)'}), '(blank=True, null=True)\n', (342, 365), False, 'from django.db import migrations, models\n')]
# Copyright 2017 The Forseti Security Authors. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the 'License'); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by ap...
[ "google.cloud.security.common.util.parser.json_stringify" ]
[((1712, 1776), 'google.cloud.security.common.util.parser.json_stringify', 'parser.json_stringify', (["FAKE_PROJECT_APPLICATIONS_MAP['project1']"], {}), "(FAKE_PROJECT_APPLICATIONS_MAP['project1'])\n", (1733, 1776), False, 'from google.cloud.security.common.util import parser\n')]
import json __all__ = [ 'dump', 'load', ] def _get_mode(fp, mode): if mode is None: if fp.endswith('.jsonline') or fp.endswith('.jsonl'): mode = 'jsonl' else: mode = 'json' return mode def _get_kwargs(**kwargs): if 'encoding' not in kwargs: kwargs...
[ "json.load", "json.dumps", "json.dump" ]
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# !/usr/bin/env python # -*- coding: utf-8 -*- """ Defines the unit tests for the :mod:`colour.appearance.hunt` module. """ import numpy as np from itertools import permutations from colour.appearance import (VIEWING_CONDITIONS_HUNT, InductionFactors_Hunt, XYZ_to_Hunt) from colour.appea...
[ "colour.utilities.domain_range_scale", "colour.utilities.as_float_array", "numpy.array", "colour.appearance.XYZ_to_Hunt", "itertools.permutations", "colour.appearance.InductionFactors_Hunt", "colour.utilities.tstack" ]
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from pathlib import Path import os import copy import sys import pytest from ploomber.util.util import add_to_sys_path, chdir_code, requires from ploomber.util import dotted_path def test_add_to_sys_path(): path = str(Path('/path/to/add').resolve()) with add_to_sys_path(path, chdir=False): assert pa...
[ "ploomber.util.dotted_path.load_dotted_path", "ploomber.util.util.requires", "pathlib.Path", "ploomber.util.util.add_to_sys_path", "os.getcwd", "pytest.raises", "ploomber.util.util.chdir_code", "copy.copy" ]
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#!/usr/bin/env python3 # -*- coding: utf-8 -*- import re import requests import sys import yaml import urllib3 urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning) action = sys.argv[1] if len(sys.argv) > 1 else "status" installfile = "install-config.yaml" with open(installfile) as f: data = yaml....
[ "requests.post", "re.match", "requests.get", "urllib3.disable_warnings", "yaml.safe_load" ]
[((113, 180), 'urllib3.disable_warnings', 'urllib3.disable_warnings', (['urllib3.exceptions.InsecureRequestWarning'], {}), '(urllib3.exceptions.InsecureRequestWarning)\n', (137, 180), False, 'import urllib3\n'), ((315, 332), 'yaml.safe_load', 'yaml.safe_load', (['f'], {}), '(f)\n', (329, 332), False, 'import yaml\n'), ...
import re import random import itertools import math from collections import defaultdict from src.utilities import * from src import debuglog, errlog, plog, users, channels from src.decorators import cmd, event_listener from src.containers import UserList, UserSet, UserDict, DefaultUserDict from src.messages import me...
[ "src.events.Event", "src.channels.Main.send", "src.debuglog", "src.decorators.event_listener" ]
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import os from setuptools import setup version = {} version_path = os.path.join('array_namespace', '__version__.py') with open(version_path, 'r', encoding='utf-8') as f: exec(f.read(), version) with open('README.rst', 'r', encoding='utf-8') as f: readme = f.read() setup( name='array_namespace', versi...
[ "os.path.join", "setuptools.setup" ]
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import copy class TreeNode(object): def __init__(self, tree, parent, title, string): self.tree = tree self.title = title self.parent = parent self.string = string self.children = [] self.adoptive_parents = [] if self in self.tree: raise ValueErro...
[ "copy.copy" ]
[((8134, 8171), 'copy.copy', 'copy.copy', (['tree_node.adoptive_parents'], {}), '(tree_node.adoptive_parents)\n', (8143, 8171), False, 'import copy\n'), ((5415, 5444), 'copy.copy', 'copy.copy', (['tree_node.children'], {}), '(tree_node.children)\n', (5424, 5444), False, 'import copy\n')]
# Generated by Django 3.0.6 on 2020-05-17 12:41 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('ramblings', '0011_auto_20200517_1237'), ] operations = [ migrations.AddField( model_name='post', name='level', ...
[ "django.db.models.PositiveIntegerField" ]
[((333, 387), 'django.db.models.PositiveIntegerField', 'models.PositiveIntegerField', ([], {'default': '(1)', 'editable': '(False)'}), '(default=1, editable=False)\n', (360, 387), False, 'from django.db import migrations, models\n'), ((538, 592), 'django.db.models.PositiveIntegerField', 'models.PositiveIntegerField', (...
# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('contenttypes', '0001_initial'), ] operations = [ migrations.CreateModel( name='...
[ "django.db.models.DateTimeField", "django.db.models.AutoField", "django.db.models.PositiveIntegerField", "django.db.models.ForeignKey" ]
[((395, 488), 'django.db.models.AutoField', 'models.AutoField', ([], {'verbose_name': '"""ID"""', 'primary_key': '(True)', 'serialize': '(False)', 'auto_created': '(True)'}), "(verbose_name='ID', primary_key=True, serialize=False,\n auto_created=True)\n", (411, 488), False, 'from django.db import models, migrations\...
import argparse import boto3 import json import time IN_FILE = "initial-servers.json" OUT_FILE = "temp-servers.json" # Network ID for main network, gamma, and beta NETWORK_ID="1" NETWORK_ID_FILTER = {'Name': 'tag:NetworkId', 'Values': [NETWORK_ID]} RUNNING_FILTER={'Name': 'instance-state-name', 'Values': ['running']}...
[ "argparse.ArgumentParser", "time.sleep", "boto3.resource", "json.load", "json.dump" ]
[((431, 502), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Create config for ssh-to via AWS"""'}), "(description='Create config for ssh-to via AWS')\n", (454, 502), False, 'import argparse\n'), ((1167, 1222), 'boto3.resource', 'boto3.resource', (['"""ec2"""'], {'region_name': 'old_exim...
# ###################################################################### # Copyright (c) 2014, Brookhaven Science Associates, Brookhaven # # National Laboratory. All rights reserved. # # # # Redistribution and use in ...
[ "logging.getLogger", "vttools.scrape._extract_default_vals", "vttools.scrape._truncate_description", "vttools.scrape.obj_src", "numpy.testing.assert_equal", "vttools.scrape._type_optional", "vttools.scrape.scrape_function", "itertools.product", "numpy.testing.assert_raises", "vttools.scrape._norma...
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import os import numpy as np import torch import torch.nn.functional as F from tqdm import tqdm from test import test import torchvision class TrainLoop(object): def __init__(self, model, optimizer, source_loader, test_source_loader, target_loader, patience, l2, penalty_weight, penalty_anneal_epochs, checkpoint_pat...
[ "numpy.argmax", "torch.utils.tensorboard.SummaryWriter", "torch.nn.CrossEntropyLoss", "torch.load", "os.path.join", "torch.optim.lr_scheduler.StepLR", "test.test", "os.getcwd", "os.path.isfile", "numpy.max", "torch.tensor", "os.path.isdir", "torch.sum", "torch.autograd.grad", "os.mkdir" ...
