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 numpy as np
from hypothesis import given
from hypothesis import strategies as st
from hypothesis.extra.numpy import arrays, array_shapes
from hypothesis.extra.pandas import data_frames, column, series, range_indexes
from timeseers.utils import MinMaxScaler
@given(
arrays(
np.float,
shape=a... | tests/test_utils.py | import numpy as np
from hypothesis import given
from hypothesis import strategies as st
from hypothesis.extra.numpy import arrays, array_shapes
from hypothesis.extra.pandas import data_frames, column, series, range_indexes
from timeseers.utils import MinMaxScaler
@given(
arrays(
np.float,
shape=a... | 0.722429 | 0.689951 |
import torch
from mmcv.runner import force_fp32
from torch import nn as nn
from typing import List
from .furthest_point_sample import (furthest_point_sample,
furthest_point_sample_with_dist)
from .utils import calc_square_dist
def get_sampler_type(sampler_type):
"""Get the typ... | mmdet3d/ops/furthest_point_sample/points_sampler.py | import torch
from mmcv.runner import force_fp32
from torch import nn as nn
from typing import List
from .furthest_point_sample import (furthest_point_sample,
furthest_point_sample_with_dist)
from .utils import calc_square_dist
def get_sampler_type(sampler_type):
"""Get the typ... | 0.940044 | 0.588594 |
from django.urls import path
from . import views
urlpatterns = [
# Global Dimension
path("dimension/", views.DimensionView.as_view(), name="dimension"),
# path("metrics/", views.MetricsView.as_view(), name="metrics"),
path(
"global-dimension/", views.GlobalDimensionView.as_view(), name="globalD... | api/cueSearch/urls.py | from django.urls import path
from . import views
urlpatterns = [
# Global Dimension
path("dimension/", views.DimensionView.as_view(), name="dimension"),
# path("metrics/", views.MetricsView.as_view(), name="metrics"),
path(
"global-dimension/", views.GlobalDimensionView.as_view(), name="globalD... | 0.467089 | 0.088741 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import multiprocessing
import os
import random
import subprocess
import sys
import time
def random_name():
return str(random.randint(0, 99999999))
def start_local_scheduler(plasma_store_name,
... | python/ray/local_scheduler/local_scheduler_services.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import multiprocessing
import os
import random
import subprocess
import sys
import time
def random_name():
return str(random.randint(0, 99999999))
def start_local_scheduler(plasma_store_name,
... | 0.502441 | 0.129046 |
import pickle
import openpyxl
from local_settings_eclipse import db
def fetch_file(path):
with open(path, 'rb') as fp:
file = pickle.load(fp)
return file
RELATIVE_PATH = "/home/imlegend19/PycharmProjects/Research - Data Mining/eclipse/"
wb = openpyxl.Workbook()
sheet = wb.active
titles = ["Assign... | eclipse/correlation/script.py | import pickle
import openpyxl
from local_settings_eclipse import db
def fetch_file(path):
with open(path, 'rb') as fp:
file = pickle.load(fp)
return file
RELATIVE_PATH = "/home/imlegend19/PycharmProjects/Research - Data Mining/eclipse/"
wb = openpyxl.Workbook()
sheet = wb.active
titles = ["Assign... | 0.178454 | 0.172625 |
"""Unit test for proxy.py"""
import abc
import asyncio
import time
from typing import List
import unittest
import proxy
class MockRng(abc.ABC):
def __init__(self, results: List[float]):
self._results = results
def uniform(self, from_val: float, to_val: float) -> float:
val_range = to_val - ... | pw_transfer/integration_test/proxy_test.py | """Unit test for proxy.py"""
import abc
import asyncio
import time
from typing import List
import unittest
import proxy
class MockRng(abc.ABC):
def __init__(self, results: List[float]):
self._results = results
def uniform(self, from_val: float, to_val: float) -> float:
val_range = to_val - ... | 0.844601 | 0.589894 |
import copy
from google.cloud import datacatalog
from google.datacatalog_connectors.commons import prepare
from google.datacatalog_connectors.apache_atlas.prepare import constant
from google.datacatalog_connectors.apache_atlas.prepare import \
datacatalog_attribute_normalizer as attr_normalizer
class DataCatal... | google-datacatalog-apache-atlas-connector/src/google/datacatalog_connectors/apache_atlas/prepare/datacatalog_tag_factory.py |
import copy
from google.cloud import datacatalog
from google.datacatalog_connectors.commons import prepare
from google.datacatalog_connectors.apache_atlas.prepare import constant
from google.datacatalog_connectors.apache_atlas.prepare import \
datacatalog_attribute_normalizer as attr_normalizer
class DataCatal... | 0.557604 | 0.11004 |
import discord
# Make sure we're using the correct version of Discord.py
if discord.__author__ != "Rapptz":
print("Error: Please use the rewrite version of Discord.py.")
