id stringlengths 3 8 | content stringlengths 100 981k |
|---|---|
3378199 | import torch
from torch.nn import functional as F
from torch.nn import Linear, Parameter, Conv1d
class AttentionBase(torch.nn.Module):
"""Abstract attention class.
Arguments:
representation_dim -- size of the hidden representation
query_dim -- size of the attention query input (probably d... |
3378213 | from sklearn.neighbors import KNeighborsClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn import preprocessing
import sqlite3 as sql
import numpy
import sys
import argparse
import time
parser = argparse.ArgumentParser(description="Classify input reads")
parser.add_argument("taxonomer_input",... |
3378249 | for i in xrange(0,10): print '??'+str(i)+'>>'+str(i)+'??'
for i in xrange(0,9): print str(i) + '??<>' + str(i+1)
print '9??>>?0\n9?>>?0'
for i in xrange(0,9): print str(i)+'?<>'+str(i+1)
print '?<>1'
for i in xrange(1,10): print str(i) + '>>' + str(i) + '??'
|
3378261 | import pytest
import torch
import torch.nn as nn
import pyro.distributions as dist
from pyro.nn import PyroModule, PyroSample
from pyro.nn.module import to_pyro_module_
import tyxe
def as_pyro_module(module):
to_pyro_module_(module, recurse=True)
for m in module.modules():
for n, p in list(m.named... |
3378264 | import sys
import signal
import os
import json
from datetime import datetime
import numpy as np
import torch
from six.moves import shlex_quote
from mpi4py import MPI
from logging import CRITICAL
from config import argparser
from config.motion_planner import add_arguments as mp_add_arguments
from rl.trainer import Tra... |
3378314 | import logging
from socket import gethostbyaddr, gethostbyname
from django.conf import settings
from django.core.cache import cache
from django.shortcuts import redirect
from ratelimit.utils import is_ratelimited
from biostar.utils import helpers
from . import util, auth
logger = logging.getLogger("engine")
def limi... |
3378323 | from rastervision.core.data.label_source import (LabelSourceConfig,
ObjectDetectionLabelSource)
from rastervision.core.data.vector_source import VectorSourceConfig
from rastervision.pipeline.config import register_config
@register_config('object_detection_label_source'... |
3378357 | import collections
EPSILON = '<empty>'
END_OF_INPUT = '<$>'
class Production(object):
"""Represents a grammar production rule."""
def __init__(self, rule, func):
items = rule.split(':', 1)
self.lhs = items[0].strip()
self.rhs = items[1].strip().split() or [EPSILON]
self.func ... |
3378361 | reader = open('test01.csv', 'r')
for line in reader:
fields = line.split(',')
print(fields)
reader.close()
|
3378364 | import inspect
import logging
import sys
from typing import Callable, Optional, Type, TypeVar
LOG = logging.getLogger("AutoClick")
EMPTY = inspect.Signature.empty
EMPTY_OR_NONE = {EMPTY, None}
GLOBAL_CONFIG = {}
T = TypeVar("T")
def set_global(name: str, value: T) -> Optional[T]:
"""
Configure global AutoCl... |
3378365 | from model.segmentation import Segmentation
from model.swin_transformer import build_model
import torch
import torch.nn as nn
import transformers
import torch.nn.functional as F
from torch import Tensor
from utils.util import load_pretrained_swin
class LVAT(nn.Module):
def __init__(self,config,logger):
sup... |
3378458 | from ..factory import Type
class jsonValueObject(Type):
members = None # type: "vector<jsonObjectMember>"
|
3378474 | import binascii
import io
from attr import dataclass
from lark.lark import Lark
from lark.visitors import Discard, Transformer
def unhex(hexdump: str) -> bytes:
"""Unparses hexdump back to binary representation.
