id stringlengths 3 8 | content stringlengths 100 981k |
|---|---|
1636185 | print 50
cnt = 1
for i in xrange(50):
for j in xrange(50):
if i == j: print 0,
else:
print cnt,
cnt += 1
print
|
1636188 | import unittest
from followthemoney.types import registry
numbers = registry.number
class NumberTest(unittest.TestCase):
def test_cast_num(self):
self.assertEqual(numbers.to_number("1,00,000"), 100000.0)
self.assertEqual(numbers.to_number(" -999.0"), -999.0)
self.assertEqual(numbers.to_n... |
1636289 | import pytest
from pynamodb.pagination import RateLimiter
class MockTime():
def __init__(self):
self.current_time = 0.0
def sleep(self, amount):
self.current_time += amount
def time(self):
return self.current_time
def increment_time(self, amount):
self.current_time +... |
1636302 | import tensorflow as tf
def last_relevant_output(output, sequence_length):
"""
Given the outputs of a LSTM, get the last relevant output that
is not padding. We assume that the last 2 dimensions of the input
represent (sequence_length, hidden_size).
Parameters
----------
output: Tensor
... |
1636309 | src = Split('''
system_stm32f4xx.c
STM32F4xx_StdPeriph_Driver/src/misc.c
STM32F4xx_StdPeriph_Driver/src/stm32f4xx_adc.c
STM32F4xx_StdPeriph_Driver/src/stm32f4xx_can.c
STM32F4xx_StdPeriph_Driver/src/stm32f4xx_crc.c
STM32F4xx_StdPeriph_Driver/src/stm32f4xx_dac.c
STM... |
1636330 | from .Grammars import reference_patterns
from .dictionary import wordlist_english
import logging
import re
REFERENCE_PREFIX = "REF_"
strip_table = str.maketrans("", "", "(){}<>[]")
strip_table = str.maketrans("", "", "(){}<>[].,!;?")
class separate_reference:
"""
Detects if a reference number has been mista... |
1636358 | import riemann
import unittest
from riemann import tx
from riemann import utils
from riemann.tests import helpers
class TestOutpoint(unittest.TestCase):
def setUp(self):
pass
def test_create_outpoint(self):
outpoint_index = helpers.P2PKH1['ser']['ins'][0]['index']
outpoint_tx_id = he... |
1636374 | import argparse
import json
import os
from collections import defaultdict
def get_datasets(args):
datasets = []
for _, _, dataset in args.input:
if dataset not in datasets:
datasets.append(dataset)
return datasets
def get_metrics(args):
metrics = []
for _, metric, _ in args.i... |
1636414 | from river import stream
from . import base
class SMTP(base.RemoteDataset):
"""SMTP dataset from the KDD 1999 cup.
The goal is to predict whether or not an SMTP connection is anomalous or not. The dataset only
contains 2,211 (0.4%) positive labels.
