id stringlengths 3 8 | content stringlengths 100 981k |
|---|---|
9958792 | from metalibm_core.core.simple_scalar_function import ScalarBinaryFunction
from metalibm_core.core.ml_formats import ML_Binary32, ML_Int32
from metalibm_core.core.precisions import ML_Faithful
from metalibm_core.core.ml_operations import (
Statement, Return,
ExponentExtraction, ExponentInsertion, MantissaExtrac... |
9958906 | import vtk
def initialize(self, VTKWebApp, args):
if not VTKWebApp.view:
# VTK specific code
renderer = vtk.vtkRenderer()
renderWindow = vtk.vtkRenderWindow()
renderWindow.AddRenderer(renderer)
renderWindowInteractor = vtk.vtkRenderWindowInteractor()
renderWindowIn... |
9958911 | from google.cloud.gapic.trace.v1 import enums
from google.cloud.gapic.trace.v1 import trace_service_api
from google.devtools.cloudtrace.v1 import trace_pb2
from google.protobuf import timestamp_pb2
import calendar
import time
import uuid
# point this at your project ID
PROJECT_ID = 'gapic-test'
api = trace_service... |
9958967 | from deepy3d import Deepy3d
from _version import __version__
__all__ = ['CNN_Model', 'ConfigReader', 'PatientIO', 'Scans', 'util']
|
9958978 | import random
from openpyxl import Workbook
from openpyxl.styles import PatternFill
from openpyxl.formatting.rule import CellIsRule
wb = Workbook()
ws = wb.active
values = random.sample(range(100), k=10)
for i, value in enumerate(values, 1):
column_a = ws.cell(i, 1)
column_a.value = value
row_le... |
9958981 | algorithm='dqn'
env_class='UnityMLVector'
model_class='TwoLayer2x'
environment = {
'name': 'compiled_unity_environments/Banana.app'
}
model = {
'state_size': 37,
'action_size': 4,
'fc_units': (32, 32)
}
agent = {
'action_size': 4,
'use_double_dqn': False,
}
train = {
'n_episodes': 1000,
... |
9959072 | from keras import backend as K
import os
import sys
def set_keras_backend(backend):
if K.backend() != backend:
os.environ['KERAS_BACKEND'] = backend
reload(K)
assert K.backend() == backend
|
9959073 | import argparse
import numpy
import sys
import csv
import os
from collections import defaultdict
parser = argparse.ArgumentParser()
parser.add_argument('--input-tsv', type=str, required=True)
args, files = parser.parse_known_args()
def main():
print("\t".join(["contig", "position", "ref", "alt", "primer_name", "... |
9959106 | from datetime import datetime
import typing
from fastapi.responses import JSONResponse as BaseResponse
class JSONResponse(BaseResponse):
def render(self, content: typing.Any) -> bytes:
if isinstance(content, datetime):
return content.replace(microsecond=0).isoformat()
return super().... |
9959132 | import json
import pytest
import brahe.data_models as bdm
from .paths import TEST_DATA
@pytest.fixture
def request_sf_point():
filepath = TEST_DATA / 'request_sf_point.json'
request_json = json.load(open(filepath, 'r'))
yield bdm.Request(**request_json)
@pytest.fixture
def request_sf_polygon():
filep... |
9959146 | import fortran_dissipation as fortran
def add_viscosity(grid, state, dstate, viscosity):
for comp in "ijk":
for direc in "ijk":
coef = viscosity*grid.ids2[direc]
cova = state.u[comp].view(direc)
dudt = dstate.u[comp].view(direc)
if direc == comp:
... |
9959149 | import sys
import numpy
from matplotlib import pyplot
from scipy import stats
import pytest
from paramnormal import activity
from paramnormal import dist
from paramnormal.utils import seed
BASELINE_DIR = 'baseline_images/test_activity'
TOLERANCE = 15
def assert_dists_are_equivalent(dist1, dist2):
numpy.rando... |
9959190 | import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
def plot(title,
filename,
xlabel=None,
ylabel=None,
n_obj=None,
algo=None,
noise=None,
new_fig=False
):
with open(filename, 'r') as f:
y = f.readlines()
y = [... |
9959201 | from ._model import CellAssign
from ._module import CellAssignModule
__all__ = ["CellAssign", "CellAssignModule"]
|
9959209 | class Affine(object):
DIE = 128
KEY = (7, 3, 55)
def __init__(self):
pass
def encryptChar(self, char):
K1, K2, kI = self.KEY
return chr((K1 * ord(char) + K2) % self.DIE)
def encrypt(self, string):
return "".join(map(self.encryptChar, string))
def decryptChar(self, char):... |
9959211 | from distutils.core import setup
from distutils.extension import Extension
from Cython.Build import cythonize
hello_parallel = Extension('hello_parallel',
['hello_parallel.pyx'],
extra_compile_args=['-fopenmp'],
extra_link_args=['-fopenmp... |
9959234 | import tensorflow as tf
class LSTMNBase(object):
'''Base class implementing the constructor and the generic soft attention reweighting.