In addition to basic parsing the following extra features are supported:
* line comments st... |
3378509 | from flask import redirect
from app.main import main
@main.route('/.well-known/security.txt', methods=['GET'])
@main.route('/security.txt', methods=['GET'])
def security_policy():
# See GDS Way security policy which this implements
# https://gds-way.cloudapps.digital/standards/vulnerability-disclosure.html#v... |
3378525 | from setuptools import setup, find_packages
import os
readme_file = os.path.join(os.path.dirname(os.path.abspath(__file__)), "README.md")
with open(readme_file, "r") as f:
readme = f.read()
ISRELEASED = True
MAJOR = 1
MINOR = 0
MICRO = 1
VERSION = f"{MAJOR}.{MINOR}.{MICRO}"
setup_dir = os.path.abspath(os.path.d... |
3378571 | from typing import Dict, Optional, Tuple, Union
import numpy as np
from autotabular.pipeline.base import DATASET_PROPERTIES_TYPE, PIPELINE_DATA_DTYPE
from autotabular.pipeline.components.base import AutotabularPreprocessingAlgorithm
from autotabular.pipeline.constants import DENSE, INPUT, SPARSE, UNSIGNED_DATA
from Co... |
3378591 | import unittest
import json
from unittest.mock import patch
from collections import namedtuple
from elasticsearch import helpers, Elasticsearch, TransportError
from flask import current_app as app
import numpy as np
import redis
from app.main import db
from app.test.base import BaseTestCase
from app.test.test_shared_m... |
3378621 | import json
import requests
from docopt import docopt
def upload_softwares(file_json, url="http://127.0.0.1:3001/api/software", ):
with open(file_json) as json_data:
softwares = json.load(json_data)
print(str(len(softwares)) + " softwares read from "+file_json )
tot_upload = 0
for... |
3378637 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
from bert import modeling
import collections
import tensorflow as tf
flags = tf.flags
FLAGS = flags.FLAGS
## Required parameters
flags.DEFINE_string(
"bert_config_file", None,
"The config j... |
3378732 | import os
import glob
import xml.etree.ElementTree as ET
import numpy
import soundfile
def main():
for f in glob.glob("*/**/*.xps"):
t = ET.parse(f)
r = t.getroot()
d = recurse_tree(r)
if not d:
continue
dirname = os.path.dirname(f)
irname = d["IRFileNam... |
3378735 | import numpy as np
import scipy.linalg as scla
from ...utils import splogdet
from pysal.spreg.utils import spdot
def logp_rho_prec(state, val):
"""
This computes the logp of the spatial parameter using the precision, rather than the covariance. This results in fewer matrix operations in the case of a SE formul... |
3378745 | import certvalidator
import pytest
from kopf._kits.webhooks import WebhookServer
def test_missing_oscrypto(no_oscrypto):
with pytest.raises(ImportError) as err:
WebhookServer.build_certificate(['...'])
assert "pip install certbuilder" in str(err.value)
def test_missing_certbuilder(no_certbuilder):
... |
3378776 | from .precheck_argus import * # noqa
from .make_gzip_file import * # noqa
from .tagutils import * # noqa
|
3378780 | import json
import type_checker
class DTODescriptor:
__slots__ = "_immutable", "_type", "_field", "_validator", "_dto_class_name", "_coerce"
def __init__(self, dto_class_name: str, field: str, type_: type, immutable: bool = True,
validator: callable = None, coerce: callable = None):
... |
3378801 | import numpy as np
import chainer
import os
import glob
from chainer import cuda, optimizers, serializers, Variable
import cv2
from .datasets_base import datasets_base
class mnist_train(datasets_base):
def __init__(self, path=None, img_size=64):
self.train, _ = chainer.datasets.get_mnist(withlabel=False, ... |
3378866 | from setuptools import setup, find_packages
setup(
name='oregami',
version='1.0.0',
packages=find_packages(),