[((634, 683), 'os.path.join', 'os.path.join', (['self.checkpoint_path', '"""IRM_{}ep.pt"""'], {}), "(self.checkpoint_path, 'IRM_{}ep.pt')\n", (646, 683), False, 'import os\n'), ((831, 898), 'torch.optim.lr_scheduler.StepLR', 'torch.optim.lr_scheduler.StepLR', (['self.optimizer'], {'step_size': 'patience'}), '(self.opti...
import sys; sys.path.append('../common') import mylib as utils # pylint: disable=import-error # Read args filename = 'input.txt' if len(sys.argv) == 1 else sys.argv[1] print(filename, '\n') ########################### # region COMMON REMINDER_VALUE = 20201227 def getNextValue(value: int, subjectNumber: int) -> int:...
[ "sys.path.append", "mylib.readFileLines" ]
[((12, 40), 'sys.path.append', 'sys.path.append', (['"""../common"""'], {}), "('../common')\n", (27, 40), False, 'import sys\n'), ((1252, 1281), 'mylib.readFileLines', 'utils.readFileLines', (['filename'], {}), '(filename)\n', (1271, 1281), True, 'import mylib as utils\n')]
import pandas as pd from rdkit import Chem import numpy as np import json from gensim.models import Word2Vec from gensim.test.utils import get_tmpfile from gensim.models import KeyedVectors from sklearn.manifold import TSNE import matplotlib.pyplot as plt import seaborn as sns import networkx as nx import re """ Load ...
[ "networkx.bipartite.projected_graph", "networkx.all_pairs_shortest_path_length", "seaborn.color_palette", "pandas.read_csv", "rdkit.Chem.MolFromSmiles", "networkx.Graph", "sklearn.manifold.TSNE", "gensim.models.KeyedVectors.load", "json.load", "networkx.connected_components", "matplotlib.pyplot....
[((447, 500), 'gensim.models.KeyedVectors.load', 'KeyedVectors.load', (['"""../vectors_fullKEGG.kv"""'], {'mmap': '"""r"""'}), "('../vectors_fullKEGG.kv', mmap='r')\n", (464, 500), False, 'from gensim.models import KeyedVectors\n'), ((3701, 3759), 'sklearn.manifold.TSNE', 'TSNE', ([], {'n_components': '(2)', 'verbose':...
"""This module contains several handy functions primarily meant for internal use.""" from __future__ import division from datetime import date, datetime, time, timedelta, tzinfo from calendar import timegm import re from pytz import timezone, utc import six try: from inspect import signature except ImportError: ...
[ "datetime.datetime", "pytz.timezone", "datetime.datetime.fromtimestamp", "datetime.time", "re.compile", "six.itervalues", "funcsigs.signature", "datetime.timedelta" ]
[((2619, 2796), 're.compile', 're.compile', (['"""(?P<year>\\\\d{4})-(?P<month>\\\\d{1,2})-(?P<day>\\\\d{1,2})(?: (?P<hour>\\\\d{1,2}):(?P<minute>\\\\d{1,2}):(?P<second>\\\\d{1,2})(?:\\\\.(?P<microsecond>\\\\d{1,6}))?)?"""'], {}), "(\n '(?P<year>\\\\d{4})-(?P<month>\\\\d{1,2})-(?P<day>\\\\d{1,2})(?: (?P<hour>\\\\d{1...
# Generated by Django 2.0.1 on 2018-02-18 20:36 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('countries', '0005_remove_locale_data'), ] operations = [ migrations.RenameField( model_name='country', old_name='mpoly', ...
[ "django.db.migrations.RenameField" ]
[((229, 317), 'django.db.migrations.RenameField', 'migrations.RenameField', ([], {'model_name': '"""country"""', 'old_name': '"""mpoly"""', 'new_name': '"""outlines"""'}), "(model_name='country', old_name='mpoly', new_name=\n 'outlines')\n", (251, 317), False, 'from django.db import migrations\n'), ((369, 448), 'dja...
import math import torch import torch.nn as nn from torch.distributions import Normal from torch.nn import init FixedNormal = Normal log_prob_normal = FixedNormal.log_prob FixedNormal.log_probs = lambda self, actions: log_prob_normal(self, actions).sum(-1, keepdim=True) entropy = FixedNormal.entropy FixedNormal.entro...
[ "torch.nn.functional.linear", "torch.nn.ReLU", "torch.nn.LeakyReLU", "torch.sigmoid", "torch.Tensor", "math.sqrt", "torch.nn.Conv2d", "torch.nn.init.xavier_normal_", "torch.nn.init.kaiming_uniform_", "torch.nn.Linear", "torch.zeros", "torch.FloatTensor", "torch.cat" ]
[((738, 766), 'torch.nn.Linear', 'nn.Linear', (['size_in', 'size_out'], {}), '(size_in, size_out)\n', (747, 766), True, 'import torch.nn as nn\n'), ((914, 938), 'torch.zeros', 'torch.zeros', (['(1)', 'size_out'], {}), '(1, size_out)\n', (925, 938), False, 'import torch\n'), ((1834, 1869), 'torch.FloatTensor', 'torch.Fl...
from django.core.management.base import BaseCommand from quotes.models import Episode, Show from quotes.quotelist import quotelistdict from django.db import IntegrityError from django.core.exceptions import ObjectDoesNotExist class Command(BaseCommand): help = 'Loads shows from quotes.quotelist.quotedictlist' ...
[ "quotes.models.Show.objects.count", "quotes.models.Show" ]
[((659, 699), 'quotes.models.Show', 'Show', ([], {'name': "item['show']", 'is_active': '(False)'}), "(name=item['show'], is_active=False)\n", (663, 699), False, 'from quotes.models import Episode, Show\n'), ((1210, 1230), 'quotes.models.Show.objects.count', 'Show.objects.count', ([], {}), '()\n', (1228, 1230), False, '...
""" Streamlit web UI for plotting model outputs """ import streamlit as st from autumn.tools import db from autumn.tools.plots.plotter import StreamlitPlotter from autumn.utils.params import load_targets from dash import selectors from .plots import PLOT_FUNCS def run_dashboard(): app_name, app_dirpath = selec...
[ "dash.selectors.app_name", "autumn.utils.params.load_targets", "streamlit.write", "autumn.tools.db.load.load_mcmc_tables", "streamlit.sidebar.slider", "autumn.tools.db.load.load_mcmc_params_tables", "autumn.tools.plots.plotter.StreamlitPlotter" ]
[((315, 355), 'dash.selectors.app_name', 'selectors.app_name', ([], {'run_type': '"""calibrate"""'}), "(run_type='calibrate')\n", (333, 355), False, 'from dash import selectors\n'), ((479, 528), 'streamlit.sidebar.slider', 'st.sidebar.slider', (['"""Number of countries"""', '(2)', '(6)', '(3)'], {}), "('Number of count...
from decimal import Decimal from rest_framework import status class MapObjectApiViewTestTemplate(object): def test_empty_filter(self, url): response = self.client.get(url) filtered_objects = response.data self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertEqua...
[ "decimal.Decimal" ]
[((1540, 1571), 'decimal.Decimal', 'Decimal', (["rect_params['min_lat']"], {}), "(rect_params['min_lat'])\n", (1547, 1571), False, 'from decimal import Decimal\n'), ((1628, 1660), 'decimal.Decimal', 'Decimal', (["rect_params['min_long']"], {}), "(rect_params['min_long'])\n", (1635, 1660), False, 'from decimal import De...