References
----------
[^1]: [SMTP (KDDCUP9... |
1636438 | import yaml
import six
script_out = """all:
children:
ungrouped:
hosts:
foobar:
should_be_artemis_here: !vault |
$ANSIBLE_VAULT;1.2;AES256;alan
30386264646430643536336230313232653130643332356531633437363837323430663031356364
383631393564303830626361363... |
1636439 | import platform
import numpy as np
import pytest
import qtpy
from napari.layers import Labels, Points
from qtpy.QtCore import QCoreApplication
from PartSeg._roi_analysis.image_view import ResultImageView
from PartSeg.common_backend.base_settings import BaseSettings
from PartSeg.common_gui.channel_control import Chann... |
1636476 | import torch
import torch.nn as nn
import torch.nn.functional as F
class AGNewsmodelWrapper(nn.Module):
def __init__(self, model):
super(AGNewsmodelWrapper, self).__init__()
self.model = model
def compute_bert_outputs( # pylint: disable=no-self-use
self, model_bert, embedding_input, ... |
1636491 | from typing import List, Iterable, Mapping
from .common import write_varint, sha256
NIL = bytes([0] * 32)
def floor_lg(n: int) -> int:
"""Return floor(log_2(n)) for a positive integer `n`"""
assert n > 0
r = 0
t = 1
while 2 * t <= n:
t = 2 * t
r = r + 1
return r
def ceil_... |
1636496 | import sys, os
sys.path.insert(0, os.path.abspath('.') + '/_extensions')
project = 'Project Bureau'
copyright = '2019-2020, whitequark'
master_doc = 'index'
rst_epilog = """
.. |o| raw:: html
<i class="fa fa-times" style="display:block;text-align:center;color:darkred;"></i>
.. |x| raw:: html
<i cla... |
1636537 | def arrange_number(a, b):
if a>b:
s=b
else:
s=a
for i in range(1, s+1):
if a%i==0 and b%i==0:
result=i
return result
m=int(input())
n=int(input())
print(arrange_number(m,n))
|
1636576 | class AudioNetwork:
"""Create a generic audio network"""
def set_volume(self, volume):
raise NotImplemented("Not implemented")
def volume(self):
raise NotImplemented("Not implemented")
def speakers(self):
"""Return a list of available devices"""
raise NotImplemented("Not ... |
1636586 | import discord
import collections
import operator
import random
import asyncio
import datetime
import uuid
from queue import Queue
from redbot.core import Config
from redbot.core import commands
from redbot.core import checks
from redbot.core.utils.predicates import ReactionPredicate
from redbot.core.utils.menus impor... |
1636671 | import torch.nn as nn
class SubCellFNN(nn.Module):
# in 10 states and a binary classification into membrane-bound vs. soluble
def __init__(self, use_batch_norm=True):
super(SubCellFNN, self).__init__()
# Linear layer, taking embedding dimension 1024 to make predictions:
if use_batch_no... |
1636685 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
from kubernetes import client, config
from kubernetes.client.rest import ApiException
from kubernetes.stream import stream
class K8sController():
def __init__(self, kube_config=None):
i... |
1636690 | import mtalg
def get_num_threads():
"""Get number of threads for MRNGs and algebra functions
Args:
num_threads: Number of threads
"""
return mtalg.core.threads._global_num_threads
|
1636702 | import matplotlib.pyplot as plt
import matplotlib.animation as animation
import pandas as pd
import time
NUM_NAMESPACES = 1
TOTAL_GOAL_PODS = 10001
GOAL_PODS = TOTAL_GOAL_PODS/NUM_NAMESPACES
fig = plt.figure()
ax1 = fig.add_subplot(2,1,1)
ax2 = fig.add_subplot(2,1,2)
time_elapsed_text = ax2.text(0.1, 0.25, '', fonts... |
1636735 | import os
import sys
import traceback
from zlib import compress, decompress, error as zlib_error
from cmemcached_imp import *
import cmemcached_imp
import threading
_FLAG_PICKLE = 1 << 0
_FLAG_INTEGER = 1 << 1
_FLAG_LONG = 1 << 2
_FLAG_BOOL = 1 << 3
_FLAG_COMPRESS = 1 << 4
_FLAG_MARSHAL = 1 << 5
VERSION = "0.41-green... |
1636748 | import subscription.signals
def impossible_downgrade(sender, subscription, **kwargs):
before = sender.subscription
after = subscription
if not after.price:
if before.price: return "You cannot downgrade to a free plan."