url='https://github.com/shemesh999/oregami',
license='MIT',
author='<NAME>',
description='IDA plugins and scripts for analyzing register usage frame',
install_requires=[
... |
3378885 | import torch
import torchvision
import numpy as np
import time
def get_batch(bs=1):
loader = torch.utils.data.DataLoader(
torchvision.datasets.MNIST('./../data/MNIST/', train=False, download=True,
transform=torchvision.transforms.ToTensor()),
batch_size=bs, shuffle=Tru... |
3378886 | import unittest
from katas.kyu_7.filter_unused_digits import unused_digits
class UnusedDigitsTestCase(unittest.TestCase):
def test_equals(self):
self.assertEqual(unused_digits(12, 34, 56, 78), '09')
def test_equals_2(self):
self.assertEqual(unused_digits(2015, 8, 26), '3479')
def test_e... |
3378909 | import tensorflow as tf
import numpy as np
import time
def relu(inputs):
return tf.nn.relu(inputs)
class model():
def conv2d(self, inputs, name, out_channels, act=relu, ksize=3):
with tf.variable_scope(name):
in_channels = inputs.get_shape()[-1]
filter = tf.get_variable('weig... |
3378913 | import unittest
import numpy as np
import tensorflow as tf
from nose.tools import assert_true
from sklearn.metrics import roc_curve, auc
import deepchem as dc
from deepchem.data import NumpyDataset
from deepchem.data.datasets import Databag
from deepchem.models.tensorgraph.layers import Dense, SoftMaxCrossEntropy, Re... |
3378914 | class NodeNotes(object):
"""
The class adds the support to the notes dynamic attribute.
"""
def __init__(self):
pass
def getNotes(self):
pass
def setNotes(self, string):
pass
__dict__ = None
__weakref__ = None
_... |
3378921 | from boa3.builtin.type import UInt160
class Policy:
@classmethod
def get_fee_per_byte(cls) -> int:
"""
Gets the network fee per transaction byte.
:return: the network fee per transaction byte
:rtype: int
"""
pass
@classmethod
def get_exec_fee_factor(cl... |
3378931 | import re
def migrate(resource):
return isced_to_object(resource)
def isced_to_object(resource):
for property in resource.keys():
if property in ["audience", "about"]:
print "Migrating " + property + " for " + resource["@id"]
objects = []
for string in resource[pro... |
3378945 | from __future__ import print_function
import numpy as np
import time
import data_util
weight_names = ["w_in", "b_in", "w_out", "b_out",
"rnn/multi_rnn_cell/cell_0/basic_lstm_cell/weights",
"rnn/multi_rnn_cell/cell_0/basic_lstm_cell/biases",
"rnn/multi_rnn_cell/cell_1/bas... |
3378967 | from os import walk, path, unlink
import pickle
import datetime
from drkns.context.get_unit_step_path import persistence_directory, extension
from drkns.stepexecutionstatus.StepExecutionStatus import StepExecutionStatus
def clean_persistence_files():
if not path.exists(persistence_directory):
return
... |
3378970 | from django.conf.urls import include, url
from . import views
urlpatterns = [
url(r'^accounts/ClientLogin$', views.login, name='login'),
url(r'^reader/api/0/', include('feedhq.reader.api_urls')),
url(r'^reader/atom/(?P<content_id>.+)?$', views.stream_contents,
{'output': 'atom'}, name='atom_conte... |
3379016 | import dicom
from numpy import *
import SimpleITK as sitk
import os
def read_ct_scan(path, verbose=False):
# type: (object) -> object
# Read the slices from the dicom file
slices = []
if os.path.isfile(path):
try:
return sitk.ReadImage(path)
except:
if verbose:
... |
3379037 | import numpy as np
from pyecsca.sca import Trace, match_pattern, match_part, pad
from .utils import Plottable
class MatchingTests(Plottable):
def test_simple_match(self):
pattern = Trace(
np.array([1, 15, 12, -10, 0, 13, 17, -1, 0], dtype=np.dtype("i1")), None
)
base = Trace(
... |
3379110 | import pathlib
import shutil
import pytest
import uqbar.io
@pytest.fixture
def rm_dirs(app):