# the functionality of this test file has not been tested. from pathlib import Path import shutil import chromedriver_binary from dash.testing.application_runners import import_app import pytest from selenium.webdriver.common.by import By from selenium.webdriver.support.ui import WebDriverWait from selenium.w...
[ "selenium.webdriver.support.ui.WebDriverWait", "pathlib.Path", "dash.testing.application_runners.import_app", "selenium.webdriver.support.expected_conditions.text_to_be_present_in_element", "shutil.rmtree" ]
[((1153, 1172), 'dash.testing.application_runners.import_app', 'import_app', (['"""usage"""'], {}), "('usage')\n", (1163, 1172), False, 'from dash.testing.application_runners import import_app\n'), ((1440, 1459), 'dash.testing.application_runners.import_app', 'import_app', (['"""usage"""'], {}), "('usage')\n", (1450, 1...
# BSD 3-Clause License # # Copyright (c) 2016-19, University of Liverpool # 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 notic...
[ "conkit.misc.deprecate" ]
[((1787, 1833), 'conkit.misc.deprecate', 'deprecate', (['"""0.11"""'], {'msg': '"""Use A2mParser instead"""'}), "('0.11', msg='Use A2mParser instead')\n", (1796, 1833), False, 'from conkit.misc import deprecate\n')]
from flask import Flask from flask_socketio import SocketIO, emit from raven.engine.default_engine import DefaultEngine as Engine from raven.input.rest_input import RESTInput from raven.output.rest_output import RESTOutput from raven.layer.cmd.wiki import WikiLayer from config.stage import settings app = Flask(__nam...
[ "flask.Flask", "raven.input.rest_input.RESTInput", "flask_socketio.SocketIO", "raven.engine.default_engine.DefaultEngine", "raven.output.rest_output.RESTOutput", "raven.layer.cmd.wiki.WikiLayer" ]
[((309, 324), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (314, 324), False, 'from flask import Flask\n'), ((373, 386), 'flask_socketio.SocketIO', 'SocketIO', (['app'], {}), '(app)\n', (381, 386), False, 'from flask_socketio import SocketIO, emit\n'), ((402, 434), 'raven.input.rest_input.RESTInput', 'RE...
import json import pytest from indy import ledger, error @pytest.mark.asyncio async def test_build_attrib_request_works_for_raw_value(): identifier = "Th7MpTaRZVRYnPiabds81Y" destination = "Th7MpTaRZVRYnPiabds81Y" raw = '{"endpoint":{"ha":"127.0.0.1:5555"}}' expected_response = { "identifier...
[ "pytest.raises", "indy.ledger.build_attrib_request" ]
[((2026, 2069), 'pytest.raises', 'pytest.raises', (['error.CommonInvalidStructure'], {}), '(error.CommonInvalidStructure)\n', (2039, 2069), False, 'import pytest\n'), ((490, 559), 'indy.ledger.build_attrib_request', 'ledger.build_attrib_request', (['identifier', 'destination', 'None', 'raw', 'None'], {}), '(identifier,...
#! /usr/bin/env python # Copyright 2020 CS Systemes d'Information, http://www.c-s.fr # # This file is part of pytest-executable # https://www.github.com/CS-SI/pytest-executable # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # Y...
[ "pathlib.Path.cwd", "yaml.safe_load", "pathlib.Path" ]
[((2077, 2091), 'pathlib.Path', 'Path', (['__file__'], {}), '(__file__)\n', (2081, 2091), False, 'from pathlib import Path\n'), ((4383, 4393), 'pathlib.Path.cwd', 'Path.cwd', ([], {}), '()\n', (4391, 4393), False, 'from pathlib import Path\n'), ((2690, 2712), 'yaml.safe_load', 'yaml.safe_load', (['stream'], {}), '(stre...
import warnings from typing import Tuple, Callable, Any, List import numpy as np from nebullvm.base import QuantizationType from nebullvm.inference_learners.base import BaseInferenceLearner from nebullvm.measure import compute_relative_difference def check_precision( optimized_learner: BaseInferenceLearner, ...
[ "warnings.warn" ]
[((1539, 1676), 'warnings.warn', 'warnings.warn', (['"""Got a valid quantization type without any given quantization threshold. The quantization step will be ignored."""'], {}), "(\n 'Got a valid quantization type without any given quantization threshold. The quantization step will be ignored.'\n )\n", (1552, 167...
import unittest import numpy as np from .bvgamma import * from flavio.physics.bdecays.formfactors.b_v import bsz_parameters from flavio.physics.eft import WilsonCoefficients from flavio.physics.bdecays.wilsoncoefficients import wctot_dict from flavio.parameters import default_parameters import flavio wc = WilsonCoeff...
[ "flavio.physics.eft.WilsonCoefficients" ]
[((309, 329), 'flavio.physics.eft.WilsonCoefficients', 'WilsonCoefficients', ([], {}), '()\n', (327, 329), False, 'from flavio.physics.eft import WilsonCoefficients\n')]
from installed_clients.specialClient import special as special import json import os import shutil def wdl(callback_url, token, params): sr = special(callback_url, token=token) src = '/kb/module/workflow.wdl' wdl_file = 'workflow.wdl' shutil.copy(src, '/kb/module/work/tmp/' + wdl_file) input_file ...
[ "json.dumps", "shutil.copy", "installed_clients.specialClient.special" ]
[((148, 182), 'installed_clients.specialClient.special', 'special', (['callback_url'], {'token': 'token'}), '(callback_url, token=token)\n', (155, 182), True, 'from installed_clients.specialClient import special as special\n'), ((253, 304), 'shutil.copy', 'shutil.copy', (['src', "('/kb/module/work/tmp/' + wdl_file)"], ...
from midca import goals, base from midca import midcatime from ._goalgen import tf_fire from ._goalgen import tf_3_scen from midca.domains.logistics import deliverstate from midca.domains.blocksworld import blockstate from midca.worldsim import stateread import copy,csv import random from midca.modules.monitors import ...
[ "midca.domains.blocksworld.blockstate.get_block_list" ]
[((1026, 1058), 'midca.domains.blocksworld.blockstate.get_block_list', 'blockstate.get_block_list', (['world'], {}), '(world)\n', (1051, 1058), False, 'from midca.domains.blocksworld import blockstate\n')]
import unittest import mock from copy import copy from tests import BaseTest import logging # Units under test import cadquery from cadquery.freecad_impl import console_logging class TestLogging(BaseTest): def setUp(self): # save root logger's state root_logger = logging.getLogger() self...
[ "logging.getLogger", "mock.patch", "cadquery.freecad_impl.console_logging.disable", "cadquery.freecad_impl.console_logging.enable", "copy.copy" ]
[((777, 836), 'mock.patch', 'mock.patch', (['"""cadquery.freecad_impl.console_logging.FreeCAD"""'], {}), "('cadquery.freecad_impl.console_logging.FreeCAD')\n", (787, 836), False, 'import mock\n'), ((1186, 1245), 'mock.patch', 'mock.patch', (['"""cadquery.freecad_impl.console_logging.FreeCAD"""'], {}), "('cadquery.freec...