else: return None
if before.recurrence_unit:
if not... |
1636753 | import scrapy
import logging
from scrapy.crawler import CrawlerProcess
logging.getLogger('scrapy').propagate = False
class Cloner(scrapy.Spider):
name = "test"
custom_settings ={
'LOG_ENABLED': False
}
def parse(self, response):
#filename = response.url.split("/")[-1] + '.html'
with open... |
1636777 | import requests
import pandas as pd
from bs4 import BeautifulSoup
import numpy as np
import datetime
pd.set_option('display.expand_frame_repr', False)
import re
def get_financial_statements(code):
# 인증값 추출
re_enc = re.compile("encparam: '(.*)'", re.IGNORECASE)
re_id = re.compile("id: '([a-zA-Z0-9]*)'... |
1636782 | import torch
import os
import random
from torch.utils.data import Dataset
from PIL import Image
import numpy as np
import sys
import json
from glob import glob
from PIL import ImageDraw
from misc.mask_utils import scatterMask
from misc.utils import denorm
import glob
from scipy.io import loadmat
from tqdm import tqdm
m... |
1636789 | from __future__ import absolute_import
from . import backend
from . import datasets
from . import layers
from . import preprocessing
from . import utils
from . import wrappers
from . import callbacks
from . import constraints
from . import initializers
from . import metrics
from . import losses
from . import optimizers... |
1636816 | import random
from jinja2 import Environment, PackageLoader
env = Environment(loader=PackageLoader('generate_test', '.'))
template = env.get_template('template.jinja')
def answer(n):
s = 0
p = 0
n = str(n)
for c in n:
if int(c) % 2 == 1:
s += 1
if p == 0:
... |
1636854 | import attr
@attr.s(slots=True)
class Booking:
id: int = attr.ib()
name: str = attr.ib()
is_active: bool = attr.ib()
asdict = attr.asdict
|
1636863 | from photons_app.errors import ApplicationCancelled, ApplicationStopped
from photons_app.errors import UserQuit
from photons_app import helpers as hp
import platform
import asyncio
import logging
import signal
import sys
log = logging.getLogger("photons_app.tasks.runner")
class Runner:
def __init__(self, task, ... |
1636876 | from networkx.algorithms.assortativity import *
from networkx.algorithms.asteroidal import *
from networkx.algorithms.boundary import *
from networkx.algorithms.bridges import *
from networkx.algorithms.chains import *
from networkx.algorithms.centrality import *
from networkx.algorithms.chordal import *
from networkx.... |
1636940 | import click
import src.cli.console as console
from src.cli.context import show_context
from src.graphql import GraphQL
from src.local.providers.helper import get_cluster_or_exit
from src.local.system import Telepresence
from src.storage.user import get_local_storage_user
@click.command()
@click.pass_obj
def ps(ctx,... |
1636941 | from datetime import datetime
from django.db.models import Count
import olympia.core.logger
from olympia.amo.celery import task
from olympia.amo.decorators import use_primary_db
from .models import Collection, CollectionAddon
log = olympia.core.logger.getLogger('z.task')
@task
@use_primary_db
def collection_met... |
1636942 | from collections import defaultdict
class Solution(object):
def longestPalindrome(self, s):
"""
:type s: str
:rtype: str
"""
# A char -> [list of indice]
matrix = defaultdict(bool)
result = ""
# initialize
for i in range(len(s)):
... |
1636949 | from numba import jit
import numpy as np
import cv2
random = np.array(np.power(np.random.rand(16, 8, 3), 3) * 255, dtype=np.uint8)
class Camera:
def _resize_frame(self, frame, dst, flip=0):
frame_shape = np.shape(frame)
frame_crop_height = int(frame_shape[1] / self._ratio)
crop_offset = (... |
1636966 | from django.db import models
from django.contrib.contenttypes.fields import GenericForeignKey
from django.contrib.contenttypes.models import ContentType
# Create your models here.
class Feature(models.Model):
object_content_type = models.ForeignKey(ContentType, related_name='features', on_delete=models.CASCADE)
... |
1636974 | import nbformat as nbf
from astropy.table import Table
#oof = nbf.read('magical_transofrms.ipynb', as_version=4)
# gool = '06.01-Initial-reduction.ipynb'
gool = 'magical_transofrms.ipynb'
def markdown_cells(nb):
"""
Iterator for markdown cells in notebook.