for path in [pathlib.Path(app.doctreedir), pathlib.Path(app.outdir) / "_images"]:
if path.exists():
shutil.rmtree(path)
yield
@pytest.mark.sphinx("html", testroot="book")
def test_sphinx_book_ht... |
3379112 | import os
import itertools
import subprocess
import argparse
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument('--act_class', type=str)
parser.add_argument('--num_threads', type=int)
return parser.parse_args()
timeout = 60 * 60 * 24 * 3
args = parse_args()
num_thread = args.nu... |
3379142 | import os
import rospy
import math
import sys
from glob import glob
from sensor_msgs.msg import PointCloud2, PointField
import std_msgs.msg
import sensor_msgs.point_cloud2 as pcl2
import numpy as np
import pickle
from pathlib import Path
import pykitti
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import ... |
3379149 | from setuptools import setup
from setuptools import find_packages
setup(name='estim2b',
version='0.2',
description='Unofficial Python API for E-stim 2B',
author='<NAME>',
author_email='<EMAIL>',
url='https://github.com/fredhatt/estim2b',
license='MIT',
install_requires=['nump... |
3379157 | import torch
import torch.nn as nn
import torch.nn.functional as F
from .basics import SpectralConv3d
class FNN3d(nn.Module):
def __init__(self, modes1, modes2, modes3, width=16, fc_dim=128, layers=None, in_dim=4, out_dim=1):
'''
Args:
modes1: list of int, first dimension maximal mode... |
3379163 | from test_junkie.decorators import Suite, test
from tests.junkie_suites.TestListener import TestListener
@Suite(listener=TestListener)
class ErrorSuite3:
@test(parameters={1, 2})
def test_1(self, parameter):
pass
|
3379168 | from mlapp.main import MLApp
from mlapp.config import settings
import pandas as pd
if __name__ == "__main__":
config = {
'handler_name': 'handler',
'files': [{
'table_name': 'table',
'file_name': 'file_name.csv'
}]
}
mlapp = MLApp({'env_file_path': 'path/to/... |
3379172 | import copy
import sys
import tornado.httputil
from asgiref.sync import sync_to_async
from furl import furl
from onelogin.saml2.errors import OneLogin_Saml2_Error
from onelogin.saml2.idp_metadata_parser import OneLogin_Saml2_IdPMetadataParser
from consoleme.config import config
from consoleme.config.config import dic... |
3379197 | import sys
from functools import wraps
from strange_case.registry import Registry
def provides(conf):
def decorator(function):
@wraps(function)
def wrapper(source_file, config):
if conf not in config:
return function(source_file, config)
return config
... |
3379210 | from math import pow
while True:
h0, num_workers = list(map(int, input().split()))
if h0 == num_workers == 0:
break
if h0 == num_workers:
v1, v2 = 0, h0
else:
N = -1
for k in range(1, 32):
n = pow(num_workers, 1/k)
N = int(n)
if N**k == num_workers:
if (N+1)*... |
3379243 | import os
import threading
import time
import yarntf
def cluster_spec_test():
"""Assumes ClusterSpecGeneratorServer is running"""
threads = []
os.environ['TENSORBOARD'] = 'true'
for i in range(0, 3):
os.environ['TB_DIR'] = 'tensorboard_' + str(i)
thread = threading.Thread(target=yarntf.createCluster... |
3379273 | import pytest
import pygamma_agreement as pa
from pyannote.core import Segment
def test_errors_continuum():
continuum = pa.Continuum()
with pytest.raises(ValueError):
cat_dissim = pa.LevenshteinCategoricalDissimilarity(continuum.categories)
cat_dissim = pa.AbsoluteCategoricalDissimilarity()
... |
3379332 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
from .scale import scale
from copy import deepcopy
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap, rgb2hex, ColorConverter
def colors_at_breaks(cmap, breaks=[0, 0.25, 0.5... |
3379347 | import numpy as np, tensorflow as tf, aolib.util as ut, aolib.img as ig, os
import tensorflow.contrib.slim as slim