#!/usr/bin/python3 import collections import contextlib import itertools import logging import math import os.path import re import json import sys import types from typing import Iterable, List, Tuple import matplotlib import numpy as np from absl import app, flags import scipy.stats FLAGS = flags.FLAGS flags.DEFIN...
[ "re.compile", "matplotlib.pyplot.ylabel", "absl.flags.register_validator", "matplotlib.pyplot.errorbar", "logging.info", "numpy.arange", "absl.flags.DEFINE_list", "matplotlib.pyplot.xlabel", "absl.app.run", "numpy.max", "matplotlib.pyplot.close", "itertools.chain.from_iterable", "matplotlib....
[((309, 387), 'absl.flags.DEFINE_string', 'flags.DEFINE_string', (['"""pdf_dir"""', '""""""', '"""directory to which PDF files are written"""'], {}), "('pdf_dir', '', 'directory to which PDF files are written')\n", (328, 387), False, 'from absl import app, flags\n'), ((388, 466), 'absl.flags.DEFINE_string', 'flags.DEFI...
# -*- coding: UTF-8 -*- """ 此脚本用于展示spectral embedding的效果 """ import numpy as np import matplotlib.pyplot as plt from spectral_embedding_ import spectral_embedding def generate_data(): """ 生成邻接矩阵 """ data = np.array([ [0, 1, 1, 1, 0, 0, 0], [1, 0, 1, 1, 1, 0, 0], [1, 1, 0, 1, ...
[ "spectral_embedding_.spectral_embedding", "numpy.array", "matplotlib.pyplot.figure", "matplotlib.pyplot.show" ]
[((226, 406), 'numpy.array', 'np.array', (['[[0, 1, 1, 1, 0, 0, 0], [1, 0, 1, 1, 1, 0, 0], [1, 1, 0, 1, 0, 0, 0], [1, 1,\n 1, 0, 0, 0, 0], [0, 1, 0, 0, 0, 1, 1], [0, 0, 0, 0, 1, 0, 1], [0, 0, 0,\n 0, 1, 1, 0]]'], {}), '([[0, 1, 1, 1, 0, 0, 0], [1, 0, 1, 1, 1, 0, 0], [1, 1, 0, 1, 0, 0, \n 0], [1, 1, 1, 0, 0, 0,...
""" clustering.py 2018.06.11 """ import sys import os import argparse import tensorflow as tf import numpy as np import facenet from scipy import misc from sklearn.cluster import KMeans class FaceNet: def __init__(self, sess, args): self.session = sess facenet.load_model(args.model) ...
[ "sklearn.cluster.KMeans", "os.path.exists", "tensorflow.ConfigProto", "facenet.get_image_paths", "argparse.ArgumentParser", "os.mkdir", "facenet.prewhiten", "numpy.concatenate", "tensorflow.GPUOptions", "facenet.to_rgb", "facenet.load_model", "tensorflow.get_default_graph" ]
[((1630, 1701), 'tensorflow.GPUOptions', 'tf.GPUOptions', ([], {'per_process_gpu_memory_fraction': 'args.gpu_memory_fraction'}), '(per_process_gpu_memory_fraction=args.gpu_memory_fraction)\n', (1643, 1701), True, 'import tensorflow as tf\n'), ((2952, 2977), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {})...
import cv2 import numpy as np import pafy """ url = 'https://youtu.be/u68EWmtKZw0?list=TLPQMDkwMzIwMjCcOgKmuF00yg' vPafy = pafy.new(url) play = vPafy.getbest(preftype="mp4") cap = cv2.VideoCapture(play.url) """ cap = cv2.VideoCapture(0) CLASSES = ["background", "aeroplane", "bicycle", "bird", "boat", "bottl...
[ "cv2.rectangle", "cv2.dnn.readNetFromCaffe", "cv2.imshow", "cv2.putText", "numpy.array", "cv2.destroyAllWindows", "cv2.VideoCapture", "cv2.resize", "cv2.waitKey", "numpy.arange" ]
[((217, 236), 'cv2.VideoCapture', 'cv2.VideoCapture', (['(0)'], {}), '(0)\n', (233, 236), False, 'import cv2\n'), ((1711, 1734), 'cv2.destroyAllWindows', 'cv2.destroyAllWindows', ([], {}), '()\n', (1732, 1734), False, 'import cv2\n'), ((601, 630), 'cv2.resize', 'cv2.resize', (['image', '(640, 640)'], {}), '(image, (640...
""" Vectorize() with support for decorating methods; for example:: from scipy.stats import rv_continuous from scipy_ext import vectorize class dist(rv_continuous): @vectorize(excluded=('n',), otypes=(float,)) def _cdf(self, x, n): if n < 5: return f(x) # One ex...
[ "numpy.arange" ]
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# @title: pbt_trainer.py # @author: <NAME> # @date: 02.09.2021 ############################################################ # Imports import torch import time import numpy as np import random from torch.utils.tensorboard import SummaryWriter from src.utility.container import ( ModelContainer, UtilityC...
[ "src.gridworld_trainer.reinforce.model.ReinforceNetwork3D", "src.gridworld_trainer.reinforce.memory.MemoryReinforce", "torch.cuda.is_available", "torchvision.utils.make_grid", "copy.copy", "logging.info", "torch.utils.tensorboard.SummaryWriter", "os.path.exists", "src.utility.container.StatisticCont...
[((3125, 3153), 'torch.manual_seed', 'torch.manual_seed', (['self.seed'], {}), '(self.seed)\n', (3142, 3153), False, 'import torch\n'), ((3162, 3187), 'numpy.random.seed', 'np.random.seed', (['self.seed'], {}), '(self.seed)\n', (3176, 3187), True, 'import numpy as np\n'), ((3196, 3218), 'random.seed', 'random.seed', ([...
# -*- coding: utf-8 -*- ''' You are given a string where you have to find its first word. When solving a task pay attention to the following points: There can be dots and commas in a string. A string can start with a letter or, for example, a dot or space. A word can contain an apostrophe and it's a part of a word. ...
[ "datetime.date" ]
[((511, 533), 'datetime.date', 'date', (['a[0]', 'a[1]', 'a[2]'], {}), '(a[0], a[1], a[2])\n', (515, 533), False, 'from datetime import date\n'), ((536, 558), 'datetime.date', 'date', (['b[0]', 'b[1]', 'b[2]'], {}), '(b[0], b[1], b[2])\n', (540, 558), False, 'from datetime import date\n')]
""" Batched Render file. """ import dirt import numpy as np import tensorflow as tf from dirt import matrices import dirt.lighting as lighting from tensorflow.python.framework import ops def orthgraphic_projection(w, h, near=0.1, far=10., name=None): """Constructs a orthographic projection matrix. This func...
[ "dirt.rasterise_batch", "tensorflow.shape", "numpy.zeros", "tensorflow.ones_like", "tensorflow.convert_to_tensor", "tensorflow.python.framework.ops.name_scope", "tensorflow.cast" ]
[((2464, 2493), 'numpy.zeros', 'np.zeros', (['(3)'], {'dtype': 'np.float32'}), '(3, dtype=np.float32)\n', (2472, 2493), True, 'import numpy as np\n'), ((2545, 2574), 'numpy.zeros', 'np.zeros', (['(3)'], {'dtype': 'np.float32'}), '(3, dtype=np.float32)\n', (2553, 2574), True, 'import numpy as np\n'), ((2611, 2640), 'num...