print("Check the README for instructions.")
exit()
import requests, asyncio, platform
from discord.ext.commands import Bot
# End imports... | main.py | import discord
# Make sure we're using the correct version of Discord.py
if discord.__author__ != "Rapptz":
print("Error: Please use the rewrite version of Discord.py.")
print("Check the README for instructions.")
exit()
import requests, asyncio, platform
from discord.ext.commands import Bot
# End imports... | 0.282295 | 0.18508 |
import torch
import torch.nn as nn
import segmentation_models_pytorch as smp
class Generator_with_Refin(nn.Module):
def __init__(self, encoder):
"""Generator initialization
Args:
encoder: an encoder for Unet generator
"""
super(Generator_with_Refin, self).__init__()
... | shadow_class/networks.py |
import torch
import torch.nn as nn
import segmentation_models_pytorch as smp
class Generator_with_Refin(nn.Module):
def __init__(self, encoder):
"""Generator initialization
Args:
encoder: an encoder for Unet generator
"""
super(Generator_with_Refin, self).__init__()
... | 0.958644 | 0.413773 |
import json
from pathlib import Path
from typing import Any, Mapping, Optional, Union, cast, get_args
import pulumi_nomad as nomad
from infra.config import STACK_NAME
from infra.nomad_service_postgres import NomadServicePostgresDbArgs
import pulumi
_ValidNomadVarTypePrimitives = Union[str, bool, int]
_ValidNomadVarT... | pulumi/infra/nomad_job.py | import json
from pathlib import Path
from typing import Any, Mapping, Optional, Union, cast, get_args
import pulumi_nomad as nomad
from infra.config import STACK_NAME
from infra.nomad_service_postgres import NomadServicePostgresDbArgs
import pulumi
_ValidNomadVarTypePrimitives = Union[str, bool, int]
_ValidNomadVarT... | 0.763572 | 0.064742 |
from __future__ import absolute_import, unicode_literals
try:
import json
except ImportError:
import simplejson as json
import textwrap
from django.core import serializers
from django.core.exceptions import ImproperlyConfigured
from django.test import TestCase
from markupmirror.fields import Markup
from mar... | tests/tests/fields.py | from __future__ import absolute_import, unicode_literals
try:
import json
except ImportError:
import simplejson as json
import textwrap
from django.core import serializers
from django.core.exceptions import ImproperlyConfigured
from django.test import TestCase
from markupmirror.fields import Markup
from mar... | 0.763572 | 0.210462 |
import time
import unittest
import hiro
from holmium.core import Page, Element, Locators, ElementMap
from holmium.core.conditions import (
ALL, MATCHES_TEXT, VISIBLE, INVISIBLE, ANY
)
from tests.utils import make_temp_page, get_driver
class WaitConditionTests(unittest.TestCase):
def setUp(self):
sel... | tests/wait_condition_tests.py | import time
import unittest
import hiro
from holmium.core import Page, Element, Locators, ElementMap
from holmium.core.conditions import (
ALL, MATCHES_TEXT, VISIBLE, INVISIBLE, ANY
)
from tests.utils import make_temp_page, get_driver
class WaitConditionTests(unittest.TestCase):
def setUp(self):
sel... | 0.360151 | 0.16228 |
from django.conf import settings
from django.urls import reverse
# Projectroles dependency
from projectroles.models import SODAR_CONSTANTS
from projectroles.plugins import ProjectAppPluginPoint
from .models import File, Folder, HyperLink
from .urls import urlpatterns
# SODAR Constants
APP_SETTING_SCOPE_PROJECT = SO... | filesfolders/plugins.py | from django.conf import settings
from django.urls import reverse
# Projectroles dependency
from projectroles.models import SODAR_CONSTANTS
from projectroles.plugins import ProjectAppPluginPoint
from .models import File, Folder, HyperLink