import tensorflow.contrib.slim.nets as nets
import vgg, h5py
import sklearn.metrics
pj = ut.pjoin
class Params(ut.Struct):
def __init__(self, **kwargs):
self.__dict__.update(kwargs)
@property
... |
3379351 | import random
import mimetypes
import urllib.request
import json
def uploadFile(url, path, post_field):
boundary = '-----------------' + str(random.randint(1, 1000000000000000000))
parts = []
parts.append('--' + boundary)
parts.append('Content-Disposition: form-data; name="{}"; filename="file.jpg"'.for... |
3379420 | import unittest
import logging
import numpy as np
import pandas as pd
import diffxpy.api as de
class _TestSingleFullRank(unittest.TestCase):
def _test_single_full_rank(self):
"""
Test if de.wald() generates a uniform p-value distribution
if it is given data simulated based on the null mo... |
3379421 | import pytest
import torch
from espnet2.enh.loss.criterions.tf_domain import FrequencyDomainL1
from espnet2.enh.loss.wrappers.fixed_order import FixedOrderSolver
@pytest.mark.parametrize("num_spk", [1, 2, 3])
def test_PITSolver_forward(num_spk):
batch = 2
inf = [torch.rand(batch, 10, 100) for spk in range(n... |
3379433 | import sys
CAFFE_ROOT = '../../../caffe/'
sys.path.insert(0, CAFFE_ROOT + 'python')
import caffe
caffe.set_mode_gpu()
NUM_DATA = {}
NUM_DATA['TRAIN'] = 10000
NUM_DATA['VAL'] = 1000
NUM_DATA['TEST'] = 1000
RAND_SEED = {}
RAND_SEED['TRAIN'] = 19654
RAND_SEED['VAL'] = 2353
RAND_SEED['TEST'] = 51235
|
3379463 | from garnett.fields import TranslatedField
def patch_compare():
from reversion_compare.compare import CompareObjects as COBase
class CompareObjects(COBase):
def __init__(self, field, field_name, obj, version1, version2, is_reversed):
if isinstance(field, TranslatedField):
... |
3379503 | import sys
import bayesnewton
import objax
from bayesnewton.cubature import Unscented
import numpy as np
import matplotlib.pyplot as plt
import time
from scipy.io import loadmat
import pickle
print('loading data ...')
y = loadmat('speech_female')['y']
fs = 44100 # sampling rate (Hz)
scale = 1000 # convert to millise... |
3379505 | from __future__ import annotations
from typing import Callable, Generic, TypeVar
T = TypeVar("T")
U = TypeVar("U")
class DoubleLinkedListNode(Generic[T, U]):
"""
Double Linked List Node built specifically for LRU Cache
>>> DoubleLinkedListNode(1,1)
Node: key: 1, val: 1, has next: False, has prev: F... |
3379539 | import bugsnag
from django.shortcuts import render
from django.http import HttpResponseRedirect, HttpResponse
from django.views import generic
from django.utils import timezone
from django.urls import reverse
from .models import Note
class IndexView(generic.ListView):
template_name = 'notes/index.html'
cont... |
3379554 | import json
import uuid
import httpretty
import pytest
from mock import patch
from lecli.log import api
ID_WITH_VALID_LENGTH = str(uuid.uuid4())
MOCK_API_URL = 'http://mydummylink.com'
LOG_RESPONSE = {
"log" : {
"id" : "XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX",
"name" : "Test Log",
"logsets... |
3379586 | from .chat import Chat
from .chats import Chats
from .friend import Friend
from .group import Group
from .groups import Groups
from .member import Member
from .mp import MP
from .user import User
|
3379598 | from tkinter import *
from tkinter import messagebox
import random
import time
unsorted_data = data = []
def draw_data(data, colors):
""""
Function that is used to draw the array of data
Inputs:
data => array of the data to be drawn
colors => array carrying the corresponding color of each value ... |
3379600 | from lxml import etree
from zipfile import ZipFile
from string import lstrip
from common import wSPar, NSM, NSW, Body, Document, wText, setx
import ct
_pd = dict()
def xdoc(nd):