#!/usr/bin/env python import sys import binascii from struct import pack, unpack ############################################################################### # color crap ############################################################################### palette = [0xbccbde, 0xc2dde6, 0xe6e9f0, 0x431c5d, 0xe05915, 0x...
[ "sys.exit" ]
[((9768, 9780), 'sys.exit', 'sys.exit', (['(-1)'], {}), '(-1)\n', (9776, 9780), False, 'import sys\n')]
# -*- coding: utf-8 import unicodedata import math import logging import pickle import numpy as np import h5py from .alignment import Alignment, Edits GAP = '\a' # reserved character that does not get mapped (for gap repairs) class Sequence2Sequence(object): '''Sequence to sequence (character-level) error correc...
[ "logging.getLogger", "numpy.nanargmax", "numpy.log", "keras.callbacks.TerminateOnNaN", "keras.layers.TimeDistributed", "keras.backend.slice", "math.sqrt", "numpy.argsort", "numpy.array", "numpy.count_nonzero", "keras.layers.Dense", "tensorflow.compat.v1.get_default_graph", "math.exp", "ten...
[((10507, 10533), 'tensorflow.compat.v1.ConfigProto', 'tf.compat.v1.ConfigProto', ([], {}), '()\n', (10531, 10533), True, 'import tensorflow as tf\n'), ((12030, 12086), 'keras.layers.Input', 'Input', ([], {'shape': '(None, self.voc_size)', 'name': '"""encoder_input"""'}), "(shape=(None, self.voc_size), name='encoder_in...
import inspect from src.Challenge import Challenge class ChainDecorators(Challenge): def __init__(self): super(ChainDecorators, self).__init__() self.challenge = 'Chain multiple decorators together' def code(self): starting_string = 'Middle' print('starting_string =', startin...
[ "inspect.getsource" ]
[((459, 491), 'inspect.getsource', 'inspect.getsource', (['decorator_one'], {}), '(decorator_one)\n', (476, 491), False, 'import inspect\n'), ((521, 553), 'inspect.getsource', 'inspect.getsource', (['decorator_two'], {}), '(decorator_two)\n', (538, 553), False, 'import inspect\n')]
import sys import re import datefinder #finds the first ID found in a string def find_id(message): result = re.search('<@!(.+?)>', message) if(result): return result.group(1) return None #finds the first date in a string def find_date(message): result = list(datefinder.find_date...
[ "re.findall", "datefinder.find_dates", "re.search" ]
[((119, 150), 're.search', 're.search', (['"""<@!(.+?)>"""', 'message'], {}), "('<@!(.+?)>', message)\n", (128, 150), False, 'import re\n'), ((300, 330), 'datefinder.find_dates', 'datefinder.find_dates', (['message'], {}), '(message)\n', (321, 330), False, 'import datefinder\n'), ((605, 651), 're.findall', 're.findall'...
############################################################################## # # # This is a demonstration of the Fast Factorized Backprojection algorithm. # # Data sets can be switched in and out by commenting/uncommenting the lines # # o...
[ "ritsar.imgTools.imshow", "matplotlib.pylab.tight_layout", "matplotlib.pylab.title", "ritsar.imgTools.img_plane_dict", "ritsar.imgTools.backprojection", "matplotlib.pylab.xlabel", "ritsar.imgTools.FFBP", "ritsar.phsRead.AFRL", "time.time", "matplotlib.pylab.subplot", "ritsar.imgTools.FFBPmp", ...
[((621, 639), 'sys.path.append', 'path.append', (['"""../"""'], {}), "('../')\n", (632, 639), False, 'from sys import path\n'), ((640, 669), 'sys.path.append', 'path.append', (['"""./dictionaries"""'], {}), "('./dictionaries')\n", (651, 669), False, 'from sys import path\n'), ((3409, 3455), 'ritsar.phsRead.AFRL', 'phsR...
# SPDX-License-Identifier: MIT # Copyright (c) 2021 Akumatic # # https://adventofcode.com/2021/day/18 import math class Node: def __init__(self, left: "Node" = None, right: "Node" = None, value: int = None, parent: "Node" = None, depth: int = 1): self.left = left self.right = right ...
[ "math.ceil", "math.floor" ]
[((1701, 1716), 'math.floor', 'math.floor', (['val'], {}), '(val)\n', (1711, 1716), False, 'import math\n'), ((1785, 1799), 'math.ceil', 'math.ceil', (['val'], {}), '(val)\n', (1794, 1799), False, 'import math\n')]
from typing import Optional, MutableMapping, List, Union from datetime import datetime, timedelta from fastapi.security import OAuth2PasswordBearer from passlib.context import CryptContext from sqlalchemy.orm.session import Session from jose import jwt from app.models import User from app.config import settings JWTP...
[ "fastapi.security.OAuth2PasswordBearer", "datetime.datetime.utcnow", "passlib.context.CryptContext", "jose.jwt.encode", "datetime.timedelta" ]
[((429, 467), 'fastapi.security.OAuth2PasswordBearer', 'OAuth2PasswordBearer', ([], {'tokenUrl': '"""token"""'}), "(tokenUrl='token')\n", (449, 467), False, 'from fastapi.security import OAuth2PasswordBearer\n'), ((482, 533), 'passlib.context.CryptContext', 'CryptContext', ([], {'schemes': "['bcrypt']", 'deprecated': '...
#!/usr/bin/env python from distutils.core import setup setup(name = 'filltex', version = '1.3.1', description = 'Automatic queries to ADS and InSPIRE databases to fill LATEX bibliography', long_description="See: `github.com/dgerosa/filltex <https://github.com/dgerosa/filltex>`_." , author = '<...
[ "distutils.core.setup" ]
[((57, 526), 'distutils.core.setup', 'setup', ([], {'name': '"""filltex"""', 'version': '"""1.3.1"""', 'description': '"""Automatic queries to ADS and InSPIRE databases to fill LATEX bibliography"""', 'long_description': '"""See: `github.com/dgerosa/filltex <https://github.com/dgerosa/filltex>`_."""', 'author': '"""<NA...
from collector import Collector from builder import Builder from defender import Defender from harvester_new import HarvesterNew from upgrader import Upgrader from creep_spawner import CreepSpawner from tower import Tower # defs is a package which claims to export all constants and some JavaScript objects, but in reali...
[ "builder.Builder", "collector.Collector", "upgrader.Upgrader", "tower.Tower", "defender.Defender", "harvester_new.HarvesterNew", "creep_spawner.CreepSpawner" ]
[((2008, 2020), 'tower.Tower', 'Tower', (['tower'], {}), '(tower)\n', (2013, 2020), False, 'from tower import Tower\n'), ((2485, 2522), 'creep_spawner.CreepSpawner', 'CreepSpawner', (['spawn', 'num_creeps', 'role'], {}), '(spawn, num_creeps, role)\n', (2497, 2522), False, 'from creep_spawner import CreepSpawner\n'), ((...
#!/usr/bin/python3 # -*- coding: utf-8 -*- import subprocess import sys import os import argparse from timeit import default_timer as timer def beep(): notes = [(0.25, 440), (0.25, 480), (0.25, 440), (0.25, 480), (0.25, 440), (0.25, 480), (0.25, 440), (0.5, 520)] try: import winsound ...