"""
for cell in nb['cells']:
if cel... |
1636980 | import os
import sys
STRICTDOC_ROOT_PATH = os.path.abspath(
os.path.join(__file__, "../../../../strictdoc")
)
assert os.path.exists(STRICTDOC_ROOT_PATH), "does not exist: {}".format(
STRICTDOC_ROOT_PATH
)
sys.path.append(STRICTDOC_ROOT_PATH)
|
1636993 | import unittest
import unittest.mock
from programy.clients.render.html import HtmlRenderer
class MockHtmlBotClient(object):
def __init__(self):
self._response = None
self.configuration = unittest.mock.Mock()
self.configuration.host = "127.0.0.1"
self.configuration.port = "6666"
... |
1637002 | import sys, cgi
import glob
import re
import keyword, token, tokenize
import string, cStringIO, StringIO
SIKULI_KEYWORDS = [
"find", "wait",
"click", "clickAll", "repeatClickAll", "doubleClick",
"doubleClickAll", "repeatDoubleClickAll", "rightClick",
"dragDrop", "type", "sleep", "popup", "capture", "input"... |
1637011 | from enum import Enum
from typing import Generator, NamedTuple
import pytest
from pms import SensorWarning
from pms.core import Sensor, Supported
@pytest.mark.parametrize("sensor", Supported)
@pytest.mark.parametrize("attr", ["Message", "Data", "Commands"])
def test_sensor_attrs(sensor, attr):
assert getattr(Se... |
1637026 | import logging
from celery import current_app
from django_celery_beat.schedulers import ModelEntry, DatabaseScheduler
from nautobot.extras.models import ScheduledJob, ScheduledJobs
logger = logging.getLogger(__name__)
class NautobotScheduleEntry(ModelEntry):
"""
Nautobot variant of the django-celery-beat ... |
1637035 | from setuptools import setup, Extension, find_packages
setup(name='gitgud',
version='1.1',
author='<NAME>',
author_email="<EMAIL>",
description="Git Gud - a utility for when you are told to 'get good'",
url="https://github.com/fsufitch/git-gud",
package_dir={'':'src'},
package... |
1637048 | import os
import unittest
import yaml
from jsonasobj import as_json
from biolinkml.meta import SchemaDefinition
from biolinkml.utils.rawloader import load_raw_schema
from biolinkml.utils.yamlutils import DupCheckYamlLoader, as_yaml
from tests.test_utils.environment import env
from tests.utils.test_environment import ... |
1637080 | from pytg import sender
from pytg.exceptions import IllegalResponseException
import os
import logging
import yaml
import datetime
import time
logging.basicConfig(level=logging.INFO)
# Ugly hack: increate timeout for document reception
# Sub hack: use a list to assign a new value
tmp_f = list(sender.functions["load_d... |
1637084 | import torch
import torch.nn.functional as F
import torch.nn as nn
from IPython import embed
class CrossE_Loss(nn.Module):
def __init__(self, args, model):
super(CrossE_Loss, self).__init__()
self.args = args
self.model = model
def forward(self, score, label):
pos = torch.log(... |
1637106 | from product_details import product_details
def get_product_details_history():
sections = [
(u'Firefox', 'firefox_history_development_releases'),
(u'Firefox', 'firefox_history_major_releases'),
(u'Firefox', 'firefox_history_stability_releases'),
(u'Firefox for Android', 'mobile_his... |
1637107 | from dataclasses import dataclass
from typing import Tuple, List, Optional, Any
import numpy as np
import torch
from src.huggingmolecules.configuration.configuration_api import PretrainedConfigMixin
from src.huggingmolecules.featurization.featurization_api import PretrainedFeaturizerMixin, RecursiveToDeviceMixin
from... |
1637137 | text = """
//------------------------------------------------------------------------------
// Explicit instantiation.
