code stringlengths 2k 1.04M | repo_path stringlengths 5 517 | parsed_code stringlengths 0 1.04M | quality_prob float64 0.02 0.95 | learning_prob float64 0.02 0.93 |
|---|---|---|---|---|
import pytest
import numpy as np
from numpy.testing import assert_allclose
from astropy.coordinates import SkyCoord
import astropy.units as u
from astropy.wcs import WCS
from regions import (
CircleAnnulusSkyRegion,
EllipseSkyRegion,
PointSkyRegion,
PolygonSkyRegion,
CircleSkyRegion,
RectangleSk... | gammapy/modeling/models/tests/test_spatial.py | import pytest
import numpy as np
from numpy.testing import assert_allclose
from astropy.coordinates import SkyCoord
import astropy.units as u
from astropy.wcs import WCS
from regions import (
CircleAnnulusSkyRegion,
EllipseSkyRegion,
PointSkyRegion,
PolygonSkyRegion,
CircleSkyRegion,
RectangleSk... | 0.897914 | 0.734536 |
from .utils import pluralise
ALL = 'ALL'
GET = 'GET'
POST = 'POST'
PUT = 'PUT'
DELETE = 'DELETE'
CRUD = 'CRUD' # shorthand for creating the ALL|GET|POST|PUT|DELETE endpoints in one swoop
METHOD_ORDER = [ALL, GET, POST, PUT, DELETE]
ENDPOINTS = {
'Banking/': {
'name': 'banking',
'methods': [
... | myob/endpoints.py | from .utils import pluralise
ALL = 'ALL'
GET = 'GET'
POST = 'POST'
PUT = 'PUT'
DELETE = 'DELETE'
CRUD = 'CRUD' # shorthand for creating the ALL|GET|POST|PUT|DELETE endpoints in one swoop
METHOD_ORDER = [ALL, GET, POST, PUT, DELETE]
ENDPOINTS = {
'Banking/': {
'name': 'banking',
'methods': [
... | 0.399226 | 0.099121 |
import json
import re
import pkg_resources
import requests
from bs4 import BeautifulSoup
import threading
import string
import random
import time
import socket
import socks
from core.alert import *
from core.targets import target_type
from core.targets import target_to_host
from core.load_modules import load_file_path
... | lib/scan/wappalyzer/engine.py | import json
import re
import pkg_resources
import requests
from bs4 import BeautifulSoup
import threading
import string
import random
import time
import socket
import socks
from core.alert import *
from core.targets import target_type
from core.targets import target_to_host
from core.load_modules import load_file_path
... | 0.192539 | 0.065575 |
import boto
from boto.exception import EC2ResponseError
from media_nommer.conf import settings
from media_nommer.utils import logger
from media_nommer.core.job_state_backend import JobStateBackend
class EC2InstanceManager(object):
"""
This class managers and creates EC2_ instances from the configured
encod... | media_nommer/feederd/ec2_instance_manager.py | import boto
from boto.exception import EC2ResponseError
from media_nommer.conf import settings
from media_nommer.utils import logger
from media_nommer.core.job_state_backend import JobStateBackend
class EC2InstanceManager(object):
"""
This class managers and creates EC2_ instances from the configured
encod... | 0.711932 | 0.264966 |
# Import python libs
from __future__ import absolute_import
import os
import grp
import pwd
from xml.dom import minidom
import platform
import socket
# Import salt libs
import salt.utils
from salt.modules.inspectlib.exceptions import InspectorKiwiProcessorException
# Import third party libs
try:
from lxml import... | salt/modules/inspectlib/kiwiproc.py |
# Import python libs
from __future__ import absolute_import
import os
import grp
import pwd
from xml.dom import minidom
import platform
import socket
# Import salt libs
import salt.utils
from salt.modules.inspectlib.exceptions import InspectorKiwiProcessorException
# Import third party libs
try:
from lxml import... | 0.52975 | 0.081923 |
import enum
import logging
import sys
from datetime import datetime, timedelta
from arborlife import config, observer
from collections import namedtuple
logger = logging.getLogger(__name__)
ONE_HOUR = timedelta(hours=1)
Epoch = namedtuple("Epoch", "event dtime",)
class Event(enum.Enum):
EOH = enum.auto()
... | arborlife/eventloop.py | import enum
import logging
import sys
from datetime import datetime, timedelta
from arborlife import config, observer
from collections import namedtuple
logger = logging.getLogger(__name__)
ONE_HOUR = timedelta(hours=1)
Epoch = namedtuple("Epoch", "event dtime",)
class Event(enum.Enum):
EOH = enum.auto()
... | 0.390941 | 0.190592 |
from pyvmodule.ast import ASTNode
__all__ = ['expr_value_calc_funcs','expr_value_prop_funcs']
def calc_bitwise_xor(expr):
x = int(expr.rhs)
if x<0:raise ValueError('Bit reduction of infinite width value.')
i = 1
while i<=x:
x = x^(x>>i)
i<<=1
return x&1
def calc_bitwise_and... | pyvmodule/compute/value.py | from pyvmodule.ast import ASTNode
__all__ = ['expr_value_calc_funcs','expr_value_prop_funcs']
def calc_bitwise_xor(expr):
x = int(expr.rhs)
if x<0:raise ValueError('Bit reduction of infinite width value.')
i = 1
while i<=x:
x = x^(x>>i)
i<<=1
return x&1
def calc_bitwise_and... | 0.120193 | 0.344471 |
import tensorflow as tf
import feature_hash_ops
class FalconModel(object):
"""
model definition of ctr prediction network
"""
def __init__(self, numbuckets, size_per_key,feature_embedding_dim):
"""
size_per_key: key's real size in bytes
"""
self.numbuckets = numbuckets
... | example/model.py | import tensorflow as tf
import feature_hash_ops
class FalconModel(object):
"""
model definition of ctr prediction network
"""
def __init__(self, numbuckets, size_per_key,feature_embedding_dim):
"""
size_per_key: key's real size in bytes
"""
self.numbuckets = numbuckets
... | 0.857455 | 0.500366 |
import numpy as np
import torch
import torch.nn as nn
from scipy import sparse
from sklearn.metrics.pairwise import cosine_similarity
from sklearn.preprocessing import MinMaxScaler
from torch.utils.data import DataLoader
from tqdm.auto import tqdm
from recoxplainer.utils.torch_utils import use_cuda
from recoxplainer.d... | recoxplainer/models/autoencoder_model.py | import numpy as np
import torch
import torch.nn as nn
from scipy import sparse
from sklearn.metrics.pairwise import cosine_similarity
from sklearn.preprocessing import MinMaxScaler
from torch.utils.data import DataLoader
from tqdm.auto import tqdm
from recoxplainer.utils.torch_utils import use_cuda
from recoxplainer.d... | 0.905813 | 0.333775 |
import torchvision.datasets as datasets
from torchvision.datasets import VisionDataset
import os
from torch.utils.data import DataLoader, Dataset
from .transformation import *
class AlbumentationsDataset(Dataset):
def __init__(self, data, targets, transform, class_to_idx):
self.data = data
self.tar... | dataset/load_dataset.py | import torchvision.datasets as datasets
from torchvision.datasets import VisionDataset
import os
from torch.utils.data import DataLoader, Dataset
from .transformation import *
class AlbumentationsDataset(Dataset):
def __init__(self, data, targets, transform, class_to_idx):
self.data = data
self.tar... | 0.897816 | 0.713241 |
from __future__ import unicode_literals
from django.db import models, migrations
from django.conf import settings
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('ancfindersite', '0001_initial'),
]
operations = [
... | ancfindersite/migrations/0002_commissionerinfo.py | from __future__ import unicode_literals
from django.db import models, migrations
from django.conf import settings
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('ancfindersite', '0001_initial'),
]
operations = [
... | 0.590543 | 0.138491 |
from tkinter import Toplevel, StringVar, N, S, E, W, EW, DISABLED, NORMAL, messagebox
try:
from tkinter.ttk import Frame, Button, Label, Entry
except ImportError:
from ttk import Frame, Button, Label, Entry
from arelle.CntlrWinTooltip import ToolTip
from arelle.UiUtil import checkbox, gridCombobox
import sys
tr... | arelle/DialogUserPassword.py | from tkinter import Toplevel, StringVar, N, S, E, W, EW, DISABLED, NORMAL, messagebox
try:
from tkinter.ttk import Frame, Button, Label, Entry