[ "os.path.exists", "os.makedirs", "argparse.ArgumentParser", "timeit.default_timer", "subprocess.call", "sys.exit", "winsound.Beep" ]
[((620, 645), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (643, 645), False, 'import argparse\n'), ((1560, 1580), 'subprocess.call', 'subprocess.call', (['cmd'], {}), '(cmd)\n', (1575, 1580), False, 'import subprocess\n'), ((1699, 1726), 'os.path.exists', 'os.path.exists', (['args.output'], ...
from setuptools import setup setup( name='hedgecock_dev', version='1.0.0', install_requires=[ "google-api-python-client", "google-auth-httplib2", "google-auth-oauthlib", "cachecontrol", 'google', 'requests', 'sanic', 'websockets', 'dat...
[ "setuptools.setup" ]
[((30, 268), 'setuptools.setup', 'setup', ([], {'name': '"""hedgecock_dev"""', 'version': '"""1.0.0"""', 'install_requires': "['google-api-python-client', 'google-auth-httplib2', 'google-auth-oauthlib',\n 'cachecontrol', 'google', 'requests', 'sanic', 'websockets',\n 'dataclasses', 'jinja2']"}), "(name='hedgecock...
from app import webapp, mysql from flask import render_template, request, flash, redirect, jsonify, make_response, session, url_for from .const import ErrorMessages import os, cv2, json import MySQLdb.cursors from werkzeug.security import generate_password_hash, check_password_hash import pymysql import boto3 import r...
[ "flask.render_template", "json.loads", "boto3.client", "flask.flash", "json.dumps", "pymysql.connect", "os.path.join", "requests.get", "app.webapp.route", "os.chdir", "os.getcwd", "flask.redirect", "flask.url_for", "werkzeug.security.check_password_hash", "cv2.cvtColor", "cv2.imread", ...
[((332, 436), 'requests.get', 'requests.get', (['"""http://169.254.169.254/latest/meta-data/iam/security-credentials/assignment2S3"""'], {}), "(\n 'http://169.254.169.254/latest/meta-data/iam/security-credentials/assignment2S3'\n )\n", (344, 436), False, 'import requests\n'), ((612, 780), 'pymysql.connect', 'pymy...
import tensorflow as tf import tef import tef.pywrap import tef.utils class BaseOptimizer(object): def __init__(self): pass def compute_gradients(self, loss): tef_trainable = tef.utils.get_collection(tef.utils.TEF_TRAINABLE_COLLECTION) gs = [] stubs = [] for stub in te...
[ "tef.pywrap.ps_hash_push", "tef.utils.get_collection", "tef.pywrap.ps_sparse_push", "tensorflow.gradients", "tensorflow.group", "tensorflow.gather", "tef.pywrap.ps_push" ]
[((202, 262), 'tef.utils.get_collection', 'tef.utils.get_collection', (['tef.utils.TEF_TRAINABLE_COLLECTION'], {}), '(tef.utils.TEF_TRAINABLE_COLLECTION)\n', (226, 262), False, 'import tef\n'), ((3053, 3071), 'tensorflow.group', 'tf.group', (['push_ops'], {}), '(push_ops)\n', (3061, 3071), True, 'import tensorflow as t...
import numpy as np import tensorflow as tf import torch from groupy.gconv.tensorflow_gconv.transform_filter import transform_filter_2d_nchw, transform_filter_2d_nhwc from groupy.gconv.make_gconv_indices import make_c4_z2_indices, make_c4_p4_indices,\ make_d4_z2_indices, make_d4_p4m_indices, flatten_indices from gr...
[ "numpy.abs", "groupy.gconv.pytorch_gconv.splitgconv2d.trans_filter", "groupy.gconv.make_gconv_indices.make_c4_z2_indices", "tensorflow.Session", "groupy.gconv.tensorflow_gconv.transform_filter.transform_filter_2d_nhwc", "tensorflow.constant", "groupy.gconv.make_gconv_indices.flatten_indices", "groupy....
[((493, 520), 'groupy.gconv.make_gconv_indices.make_c4_z2_indices', 'make_c4_z2_indices', ([], {'ksize': '(3)'}), '(ksize=3)\n', (511, 520), False, 'from groupy.gconv.make_gconv_indices import make_c4_z2_indices, make_c4_p4_indices, make_d4_z2_indices, make_d4_p4m_indices, flatten_indices\n'), ((529, 559), 'numpy.rando...
"""Tanslate SMS language to French.""" import sys import enchant # import tempfile # import os smsdic = { "cc": "Coucou, ", "cv": "Ça va ?", "tfq": "Tu fait quoi ?", "pq": "Pourquoi ?", "c": "C'est", "t": "Tu est", "xd": "😂", "yep": "Oui", "k": "Ok", "nan": "Non", "nop": ...
[ "enchant.Dict" ]
[((1254, 1272), 'enchant.Dict', 'enchant.Dict', (['"""fr"""'], {}), "('fr')\n", (1266, 1272), False, 'import enchant\n')]
# -*- coding: utf-8 -*- """ Tencent is pleased to support the open source community by making 蓝鲸智云PaaS平台社区版 (BlueKing PaaS Community Edition) available. Copyright (C) 2017-2018 THL A29 Limited, a Tencent company. All rights reserved. Licensed under the MIT License (the "License"); you may not use this file except in co...
[ "common.responses.OKJsonResponse", "user_center.weixin.utils.get_user_wx_info", "home.models.UserSettings.objects.filter", "home.utils.get_user_apps", "home.models.UsefulLinks.objects.get_common_links" ]
[((1455, 1478), 'home.utils.get_user_apps', 'get_user_apps', (['username'], {}), '(username)\n', (1468, 1478), False, 'from home.utils import get_user_apps\n'), ((1557, 1595), 'home.models.UsefulLinks.objects.get_common_links', 'UsefulLinks.objects.get_common_links', ([], {}), '()\n', (1593, 1595), False, 'from home.mo...
from collections import defaultdict class Node: def __init__(self, value): self.parent = None self.value = value def get_height(node): height = 0 while node is not None: height += 1 node = node.parent return height def solution2(node1, node2): height1, height2...
[ "collections.defaultdict" ]
[((876, 893), 'collections.defaultdict', 'defaultdict', (['bool'], {}), '(bool)\n', (887, 893), False, 'from collections import defaultdict\n')]
# Generated by Django 3.1.2 on 2020-10-12 18:42 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('listings', '0003_auto_20201012_2208'), ] operations = [ migrations.AddField( model_name='joblist', name='icon', ...
[ "django.db.models.ImageField" ]
[((334, 392), 'django.db.models.ImageField', 'models.ImageField', ([], {'blank': '(True)', 'upload_to': '"""photos/%Y/%m/%d"""'}), "(blank=True, upload_to='photos/%Y/%m/%d')\n", (351, 392), False, 'from django.db import migrations, models\n')]
__version__ = "1.5.0" from deriva.qt.common.async_task import async_execute, Task from deriva.qt.common.log_widget import QPlainTextEditLogger from deriva.qt.common.table_widget import TableWidget from deriva.qt.common.json_editor import JSONEditor from deriva.qt.auth_agent.ui.auth_window import AuthWindow from deriv...
[ "os.path.dirname", "os.path.join" ]
[((750, 924), 'os.path.join', 'os.path.join', (['executableDir', '"""lib"""', '"""PyQt5"""', '"""Qt5"""', '"""lib"""', '"""QtWebEngineCore.framework"""', '"""Helpers"""', '"""QtWebEngineProcess.app"""', '"""Contents"""', '"""MacOS"""', '"""QtWebEngineProcess"""'], {}), "(executableDir, 'lib', 'PyQt5', 'Qt5', 'lib',\n ...