from .urls import urlpatterns
# SODAR Constants
APP_SETTING_SCOPE_PROJECT = SO... | 0.657868 | 0.126569 |
try:
from collections import Sequence
except ImportError:
from collections.abc import Sequence
from io import BytesIO
import zipfile
class DocumentCollection(Sequence):
def __init__(
self,
sumo_client,
query,
mapper_function=None
):
self.sumo = sumo_client
... | src/fmu/sumo/explorer/_document_collection.py | try:
from collections import Sequence
except ImportError:
from collections.abc import Sequence
from io import BytesIO
import zipfile
class DocumentCollection(Sequence):
def __init__(
self,
sumo_client,
query,
mapper_function=None
):
self.sumo = sumo_client
... | 0.554229 | 0.149687 |
map_template = (
(
(0,0,0,0,3,3,3,3,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
(0,0,0,0,3,3,3,3,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
(0,0,0,0,3,3,3,3,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
(0,0... | games/world_gen_output.py | map_template = (
(
(0,0,0,0,3,3,3,3,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
(0,0,0,0,3,3,3,3,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
(0,0,0,0,3,3,3,3,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
(0,0... | 0.069977 | 0.140248 |
import logging
_global_dict = {}
def init_glb():
"""
initialize global variables
"""
global _global_dict
_global_dict = {
"configManage": None,
"projectScript": None,
"userData": {},
"deviceInstance": None,
"pocoInstance": None,
"rerunFailInfo": Non... | flybirds/core/global_resource.py | import logging
_global_dict = {}
def init_glb():
"""
initialize global variables
"""
global _global_dict
_global_dict = {
"configManage": None,
"projectScript": None,
"userData": {},
"deviceInstance": None,
"pocoInstance": None,
"rerunFailInfo": Non... | 0.419291 | 0.06951 |
from __future__ import absolute_import, unicode_literals
from django.core import mail
from django.core.urlresolvers import reverse
from django.contrib.auth.tests.utils import skipIfCustomUser
from django.test import TestCase, Client
from django.utils.translation import ugettext as _
from feincms.content.application.mod... | tests/postfinance/test_api.py | from __future__ import absolute_import, unicode_literals
from django.core import mail
from django.core.urlresolvers import reverse
from django.contrib.auth.tests.utils import skipIfCustomUser
from django.test import TestCase, Client
from django.utils.translation import ugettext as _
from feincms.content.application.mod... | 0.292494 | 0.158923 |
import pygame
import random
import math
from pygame import mixer
#Initializing pygame
pygame.init()
#initializing the screen
screen = pygame.display.set_mode((800,600))
#Titile & Icon
pygame.display.set_caption("Space Invaders")
icon = pygame.image.load("alien.png")
pygame.display.set_icon(icon)
#score
score_va... | games/SpaceInvaders/Pygame_original.py | import pygame
import random
import math
from pygame import mixer
#Initializing pygame
pygame.init()
#initializing the screen
screen = pygame.display.set_mode((800,600))
#Titile & Icon
pygame.display.set_caption("Space Invaders")
icon = pygame.image.load("alien.png")
pygame.display.set_icon(icon)
#score
score_va... | 0.090624 | 0.242643 |
import os
import platform
import sys
import traceback
import discord
from kithscord import common, util
class ArgError(Exception):
pass
class UserCommand:
"""
Base class to handle user commands.
"""
def __init__(self):
"""
Initialise UserCommand class
"""
# Cre... | kithscord/user_commands.py | import os
import platform
import sys
import traceback
import discord
from kithscord import common, util
class ArgError(Exception):
pass
class UserCommand:
"""
Base class to handle user commands.