Args:
num_units (int): Number of units in the hidden LSTMN layer
scope (Optional[tf VariableScope]): Scope that all operations will be prefixed with.
Att... |
9959236 | import click
from a2ml.api.a2ml_experiment import A2MLExperiment
from a2ml.api.utils.context import pass_context
@click.group('experiment', short_help='Experiment management')
@pass_context
def cmdl(ctx):
"""Experiment management"""
ctx.setup_logger(format='')
@click.command(short_help='List Experiments for... |
9959241 | import subprocess
import threading
import re
def getClipboardData():
p = subprocess.Popen(['pbpaste'], stdout=subprocess.PIPE)
retcode = p.wait()
data = p.stdout.read()
return data.decode('utf-8')
clip = getClipboardData()
def check_for_clipboard_change():
global clip
threading.Timer(0.5,... |
9959245 | import asyncio
import logging
import threading
import multiprocessing
from construct import Container
from xbox.nano.render.client import Client
from xbox.nano.render.sink import Sink
from xbox.nano.render.video.sdl import SDLVideoRenderer
from xbox.nano.render.audio.sdl import SDLAudioRenderer
class BlockingClient(... |
9959284 | from typing import Dict, Any, Union
from bxcommon.feed.eth.eth_transaction_feed_entry import EthTransactionFeedEntry
from bxcommon.utils.object_hash import Sha256Hash
class EthTransactionNoSignatureFeedEntry(EthTransactionFeedEntry):
def __init__(self, tx_hash: Sha256Hash, tx_contents: Union[memoryview, Dict[str... |
9959296 | import torch
from torch.autograd import Variable
import torchvision
from torchvision import transforms
from PIL import Image
import numpy as np
from const import PAD
class Data_loader(object):
def __init__(self, path, imgs, labels, max_len, batch_size, is_cuda, img_size=299, evaluation=False):
self._pa... |
9959298 | import logging
import uuid
from config import SQLALCHEMY_DATABASE_URI
from sqlalchemy import Boolean, Column, DateTime, Float, Integer, String, create_engine
from sqlalchemy.dialects.postgresql import UUID
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import scoped_session, sessionmaker
... |
9959312 | from .kb_helper import *
from .state_tracker import *
from .dialog_manager import *
from .dict_reader import *
from .utils import * |
9959357 | from SimpleHTTPServer import SimpleHTTPRequestHandler
from json import loads
from random import randint
from re import search as re_search
from urllib import unquote
class TinyHandler(SimpleHTTPRequestHandler, object):
the_number = randint(1, 99999)
def __init__(s... |
9959371 | from __future__ import absolute_import
from __future__ import print_function
# -*- coding: utf-8 -*-
import numpy as np
import os
from keras.models import load_model
import cv2
os.environ["CUDA_VISIBLE_DEVICES"]="2"
learning_rate=0.001
continue_from_best=False
model=load_model('bestweights3')
os.... |
9959374 | import unittest
from isceobj.Util.mathModule import MathModule as MM
class MathModuleTest(unittest.TestCase):
def setUp(self):
self.V = [1,2,3]
self.M = [[1,2,3],
[4,5,6],
[7,8,9]]
self.N = [[1,2,3],
[1,2,3],
[1,2,3]]
... |
9959449 | import haiku as hk
from ..utils import is_stochastic, jit
from .._core.base_stochastic_func_type1 import BaseStochasticFuncType1
from .._core.base_stochastic_func_type2 import BaseStochasticFuncType2
class Regularizer:
r"""
Abstract base class for policy regularizers. Check out
:class:`coax.regularizers... |
9959481 | from speedtest import Speedtest #pip install speedtest-cli
speedTest = Speedtest()
print("donwload : ",speedTest.download())
print("upload :",speedTest.upload())
speedTest.get_servers([])
print("ping : ",speedTest.results.ping + " ms")
|
9959485 | from __future__ import print_function
from datetime import datetime
import json
import boto3
config = boto3.client('config')
s3 = boto3.client('s3')
def evaluate_compliance(rule_parameters):
s3_bucket_name = rule_parameters['S3BucketName']
bucket_list = rule_parameters['LogBuckets']
non_compliant_list =... |
9959496 | from copy import deepcopy
from easydict import EasyDict as edict
import multiprocessing
from lib import arguments, cfg_utils, fdutil, io_control_file, utils
from lib.config import cfg as cfg_default
from lib.validate_arguments import all_keys_known, is_boolean, is_string, is_positive_integer, valid_act_fn,\
valid_... |
9959499 | import glfw
import compushady.config
import compushady.formats
import compushady
from compushady.shaders import hlsl
import struct
import platform
import math
compushady.config.set_debug(True)
print('Using device', compushady.get_current_device().name)
target = compushady.Texture2D(1024, 1024, compushady.formats.B8G... |
9959510 | class BitcartError(Exception):
"""Generic error class for all errors raised"""
class TemplateDoesNotExistError(BitcartError):
"""Template does not exist and has no default"""
class TemplateLoadError(BitcartError):
"""Failed to load template file from disk"""
|
9959546 | from pytezos.sandbox.node import SandboxedNodeAutoBakeTestCase
from pytezos import ContractInterface
from pytezos.operation.result import OperationResult
code = """
parameter (or (int %decrement) (int %increment));
storage int;
code { UNPAIR ; IF_LEFT { SWAP ; SUB } { ADD } ; NIL operation ; PAIR }
"""
class Concurr... |
9959551 | import os
import re
import datetime
import dateutil.parser
import configparser
import numpy as np
import astropy.io.fits as fits
from astropy.table import Table
from ...utils.misc import extract_date
from ..common import load_obslog, load_config
from .common import print_wrapper, get_ccd_geometry
from .reduce import ... |
9959582 | import datetime
import json
import subprocess
from urllib.parse import urljoin
import requests
import jsonpath_rw_ext as jp
from openpyxl import Workbook
from openpyxl.utils import get_column_letter
from web.apps.web_copo.lookup import lookup as lk
from web.apps.web_copo.schemas.utils.data_utils import json_to_pytype... |
9959593 | from fastapi import FastAPI
from fastapi.openapi.docs import (
get_redoc_html,
get_swagger_ui_html,
get_swagger_ui_oauth2_redirect_html,
)
from starlette.exceptions import HTTPException
from starlette.middleware.cors import CORSMiddleware
from starlette.staticfiles import StaticFiles
from starlette.status i... |
9959595 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import numpy as np
import pandas as pd
import pytest
from treecat.format import export_rows
from treecat.format import guess_schema
from treecat.format import import_data
from treecat.format import ... |
9959596 | import sys
import numpy as np
import tensorflow as tf
sys.path.append("..")