# vim: set encoding=utf-8 : # ***********************IMPORTANT NMAP LICENSE TERMS************************ # * * # * The Nmap Security Scanner is (C) 1996-2013 Insecure.Com LLC. Nmap is * # * also a registered trademark of Insecure.Com LLC. Thi...
[ "gtk.ComboBox", "gtk.ListStore", "zenmapGUI.higwidgets.higboxes.HIGHBox", "gtk.CellRendererText" ]
[((10243, 10274), 'gtk.ListStore', 'gtk.ListStore', (['str', 'object', 'str'], {}), '(str, object, str)\n', (10256, 10274), False, 'import gtk\n'), ((10363, 10388), 'gtk.ComboBox', 'gtk.ComboBox', (['types_store'], {}), '(types_store)\n', (10375, 10388), False, 'import gtk\n'), ((10404, 10426), 'gtk.CellRendererText', ...
from __future__ import print_function import pickle import os.path from googleapiclient.discovery import build from google_auth_oauthlib.flow import InstalledAppFlow from google.auth.transport.requests import Request class GoogleSheet: def __init__(self, spreadsheet_id): self.spreadsheet_id=spreadsheet_id ...
[ "pickle.dump", "google.auth.transport.requests.Request", "pickle.load", "googleapiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow.from_client_secrets_file" ]
[((1555, 1600), 'googleapiclient.discovery.build', 'build', (['"""sheets"""', '"""v4"""'], {'credentials': 'self.creds'}), "('sheets', 'v4', credentials=self.creds)\n", (1560, 1600), False, 'from googleapiclient.discovery import build\n'), ((914, 932), 'pickle.load', 'pickle.load', (['token'], {}), '(token)\n', (925, 9...
from django import forms from django.core.exceptions import ValidationError class ContactForm(forms.Form): full_name = forms.CharField(label= "Your name and surname", required=True, widget=forms.TextInput (attrs={'placeholder': 'Your full name'})) email = forms.EmailField(required=Tr...
[ "django.forms.Textarea", "django.forms.EmailInput", "django.forms.TextInput" ]
[((194, 250), 'django.forms.TextInput', 'forms.TextInput', ([], {'attrs': "{'placeholder': 'Your full name'}"}), "(attrs={'placeholder': 'Your full name'})\n", (209, 250), False, 'from django import forms\n'), ((332, 391), 'django.forms.EmailInput', 'forms.EmailInput', ([], {'attrs': "{'placeholder': 'Enter your email'...
import kivy kivy.require('1.0.6') # replace with your current kivy version ! from kivy.app import App from kivy.uix.label import Label import os import shutil import json import codecs class MyApp(App): def build(self): self.root = "/home/Games/Crusader-HDUP/CrusaderAIManager" self.ai_shorts =...
[ "kivy.require", "os.path.join", "kivy.uix.label.Label", "os.mkdir", "json.load", "json.dump" ]
[((12, 33), 'kivy.require', 'kivy.require', (['"""1.0.6"""'], {}), "('1.0.6')\n", (24, 33), False, 'import kivy\n'), ((1214, 1239), 'kivy.uix.label.Label', 'Label', ([], {'text': '"""Hello world"""'}), "(text='Hello world')\n", (1219, 1239), False, 'from kivy.uix.label import Label\n'), ((1391, 1425), 'os.path.join', '...
import os, json, time from flask import Flask, request import ml_utils import sqlite3 as sql import run_backend app = Flask(__name__) def get_predictions(): videos = [] with sql.connect(run_backend.db_name) as conn: c = conn.cursor() for line in c.execute("SELECT * FROM videos"): ...
[ "flask.request.args.get", "sqlite3.connect", "flask.Flask", "ml_utils.compute_predictions", "json.dumps" ]
[((121, 136), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (126, 136), False, 'from flask import Flask, request\n'), ((1254, 1297), 'flask.request.args.get', 'request.args.get', (['"""yt_video_id"""'], {'default': '""""""'}), "('yt_video_id', default='')\n", (1270, 1297), False, 'from flask import Flask,...
import numpy as np import nanocut.common as nc from nanocut.output import error, printstatus __all__ = [ "Periodicity", ] def gcd(numbers): """Calculates greatest common divisor of a list of numbers.""" aa = numbers[0] for bb in numbers[1:]: while bb: aa, bb = bb, aa % bb re...
[ "nanocut.output.printstatus", "numpy.prod", "numpy.equal", "numpy.not_equal", "numpy.array", "numpy.linalg.norm", "numpy.sin", "nanocut.output.error", "numpy.arange", "numpy.greater", "numpy.less", "numpy.cross", "numpy.dot", "numpy.abs", "numpy.eye", "numpy.ones", "numpy.cos", "nu...
[((945, 968), 'numpy.prod', 'np.prod', (['miller_nonzero'], {}), '(miller_nonzero)\n', (952, 968), True, 'import numpy as np\n'), ((1061, 1088), 'numpy.zeros', 'np.zeros', (['(2, 3)'], {'dtype': 'int'}), '((2, 3), dtype=int)\n', (1069, 1088), True, 'import numpy as np\n'), ((3785, 3812), 'numpy.zeros', 'np.zeros', (['(...
# coding=utf-8 from __future__ import unicode_literals from transit.transit_types import Keyword, Symbol, true, false from transit.pyversion import string_types class KeywordUnicorn(Keyword): def __init__(self): self.parent = None def __getattr__(self, value): assert isinstance(value, string_...
[ "transit.transit_types.Symbol", "transit.transit_types.Keyword" ]
[((1377, 1389), 'transit.transit_types.Symbol', 'Symbol', (['"""?e"""'], {}), "('?e')\n", (1383, 1389), False, 'from transit.transit_types import Keyword, Symbol, true, false\n'), ((1394, 1405), 'transit.transit_types.Symbol', 'Symbol', (['"""_"""'], {}), "('_')\n", (1400, 1405), False, 'from transit.transit_types impo...
#! /usr/bin/env python3 import numpy as np from sklearn.neighbors import NearestNeighbors from computeNeighborWeights import computeNeighborWeights from computeWeightedMRecons import computeWeightedMRecons from computeFeatures import computeFeatures def computeFullERD(MeasuredValues,MeasuredIdxs,UnMeasuredIdxs,Theta,S...
[ "numpy.sqrt", "numpy.logical_and", "numpy.where", "numpy.delete", "computeNeighborWeights.computeNeighborWeights", "computeFeatures.computeFeatures", "numpy.max", "numpy.zeros", "computeWeightedMRecons.computeWeightedMRecons", "sklearn.neighbors.NearestNeighbors", "numpy.min" ]
[((690, 884), 'computeFeatures.computeFeatures', 'computeFeatures', (['MeasuredValues', 'MeasuredIdxs', 'UnMeasuredIdxs', 'SizeImage', 'NeighborValues', 'NeighborWeights', 'NeighborDistances', 'TrainingInfo', 'ReconValues', 'ReconImage', 'Resolution', 'ImageType'], {}), '(MeasuredValues, MeasuredIdxs, UnMeasuredIdxs, S...
from aiida_nanotech_empa.workflows.gaussian import common from aiida_nanotech_empa.utils import common_utils from aiida.engine import WorkChain, calcfunction, ExitCode from aiida.orm import Int, Str, Code, Dict from aiida.orm import StructureData, RemoteData from aiida.plugins import WorkflowFactory GaussianBaseWork...