except ImportError:
from ttk import Frame, Button, Label, Entry
from arelle.CntlrWinTooltip import ToolTip
from arelle.UiUtil import checkbox, gridCombobox
import sys
tr... | 0.237046 | 0.066569 |
import uuid
import torch
import argparse
import matplotlib
import numpy as np
import pandas as pd
matplotlib.use('Agg')
import seaborn as sns
from pathlib import Path
import matplotlib.pyplot as plt
from external_libs.hessian_eigenthings import compute_hessian_eigenthings
TRIAL_ID = uuid.uuid4().hex.upper()[0:6]
EXPE... | other_models/stable_sgd/stable_sgd/utils.py | import uuid
import torch
import argparse
import matplotlib
import numpy as np
import pandas as pd
matplotlib.use('Agg')
import seaborn as sns
from pathlib import Path
import matplotlib.pyplot as plt
from external_libs.hessian_eigenthings import compute_hessian_eigenthings
TRIAL_ID = uuid.uuid4().hex.upper()[0:6]
EXPE... | 0.605099 | 0.179099 |
from torch import nn, einsum
from einops import rearrange
from einops.layers.torch import Rearrange
from math import sqrt
class Residual(nn.Module):
def __init__(self, fn):
super().__init__()
self.fn = fn
def forward(self, x, **kwargs):
return self.fn(x, **kwargs) + x
class PreNorm(nn.... | module.py | from torch import nn, einsum
from einops import rearrange
from einops.layers.torch import Rearrange
from math import sqrt
class Residual(nn.Module):
def __init__(self, fn):
super().__init__()
self.fn = fn
def forward(self, x, **kwargs):
return self.fn(x, **kwargs) + x
class PreNorm(nn.... | 0.965119 | 0.362165 |
import pytest
import os
import time
from pathlib import Path
from hashlib import blake2b
from gtmcore.dataset.manifest.hash import SmartHash
from gtmcore.fixtures.datasets import mock_dataset_with_cache_dir, mock_dataset_with_manifest
def helper_append_file(cache_dir, revision, rel_path, content):
with open(os.p... | packages/gtmcore/gtmcore/dataset/tests/test_hash.py | import pytest
import os
import time
from pathlib import Path
from hashlib import blake2b
from gtmcore.dataset.manifest.hash import SmartHash
from gtmcore.fixtures.datasets import mock_dataset_with_cache_dir, mock_dataset_with_manifest
def helper_append_file(cache_dir, revision, rel_path, content):
with open(os.p... | 0.514156 | 0.285397 |
import tensorflow as tf
# Solve the differential equations using Euler method
@tf.function(autograph=True,experimental_relax_shapes=True)
def riekeModel(X_fun,TimeStep,sigma,phi,eta,cgmp2cur,cgmphill,cdark,beta,betaSlow,hillcoef,hillaffinity,gamma,gdark):
darkCurrent = gdark**cgmphill * cgmp2cur/2
gdark = (2 *... | dynRetModels.py | import tensorflow as tf
# Solve the differential equations using Euler method
@tf.function(autograph=True,experimental_relax_shapes=True)
def riekeModel(X_fun,TimeStep,sigma,phi,eta,cgmp2cur,cgmphill,cdark,beta,betaSlow,hillcoef,hillaffinity,gamma,gdark):
darkCurrent = gdark**cgmphill * cgmp2cur/2
gdark = (2 *... | 0.778944 | 0.400046 |
try:
from inspect import getfullargspec
except ImportError:
from inspect import getargspec as getfullargspec
import pprint
import re # noqa: F401
import six
from openapi_client.configuration import Configuration
class TypesStatus(object):
"""NOTE: This class is auto generated by OpenAPI Generator.
R... | openapi_client/models/types_status.py | try:
from inspect import getfullargspec
except ImportError:
from inspect import getargspec as getfullargspec
import pprint
import re # noqa: F401
import six
from openapi_client.configuration import Configuration
class TypesStatus(object):
"""NOTE: This class is auto generated by OpenAPI Generator.
R... | 0.59408 | 0.092033 |
from tensorflow.keras.datasets import mnist
from tensorflow.keras import layers, regularizers
from tensorflow import keras
import tensorflow as tf
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' # change to 2
class style():
BLACK = '\033[30m'
RED = '\033[31m'
GREEN = '\033[32m'
YELLOW = '\033[33m'... | project/10-save-and-load.py | from tensorflow.keras.datasets import mnist
from tensorflow.keras import layers, regularizers
from tensorflow import keras
import tensorflow as tf
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' # change to 2
class style():
BLACK = '\033[30m'
RED = '\033[31m'
GREEN = '\033[32m'
YELLOW = '\033[33m'... | 0.686475 | 0.38885 |
import imp
import os
import numpy as np
from pyrl import utils
from pyrl.figtools import Figure
#=========================================================================================
# Files
#=========================================================================================
here = ... | paper/fig_rdm_value.py | import imp
import os
import numpy as np
from pyrl import utils
from pyrl.figtools import Figure
#=========================================================================================
# Files
#=========================================================================================
here = ... | 0.349311 | 0.100437 |
class DataObjectFieldAttribute(Attribute,_Attribute):
"""
Provides metadata for a property representing a data field. This class cannot be inherited.
DataObjectFieldAttribute(primaryKey: bool)
DataObjectFieldAttribute(primaryKey: bool,isIdentity: bool)
DataObjectFieldAttribute(primaryKey: bool,isIdenti... | stubs.min/System/ComponentModel/__init___parts/DataObjectFieldAttribute.py | class DataObjectFieldAttribute(Attribute,_Attribute):
"""
Provides metadata for a property representing a data field. This class cannot be inherited.
DataObjectFieldAttribute(primaryKey: bool)
DataObjectFieldAttribute(primaryKey: bool,isIdentity: bool)
DataObjectFieldAttribute(primaryKey: bool,isIdenti... | 0.802865 | 0.392803 |
from typing import List, TYPE_CHECKING, cast
from constants import KILLER_CLAIM, role_recycling, \
target_single_flag
from creeps.behaviors.military import MilitaryBase
from empire import stored_data
from jstools.screeps import *
from utilities import movement
if TYPE_CHECKING:
pass
__pragma__('noalias', 'na... | src/creeps/roles/cleaning.py | from typing import List, TYPE_CHECKING, cast
from constants import KILLER_CLAIM, role_recycling, \
target_single_flag
from creeps.behaviors.military import MilitaryBase
from empire import stored_data
from jstools.screeps import *
from utilities import movement
if TYPE_CHECKING:
pass
__pragma__('noalias', 'na... | 0.603465 | 0.157493 |
from django.conf.urls import patterns, url
from django.views.generic import RedirectView
from . import views
APP_SLUGS = {
'chrono': 'Chrono',
'face_value': 'Face_Value',
'podcasts': 'Podcasts',
'roller': 'Roller',
'webfighter': 'Webfighter',
'generalnotes': 'General_Notes',
'rtcamera': '... | mkt/ecosystem/urls.py | from django.conf.urls import patterns, url
from django.views.generic import RedirectView
from . import views
APP_SLUGS = {
'chrono': 'Chrono',
'face_value': 'Face_Value',
'podcasts': 'Podcasts',
'roller': 'Roller',
'webfighter': 'Webfighter',
'generalnotes': 'General_Notes',
'rtcamera': '... | 0.436142 | 0.058319 |
from utils.video_generator import VideoGenerator
from utils.video_writer import *
import numpy as np
import argparse
# locate all concat layers for visualization
def return_concat_layers(layers):
"""Returns a list of every concatenation layer at the end of each I3D block
Parameters
----------
la... | activation_visualizer.py | from utils.video_generator import VideoGenerator
from utils.video_writer import *
import numpy as np
import argparse
# locate all concat layers for visualization
def return_concat_layers(layers):
"""Returns a list of every concatenation layer at the end of each I3D block
Parameters
----------
la... | 0.856902 | 0.481941 |
import pandas as pd
import numpy as np
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error
from sklearn.linear_model import LinearRegression
from sklearn.tree import DecisionTreeRegressor
from sklearn.ensemble import Rand... | scripts/regression.py | import pandas as pd