from libs import octree_samples
tf.enable_eager_execution()
# dump the octree samples
for i in range(1, 7):
name = 'octree_%d' % i
octree = octree_samples(name)
with open(name + '.octree', 'wb') as fid:
fid.write(octree.numpy())
|
9959606 | import numpy as np
from helper import f
from helper import f_prime_x0
from helper import f_prime_x1
from helper import plot_rosenbrock
np.random.seed(0)
def main() -> None:
x0 = np.random.uniform(-2.0, 2.0)
x1 = np.random.uniform(-2.0, 2.0)
x_start = (x0, x1)
y_start = f(x0, x1)
print(f"Globa... |
9959612 | import sys
from typing import Union
from internalblue import Address
def bytes_to_hex(data):
# type: (Union[bytes, bytearray]) -> str
return "".join(format(x, "02x") for x in bytearray(data))
def flat(data: [Address, bytes], filler: int) -> bytes:
res = bytes()
last_section_end = 0
for address ... |
9959630 | import pytest
from mongoengine_migrate import actions
@pytest.fixture
def actions_rank():
"""Actions are sorted by priority ascending"""
return [
actions.RenameEmbedded,
actions.CreateEmbedded,
actions.AlterEmbedded,
actions.RenameDocument,
actions.CreateDocument,
... |
9959641 | import sys
test_cases = open(sys.argv[1], 'r')
for test in test_cases:
test = test.strip()
if len(test) == 0:
continue
lower = 0
upper = 0
for character in test:
if character.islower():
lower += 1
else:
upper += 1
lower = float(lower) / len(test) ... |
9959679 | import unittest
from dbTools import *
class TestDbRestaurantTable(unittest.TestCase):
test_cases_insert = [
{
'signIn': [False, '', ''],
'tableNumber': 2,
'result': False
},
{
'signIn': [True, 'rName1', '123456'],
'tabl... |
9959722 | from . import cli
# __ __ ____ _ __ ___
# ____ ____ _ / /_ / /_ ___ / __ \ / | / // |
# / __ \ / __ `// __// __// _ \ / /_/ // |/ // /| |
# / /_/ // /_/ // /_ / /_ / __// _, _// /| // ___ |
# / .___/ \__,_/ \__/ \__/ \___//_/ |_|/_/ |_//_/ |_|
# /_/
#
# (c) 2018-202... |
9959733 | import logging
import os.path
from typing import Any, Callable, Generator, Union, cast
from more_itertools import ilen
from thenewboston_node.business_logic.blockchain.file_blockchain.base import ( # noqa: I101
EXPECTED_LOCK_EXCEPTION, LOCKED_EXCEPTION, FileBlockchainBaseMixin
)
from thenewboston_node.business_l... |
9959742 | from collections import namedtuple
import re
inequalities = {
'.lt': lambda x, y: x < y,
'.leq': lambda x, y: x <= y,
'.eq': lambda x, y: x == y,
'.geq': lambda x, y: x >= y,
'.gt': lambda x, y: x > y,
}
class Phrase(object):
fields = ['text', 'words', 'char_offsets', 'pos_tags', 'ner_tags', ... |
9959764 | import os
import random
import shell
import string
from hypothesis.database import ExampleDatabase
from hypothesis import given, settings
from hypothesis.strategies import lists, composite, integers, randoms, floats, text, sampled_from
from test_util import run, clone_source, compile_buffer_sizes
if os.environ.get('TE... |
9959769 | import logging
import time
from typing import Optional, List, Any, Dict
import hydra
import numpy as np
import torch
import torch.nn.functional as F
from omegaconf import DictConfig
from torch import Tensor, nn
from pytorch_lightning import LightningModule
from climart.data_loading.constants import TEST_YEARS, get_da... |
9959781 | import json
import logging
import os
import sys
from distutils.util import strtobool
from typing import Any, Callable, Iterator, List, Optional, TypeVar, Union
import requests