"""
def __init__(self):
"""
Initialise UserCommand class
"""
# Cre... | 0.309232 | 0.101456 |
import re
import numpy as np
from .. import util
def load_off(file_obj, **kwargs):
"""
Load an OFF file into the kwargs for a Trimesh constructor
Parameters
----------
file_obj : file object
Contains an OFF file
Returns
----------
loaded : dict
kwargs for Trimesh constr... | trimesh/exchange/off.py | import re
import numpy as np
from .. import util
def load_off(file_obj, **kwargs):
"""
Load an OFF file into the kwargs for a Trimesh constructor
Parameters
----------
file_obj : file object
Contains an OFF file
Returns
----------
loaded : dict
kwargs for Trimesh constr... | 0.67694 | 0.380011 |
import oculus
import vizcam
import vizfx
import viz
import vizconnect
import vizact
import vizproximity
import vizinfo
viz.phys.enable()
viz.go()
boxInfo = vizinfo.InfoPanel('Box Material Characteristics', align=viz.ALIGN_LEFT_TOP)
boxInfo.addSeparator()
boxScale = boxInfo.addLabelItem('Scale',viz.addS... | Vizardcit.py | import oculus
import vizcam
import vizfx
import viz
import vizconnect
import vizact
import vizproximity
import vizinfo
viz.phys.enable()
viz.go()
boxInfo = vizinfo.InfoPanel('Box Material Characteristics', align=viz.ALIGN_LEFT_TOP)
boxInfo.addSeparator()
boxScale = boxInfo.addLabelItem('Scale',viz.addS... | 0.340924 | 0.068475 |
import pytest
from sqlalchemy.orm import Session
from ...scrapers.course import Course
from ...scrapers.course_class import CourseClass
from .. import crud, models
from ..sql import SessionLocal, engine
class University:
def __init__(self, name):
self.name = name
university = University("test1")
term_... | coursecake/database/tests/test_crud.py | import pytest
from sqlalchemy.orm import Session
from ...scrapers.course import Course
from ...scrapers.course_class import CourseClass
from .. import crud, models
from ..sql import SessionLocal, engine
class University:
def __init__(self, name):
self.name = name
university = University("test1")
term_... | 0.240061 | 0.49646 |
from __future__ import absolute_import, division, print_function, unicode_literals
import pytest
from tests import debug
from tests.patterns import some
from tests.timeline import Event
@pytest.mark.parametrize("module", ["module", ""])
@pytest.mark.parametrize("line", ["line", ""])
def test_stack_format(pyfile, t... | tests/ptvsd/server/test_vs_specific.py |
from __future__ import absolute_import, division, print_function, unicode_literals
import pytest
from tests import debug
from tests.patterns import some
from tests.timeline import Event
@pytest.mark.parametrize("module", ["module", ""])
@pytest.mark.parametrize("line", ["line", ""])
def test_stack_format(pyfile, t... | 0.457379 | 0.299272 |
from PyQt5 import QtWidgets, QtCore
__all__ = ['TabWidget', 'CustomQDialog', 'CustomQMainWidget']
class TabWidget(QtWidgets.QTabWidget):
"""
Table widget to populate all the samples.
"""
def __init__(self, n_array, parent=None):
super(TabWidget, self).__init__(parent)
tab_list = []
... | smlgui/widgets.py | from PyQt5 import QtWidgets, QtCore
__all__ = ['TabWidget', 'CustomQDialog', 'CustomQMainWidget']
class TabWidget(QtWidgets.QTabWidget):
"""
Table widget to populate all the samples.
"""
def __init__(self, n_array, parent=None):
super(TabWidget, self).__init__(parent)
tab_list = []
... | 0.636127 | 0.110279 |
import sys
from pyspark import SparkConf, SparkContext
import re
import numpy as np
import scipy.sparse as sps
from pyspark.mllib.linalg import Vectors
from pyspark.mllib.linalg import SparseVector
from pyspark.mllib.regression import LabeledPoint
# Load and parse the data
def parsePoint(line):
data = line.split("... | part4-SimRank PageRank/wez311_task4.py | import sys
from pyspark import SparkConf, SparkContext
import re
import numpy as np
import scipy.sparse as sps
from pyspark.mllib.linalg import Vectors
from pyspark.mllib.linalg import SparseVector
from pyspark.mllib.regression import LabeledPoint
# Load and parse the data
def parsePoint(line):
data = line.split("... | 0.339718 | 0.572424 |
from ... import main
from json import loads as json
from json import JSONDecodeError
from datetime import datetime
from ...settings import Settings as s
import unittest
class Test(unittest.TestCase):
def setUp(self):
self.eazy = main.EazySDK().get
def test_searching_more_than_one_parameter_narrows_se... | tests/customer/get_customer.py | from ... import main
from json import loads as json
from json import JSONDecodeError
from datetime import datetime
from ...settings import Settings as s
import unittest
class Test(unittest.TestCase):
def setUp(self):
self.eazy = main.EazySDK().get
def test_searching_more_than_one_parameter_narrows_se... | 0.435902 | 0.335814 |
import struct
# @todo: use these
PACKET_LENGTH = 12
DATA_OFFSET = 8
class CommandPacket(object):
def __init__(self, rnw=True, address=0, vals=None):
""" """
assert isinstance(vals, (type(None), list))
self.rawbytes = bytearray([0 for _ in range(PACKET_LENGTH)])
self.rawbytes[0] =... | rhea/utils/command_packet.py | import struct
# @todo: use these
PACKET_LENGTH = 12
DATA_OFFSET = 8
class CommandPacket(object):
def __init__(self, rnw=True, address=0, vals=None):
""" """
assert isinstance(vals, (type(None), list))
self.rawbytes = bytearray([0 for _ in range(PACKET_LENGTH)])