import numpy as np
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error
from sklearn.linear_model import LinearRegression
from sklearn.tree import DecisionTreeRegressor
from sklearn.ensemble import Rand... | 0.576542 | 0.459319 |
import sys
import os
import getopt
import gkeepapi
import keyring
import getpass
import requests
import imghdr
import shutil
import re
import time
import configparser
import click
from pathlib import Path
from collections import namedtuple
KEEP_CACHE = 'kdata.json'
KEEP_KEYRING_ID = 'google-keep-token'
KEEP_NOTE_URL =... | kim.py | import sys
import os
import getopt
import gkeepapi
import keyring
import getpass
import requests
import imghdr
import shutil
import re
import time
import configparser
import click
from pathlib import Path
from collections import namedtuple
KEEP_CACHE = 'kdata.json'
KEEP_KEYRING_ID = 'google-keep-token'
KEEP_NOTE_URL =... | 0.247532 | 0.07921 |
import os
import json
import requests
import datetime
import time
from tqdm import tqdm
from multiprocessing import Pool
def divide_chunks(l, n):
for i in range(0, len(l), n):
yield l[i : i + n]
app_key = ""
app_id = ""
with open("credentials.json", "r") as cred_file:
creds = json.load(cred_file)
... | get_directions.py | import os
import json
import requests
import datetime
import time
from tqdm import tqdm
from multiprocessing import Pool
def divide_chunks(l, n):
for i in range(0, len(l), n):
yield l[i : i + n]
app_key = ""
app_id = ""
with open("credentials.json", "r") as cred_file:
creds = json.load(cred_file)
... | 0.069073 | 0.093182 |
import sys
import argparse
#位置合わせパターンの座標
alignment_pattern_array = [
[],
[6, 18],
[6, 22],
[6, 26],
[6, 30],
[6, 34],
[6, 22, 38],
[6, 24, 42],
[6, 26, 46],
[6, 28, 50],
[6, 30, 54],
[6, 32, 58],
[6, 34, 62],
[6, 26, 46, 66],
[6, 26, 48, 70],
[6, 26, 50, 74],
[6, 30, 54, 78],
[6, 30, 56, 82],
[6, 30, 58, 86],
[6, 34,... | sqrd.py |
import sys
import argparse
#位置合わせパターンの座標
alignment_pattern_array = [
[],
[6, 18],
[6, 22],
[6, 26],
[6, 30],
[6, 34],
[6, 22, 38],
[6, 24, 42],
[6, 26, 46],
[6, 28, 50],
[6, 30, 54],
[6, 32, 58],
[6, 34, 62],
[6, 26, 46, 66],
[6, 26, 48, 70],
[6, 26, 50, 74],
[6, 30, 54, 78],
[6, 30, 56, 82],
[6, 30, 58, 86],
[6, 34,... | 0.16492 | 0.38266 |
from django.contrib import admin
from django.contrib import messages
from django.http import HttpResponseRedirect
from django.contrib.auth import get_permission_codename
from django.utils.translation import ugettext_lazy as _
from . import conf
class ReadOnlyMixin(object):
read_only_per_codename = conf.READONLY_... | admin_extras/admin.py | from django.contrib import admin
from django.contrib import messages
from django.http import HttpResponseRedirect
from django.contrib.auth import get_permission_codename
from django.utils.translation import ugettext_lazy as _
from . import conf
class ReadOnlyMixin(object):
read_only_per_codename = conf.READONLY_... | 0.38943 | 0.055797 |
from typing import Optional
import torch
from torch import Tensor
from fracdiff.fdiff import fdiff_coef as fdiff_coef_numpy
def fdiff_coef(d: float, window: int) -> Tensor:
"""Returns sequence of coefficients in fracdiff operator.
Args:
d : float
Order of differentiation.
window... | fracdiff/torch/functional.py | from typing import Optional
import torch
from torch import Tensor
from fracdiff.fdiff import fdiff_coef as fdiff_coef_numpy
def fdiff_coef(d: float, window: int) -> Tensor:
"""Returns sequence of coefficients in fracdiff operator.
Args:
d : float
Order of differentiation.
window... | 0.900414 | 0.759315 |
import cv2
from PyQt5.QtCore import *
from PyQt5.QtWidgets import *
from PyQt5.QtGui import *
import numpy as np
import time
class Videothread(QThread, QObject):
videothread_signal = pyqtSignal(dict)
camera_error_signal = pyqtSignal()
# plotROI_signl = pyqtSignal(dict)
def __init__(self):
'''... | client/ui/gui_thread.py | import cv2
from PyQt5.QtCore import *
from PyQt5.QtWidgets import *
from PyQt5.QtGui import *
import numpy as np
import time
class Videothread(QThread, QObject):
videothread_signal = pyqtSignal(dict)
camera_error_signal = pyqtSignal()
# plotROI_signl = pyqtSignal(dict)
def __init__(self):
'''... | 0.255251 | 0.198549 |
import logging
from pprint import pprint
import markdown
from django.conf import settings
from django.core.mail import send_mail
from django.template import Context, Engine
from messages_extends import constants as message_constants
from readthedocs.notifications import SiteNotification
from readthedocs.notifications... | readthedocs/core/utils/contact.py | import logging
from pprint import pprint
import markdown
from django.conf import settings
from django.core.mail import send_mail
from django.template import Context, Engine
from messages_extends import constants as message_constants
from readthedocs.notifications import SiteNotification
from readthedocs.notifications... | 0.517815 | 0.148633 |
import os
import sys
import xml.etree.ElementTree as ET
if sys.version_info[0] >= 3:
import urllib.request as url_request
import urllib.parse as url_parse
import urllib.error as url_error
else:
import urllib2 as url_request
import urllib as url_parse
import urllib2 as url_error
import pandas as... | fredapi/fred.py | import os
import sys
import xml.etree.ElementTree as ET
if sys.version_info[0] >= 3:
import urllib.request as url_request
import urllib.parse as url_parse
import urllib.error as url_error
else:
import urllib2 as url_request
import urllib as url_parse
import urllib2 as url_error
import pandas as... | 0.590071 | 0.25124 |
"""Text style transfer
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
# pylint: disable=invalid-name, too-many-locals
import tensorflow as tf
import texar as tx
from texar.modules import WordEmbedder, UnidirectionalRNNEncoder, \
MLPTransformCo... | examples/text_style_transfer/ctrl_gen_model.py | """Text style transfer
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
# pylint: disable=invalid-name, too-many-locals
import tensorflow as tf
import texar as tx
from texar.modules import WordEmbedder, UnidirectionalRNNEncoder, \
MLPTransformCo... | 0.928347 | 0.227126 |
from django.conf.urls import url
from django.contrib.auth import views as auth_views
from . import views, tables, api
app_name = 'dz'
urlpatterns = [
url(r'^$', views.index, name='index'),
url(r'^login/$', auth_views.login,
{'template_name': 'dz/tables/login.html'}, name='login'),
url(r'^tables/ne... | dz/urls.py | from django.conf.urls import url
from django.contrib.auth import views as auth_views
from . import views, tables, api
app_name = 'dz'
urlpatterns = [
url(r'^$', views.index, name='index'),
url(r'^login/$', auth_views.login,
{'template_name': 'dz/tables/login.html'}, name='login'),
url(r'^tables/ne... | 0.217005 | 0.080177 |
# articlestats.xls
# start sheet 'referencesamples'
# worksheet.cell(7, 4).value == 'article ID'
# articleid ids [8,4] (or reverse) for full text for sheet_names
import xlrd
import sys
class DupHolder:
def __init__(self, placename):
self.placename = placename
self.dict_id_measure = {}
s... | collect-data.py |
# articlestats.xls
# start sheet 'referencesamples'
# worksheet.cell(7, 4).value == 'article ID'
# articleid ids [8,4] (or reverse) for full text for sheet_names
import xlrd
import sys
class DupHolder:
def __init__(self, placename):
self.placename = placename
self.dict_id_measure = {}
s... | 0.117534 | 0.238495 |
"""API for Tensorflow Model Analysis."""
# TODO(b/149126671): Put ValidationResultsWriter in a separate file.
from __future__ import absolute_import
from __future__ import division
# Standard __future__ imports
from __future__ import print_function
import os
import tempfile
from typing import Any, Dict, Iterator, L... | tensorflow_model_analysis/api/model_eval_lib.py | """API for Tensorflow Model Analysis."""