from flask import Flask, Response, abort, jsonify, request, stream_with_context
from plz.controller import configuration
from plz.controller.a... |
9959820 | from typing import Union
from boa3.builtin.interop.blockchain.block import Block
from boa3.builtin.interop.blockchain.transaction import Transaction
from boa3.builtin.interop.contract import Contract
from boa3.builtin.type import UInt160, UInt256
current_height: int = 0
def get_contract(hash: UInt160) -> Contract:
... |
9959838 | import gtk
from pyscrabble.constants import *
class InfoWindow(gtk.Window):
'''
Information window
'''
def __init__(self, title, header, main):
'''
Constructor
@param title: Window title
@param header: Header text
'''
... |
9959916 | import torchvision
import typing
import torch
import logging
log = logging.getLogger(__name__)
__all__ = ['CIFAR10', 'CIFAR100']
#NOTE: normalization values taken from: https://github.com/kuangliu/pytorch-cifar/issues/19
__NORM_MEAN_STD__ = {
'CIFAR10': {
'mean': torch.Tensor([
[[0.49139968]... |
9959952 | import re
import os
from itertools import zip_longest
class ReviewPair:
def __init__(self, reference_file, target_file):
self.reference_file = reference_file
self.target_file = target_file
def partition_files(reference_language, target_language, file_map):
result = []
for path in file_ma... |
9959973 | import imagej
import imagej.stack as ijs
import xarray as xr
# start imagej
print("Starting ImageJ...")
ij = imagej.init(headless=False)
print(f"ImageJ Version: {ij.getVersion()}")
# get xarray from dataset
img = ij.io().open('/home/eevans/Downloads/test_stack.tif')
img_xr = ij.pyfrom_java(img)
# extract first chann... |
9959974 | from __future__ import division, absolute_import, print_function
from .cifar10 import CIFAR10
from .mnist import MNIST
|
9960001 | from .models import (TestModel,
GenericModel,
ReleaseResourcesParamsModel,
ResourceDescriptorModel,
UpdateFieldsParamsModel,
LockResourcesParamsModel,
StatisticsRequestModel)
|
9960002 | from unittest import TestCase
from back_propagation import *
class TestBackPropagation(TestCase):
def test_unit(self):
unit1 = Unit()
unit2 = Unit()
unit3 = Unit(unit1, unit2)
self.assertSequenceEqual(unit1.get_parents(), [])
self.assertSequenceEqual(unit1.get_children(), [... |
9960008 | import numpy as np
import pandas as pd
from sklearn.metrics import confusion_matrix
from sklearn.metrics import roc_auc_score
from sklearn.metrics import mean_squared_error
import matplotlib
matplotlib.use("TkAgg")
# initiating random number
np.random.seed(11)
#### Creating the dataset
# mean and standard deviation... |
9960021 | import pytest
pytestmark = [pytest.mark.django_db]
@pytest.fixture
def api(api):
api.user.is_superuser = True
api.user.save()
return api
def test(api, diploma):
api.delete(f'/api/v2/diplomas/{diploma.slug}/', expected_status_code=405)
|
9960103 | import argparse
import json
import os
import urllib
import urllib.request
import requests
import sys
from requests.auth import HTTPBasicAuth
def get_course_page(api_url, token):
return json.loads(requests.get(api_url, headers={'Authorization': 'Bearer ' + token}).text)
def get_all_weeks(stepik_resp):
return... |
9960111 | from abc import abstractmethod
from openpype.modules import OpenPypeInterface
class ISettingsChangeListener(OpenPypeInterface):
"""Module has plugin paths to return.
Expected result is dictionary with keys "publish", "create", "load" or
"actions" and values as list or string.