self.rawbytes[0] =... | 0.40028 | 0.394755 |
from django.shortcuts import redirect, render, get_object_or_404
from signup.models import MyUser
from .models import Profile
from .forms import ProfileForm
from django.contrib.auth import get_user_model
from post.models import Post
# Create your views here.
def writeprofile(request):
id =request.user.id
user... | user/views.py | from django.shortcuts import redirect, render, get_object_or_404
from signup.models import MyUser
from .models import Profile
from .forms import ProfileForm
from django.contrib.auth import get_user_model
from post.models import Post
# Create your views here.
def writeprofile(request):
id =request.user.id
user... | 0.310276 | 0.063135 |
import numpy as np
import matplotlib.pyplot as plt
from astropy.io import fits
# Class that will be saved locally ==============
class Dust():
def __init__(self, path = ''):
self.path = path + 'data_dust/'
self.angles = [inp for inp in np.arange(0,181)]
def read_lambda(self):
"""
... | library/mcfost_dust.py | import numpy as np
import matplotlib.pyplot as plt
from astropy.io import fits
# Class that will be saved locally ==============
class Dust():
def __init__(self, path = ''):
self.path = path + 'data_dust/'
self.angles = [inp for inp in np.arange(0,181)]
def read_lambda(self):
"""
... | 0.556641 | 0.431824 |
import logging
import traceback
from modules.helpers import get_initial_alarm_result, get_query
info = {
'version': 0.1,
'name': 'User-agent module',
'alarmmsg': 'VISIT FROM BLACKLISTED USERAGENT TO C2_*',
'description': 'This check queries for UA\'s that are listed in any blacklist_useragents.conf an... | elkserver/docker/redelk-base/redelkinstalldata/scripts/modules/alarm_useragent/module.py | import logging
import traceback
from modules.helpers import get_initial_alarm_result, get_query
info = {
'version': 0.1,
'name': 'User-agent module',
'alarmmsg': 'VISIT FROM BLACKLISTED USERAGENT TO C2_*',
'description': 'This check queries for UA\'s that are listed in any blacklist_useragents.conf an... | 0.42919 | 0.093802 |
import csv
import pandas as pd
import geopandas as gpd
import dash_html_components as html
def seismic_reporting_data(occurence):
'''
Seismic Reporting Function
Collects the additional features of the disaster like 'Tsunami Alerts', 'Danger Alerts'
Depends on the occurence type that is being chosen
Parameter : `... | report_alerts.py | import csv
import pandas as pd
import geopandas as gpd
import dash_html_components as html
def seismic_reporting_data(occurence):
'''
Seismic Reporting Function
Collects the additional features of the disaster like 'Tsunami Alerts', 'Danger Alerts'
Depends on the occurence type that is being chosen
Parameter : `... | 0.632616 | 0.387864 |
import tkinter as tk
from tkinter import ttk
from scrolledlist_frame import ScrolledList
class CatFrm(tk.Frame):
"""A frame where a word for translation might be selected from
a category or a subcategory of words.
Contains widgets:
'self.catcb' combobox for choosing a category,
'self.subcatcb' co... | dictionary/categories_frame.py | import tkinter as tk
from tkinter import ttk
from scrolledlist_frame import ScrolledList
class CatFrm(tk.Frame):
"""A frame where a word for translation might be selected from
a category or a subcategory of words.