# TODO(b/149126671): Put ValidationResultsWriter in a separate file.
from __future__ import absolute_import
from __future__ import division
# Standard __future__ imports
from __future__ import print_function
import os
import tempfile
from typing import Any, Dict, Iterator, L... | 0.666714 | 0.303009 |
from baconian.algo.algo import Algo
from baconian.algo.dynamics.dynamics_model import DynamicsModel
from baconian.core.core import EnvSpec
from baconian.common.logging import record_return_decorator
import numpy as np
class ModelFreeAlgo(Algo):
def __init__(self, env_spec: EnvSpec, name: str = 'model_free_algo', ... | baconian/algo/rl_algo.py | from baconian.algo.algo import Algo
from baconian.algo.dynamics.dynamics_model import DynamicsModel
from baconian.core.core import EnvSpec
from baconian.common.logging import record_return_decorator
import numpy as np
class ModelFreeAlgo(Algo):
def __init__(self, env_spec: EnvSpec, name: str = 'model_free_algo', ... | 0.743261 | 0.194578 |
from ansible.module_utils.hashivault import hashivault_argspec
from ansible.module_utils.hashivault import hashivault_auth_client
from ansible.module_utils.hashivault import hashivault_init
from ansible.module_utils.hashivault import hashiwrapper
ANSIBLE_METADATA = {'status': ['stableinterface'], 'supported_by': 'comm... | ansible/modules/hashivault/hashivault_token_create.py | from ansible.module_utils.hashivault import hashivault_argspec
from ansible.module_utils.hashivault import hashivault_auth_client
from ansible.module_utils.hashivault import hashivault_init
from ansible.module_utils.hashivault import hashiwrapper
ANSIBLE_METADATA = {'status': ['stableinterface'], 'supported_by': 'comm... | 0.792384 | 0.346293 |
from .model import Model
from .stepmodel import Step
class Scenario(Model):
"""
Represents a Scenario
"""
def __init__(self, id, keyword, sentence, path, line, parent, tags=None, preconditions=None, background=None):
super(Scenario, self).__init__(id, keyword, sentence, path, line, parent,... | radish/scenario.py | from .model import Model
from .stepmodel import Step
class Scenario(Model):
"""
Represents a Scenario
"""
def __init__(self, id, keyword, sentence, path, line, parent, tags=None, preconditions=None, background=None):
super(Scenario, self).__init__(id, keyword, sentence, path, line, parent,... | 0.725551 | 0.342159 |
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_in... | collector_service_sdk/api/metric/get_metric_name_detail_pb2.py |
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_in... | 0.256739 | 0.124372 |
import json
from psycopg2.extras import DateRange, DateTimeTZRange, NumericRange, Range
from django.contrib.postgres import forms, lookups
from django.db import models
from django.utils import six
from .utils import AttributeSetter
__all__ = [
'RangeField', 'IntegerRangeField', 'BigIntegerRangeField',
'Floa... | django/contrib/postgres/fields/ranges.py | import json
from psycopg2.extras import DateRange, DateTimeTZRange, NumericRange, Range
from django.contrib.postgres import forms, lookups
from django.db import models
from django.utils import six
from .utils import AttributeSetter
__all__ = [
'RangeField', 'IntegerRangeField', 'BigIntegerRangeField',
'Floa... | 0.627267 | 0.213972 |
import logging
import pprint
import socket
import subprocess
import time
import traceback
import unittest
from magma.pipelined.bridge_util import BridgeTools
from magma.pipelined.qos.qos_tc_impl import TrafficClass
from magma.pipelined.qos.tc_ops_cmd import TcOpsCmd
from magma.pipelined.qos.tc_ops_pyroute2 import TcOp... | lte/gateway/python/magma/pipelined/tests/test_qos_pyroute2.py | import logging
import pprint
import socket
import subprocess
import time
import traceback
import unittest
from magma.pipelined.bridge_util import BridgeTools
from magma.pipelined.qos.qos_tc_impl import TrafficClass
from magma.pipelined.qos.tc_ops_cmd import TcOpsCmd
from magma.pipelined.qos.tc_ops_pyroute2 import TcOp... | 0.19923 | 0.259038 |
import re
import pytest
from inifile import IniFile
from lektor.markdown import (
ImprovedRenderer,
MarkdownConfig,
)
from lektor_responsive_image import (
ResponsiveImage,
resolve_image,
ResponsiveImageMixin,
ResponsiveImagePlugin,
)
class DummyImage(object):
def __init__(self,... | tests/test_plugin.py | import re
import pytest
from inifile import IniFile
from lektor.markdown import (
ImprovedRenderer,
MarkdownConfig,
)
from lektor_responsive_image import (
ResponsiveImage,
resolve_image,
ResponsiveImageMixin,
ResponsiveImagePlugin,
)
class DummyImage(object):
def __init__(self,... | 0.553747 | 0.404978 |
import os
import sys
from zope.interface import Interface, implementer
from subprocess import check_output, STDOUT, CalledProcessError
from twisted.python.compat import execfile
from twisted.python.filepath import FilePath
from twisted.python.monkey import MonkeyPatcher
# Types of newsfragments.
NEWSFRAGMENT_TYPES ... | TheFuzzer/lib/python2.7/site-packages/twisted/python/_release.py | import os
import sys
from zope.interface import Interface, implementer
from subprocess import check_output, STDOUT, CalledProcessError
from twisted.python.compat import execfile
from twisted.python.filepath import FilePath
from twisted.python.monkey import MonkeyPatcher
# Types of newsfragments.
NEWSFRAGMENT_TYPES ... | 0.490724 | 0.262062 |
import argparse
import pathlib
from collections import OrderedDict
import numpy as np
from typing import Dict, Tuple, Any, Optional
from sklearn.preprocessing import LabelEncoder
import torch
from torch import nn
from torch.nn import functional as F
from torch import optim
from torch.utils.data import TensorDataset, r... | sigver/featurelearning/train.py | import argparse
import pathlib
from collections import OrderedDict
import numpy as np
from typing import Dict, Tuple, Any, Optional
from sklearn.preprocessing import LabelEncoder
import torch
from torch import nn
from torch.nn import functional as F
from torch import optim
from torch.utils.data import TensorDataset, r... | 0.945876 | 0.454835 |
import os
import sys
import compound
import networkx as nx
import json
import calculate_penalties
import requests
from unsaturated_monosaccharides import unsaturated_carb_17
from linear_substructures import type_linear_structures_generic
from rings_substructures import find_xylos_rings
from find_fragments import find... | main.py | import os
import sys
import compound
import networkx as nx
import json
import calculate_penalties
import requests
from unsaturated_monosaccharides import unsaturated_carb_17
from linear_substructures import type_linear_structures_generic
from rings_substructures import find_xylos_rings
from find_fragments import find... | 0.26341 | 0.216954 |
from sysinv.common import constants as sysinv_constants
from tsconfig import tsconfig
CONFIG_WORKDIR = '/tmp/config'
CGCS_CONFIG_FILE = CONFIG_WORKDIR + '/cgcs_config'
CONFIG_PERMDIR = tsconfig.CONFIG_PATH
HIERADATA_WORKDIR = '/tmp/hieradata'
HIERADATA_PERMDIR = tsconfig.PUPPET_PATH + 'hieradata'
KEYRING_WORKDIR =... | controllerconfig/controllerconfig/controllerconfig/common/constants.py |
from sysinv.common import constants as sysinv_constants
from tsconfig import tsconfig
CONFIG_WORKDIR = '/tmp/config'
CGCS_CONFIG_FILE = CONFIG_WORKDIR + '/cgcs_config'
CONFIG_PERMDIR = tsconfig.CONFIG_PATH
HIERADATA_WORKDIR = '/tmp/hieradata'
HIERADATA_PERMDIR = tsconfig.PUPPET_PATH + 'hieradata'
KEYRING_WORKDIR =... | 0.201892 | 0.039919 |
import json
from .readers import csv, UNICODE_CSV, SkipPreludeReader
from xml.etree import ElementTree as ET
from .base import BaseParser, TableParser
from ..exceptions import ParseFailed
class CsvParser(TableParser):
delimiter = ","
quotechar = '"'
no_pickle_parser = ['csvdata']
binary = UNICODE_CSV... | itertable/parsers/text.py | import json
from .readers import csv, UNICODE_CSV, SkipPreludeReader
from xml.etree import ElementTree as ET
from .base import BaseParser, TableParser
from ..exceptions import ParseFailed
class CsvParser(TableParser):
delimiter = ","
quotechar = '"'
no_pickle_parser = ['csvdata']
binary = UNICODE_CSV... | 0.316581 | 0.081119 |
import numpy as np
def transition_rates(hv, hmv, fv, fmv, N=4):
"""outputs the matrix for the dynamics of Markovian jump process with odd-parity in a N-site ring.
Parameters: hv : float
transition rate from (n,v) to (n+v,v)
hmv: float
transition rate f... | data/odd_markov_jump.py | import numpy as np
def transition_rates(hv, hmv, fv, fmv, N=4):
"""outputs the matrix for the dynamics of Markovian jump process with odd-parity in a N-site ring.