{
"publish": ["p... |
9960124 | import a
import b
import c
import d
import f
A = 1
A = 1
A = 1
A = 1
A = 1
A = 1
def a():
pass
def a():
pass
def a():
pass
def a():
pass
A = 1
def a():
pass
A = 1
def a():
pass
A = 1
def a():
pass
A = 1
A = 1
class a:
pass
class a:
pass
class a:
pass
... |
9960162 | import configparser
from typing import List, Dict, Optional, Union
from math import ceil
from pathlib import Path
from jira import JIRA, JIRAError
from django.conf import settings
from apps.extractor.main.cleaner import clean_text
from apps.extractor.main.preprocessor import calculate_ttr
from apps.extractor.main.ma... |
9960265 | import warnings
import numpy as np
import matplotlib.pyplot as plt
def plot(shapley_values,
feature_names=None,
sort_features=True,
max_features=np.inf,
orientation='horizontal',
error_bars=True,
color='tab:green',
title='Feature Importance',
tit... |
9960297 | from __future__ import print_function
import argparse
import sys
import time
import torch
import torch.nn as nn
import torch.optim as optim
import torch.backends.cudnn as cudnn
from torch.autograd import Variable
import torch.utils.data as data
import torchvision
import torchvision.transforms as transforms
from data_lo... |
9960310 | import FWCore.ParameterSet.Config as cms
beamspotanalyzer = cms.EDAnalyzer('AnotherBeamSpotAnalyzer',
bsCollection = cms.InputTag("offlineBeamSpot"),
bsHistogramMakerPSet = cms.PSet(
histoPa... |
9960315 | import unittest
import hcl2
from checkov.terraform.checks.resource.gcp.GoogleProjectDefaultNetwork import check
from checkov.common.models.enums import CheckResult
class TestGoogleProjectDefaultNetwork(unittest.TestCase):
def test_failure(self):
hcl_res = hcl2.loads("""
resource "google... |
9960330 | def _create_ref(ref_type, pkg_name, name):
"""Creates a reference for the specified type.
Args:
ref_type: A `string` value. Must be one of the values in
`reference_types`.
pkg_name: The package name as a `string`.
name: The name of the item as a `string`.
Returns:... |
9960367 | import json
import os
import numpy as np
import scipy as sp
import pandas as pd
from pandas.tools.plotting import scatter_matrix
import seaborn as sns
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid.inset_locator import inset_axes
import ast
import cPickle as pickle
for i in range(1,21):
temp = []
... |
9960368 | from yozuch.generators.template import TemplateEntry, TemplateGenerator
from yozuch.paginator import Paginator
class BlogIndexGenerator(TemplateGenerator):
def __init__(self, url_template, name, template, posts_per_page=0, pagination_url=None):
super().__init__(url_template, name, template)
self.... |
9960440 | class Solution:
def createTargetArray(self, nums: List[int], index: List[int]) -> List[int]:
result = []
for i in range(len(nums)):
result = result[0:index[i]] + [nums[i]] + result[index[i]:]
return result
|
9960462 | def test_singleton():
from trame.app.singleton import Singleton
@Singleton
def new_object():
return object()
# Normally, a new object would be returned each time
# However, since this is a singleton, the same object should be returned
assert new_object() is new_object()
|
9960471 | from automlk.dataset import get_dataset_list, create_dataset_sets
"""
module specifically designed to update Xyset after new version
"""
for dt in get_dataset_list():
if dt.status != 'created':
print(dt.name)
# update X y set
create_dataset_sets(dt)
|
9960486 | import torch.nn as nn
import FrEIA.framework as Ff
import FrEIA.modules as Fm
from .. import InvertibleArchitecture
from .. import CouplingType
from ..coupling_blocks.slow import AIO_SlowCouplingBlock
from ..coupling_blocks.glow import AIO_GlowCouplingBlock
from ...utils.dct_transform import DCTPooling2d
class Inv... |
9960581 | import tensorflow as tf
import numpy as np
def sample_gumbel(shape, eps=1e-20):
"""Sample from Gumbel(0, 1)"""
U = tf.random_uniform(shape,minval=0,maxval=1)
return -tf.log(-tf.log(U + eps) + eps)
def gumbel_softmax(logits, temperature):
""" Draw a sample from the Gumbel-Softmax distribution"""
y = logits + sa... |
9960674 | import math
from . import meter
import torch
import numpy as np
class ValueSummaryMeter(meter.Meter):
def __init__(self):
super(ValueSummaryMeter, self).__init__()
self.reset()
self.val = 0
def add(self, value, n=1):
self.val = value
self.sum += value