//------------------------------------------------------------------------------
#include "Geometry/Dimension.hh"
#include "RK/ReproducingKernelMethods.cc"
namespace Spheral {
template class Reproduci... |
1637187 | input = """
1 2 0 0
1 3 0 0
1 4 0 0
1 5 0 0
1 6 0 0
1 7 0 0
1 8 0 0
1 9 0 0
1 10 0 0
1 11 0 0
1 12 0 0
1 13 0 0
1 14 0 0
1 15 0 0
1 16 0 0
1 17 0 0
1 18 0 0
1 19 0 0
1 20 2 1 21 22
1 21 2 1 20 22
1 22 0 0
1 23 2 1 24 25
1 24 2 1 23 25
1 25 0 0
1 26 2 1 27 28
1 27 2 1 26 28
1 28 0 0
1 29 2 1 30 31
1 30 2 1 29 31
1 31 0 ... |
1637213 | import ast
import sys
import dace
from dace.transformation.transformation import Transformation
from dace.transformation.dataflow import MapFission
from typing import Any, Dict, Set
import warnings
from dace import registry, sdfg as sd, symbolic
from dace.properties import make_properties
from dace.sdfg import nodes, ... |
1637214 | run(args, *, stdin=None, input=None,
stdout=None, stderr=None, shell=False, timeout=None, check=False)
call(args, *, stdin=None, stdout=None,
stderr=None, shell=False, timeout=None)
check_output(args, *, stdin=None, stdout=None,
stderr=None, shell=False, timeout=None)
|
1637247 | import copy
import json
import multiprocessing
import os
import random
import shutil
import string
import tempfile
from contextlib import contextmanager
from os import chdir, getcwd, mkdir
from os.path import exists
import pkgpanda.build.constants
import pkgpanda.build.src_fetchers
from pkgpanda import expand_require ... |
1637253 | class Solution:
def replaceWords(self, dictionary: List[str], sentence: str) -> str:
Trie = lambda : defaultdict(Trie)
trie = Trie()
END = True
for word in dictionary:
current = trie
for char in word:
current = current.setdefault(char, Trie())
... |
1637271 | import numpy
import theano
from nose.plugins.skip import SkipTest
from theano.tests.unittest_tools import verify_grad
try:
from pylearn2.sandbox.cuda_convnet.response_norm import (
CrossMapNorm,
CrossMapNormUndo
)
from theano.sandbox.cuda import CudaNdarrayType, CudaNdarray
from theano.... |
1637325 | from math import ceil, log2
def clog2(x):
return int(ceil(log2(x)))
def flatten(l):
return [item for sublist in l for item in sublist]
def has_kratos_runtime():
try:
import kratos_runtime
return True
except ImportError:
return False
def is_valid_file_mode(file_mode):
... |
1637376 | from abc import abstractmethod
from datetime import datetime
from typing import TYPE_CHECKING, Dict, List, Optional, Type, cast
import pandas as pd
import pyarrow
from google.protobuf.json_format import MessageToJson
from feast.data_source import DataSource
from feast.dqm.profilers.profiler import Profile, Profiler
f... |
1637394 | from .__info__ import __authors__, __version__
from .analysis import DataAnalyzer
from .core import MadMiner
from .delphes import DelphesReader
from .fisherinformation import (
FisherInformation,
InformationGeometry,
profile_information,
project_information,
)
from .lhe import LHEReader
from .likelihood... |
1637412 | from django.db.models.sql.where import (
WhereNode,
EverythingNode
)
class CQLWhereNode(WhereNode):
def as_cql(
self,
qn,
connection
):
return self.as_sql(
qn,
connection
)
class CQLEverythingNode(EverythingNode):
pass
|
1637420 | from binding import *
from ..namespace import llvm
from src.Pass import ImmutablePass
TargetLibraryInfo = llvm.Class(ImmutablePass)
LibFunc = llvm.Namespace('LibFunc')
LibFunc.Enum('Func', '''
ZdaPv, ZdlPv, Znaj, ZnajRKSt9nothrow_t,
Znam, ZnamRKSt9nothrow_t, Znwj, ZnwjRKSt9nothrow_t,... |
1637470 | import emacspy, socket, tempfile, queue, threading
from emacspy import sym
from typing import Optional
import concurrent.futures, traceback
_call_soon_queue: queue.Queue = queue.Queue(0)
_wakeup_conn: Optional[socket.socket] = None
_emacs_thread = threading.current_thread()