Parameters: hv : float
transition rate from (n,v) to (n+v,v)
hmv: float
transition rate f... | 0.903772 | 0.713909 |
from logging import ERROR
import d4rl_pybullet
import gym
import numpy as np
import torch
from training import TransitionDataset
gym.logger.set_level(ERROR) # Ignore warnings from Gym logger
D4RL_ENV_NAMES = ['ant-bullet-medium-v0', 'halfcheetah-bullet-medium-v0', 'hopper-bullet-medium-v0', 'walker2d-bullet-medium... | environments.py | from logging import ERROR
import d4rl_pybullet
import gym
import numpy as np
import torch
from training import TransitionDataset
gym.logger.set_level(ERROR) # Ignore warnings from Gym logger
D4RL_ENV_NAMES = ['ant-bullet-medium-v0', 'halfcheetah-bullet-medium-v0', 'hopper-bullet-medium-v0', 'walker2d-bullet-medium... | 0.799716 | 0.462837 |
import os
import copy
import torch
import pickle
import numpy as np
from language import Lang
def initialize_env(config):
try:
os.mkdir(config['root'])
except:
print("Directory found!!!!")
config['batch_size'] = int(config['batch_size'])
config['bidirectional'] = True if config['bidir... | utils.py | import os
import copy
import torch
import pickle
import numpy as np
from language import Lang
def initialize_env(config):
try:
os.mkdir(config['root'])
except:
print("Directory found!!!!")
config['batch_size'] = int(config['batch_size'])
config['bidirectional'] = True if config['bidir... | 0.444083 | 0.141548 |
from __future__ import unicode_literals
from django.db import models, transaction
from django.db.models import PROTECT
from django.db.models.signals import post_save, pre_delete
from django.utils.translation import ugettext_lazy as _
from river.config import app_config
from river.models import Workflow
from river.mod... | river/models/transitionapprovalmeta.py | from __future__ import unicode_literals
from django.db import models, transaction
from django.db.models import PROTECT
from django.db.models.signals import post_save, pre_delete
from django.utils.translation import ugettext_lazy as _
from river.config import app_config
from river.models import Workflow
from river.mod... | 0.595022 | 0.080105 |
from flask import Flask, jsonify, redirect, request, send_from_directory, Response
from io import StringIO
from github import Github, UnknownObjectException
from os import environ, path, rename, listdir
import re
import requests
from shutil import copytree, rmtree
from storage import set_status, get_status, set_badge, ... | main.py | from flask import Flask, jsonify, redirect, request, send_from_directory, Response
from io import StringIO
from github import Github, UnknownObjectException
from os import environ, path, rename, listdir
import re
import requests
from shutil import copytree, rmtree
from storage import set_status, get_status, set_badge, ... | 0.287568 | 0.0771 |
from flask import Flask, abort, jsonify, request
import requests, json
from marshmallow import EXCLUDE
from .. import vloads as createGOTreeTestUniverseFromAPI
from .. import uloads as createGOTreeTestFromAPI
from .. import utils
from .io import checkPwasInput
from ..stat_utils import applyOraToVector, kappaClustering
... | src/unigo/api/pwas.py | from flask import Flask, abort, jsonify, request
import requests, json
from marshmallow import EXCLUDE
from .. import vloads as createGOTreeTestUniverseFromAPI
from .. import uloads as createGOTreeTestFromAPI
from .. import utils
from .io import checkPwasInput
from ..stat_utils import applyOraToVector, kappaClustering
... | 0.31216 | 0.207415 |
import argparse
import shlex
from itertools import islice
from typing import List, NamedTuple, Dict
from redbot.core.commands import RoleConverter, Context, BadArgument, GuildContext
import discord
_RoleConverter = RoleConverter()
class NoExitParser(argparse.ArgumentParser):
def error(self, message):
r... | rolemanagement/converters.py | import argparse
import shlex
from itertools import islice
from typing import List, NamedTuple, Dict
from redbot.core.commands import RoleConverter, Context, BadArgument, GuildContext
import discord
_RoleConverter = RoleConverter()
class NoExitParser(argparse.ArgumentParser):
def error(self, message):
r... | 0.707607 | 0.162546 |
import ply.yacc as yacc
from nodes import *
import lexer
# Get the token map.
tokens = lexer.tokens
precedence = (
('left', 'OR'),
('left', 'AND'),
('nonassoc', 'LE', 'LE', 'GE', 'GT', 'EQ', 'NE'), # Nonassociative operators
)
def p_start(p):
""" start : command ';' """
p[0] = p[1]
def p_com... | test/testflask/dsltest/parser.py |
import ply.yacc as yacc
from nodes import *
import lexer
# Get the token map.
tokens = lexer.tokens
precedence = (
('left', 'OR'),
('left', 'AND'),
('nonassoc', 'LE', 'LE', 'GE', 'GT', 'EQ', 'NE'), # Nonassociative operators
)
def p_start(p):
""" start : command ';' """
p[0] = p[1]
def p_com... | 0.203193 | 0.557062 |
## Binary Analysis Tool
## Copyright 2014-2015 <NAME> for Tjaldur Software Governance Solutions
## Licensed under Apache 2.0, see LICENSE file for details
import sys, os, os.path
import sqlite3
from optparse import OptionParser
def main(argv):
alpha = 5.0
parser = OptionParser()
parser.add_option("-d", "--databa... | src/maintenance/scorecache.py |
## Binary Analysis Tool
## Copyright 2014-2015 <NAME> for Tjaldur Software Governance Solutions
## Licensed under Apache 2.0, see LICENSE file for details
import sys, os, os.path
import sqlite3
from optparse import OptionParser
def main(argv):
alpha = 5.0
parser = OptionParser()
parser.add_option("-d", "--databa... | 0.26218 | 0.135489 |
import os
from typing import Iterable, Tuple, Union
from ..functional.inplace import _inplace_add_
from ..tensor import Parameter, tensor
from .optimizer import Optimizer
class Adam(Optimizer):
r"""
Implements Adam algorithm proposed in `"Adam: A Method for Stochastic Optimization" <https://arxiv.org/abs/141... | imperative/python/megengine/optimizer/adam.py | import os
from typing import Iterable, Tuple, Union
from ..functional.inplace import _inplace_add_
from ..tensor import Parameter, tensor
from .optimizer import Optimizer
class Adam(Optimizer):
r"""
Implements Adam algorithm proposed in `"Adam: A Method for Stochastic Optimization" <https://arxiv.org/abs/141... | 0.874359 | 0.429011 |
import os,time,cv2, sys, math
import bchlib
import tensorflow as tf
import argparse
import numpy as np
import tensorflow.contrib.image
from tensorflow.python.saved_model import tag_constants
from tensorflow.python.saved_model import signature_constants
parser = argparse.ArgumentParser()
parser.add_argument('--detector... | detector.py | import os,time,cv2, sys, math
import bchlib
import tensorflow as tf
import argparse
import numpy as np
import tensorflow.contrib.image
from tensorflow.python.saved_model import tag_constants
from tensorflow.python.saved_model import signature_constants
parser = argparse.ArgumentParser()
parser.add_argument('--detector... | 0.418222 | 0.231039 |
import pytest
import torch
from copy import deepcopy
from pytest import approx
from torch import nn
from nncf.compression_method_api import PTStubCompressionScheduler
from nncf.config import NNCFConfig
from nncf.module_operations import UpdateWeight
from nncf.sparsity.rb.algo import RBSparsityController
from nncf.spar... | tests/sparsity/rb/test_algo.py | import pytest
import torch
from copy import deepcopy
from pytest import approx
from torch import nn
from nncf.compression_method_api import PTStubCompressionScheduler
from nncf.config import NNCFConfig
from nncf.module_operations import UpdateWeight
from nncf.sparsity.rb.algo import RBSparsityController
from nncf.spar... | 0.903095 | 0.558447 |
# NOTE: This file is autogenerated and should not be edited by hand.
from apitools.base.py import base_api
from googlecloudsdk.third_party.apis.dataproc.v1beta2 import dataproc_v1beta2_messages as messages
class DataprocV1beta2(base_api.BaseApiClient):
"""Generated client library for service dataproc version v1beta... | google-cloud-sdk/lib/googlecloudsdk/third_party/apis/dataproc/v1beta2/dataproc_v1beta2_client.py | # NOTE: This file is autogenerated and should not be edited by hand.