self.var ... |
9960738 | import torch
from models.distributions import BaseDistribution
from models.distributions.diagonalgaussian import DiagonalGaussian
from models.transformations.coupling import Coupling
from models.transformations.squeeze import Squeeze
from models.transformations.conv1x1 import Conv1x1
from models.transformations.normal... |
9960741 | from flask_sqlalchemy import SQLAlchemy
from sqlalchemy import Table, Column, Float, Integer, String, DateTime, MetaData, ForeignKey, func
import os
import random
import string
db=SQLAlchemy()
class Users(db.Model):
address = db.Column(db.String(80), primary_key=True, unique=True)
submit_token = db.Column(db.Stri... |
9960764 | import unittest
import torch
from torch.utils.data import DataLoader
from pytorchtrainer import create_default_trainer
from pytorchtrainer.stop_condition import EarlyStopping
from pytorchtrainer.callback import MetricCallback
from pytorchtrainer.metric import Accuracy
from test.common import XorModule, XorDataset
c... |
9960787 | import lightgbm as lgb
import pandas as pd
import numpy as np
from datetime import datetime
from pathlib import Path
from sklearn.model_selection import StratifiedKFold
from sklearn.model_selection import RepeatedStratifiedKFold
from sklearn.model_selection import train_test_split
path=Path("data/")
train=pd.read_c... |
9960791 | class NoElementsError(Exception):
pass
class NullArgumentError(Exception):
pass
class NoMatchingElement(Exception):
pass
class MoreThanOneMatchingElement(Exception):
pass
|
9960864 | from typing import Type
from uuid import UUID
from sqlalchemy import select
from api.db.errors import DoesNotExist
from api.db.models.tenant import TenantCreate, TenantUpdate, TenantRead, Tenant
from api.db.repositories.base import BaseRepository
class TenantsRepository(BaseRepository[TenantCreate, TenantUpdate, Ten... |
9960879 | import pytest
import open_cp.scripted.preds as preds
import datetime
def test_TimeRange():
tr = preds.TimeRange(datetime.datetime(2016,1,1),
datetime.datetime(2016,1,5), datetime.timedelta(days=1))
assert tr.first == datetime.datetime(2016,1,1)
assert tr.stop_before == datetime.datetime(2016,1,5... |
9960888 | import unittest
from pyNTM import PerformanceModel
class TestRSVPLSPConfigSetupBW(unittest.TestCase):
def test_config_setup_bw_model_load(self):
model = PerformanceModel.load_model_file(
"test/lsp_configured_setup_bw_model.csv"
)
model.update_simulation()
self.assertEq... |
9960914 | import argparse
import os.path as path
import torch
import torch.nn.functional as F
from torch_geometric.datasets import Planetoid
import torch_geometric.transforms as T
from torch_geometric.nn import GCNConv, GAE, VGAE
from torch_geometric.utils import train_test_split_edges
from tinydfa import DFALayer, DFA
from mod... |
9960989 | import pandas as pd
import pytest
from torch.utils.data import DataLoader
from transformers import BertTokenizer
from octopod import MultiDatasetLoader
from octopod.ensemble import OctopodEnsembleDataset, OctopodEnsembleDatasetMultiLabel
from octopod.text.dataset import OctopodTextDataset, OctopodTextDatasetMultiLabel... |
9960992 | import os
import numpy as np
import pickle
from umap import UMAP
target_output_dim = 2
batch_size = 10
input_dim = 28
model_path = 'pre-trained.model'
train_data = np.random.rand(batch_size, input_dim)
model = UMAP(n_components=target_output_dim, random_state=42)
model.fit(train_data)
pickle.dump(model, open(model_... |
9961006 | import unittest
import Adafruit_NeoPixel_FTDI as neo
class MockMPSSE(object):
def __init__(self):
self.output = None
def Start(self):
pass
def Stop(self):
pass
def Write(self, data):
self.output = data
class Test_NeoPixel(unittest.TestCase):
def test_build_byte_lookup(self):
self.assertEqual(ne... |
9961018 | import configparser
import logging
logger = logging.getLogger(__name__)
import cv2
from pose.hand_dataset.selector import select_dataset
from pose.hand_dataset import common_dataset
cv2.setNumThreads(0)
def visualize_dataset(config, debug=True, visualize=True, iterate_all=False):
dataset = select_dataset(conf... |
9961054 | from .runner import Runner
import raylink
import time
class Manager(raylink.OutlineNode):
TYPE = 'manager'
def setup(self):
"""Setup manager node, create storage, ps captain, logger and runner,
and put the config into the storage.