def call_soon_in_main_thread(f):
_call... |
1637481 | import os
class Card:
suits = ["clubs", "diamonds", "hearts", "spades"]
def __init__(self, suit: str, value: int, down=False):
self.suit = suit
self.value = value
self.down = down
self.symbol = self.name[0].upper()
@property
def name(self) -> str:
"""The name o... |
1637485 | from typing import NamedTuple
import pandas as pd
from pandas import DataFrame
from dbnd import task
@task(result=("features", "scores"))
def f_returns_two_dataframes_v1(p: int) -> (DataFrame, DataFrame):
return (
pd.DataFrame(data=[[p, 1]], columns=["c1", "c2"]),
pd.DataFrame(data=[[p, 1]], co... |
1637508 | from chainerrl_visualizer.utils.string_generators import generate_timestamp, generate_random_string # NOQA
from chainerrl_visualizer.utils.jsonize_datetime import jsonize_datetime # NOQA
|
1637540 | import astropy.units as u
import exifread
import matplotlib
import numpy as np
import scipy.ndimage as ndimage
from skimage.transform import hough_circle, hough_circle_peaks
from sunpy.map import GenericMap
import eclipse.meta as m
__all__ = ['find_sun_center_and_radius', 'eclipse_image_to_map']
def find_sun_center... |
1637543 | import sys, boto3, json
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.job import Job
from pyspark.sql.functions import *
def load_state_information():
"""
reads state information
... |
1637555 | from plex.objects.core.base import Descriptor, Property
class Director(Descriptor):
id = Property(type=int)
tag = Property
@classmethod
def from_node(cls, client, node):
return cls.construct(client, cls.helpers.find(node, 'Director'), child=True)
|
1637560 | import torch
import Corr2D_ext
def int_2_tensor(intList):
return torch.tensor(intList, dtype=torch.int, requires_grad=False)
def tensor_2_int(t):
assert len(t.size()) == 1
assert t.size()[0] == 5
assert t.dtype == torch.int
return t.tolist()
class Corr2DF(torch.autograd.Function):
@staticme... |
1637576 | import typing
from anchorpy.error import ProgramError
class TileOutOfBounds(ProgramError):
def __init__(self) -> None:
super().__init__(6000, None)
code = 6000
name = "TileOutOfBounds"
msg = None
class TileAlreadySet(ProgramError):
def __init__(self) -> None:
super().__init__(60... |
1637580 | import zipfile
from matplotlib.ticker import FormatStrFormatter
import matplotlib.ticker as tick
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import os
import logging
import matplotlib.pyplot as plt
from matplotlib.ticker import LinearLocator,MaxNLocator
from matplotlib.offsetbox import TextAr... |
1637609 | from yowsup.layers.protocol_contacts.protocolentities import AddContactNotificationProtocolEntity
from yowsup.structs.protocolentity import ProtocolEntityTest
import time
import unittest
entity = AddContactNotificationProtocolEntity("1234", "<EMAIL>", int(time.time()), "notify", False,
... |
1637621 | from .metropolis import Metropolis
from .hamiltonian import Hamiltonian
from .NUTS import NUTS
from .chain import Chain
from .slice import Slice
from .base import Sampler
|
1637634 | import sys
sys.path.append('../')
import constants as cnst
import os
import torch
import tqdm
import numpy as np
import constants
SHAPE = [0, 1, 2]
EXP = [50, 51, 52]
POSE = [150, 151, 152, 153, 154, 155]
def centre_using_nearest(flame_seq, flame_dataset, one_translation_for_whole_seq=True):
shape_weigth = 0
... |
1637644 | import numpy as np
from sklearn.metrics import mean_squared_error, accuracy_score
class BaseModel(object):
"""
Base model to run the test
"""
def __init__(self):
self.max_depth = 6
self.learning_rate = 1
self.min_split_loss = 1
self.min_weight = 1
self.L1_r... |
1637649 | import asyncio
import gevent.selectors
__all__ = ["EventLoop"]
class EventLoop(asyncio.SelectorEventLoop):
"""
An asyncio event loop that uses gevent for scheduling and runs in a spawned