setx(nd, Document, Document)
ct.cnl(nd)
def xdocument(nd):
setx(nd, Body, Body)
ct.cnl(nd)
def save(name):
zf = Z... |
3379634 | import csv
import config
import os as os
# Read the metadata of LibriSpeech dataset
# Put them in a dictionnary with the following structure
# {
# [speaker_key:{'sex':M/F, 'chapters':[(int), ...]}, ..., speaker_key:{..},]
# }
def read_metadata(subset_name=config.data_subset):
metadata = {}
path_speake... |
3379679 | from markupsafe import Markup
import heroicons
def heroicon_outline(name: str, *, size: int = 24, **kwargs: object) -> str:
return _render_icon("outline", name, size, **kwargs)
def heroicon_solid(name: str, *, size: int = 20, **kwargs: object) -> str:
return _render_icon("solid", name, size, **kwargs)
de... |
3379730 | from mojo.roboFont import CurrentFont
from glyphConstructionController import GlyphBuilderController
GlyphBuilderController(CurrentFont())
|
3379773 | from __future__ import division, print_function
import fileinput
import re
import itertools
from collections import defaultdict
pattern = re.compile("(\w+) can fly (\d+) km\/s for (\d+) seconds, but then must rest for (\d+) seconds.")
runners = defaultdict(lambda: 0)
runnerData = {}
runnerPoints = defaultdict(lambda:... |
3379774 | import time
import plot_confusion_matrix
START_TIME = None
STOPPED = False
def start_measurement():
global START_TIME
START_TIME = time.time()
def stop_measurement():
global STOPPED, START_TIME
if not STOPPED:
elapsed_seconds = time.time() - START_TIME
m, s = divmod(elapsed_seconds,... |
3379795 | import os
import torch
from collections import OrderedDict
from PIL import Image
import numpy as np
from matplotlib import pyplot as plt
import sys
from torch.nn.functional import upsample
this_dir = os.path.dirname(__file__)
sys.path.insert(0, 'dextr')
import networks.deeplab_resnet as resnet
from dataloaders import h... |
3379815 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
'''
This is the models of TSception and its variant
To use the models, please manage the data into
the dimension of(mini-batch, 1, EEG-channels,data point)
before feed the data into forward()
For more d... |
3379872 | from .fc import FC as FullyConnectedClassifier
from .rnn import RNNClassifier
from .bert_hf import BERT
__all__ = ["FullyConnectedClassifier", "RNNClassifier", "BERT"]
|
3379905 | from setuptools import setup
exec (open('dash_resumable_upload/version.py').read())
setup(
name='dash_resumable_upload',
version=__version__,
author='marrenr',
packages=['dash_resumable_upload'],
include_package_data=True,
license='MIT',
description='Dash Resumable Upload component for lar... |
3379964 | import os
import shutil
from nose.tools import assert_raises
from paradrop.lib.utils import pdos, pdosq
from paradrop.base import nexus, settings
class TestingNexus(nexus.NexusBase):
pass
def setup():
settings.loadSettings(mode="unittest")
def teardown():
pdos.remove(settings.CONFIG_HOME_DIR)
#####... |
3379990 | import sys, time
import time
from collections import namedtuple
import mxnet as mx
import numpy as np
def evaluate_model(cnn_model, batch_size,
max_grad_norm, learning_rate,
epoch, x_train, y_train, x_dev,
y_dev):
'''
Train the cnn_model using back pro... |
3380002 | import time
import inspect
from functools import update_wrapper
from fixate.core.common import mode_builder, unit_scale
from fixate.core.exceptions import ParameterError, InstrumentError
from fixate.drivers.funcgen.helper import FuncGen
MODES = {
":SINusoid": {
" [{frequency}]": {",[{amplitude}]": {",[{off... |
3380015 | import torch.nn as nn
import torch.nn.functional as F
class TransformMatrix(nn.Module):
def __init__(self, input_dim, output_dim):
super(TransformMatrix, self).__init__()
self.fc = nn.Linear(in_features=input_dim, out_features=output_dim, bias=False)