from apitools.base.py import base_api
from googlecloudsdk.third_party.apis.dataproc.v1beta2 import dataproc_v1beta2_messages as messages
class DataprocV1beta2(base_api.BaseApiClient):
"""Generated client library for service dataproc version v1beta... | 0.77535 | 0.077169 |
import re
import sublime
from sublime_plugin import EventListener, TextCommand, WindowCommand
from ..runtime import enqueue_on_worker
from ..git_command import GitCommand
from ..ui_mixins.quick_panel import PanelCommandMixin
from ..ui_mixins.quick_panel import show_stash_panel
from ..ui_mixins.input_panel import show... | core/commands/stash.py | import re
import sublime
from sublime_plugin import EventListener, TextCommand, WindowCommand
from ..runtime import enqueue_on_worker
from ..git_command import GitCommand
from ..ui_mixins.quick_panel import PanelCommandMixin
from ..ui_mixins.quick_panel import show_stash_panel
from ..ui_mixins.input_panel import show... | 0.531939 | 0.100525 |
import sys
import subprocess
COLOR_NORM = '\x1B[0m' # normal color
COLOR_ERR = '\x1B[1;31m' # bold red
COLOR_NOMSGS= '\x1B[1;32m' # bold green
COLOR_SUBJ = COLOR_NORM
COLOR_DATE = '\x1B[1;34m' # bold blue
COLOR_TIME = '\x1B[1;32m' # bold green
COLOR_FROM = '\x1B[0;33m' # yellow
STR_ERR = COLOR_ERR + 'ERROR: ' + COL... | mail/check_new_mail.osx.py | import sys
import subprocess
COLOR_NORM = '\x1B[0m' # normal color
COLOR_ERR = '\x1B[1;31m' # bold red
COLOR_NOMSGS= '\x1B[1;32m' # bold green
COLOR_SUBJ = COLOR_NORM
COLOR_DATE = '\x1B[1;34m' # bold blue
COLOR_TIME = '\x1B[1;32m' # bold green
COLOR_FROM = '\x1B[0;33m' # yellow
STR_ERR = COLOR_ERR + 'ERROR: ' + COL... | 0.07295 | 0.093471 |
from __future__ import print_function
import os
import shutil
import socket
import datetime
import json
import numpy as np
try:
import ConfigParser as configparser
except ImportError:
import configparser
import astropy.io.fits as pyfits
import lsst.cr_eotest.sensor as sensorTest
import lcatr.schema
from lcatr.h... | python/eotestUtils.py | from __future__ import print_function
import os
import shutil
import socket
import datetime
import json
import numpy as np
try:
import ConfigParser as configparser
except ImportError:
import configparser
import astropy.io.fits as pyfits
import lsst.cr_eotest.sensor as sensorTest
import lcatr.schema
from lcatr.h... | 0.522933 | 0.167219 |
import factory
from modoboa.core.factories import PermissionFactory, UserFactory
from . import models
class DomainFactory(PermissionFactory):
"""Factory to create Domains."""
class Meta:
model = models.Domain
django_get_or_create = ("name", )
name = factory.Sequence(lambda n: "domain{}... | modoboa/admin/factories.py | import factory
from modoboa.core.factories import PermissionFactory, UserFactory
from . import models
class DomainFactory(PermissionFactory):
"""Factory to create Domains."""
class Meta:
model = models.Domain
django_get_or_create = ("name", )
name = factory.Sequence(lambda n: "domain{}... | 0.555918 | 0.229719 |
from utility.utils import validate_email, validate_user_input_to_int
class Account:
def __init__(self, name, email, password, balance):
if validate_email(email):
self.account_name = name
self.account_email = email
self.account_password = password
self.acco... | bank/bank.py | from utility.utils import validate_email, validate_user_input_to_int
class Account:
def __init__(self, name, email, password, balance):
if validate_email(email):
self.account_name = name
self.account_email = email
self.account_password = password
self.acco... | 0.602296 | 0.302752 |
import pytest
from pyha import Hardware, Sfix, Complex, simulate, sims_close
import numpy as np
from pyha.cores import Cordic, CordicMode
class NCO(Hardware):
"""
Baseband signal generator. Integrated phase accumulator.
"""
def __init__(self, cordic_iterations=14):
"""
:param cordic... | pyha/cores/cordic/nco/nco.py | import pytest
from pyha import Hardware, Sfix, Complex, simulate, sims_close
import numpy as np
from pyha.cores import Cordic, CordicMode
class NCO(Hardware):
"""
Baseband signal generator. Integrated phase accumulator.
"""
def __init__(self, cordic_iterations=14):
"""
:param cordic... | 0.814975 | 0.45744 |
from pylatex import Figure as FigureOriginal
from pylatex import Package, NoEscape
from .saving import LatexSaving
from .float import FloatAdditions
import matplotlib.pyplot as plt
class Figure(FloatAdditions, LatexSaving, FigureOriginal):
"""A class that represents a Figure environment with modified methods comp... | pythonlatex/figure.py | from pylatex import Figure as FigureOriginal
from pylatex import Package, NoEscape
from .saving import LatexSaving
from .float import FloatAdditions
import matplotlib.pyplot as plt
class Figure(FloatAdditions, LatexSaving, FigureOriginal):
"""A class that represents a Figure environment with modified methods comp... | 0.927548 | 0.40592 |
import argparse
import glob
import json
import os
from pythia.utils.preprocessing import text_tokenize
class IMDBBuilder:
def __init__(self):
self.args = self.get_args()
def get_args(self):
parser = argparse.ArgumentParser("Build IMDB for VisDial")
parser.add_argument(
... | pythia/datasets/dialog/visual_dialog/scripts/build_imdb.py | import argparse
import glob
import json
import os
from pythia.utils.preprocessing import text_tokenize
class IMDBBuilder:
def __init__(self):
self.args = self.get_args()
def get_args(self):
parser = argparse.ArgumentParser("Build IMDB for VisDial")
parser.add_argument(
... | 0.338624 | 0.092237 |
import re
from collections import namedtuple
import xlrd
import tkinter as tk
import tkinter.filedialog
import logging
import logging.config
class CoordinateConverter(tk.Frame):
def __init__(self, master=None):
super().__init__(master)
self.master = master
self.pack()
... | CoordinateCoverter.py | import re
from collections import namedtuple
import xlrd
import tkinter as tk
import tkinter.filedialog
import logging
import logging.config
class CoordinateConverter(tk.Frame):
def __init__(self, master=None):
super().__init__(master)
self.master = master
self.pack()
... | 0.205018 | 0.09118 |
# This script parses the IDNA table from
# https://unicode.org/Public/idna/11.0.0/IdnaMappingTable.txt,
# and converts it to a C++ table.
import sys
import jinja2
def parse_line(line):
line = line[0:line.find('#')]
tokens = [token.strip() for token in line.split(';')] if line else []
if len(tokens) == ... | tools/make_idna_table_v2.py |
# This script parses the IDNA table from
# https://unicode.org/Public/idna/11.0.0/IdnaMappingTable.txt,
# and converts it to a C++ table.
import sys
import jinja2
def parse_line(line):
line = line[0:line.find('#')]
tokens = [token.strip() for token in line.split(';')] if line else []
if len(tokens) == ... | 0.53437 | 0.280395 |
import nbformat
from tempfile import TemporaryDirectory
from nbgrader.coursedir import CourseDirectory
from nbgrader.utils import is_grade
from e2xgrader.models import TemplateModel, PresetModel
def create_temp_course():
tmp_dir = TemporaryDirectory()
coursedir = CourseDirectory()
coursedir.root = tmp_di... | e2xgrader/tests/test_utils/test_utils.py | import nbformat
from tempfile import TemporaryDirectory
from nbgrader.coursedir import CourseDirectory
from nbgrader.utils import is_grade
from e2xgrader.models import TemplateModel, PresetModel
def create_temp_course():
tmp_dir = TemporaryDirectory()
coursedir = CourseDirectory()
coursedir.root = tmp_di... | 0.265119 | 0.155591 |
import traceback
from types import FunctionType
from flask import Blueprint, request, Response
from ..handlers.mock_handler import MockHandler
from ..handlers.proxy_handler import ProxyHandler
from ..handlers.path_not_found_handler import RequestPathNotFound
from ..handlers.handler_context import HandlerContext
from .... | lyrebird/mock/blueprints/core.py | import traceback
from types import FunctionType
from flask import Blueprint, request, Response
from ..handlers.mock_handler import MockHandler
from ..handlers.proxy_handler import ProxyHandler
from ..handlers.path_not_found_handler import RequestPathNotFound