greenlet
"""
def __init__(self, selector=None):
super().__init__(selector or gevent.selectors.Defaul... |
1637675 | import time
import analysis.event
import analysis.beamline
import analysis.background
import analysis.pixel_detector
import ipc
import random
import numpy
numpy.random.seed()
state = {
'Facility': 'dummy',
'squareImage' : True,
'Dummy': {
'Repetition Rate' : 10,
'Data Sources': {
... |
1637719 | from django.db import transaction
from denorm.db import base
import logging
logger = logging.getLogger('denorm-sqlite')
class RandomBigInt(base.RandomBigInt):
def sql(self):
return 'RANDOM()'
class TriggerNestedSelect(base.TriggerNestedSelect):
def sql(self):
columns = self.columns
... |
1637721 | import numpy as np
from sklearn.linear_model import LogisticRegression
from .base import TransformationBaseModel
class Kane(TransformationBaseModel):
"""The class which implements the Kane's approach.
+----------------+-----------------------------------------------------------------------------------+
... |
1637831 | from pathlib import Path
from numpy import array
from manim import *
class DottedLine(Line):
"""A dotted :class:`Line`.
Parameters
----------
args : Any
Arguments to be passed to :class:`Line`
dot_spacing : Optional[:class:`float`]
Minimal spacing of the dots. The spacing is scale... |
1637832 | from tensor2struct.models import decoder, batched_decoder
from tensor2struct.utils import registry, vocab
class CogsPreproc(decoder.DecoderPreproc):
def add_item(self, item, section, validation_info):
actions = item.code.split()
if section == "train":
for action in actions:
... |
1637852 | import torch
import torch.nn as nn
from torch.nn import init
import functools
from torch.optim import lr_scheduler
from collections import OrderedDict
import torch.nn.functional as F
def get_scheduler(optimizer, opt):
if opt.lr_policy == 'lambda':
def lambda_rule(epoch):
lr_l = 1.0 - max(0, epo... |
1637878 | import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
import os
import sys
import tensorflow as tf
import jpegio as jio
from tensorflow.python.framework import ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import st... |
1637923 | from collections import defaultdict
from stoichiograph import speller
from stoichiograph.speller import Node
ELEMENTS = {
'H', 'He', 'Li', 'Be', 'B', 'C', 'N', 'O', 'F', 'Ne', 'Na', 'Mg', 'Al',
'Si', 'P', 'S', 'Cl', 'Ar', 'K', 'Ca', 'Sc', 'Ti', 'V', 'Cr', 'Mn', 'Fe',
'Co', 'Ni', 'Cu', 'Zn', 'Ga', 'Ge', 'As... |
1637936 | import os, sys
# sys.path.append('/home/shaunxliu/projects/nnsp')
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator
import torch
from torch.utils.data import DataLoader
import numpy as np
from src.solver import BaseSolver
from src.data_load import OneshotV... |
1637937 | from .token import Token
from typing import List
from typing import Dict
from typing import Set
from typing import Union
from typing import Generator
from .span import Span
from .utils import normalize_slice
class TextDoc:
def __init__(self):
# This list is populated in the __call__ method of the Tokeni... |
1637969 | import enum
from uuid import UUID
from pydantic import BaseModel
class ProfileShort(BaseModel):
id: UUID
username: str
class FriendshipRequest(BaseModel):
profile_id: UUID
target_profile_id: UUID
class Relationship(str, enum.Enum):
FRIEND = "FRIEND"
OUTGOING_FRIEND_REQUEST = "OUTGOING_FRI... |
1637977 | from openie import StanfordOpenIE
import spacy
import neuralcoref
from difflib import SequenceMatcher
import nltk
from nltk.corpus import stopwords
import argparse
import random
parser = argparse.ArgumentParser()
parser.add_argument('--file', type=str)
parser.add_argument('--outfile', type=str)
parser.add_argument('--... |
1637987 | import os