"""
st_time = time.time()
self._stora... |
9961132 | import neptune
neptune.init('shared/onboarding', api_token='<KEY>')
with neptune.create_experiment(name='hello-neptune'):
neptune.append_tag('introduction-minimal-example')
n = 117
for i in range(1, n):
neptune.log_metric('iteration', i)
neptune.log_metric('loss', 1/i**0.5)
neptune.log_text('magi... |
9961167 | import torch
import torch.nn as nn
from torch.nn import init
import functools
from torch.optim import lr_scheduler
###############################################################################
# Helper Functions
###############################################################################
class LayerNorm(nn.Modu... |
9961178 | import json
import logging
from http import HTTPStatus
from random import randint
from celery import chain
from django.conf import settings
from django.utils.decorators import method_decorator
from django.views.decorators.cache import cache_page
from drf_yasg.utils import swagger_auto_schema
from requests import HTTPE... |
9961193 | import argparse
from typing import Dict, Any
import numpy as np
import torch
from main_loop import generate_dataset, create_fold_generator
from utils import AnalysisType, DatasetType, ConnType, Normalisation, EncodingStrategy
def save_svm_format(dataset_slice, fold_num: int, fold_name: str, dataset_type: str, analy... |
9961196 | from django.urls import path
from django.views.decorators.csrf import csrf_exempt
from graphene_django.views import GraphQLView
from ingest.schema import schema
app_name = "ingest"
urlpatterns = [
path("graphql", csrf_exempt(GraphQLView.as_view(graphiql=True, schema=schema))),
]
|
9961294 | import itertools
import os
import pickle
import numpy as np
from hypergrad.util import dictslice
from hypergrad.mnist import random_partition
def datapath(fname):
project_dir = os.environ['EXPERI_PROJECT_PATH']
datadir = project_dir+"/library/hypergrad/data/mnist"
# datadir = os.path.expanduser('/Users/... |
9961318 | import argparse
import math
import multiprocessing
import os
import random
import sys
import chainer
import chainer.functions as cf
import chainermn
import cupy as cp
import matplotlib.pyplot as plt
import numpy as np
from chainer.backends import cuda
import gqn
from gqn.data import Dataset, Iterator
from gqn.preproc... |
9961402 | import sys
import os
import ntpath
import json
import requests
_AZFUNC_API_KEY="AZURE_FUNCTION_KEY: ex. aRVQ7Lj0vzDhY0JBYF8gpxYyEBxLwhO51JSC7X5dZFbTvROs7xNg=="
_AZFUNC_API_URL="AZURE_FUNCTION_ENDPOINT: ex. https://<app_account>.azurewebsites.net/api/<func_name>"
if __name__ == '__main__':
file_path = "/tmp/... |
9961415 | import numpy as np
from audiomate.utils import stats
from . import container
class FeatureContainer(container.Container):
"""
The FeatureContainer is a container for storing features
extracted from audio data. Features are array-like data,
where every feature represents the properties of a given segm... |
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