from ..handlers.handler_context import HandlerContext
from .... | 0.264548 | 0.038214 |
import os
import sys
import scheduler_sdk.model.scheduler.task_pb2
import scheduler_sdk.api.task.create_task_pb2
import scheduler_sdk.api.task.delete_task_detail_pb2
import google.protobuf.empty_pb2
import scheduler_sdk.api.task.get_task_detail_pb2
import scheduler_sdk.api.task.list_task_pb2
import scheduler_sd... | scheduler_sdk/api/task/task_client.py | import os
import sys
import scheduler_sdk.model.scheduler.task_pb2
import scheduler_sdk.api.task.create_task_pb2
import scheduler_sdk.api.task.delete_task_detail_pb2
import google.protobuf.empty_pb2
import scheduler_sdk.api.task.get_task_detail_pb2
import scheduler_sdk.api.task.list_task_pb2
import scheduler_sd... | 0.247896 | 0.112429 |
from typing import Dict, List, Tuple, Union
from pyrogram.types import InlineKeyboardButton as InlineKB
from prodil.BotConfig import api
class Local:
QUESTION = "Whats your preferences of resources"
ANSWER = {
"AU": "Only Audio",
"VID": "Only Video",
"__": "Both video and audio",
... | prodil/utils/quest.py | from typing import Dict, List, Tuple, Union
from pyrogram.types import InlineKeyboardButton as InlineKB
from prodil.BotConfig import api
class Local:
QUESTION = "Whats your preferences of resources"
ANSWER = {
"AU": "Only Audio",
"VID": "Only Video",
"__": "Both video and audio",
... | 0.787523 | 0.402392 |
import binascii
import hashlib
import base58
from . import Hash
class Protocol(object):
ADDRESS_GEN_PREFIX = '02b825'
ADDRESS_GEN_PREFIX_LEN = int(len(ADDRESS_GEN_PREFIX) / 2)
UINT160_LEN = 20
CHECKSUM_LEN = 4
ADDRESS_LEN = ADDRESS_GEN_PREFIX_LEN + UINT160_LEN + CHECKSUM_LEN
@staticmethod
... | nknsdk/crypto/protocol.py | import binascii
import hashlib
import base58
from . import Hash
class Protocol(object):
ADDRESS_GEN_PREFIX = '02b825'
ADDRESS_GEN_PREFIX_LEN = int(len(ADDRESS_GEN_PREFIX) / 2)
UINT160_LEN = 20
CHECKSUM_LEN = 4
ADDRESS_LEN = ADDRESS_GEN_PREFIX_LEN + UINT160_LEN + CHECKSUM_LEN
@staticmethod
... | 0.646237 | 0.170508 |
import argparse
import torch
import torch.jit
import torch.nn as nn
import torch.nn.functional as F
from generate_cnn_model import PolicyHead, ValueHead
class TransformerModel(nn.Module):
def __init__(self, input_channel_num, block_num, channel_num, policy_channel_num, board_size):
super(TransformerModel,... | scripts/generate_transformer_model2.py | import argparse
import torch
import torch.jit
import torch.nn as nn
import torch.nn.functional as F
from generate_cnn_model import PolicyHead, ValueHead
class TransformerModel(nn.Module):
def __init__(self, input_channel_num, block_num, channel_num, policy_channel_num, board_size):
super(TransformerModel,... | 0.859973 | 0.383468 |
import urllib
import urllib2
import json
import sys
import logging
import datetime
from datetime import datetime
import time
import re
from bql_parser import BQLParser, BQLRequest
from sensei_components import *
from pyparsing import ParseException, ParseFatalException, ParseSyntaxException
BQL_PARSING_ERROR_CODE = 1... | clients/python/sensei/sensei_client.py | import urllib
import urllib2
import json
import sys
import logging
import datetime
from datetime import datetime
import time
import re
from bql_parser import BQLParser, BQLRequest
from sensei_components import *
from pyparsing import ParseException, ParseFatalException, ParseSyntaxException
BQL_PARSING_ERROR_CODE = 1... | 0.21036 | 0.100746 |
from GremlinConnect import GremlinConnection
from PandasFunctions import PandasFunctions as PF
from pprint import pprint
import json
from gremlin_python import statics
from gremlin_python.process.anonymous_traversal import traversal
from gremlin_python.process.graph_traversal import __
from gremlin_python.process.stra... | Application.py |
from GremlinConnect import GremlinConnection
from PandasFunctions import PandasFunctions as PF
from pprint import pprint
import json
from gremlin_python import statics
from gremlin_python.process.anonymous_traversal import traversal
from gremlin_python.process.graph_traversal import __
from gremlin_python.process.stra... | 0.500244 | 0.113604 |
import os
import torch
import numpy as np
import re
import glob
import torchvision.transforms as transforms
from PIL import Image
from torch.utils import data
# taken from https://github.com/intel-isl/MultiObjectiveOptimization and adapted
class CelebA(data.Dataset):
def __init__(self, split, task_ids=[], root=... | multi_objective/loaders/celeba_loader.py | import os
import torch
import numpy as np
import re
import glob
import torchvision.transforms as transforms
from PIL import Image
from torch.utils import data
# taken from https://github.com/intel-isl/MultiObjectiveOptimization and adapted
class CelebA(data.Dataset):
def __init__(self, split, task_ids=[], root=... | 0.516108 | 0.521106 |
import hashlib
import inspect
import os
import shutil
import urllib
from pathlib import Path
from typing import Callable
from tempfile import NamedTemporaryFile
from tqdm import tqdm
from danlp.utils import extract_single_file_from_zip
DEFAULT_CACHE_DIR = os.path.join(str(Path.home()), '.danlp')
DANLP_STORAGE_URL =... | danlp/download.py | import hashlib
import inspect
import os
import shutil
import urllib
from pathlib import Path
from typing import Callable
from tempfile import NamedTemporaryFile
from tqdm import tqdm
from danlp.utils import extract_single_file_from_zip
DEFAULT_CACHE_DIR = os.path.join(str(Path.home()), '.danlp')
DANLP_STORAGE_URL =... | 0.549399 | 0.145237 |
import logging
import os
import numpy as np
from toolz import curry, valmap
import torch
from uwnet.numpy_interface import NumpyWrapper
from uwnet.sam_ngaqua import get_ngaqua_nudger
def get_configuration_from_environment():
models = []
try:
model = {"type": "neural_network", "path": os.environ['UWN... | uwnet/sam_interface.py | import logging
import os
import numpy as np
from toolz import curry, valmap
import torch
from uwnet.numpy_interface import NumpyWrapper
from uwnet.sam_ngaqua import get_ngaqua_nudger
def get_configuration_from_environment():
models = []
try:
model = {"type": "neural_network", "path": os.environ['UWN... | 0.625781 | 0.284643 |
import unittest
from instruments.instrument_catalog import InstrumentCatalog
from structure.score import Score
from structure.instrument_voice import InstrumentVoice
from structure.line import Line
from structure.note import Note
from timemodel.duration import Duration
from timemodel.position import Position
from timem... | tests/midi_tests/test_score_to_midi_converter.py | import unittest
from instruments.instrument_catalog import InstrumentCatalog
from structure.score import Score
from structure.instrument_voice import InstrumentVoice
from structure.line import Line
from structure.note import Note
from timemodel.duration import Duration
from timemodel.position import Position
from timem... | 0.580352 | 0.54583 |
import os
import shutil
# Obtain and import the installLib library - should work on Windows and Linux / MacOS.
if os.path.exists("install-lib"):
os.system("git -C install-lib pull https://github.com/dhicks6345789/install-lib.git")
else:
os.system("git clone https://github.com/dhicks6345789/install-lib.git")
shutil.c... | install.py | import os
import shutil
# Obtain and import the installLib library - should work on Windows and Linux / MacOS.
if os.path.exists("install-lib"):
os.system("git -C install-lib pull https://github.com/dhicks6345789/install-lib.git")
else:
os.system("git clone https://github.com/dhicks6345789/install-lib.git")
shutil.c... | 0.227469 | 0.097048 |
# Builtins
from __future__ import with_statement
import os
import unittest
import requires_internet
requires_internet.check()
# Biopython
from Bio.Graphics.ColorSpiral import ColorSpiral
# Do we have ReportLab? Raise error if not present.
from Bio import MissingExternalDependencyError
try:
from reportlab.pdfgen... | Tests/test_KGML_graphics_online.py | # Builtins
from __future__ import with_statement
import os
import unittest
import requires_internet
requires_internet.check()