[ "aiida.engine.ExitCode", "aiida.orm.Int", "aiida_nanotech_empa.utils.common_utils.check_if_calc_ok", "aiida_nanotech_empa.workflows.gaussian.common.get_gaussian_cores_and_memory", "aiida_nanotech_empa.workflows.gaussian.common.setup_context_variables", "aiida.plugins.WorkflowFactory", "aiida_nanotech_em...
[((328, 360), 'aiida.plugins.WorkflowFactory', 'WorkflowFactory', (['"""gaussian.base"""'], {}), "('gaussian.base')\n", (343, 360), False, 'from aiida.plugins import WorkflowFactory\n'), ((2350, 2386), 'aiida_nanotech_empa.workflows.gaussian.common.setup_context_variables', 'common.setup_context_variables', (['self'], ...
import argparse import os import json import sys def copyright_main(): parser = argparse.ArgumentParser( description="automatically set the copyright for you" ) parser.add_argument("-p", "--path", help="choose the path you want to add the copyright") parser....
[ "json.loads", "os.walk", "argparse.ArgumentParser", "sys.exit" ]
[((93, 171), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""automatically set the copyright for you"""'}), "(description='automatically set the copyright for you')\n", (116, 171), False, 'import argparse\n'), ((3257, 3275), 'os.walk', 'os.walk', (['args.path'], {}), '(args.path)\n', (326...
from keras.models import Sequential from keras.layers import Dense from sklearn.cross_validation import StratifiedKFold import numpy as np # init seed seed = 7 np.random.seed(seed) # load data (CSV) dataset = np.loadtxt('pima-indians-diabetes.data', delimiter=',') # split in put and output X = dataset[:, 0:8] Y = da...
[ "numpy.mean", "keras.models.Sequential", "sklearn.cross_validation.StratifiedKFold", "numpy.random.seed", "numpy.std", "keras.layers.Dense", "numpy.loadtxt" ]
[((161, 181), 'numpy.random.seed', 'np.random.seed', (['seed'], {}), '(seed)\n', (175, 181), True, 'import numpy as np\n'), ((211, 266), 'numpy.loadtxt', 'np.loadtxt', (['"""pima-indians-diabetes.data"""'], {'delimiter': '""","""'}), "('pima-indians-diabetes.data', delimiter=',')\n", (221, 266), True, 'import numpy as ...
import tinyapi from unittest import TestCase from getpass import getpass from nose.tools import raises import os DEFAULT_USERNAME = "tinyapi-test-account" USERNAME = os.environ.get("TINYAPI_TEST_USERNAME") or DEFAULT_USERNAME PASSWORD = os.environ.get("TINYAPI_TEST_PASSWORD") or getpass() class TestDraft(TestCase): ...
[ "tinyapi.Session", "os.environ.get", "nose.tools.raises", "getpass.getpass" ]
[((167, 206), 'os.environ.get', 'os.environ.get', (['"""TINYAPI_TEST_USERNAME"""'], {}), "('TINYAPI_TEST_USERNAME')\n", (181, 206), False, 'import os\n'), ((238, 277), 'os.environ.get', 'os.environ.get', (['"""TINYAPI_TEST_PASSWORD"""'], {}), "('TINYAPI_TEST_PASSWORD')\n", (252, 277), False, 'import os\n'), ((281, 290)...
#!/usr/bin/env python import vtk from vtk.test import Testing from vtk.util.misc import vtkGetDataRoot VTK_DATA_ROOT = vtkGetDataRoot() # demonstrates the use of vtkPropAssembly # create four parts: a top level assembly and three primitives # sphere = vtk.vtkSphereSource() sphereMapper = vtk.vtkPolyDataMappe...
[ "vtk.util.misc.vtkGetDataRoot", "vtk.vtkCylinderSource", "vtk.vtkPropAssembly", "vtk.vtkSphereSource", "vtk.vtkRenderWindowInteractor", "vtk.vtkRenderWindow", "vtk.vtkPolyDataMapper", "vtk.vtkActor", "vtk.vtkRenderer", "vtk.vtkConeSource", "vtk.vtkCubeSource", "vtk.vtkAssembly" ]
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import pandas as pd import dash_bootstrap_components as dbc import json from dash import Dash, html, Input, Output, dash_table as dt from dash.exceptions import PreventUpdate from dash_extensions import EventListener df = pd.read_csv("https://git.io/Juf1t") df["id"] = df.index app = Dash(external_stylesheets=[dbc.th...
[ "pandas.read_csv", "dash.html.Div", "json.dumps", "dash_extensions.EventListener", "dash.Input", "dash.Output", "dash_bootstrap_components.Alert", "dash_bootstrap_components.Label", "dash.Dash" ]
[((224, 259), 'pandas.read_csv', 'pd.read_csv', (['"""https://git.io/Juf1t"""'], {}), "('https://git.io/Juf1t')\n", (235, 259), True, 'import pandas as pd\n'), ((287, 336), 'dash.Dash', 'Dash', ([], {'external_stylesheets': '[dbc.themes.BOOTSTRAP]'}), '(external_stylesheets=[dbc.themes.BOOTSTRAP])\n', (291, 336), False...
# Generated by Django 1.10.7 on 2017-07-11 12:26 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('phonelog', '0012_server_date_not_null'), ] operations = [ migrations.DeleteModel( name='OldDeviceReportEntry', ), ]
[ "django.db.migrations.DeleteModel" ]
[((231, 282), 'django.db.migrations.DeleteModel', 'migrations.DeleteModel', ([], {'name': '"""OldDeviceReportEntry"""'}), "(name='OldDeviceReportEntry')\n", (253, 282), False, 'from django.db import migrations\n')]
from __future__ import unicode_literals import io import json import os import re from collections import OrderedDict VALID_COUNTRY_CODE = re.compile(r"^\w{2,3}$") VALIDATION_DATA_DIR = os.path.join(os.path.dirname(__file__), "data") VALIDATION_DATA_PATH = os.path.join(VALIDATION_DATA_DIR, "%s.json") FIELD_MAPPING =...
[ "re.split", "collections.OrderedDict", "os.path.exists", "re.compile", "os.path.join", "io.open", "os.path.dirname", "re.finditer", "json.load" ]
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import numpy as np import tensorflow as tf from PIL import Image import os from crawl_HHU.cfg import MAX_CAPTCHA, CHAR_SET_LEN, model_path from crawl_HHU.cnn_sys import crack_captcha_cnn, X, keep_prob from crawl_HHU.utils import vec2text, get_clear_bin_image def hack_function(sess, predict, captcha_image): """ ...
[ "tensorflow.Session", "tensorflow.train.Saver", "crawl_HHU.utils.vec2text", "numpy.array", "numpy.zeros", "crawl_HHU.cnn_sys.crack_captcha_cnn", "tensorflow.reshape", "tensorflow.train.latest_checkpoint", "crawl_HHU.utils.get_clear_bin_image" ]
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import traceback from io import StringIO from typing import Union from discord import Color, File from discord.ext.commands import Context from discord_slash.context import InteractionContext from discord_slash.error import SlashCommandError from .classes import BotPlus from .database.translation import Translation ...
[ "io.StringIO", "traceback.extract_tb", "discord.File", "discord.Color.red" ]
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