# self.fc.apply(init_weights)
def ... |
3380063 | import os
import sys
sys.path.insert(1, os.path.dirname(os.path.realpath(__file__)) + '/../')
from common import utils
import models
from common.log import log, LogLevel
from common.state import State
from common import cuda
from common import paths
import common.torch
import common.numpy
from training import train_cla... |
3380094 | import requests
from urllib.parse import urlparse
class CFProxy:
TOKEN_HEADER = 'Px-Token'
TOKEN_VALUE = '<PASSWORD>'
HOST_HEADER = 'Px-Host'
IP_HEADER = 'Px-IP'
def __init__(self, proxy_host, ua, fake_ip, proxy=None):
self.session = requests.Session()
self.session.proxies.update(... |
3380126 | import asyncio
import json
import logging
import os
import re
import shutil
import string
from collections import Counter
from dataclasses import dataclass, asdict, field
from random import random
from typing import List, Optional, Dict, Generator
import aiofiles
import github
import time
import github_util
git_hub ... |
3380136 | import json as jsonlib
from html import unescape
from django import template
from django.template import engines, TemplateSyntaxError
from django.template.base import NodeList, token_kwargs
from django.template.defaulttags import IfNode
from django.template.loader import get_template
from django.template.loader_tags i... |
3380142 | from __future__ import print_function
from django.core.management.base import BaseCommand
from django.utils.translation import ugettext_lazy
from odk_logger.models import XForm
class Command(BaseCommand):
help = ugettext_lazy('Repair submission counts for all users')
def handle(self, *args, **kwargs):
... |
3380164 | from datetime import datetime
from recurrence import Recurrence, Rule
import recurrence
RULE = Rule(
recurrence.DAILY
)
PATTERN = Recurrence(
rrules=[RULE]
)
def test_between_without_dtend_and_dtstart():
occurrences = [
instance for instance in
PATTERN.between(
datetime(2014... |
3380186 | INSTALL_WINDOWS_AGENT = """
# download the cloud endure agent
Invoke-WebRequest -Uri https://console.cloudendure.com/installer_win.exe -OutFile C:\installer_win.exe
# install the agent, and configure it using your account's agent installation token.
C:\installer_win.exe -t "{{ agent_installation_token }}" --no-prompt
... |
3380271 | data_dir_test = data_dir+'test/'
N_test = len(os.listdir(data_dir_test+"/test"))
test_datagen = kpi.ImageDataGenerator(rescale=1. / 255)
test_generator = test_datagen.flow_from_directory(
data_dir_test,
#data_dir_sub+"/train/",
target_size=(img_height, img_width),
batch_size=batch_size,
class_mode... |
3380275 | from core.agent.reinforce import REINFORCE
from .utils import check_interact, check_save_load, check_sync_in_out
def test_discrete_reinforce(MockEnv):
state_size, action_size, action_type = 2, 3, "discrete"
episode_len = 10
env = MockEnv(state_size, action_size, action_type, episode_len)
hidden_size ... |
3380304 | import re
PRIVILEGED_STATEMENT_RULES = {
"\*:\*": "Full AWS Account Admin",
"^[A-Za-z0-9]+:\*$": "Full {service} Admin"
}
FIND_SERVICE_REGEX = "^([A-Za-z0-9]+)(?=:)"
RESOURCE_ARN_WITH_SERVICE_REGEX = "^arn:aws(-cn|):{service}:.+"
class PoliciesPermissionsParser(object):
def __init__(self, policies):
... |
3380339 | from kivy.properties import BooleanProperty
from kivy.properties import (
NumericProperty,
)
from kivymd.color_definitions import colors
from kivymd.uix.behaviors.toggle_behavior import MDToggleButton
from kivymd.uix.button import MDFloatingActionButton, \
MDRoundFlatIconButton, \
MDRectangleFlatButton
fro... |
3380362 | import torch
import numpy as np
import itertools
"""
Qnt: Quantization Methods. this collection of methods, compute the quantization tables for RGB, and LAB color space.