# Biopython
from Bio.Graphics.ColorSpiral import ColorSpiral
# Do we have ReportLab? Raise error if not present.
from Bio import MissingExternalDependencyError
try:
from reportlab.pdfgen... | 0.620047 | 0.244803 |
bl_info = {
"name": "Edit Operator Source",
"author": "scorpion81",
"version": (1, 2, 2),
"blender": (2, 78, 0),
"location": "Text Editor > Edit > Edit Operator",
"description": "Opens source file of chosen operator, if it is an add-on one",
"warning": "",
"wiki_url": "https://wiki.ble... | development_edit_operator.py |
bl_info = {
"name": "Edit Operator Source",
"author": "scorpion81",
"version": (1, 2, 2),
"blender": (2, 78, 0),
"location": "Text Editor > Edit > Edit Operator",
"description": "Opens source file of chosen operator, if it is an add-on one",
"warning": "",
"wiki_url": "https://wiki.ble... | 0.425605 | 0.248657 |
import torch
import torch.nn as nn
from torch.autograd import Variable
import torch.nn.functional as F
import numpy as np
import math
import scipy.stats as stats
pixel_mean = Variable(torch.FloatTensor(
[115.9839754, 126.63120922, 137.73309306]).view(1, 3, 1, 1))
eps_div = 1e-20
class Loss(nn.Module):
def ... | junc/loss/balance_loss.py | import torch
import torch.nn as nn
from torch.autograd import Variable
import torch.nn.functional as F
import numpy as np
import math
import scipy.stats as stats
pixel_mean = Variable(torch.FloatTensor(
[115.9839754, 126.63120922, 137.73309306]).view(1, 3, 1, 1))
eps_div = 1e-20
class Loss(nn.Module):
def ... | 0.845177 | 0.401453 |
import sys, unittest, time
from selenium.webdriver.common.by import By
from selenium.webdriver.common.keys import Keys
from selenium.common.exceptions import NoSuchElementException
from selenium.common.exceptions import NoAlertPresentException
from model.names import info_mail
from model.elements import wait
class ... | fixture/regHelperMail_verify.py | import sys, unittest, time
from selenium.webdriver.common.by import By
from selenium.webdriver.common.keys import Keys
from selenium.common.exceptions import NoSuchElementException
from selenium.common.exceptions import NoAlertPresentException
from model.names import info_mail
from model.elements import wait
class ... | 0.132599 | 0.114765 |
"""Container View Permissions Tests
"""
import unittest
import transaction
from zope.annotation.interfaces import IAttributeAnnotatable
from zope.interface import alsoProvides
from zope.security.interfaces import Unauthorized
from zope.container.ordered import OrderedContainer
from zope.dublincore.interfaces import ... | src/zope/app/container/browser/tests/test_view_permissions.py | """Container View Permissions Tests
"""
import unittest
import transaction
from zope.annotation.interfaces import IAttributeAnnotatable
from zope.interface import alsoProvides
from zope.security.interfaces import Unauthorized
from zope.container.ordered import OrderedContainer
from zope.dublincore.interfaces import ... | 0.632276 | 0.405566 |
import cv2
import numpy as np
import tensorflow as tf
def get_mesh(model_path='models/model.tflite'):
# Load the model
interpreter = tf.lite.Interpreter(model_path=model_path)
# Set model input
interpreter.allocate_tensors()
input_details = interpreter.get_input_details()
output_details = i... | helper/face_landmarks.py | import cv2
import numpy as np
import tensorflow as tf
def get_mesh(model_path='models/model.tflite'):
# Load the model
interpreter = tf.lite.Interpreter(model_path=model_path)
# Set model input
interpreter.allocate_tensors()
input_details = interpreter.get_input_details()
output_details = i... | 0.612657 | 0.591605 |
from functools import partial
import argparse
import numpy as np
import os
import torch
import datetime
import logging
from pathlib import Path
from dataset.ScanObjectNNDataLoader import ScanObjectNNDataLoader
from modules.ptaug_utils import transform_point_cloud, scale_point_cloud, get_aug_args
from modules.pointnet... | train_cls_scanobjectnn.py | from functools import partial
import argparse
import numpy as np
import os
import torch
import datetime
import logging
from pathlib import Path
from dataset.ScanObjectNNDataLoader import ScanObjectNNDataLoader
from modules.ptaug_utils import transform_point_cloud, scale_point_cloud, get_aug_args
from modules.pointnet... | 0.586404 | 0.104067 |
import numpy as np
from util import patches
from util import convert_label
from tensorflow.python.keras.utils import Sequence
class DataGenerator(Sequence):
'''Generate data for keras'''
def __init__(self, images, labels, patch_pos, keys, batch_size = 500,
patch_size = [40,16], n_channels = 1,... | body_part_identification/training/data_generator.py | import numpy as np
from util import patches
from util import convert_label
from tensorflow.python.keras.utils import Sequence
class DataGenerator(Sequence):
'''Generate data for keras'''
def __init__(self, images, labels, patch_pos, keys, batch_size = 500,
patch_size = [40,16], n_channels = 1,... | 0.779993 | 0.395776 |
import logging
import re
import geohash # python-geohash package
import googlemaps
import numpy as np
import pandas as pd
from geographiclib.geodesic import Geodesic
from anyway.parsers.news_flash_db_adapter import init_db
from . import resolution_dict
def extract_road_number(location):
"""
extract road n... | anyway/parsers/location_extraction.py |
import logging
import re
import geohash # python-geohash package
import googlemaps
import numpy as np
import pandas as pd
from geographiclib.geodesic import Geodesic
from anyway.parsers.news_flash_db_adapter import init_db
from . import resolution_dict
def extract_road_number(location):
"""
extract road n... | 0.540924 | 0.402627 |
import datetime
from operator import attrgetter
import sys
# noinspection PyPep8Naming
import acitoolkit as ACI
# Take login credentials from the command line if provided
# Otherwise, take them from your environment variables file ~/.profile
description = 'Simple application that logs on to the APIC and displays repo... | applications/reports/aci-report-switch.py | import datetime
from operator import attrgetter
import sys
# noinspection PyPep8Naming
import acitoolkit as ACI
# Take login credentials from the command line if provided
# Otherwise, take them from your environment variables file ~/.profile
description = 'Simple application that logs on to the APIC and displays repo... | 0.365796 | 0.091301 |
import numpy as np
import pandas as pd
from tqdm import tqdm
from prereise.gather.winddata.rap.power_curves import (
get_power,
get_state_power_curves,
get_turbine_power_curves,
)
def _check_curve(curve):
allowed_curves = ["state", "IEC class 2"]
if curve not in allowed_curves:
err_msg = ... | prereise/gather/winddata/rap/impute.py | import numpy as np
import pandas as pd
from tqdm import tqdm
from prereise.gather.winddata.rap.power_curves import (
get_power,
get_state_power_curves,
get_turbine_power_curves,
)
def _check_curve(curve):
allowed_curves = ["state", "IEC class 2"]
if curve not in allowed_curves:
err_msg = ... | 0.786254 | 0.601857 |
from random import choice
# Import the register function.
from django.db.models import Q
from django.views.generic import TemplateView
from siteblocks.siteblocksapp import register_dynamic_block
import datetime
from digest.models import Item
def get_active_items():
return Item.objects.filter(status='active',
... | landings/views.py | from random import choice
# Import the register function.
from django.db.models import Q
from django.views.generic import TemplateView
from siteblocks.siteblocksapp import register_dynamic_block
import datetime
from digest.models import Item
def get_active_items():
return Item.objects.filter(status='active',
... | 0.445047 | 0.143008 |
from rest_framework import pagination
class MyCursorPagination(pagination.CursorPagination):
"""
Cursor 光标分页 性能高，安全
"""
page_size = 10
ordering = '-update_time'
page_size_query_param = "size"
page_query_param = 'page'
max_page_size = 20
class MyPageNumberPagination(pagination.PageNum... | STL/pagination.py | from rest_framework import pagination
class MyCursorPagination(pagination.CursorPagination):
"""
Cursor 光标分页 性能高，安全
"""
page_size = 10
ordering = '-update_time'
page_size_query_param = "size"
page_query_param = 'page'
max_page_size = 20
class MyPageNumberPagination(pagination.PageNum... | 0.560012 | 0.198394 |
import os
import shutil
import boto3
import pytest
from moto import mock_s3
from base64 import b64encode
from passlib.apps import custom_app_context
from werkzeug.datastructures import FileStorage
from extrapypi.app import create_app
from extrapypi.extensions import db as _db
from extrapypi.models import Package, Use... | tests/conftest.py | import os
import shutil
import boto3
import pytest
from moto import mock_s3
from base64 import b64encode
from passlib.apps import custom_app_context
from werkzeug.datastructures import FileStorage
from extrapypi.app import create_app
from extrapypi.extensions import db as _db
from extrapypi.models import Package, Use... | 0.316898 | 0.113481 |
import numpy as np
class LinearRegressionNumpy:
"""Linear Regresion using gradient descent algorithm.
Implemented in numpy.
Related equations:
# hypothesis function: y_pred = xw + b
# Loss function: J = (1/2m) sum_i^m (h(xi)-yi)^2
# Take derivative of the loss function w.r.t. the parameters: dw... | kutu/linear_regression.py | import numpy as np
class LinearRegressionNumpy:
"""Linear Regresion using gradient descent algorithm.
Implemented in numpy.
Related equations:
# hypothesis function: y_pred = xw + b
# Loss function: J = (1/2m) sum_i^m (h(xi)-yi)^2
# Take derivative of the loss function w.r.t. the parameters: dw... | 0.857947 | 0.824921 |
import numpy as np
import matplotlib.pylab as plt
from dmp_4 import DMPs_discrete
from dmp_4 import TdwFormulation, OriginalFormulation
#
# -------------------------------
dmp1 = DMPs_discrete(dims=1, bfs=10, w=np.zeros((1,10)), ts=TdwFormulation())
y1_track, dy1_track, ddy1_track = dmp1.plan()
plt.figure(1, figs... | tests/test_dmp_4.py |
import numpy as np
import matplotlib.pylab as plt
from dmp_4 import DMPs_discrete
from dmp_4 import TdwFormulation, OriginalFormulation
#
# -------------------------------
dmp1 = DMPs_discrete(dims=1, bfs=10, w=np.zeros((1,10)), ts=TdwFormulation())
y1_track, dy1_track, ddy1_track = dmp1.plan()
plt.figure(1, figs... | 0.446253 | 0.611614 |