file_chars_reference = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
def create_letters_text_files():
try:
# Obtenemos la ruta absoluta del directorio en el que estamos trabajando
script_directory = os.path.dirname(__file__)
for letter in file_chars_reference:
file_path = f"{script_d... |
1637989 | import demistomock as demisto # noqa: F401
from CommonServerPython import * # noqa: F401
def test_module(client, url):
result = client._http_request('GET', full_url=url)
if isinstance(result, list):
return 'ok'
else:
return 'Test failed: ' + str(result)
def find_type_and_value(indicato... |
1638020 | import numpy as np
import torch
from sklearn.preprocessing import normalize
from torch_geometric.datasets import Planetoid
def get_dataset(dataset):
datasets = Planetoid('./dataset', dataset)
return datasets
def data_preprocessing(dataset):
dataset.adj = torch.sparse_coo_tensor(
dataset.edge_ind... |
1638079 | def main():
import os
import sys
import sysconfig
import site
try:
import vapoursynth
except ImportError as e:
print("It seems you have not installed VapourSynth yet.")
exit(e)
from .install import install
def print_help():
print(
... |
1638131 | from collections import deque
class Node:
"""A Node which maps a node proto. It has pointers to its parents and
children.
"""
def __init__(self, onnx_node):
"""Initialize a node. This initialization only set up the mapping to
node proto. The pointers should be set up by outside.
... |
1638133 | from pathlib import Path
import ujson
class BotGeneratorPreset:
def __init__(self, database_dir: Path, bot_role: str):
bots_dir = database_dir.joinpath("bots", bot_role)
self.generation: dict = ujson.load(
bots_dir.joinpath("generation.json").open(encoding="utf8")
)
s... |
1638158 | import sys
import json
import subprocess
def runner(language, commands, is_test):
print("\nRunning {language} formatter{mode}...\n".format(
language = language,
mode = " in test mode" if is_test else ""
))
process = subprocess.run(commands)
if process.returncode != 0:
exit(process.returncode)
arg... |
1638164 | from typing import Tuple, Dict, List
import numpy as np
from graph_nets.graphs import GraphsTuple
from .tf_tools import graphs_tuple_to_data_dicts, data_dicts_to_graphs_tuple
MIN_STD = 1E-6
class Standardizer:
@staticmethod
def compute_mean_std(a: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
retur... |
1638205 | from pkgconf import Conf
class ControlCenter(Conf):
DASHBOARDS = []
CHARTIST_COLORS = 'default'
SHARP = '#'
|
1638211 | import os
import sys
import glob
import gzip
import bs4, lxml
import concurrent.futures
import re
from pathlib import Path
import json
import random
import CONFIG
def pmap(arg):
key, names = arg
random.shuffle(names)
for name in names:
try:
sha256 = name.split('/')[-1]
if Pa... |
1638226 | from django.shortcuts import render, get_object_or_404, redirect, reverse
from django.http import HttpResponse, HttpResponseBadRequest, StreamingHttpResponse
from django.views.decorators.csrf import csrf_exempt
from django.views.decorators.debug import sensitive_post_parameters
from django.contrib.auth.decorators impor... |
1638257 | import numpy as np
from .base import Prior, PriorException
from .interpolated import Interped
from .analytical import DeltaFunction, PowerLaw, Uniform, LogUniform, \
SymmetricLogUniform, Cosine, Sine, Gaussian, TruncatedGaussian, HalfGaussian, \
LogNormal, Exponential, StudentT, Beta, Logistic, Cauchy, Gamma, ... |
1638274 | import numpy as np
import torch as th
from torchvision import transforms
from .data_utils import is_tuple_or_list
class BaseDataset:
"""An abstract class representing a Dataset.
All other datasets should subclass it. All subclasses should override
``__len__``, that provides the size of the dataset, and `... |
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