These methods are organized in a way that each bin is recognized by its central value.
ES: RGB 0-255
2 levels of quantization for each channel
... |
3380394 | from taskutils import task
import logging
import math
def TaskTest1():
def Go():
@task
def Length(inp):
logging.info("Post, Length: %s" % len(inp))
for exponent in range(3):
length = int(math.pow(10, exponent + 5))
logging.info("Pre, Length: ... |
3380411 | def readposint():
while True:
try:
a = int(input("Please enter a positive integer: "))
if a <= 0:
print("Non-positive integers are not allowed")
else:
break
except ValueError as e:
print(e)
print("The positive integer ... |
3380436 | import unittest
import functools
import numpy as np
import pandas as pd
import scipy.signal
from spatial_lda import featurization
def make_grid_df(neighborhood_data, make_all_cells_anchors=False):
n, m, k = neighborhood_data.shape
xs, ys = np.meshgrid(range(n), range(n))
xs = xs.flatten()
ys = ys.fla... |
3380449 | from core.advbase import *
class Veronica(Adv):
comment = "last destruction teambuff not considered"
def prerun(self):
if not self.nihilism:
SingleActionBuff("last_destruction", 0.1, 1, "s").on()
variants = {None: Veronica}
|
3380523 | import os
import shutil
import pytest
import unittest
if os.name == "posix":
TMPDIR = "/tmp/"
else:
TMPDIR = "%TMP%"
if not os.environ.get("TRAVIS") == "true":
from pyveg.src.download_modules import VegetationDownloader, WeatherDownloader
@unittest.skipIf(os.environ.get("TRAVIS") == "true", "Skipping t... |
3380545 | from __future__ import annotations
from dataclasses import InitVar, dataclass
import re
from typing import Callable, ClassVar, Dict, List, Optional, Union
import ibis
from ibis.expr.types import AnyColumn, AnyScalar, TableExpr, ValueExpr
from lark import Tree
from pandas import Series
from sql_to_ibis.sql.column_uti... |
3380556 | from dataclasses import dataclass
from .base import BasePosition
from .types import Literal
@dataclass
class Namespace(BasePosition):
type: Literal["namespace"] = "namespace"
|
3380565 | import re
from typing import cast
def replace_colons(text: str, strip: bool = False) -> str:
"""Parses a string with colon encoded emoji and renders found emoji.
Unknown emoji are left as is unless `strip` is set to `True`
:param text: String of text to parse and replace
:param strip: Whether to stri... |
3380577 | import torch
import torch.nn as nn
class MLP(torch.nn.Module):
def __init__(self, out_features, in_features, hidden_layer_size, output_nonlinearity):
super().__init__()
self.fc1 = nn.Linear(in_features=in_features, out_features=hidden_layer_size)
self.fc2 = nn.Linear(in_features=hidden_lay... |
3380580 | import unittest
import mock
from pyhive.presto import Cursor, Connection
from pyhive.exc import DatabaseError
from luigi.contrib.presto import PrestoTask, PrestoClient, PrestoTarget
class WithPrestoClientTest(unittest.TestCase):
def test_creates_client_with_expected_params(self):
# arrange
class... |
3380617 | workclass_map = {"Not in universe": "None",
"Private": "Private",
"Self-employed-not incorporated": "Self-emp-not-inc",
"Local government": "Local-gov",
"State government": "State-gov",
"Self-employed-incorporated": "Self-emp-inc",
... |
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