Contains widgets:
'self.catcb' combobox for choosing a category,
'self.subcatcb' co... | 0.64969 | 0.386503 |
from flask import Flask , request, render_template
from threading import Thread
import youtube_dl
from flask_socketio import SocketIO, emit
import os
app = Flask(__name__)
app.config['SECRET_KEY'] = os.getenv("secret")
socketio = SocketIO(app)
user_sess = {}
@socketio.on('bg-job')
def handle_json(messag... | app.py | from flask import Flask , request, render_template
from threading import Thread
import youtube_dl
from flask_socketio import SocketIO, emit
import os
app = Flask(__name__)
app.config['SECRET_KEY'] = os.getenv("secret")
socketio = SocketIO(app)
user_sess = {}
@socketio.on('bg-job')
def handle_json(messag... | 0.226441 | 0.062445 |
# use tdklib library,which provides a wrapper for tdk testcase script
import tdklib;
from time import sleep;
#Test component to be tested
obj = tdklib.TDKScriptingLibrary("sysutil","1");
#IP and Port of box, No need to change,
#This will be replaced with corresponding DUT Ip and port while executing script
ip = <ipadd... | testscripts/RDKB/component/sysutil/TS_SANITY_CheckForSignificantErrorLogMsg.py | # use tdklib library,which provides a wrapper for tdk testcase script
import tdklib;
from time import sleep;
#Test component to be tested
obj = tdklib.TDKScriptingLibrary("sysutil","1");
#IP and Port of box, No need to change,
#This will be replaced with corresponding DUT Ip and port while executing script
ip = <ipadd... | 0.228071 | 0.173201 |
import numpy as np
import scipy.special
import masp.array_response_simulator as asr
import masp.utils
from masp.validate_data_types import _validate_int, _validate_ndarray_2D, _validate_string, _validate_float, \
_validate_ndarray_1D, _validate_ndarray
def simulate_sph_array(N_filt, mic_dirs_rad, src_dirs_rad, a... | masp/array_response_simulator/simulate_array.py |
import numpy as np
import scipy.special
import masp.array_response_simulator as asr
import masp.utils
from masp.validate_data_types import _validate_int, _validate_ndarray_2D, _validate_string, _validate_float, \
_validate_ndarray_1D, _validate_ndarray
def simulate_sph_array(N_filt, mic_dirs_rad, src_dirs_rad, a... | 0.873943 | 0.740491 |
from django.core.exceptions import ObjectDoesNotExist
from django.utils.encoding import smart_text
from rest_framework import exceptions, relations
from resolwe.permissions.shortcuts import get_objects_for_user
from resolwe.permissions.utils import get_full_perm
class DictRelatedField(relations.RelatedField):
"... | resolwe/flow/serializers/fields.py | from django.core.exceptions import ObjectDoesNotExist
from django.utils.encoding import smart_text
from rest_framework import exceptions, relations
from resolwe.permissions.shortcuts import get_objects_for_user
from resolwe.permissions.utils import get_full_perm
class DictRelatedField(relations.RelatedField):
"... | 0.817502 | 0.216239 |
from nemo.collections import nlp as nemo_nlp
from nemo.utils.exp_manager import exp_manager
from nemo.collections.nlp.parts.utils_funcs import tensor2list
from nemo.collections.nlp.parts.nlp_overrides import NLPDDPPlugin
import os
import wget
import torch
import pytorch_lightning as pl
from omegaconf import OmegaConf... | finetuning/re/re_ddp.py | from nemo.collections import nlp as nemo_nlp
from nemo.utils.exp_manager import exp_manager
from nemo.collections.nlp.parts.utils_funcs import tensor2list
from nemo.collections.nlp.parts.nlp_overrides import NLPDDPPlugin
import os
import wget
import torch
import pytorch_lightning as pl
from omegaconf import OmegaConf... | 0.44553 | 0.250649 |
import logging
from os.path import join
import numpy as np
from src.utils.rand_utils import RandUtils
from src.data.data_loader import DataLoader
from src.utils.config_loader import ConfigLoader
from src.data.data_preprocessor import DataPreprocessor
from src.features.text_vectorizer import TextVectorizer
from src.mo... | WP3/Task3.3/src/tasks/experiments.py | import logging
from os.path import join
import numpy as np
from src.utils.rand_utils import RandUtils
from src.data.data_loader import DataLoader
from src.utils.config_loader import ConfigLoader
from src.data.data_preprocessor import DataPreprocessor
from src.features.text_vectorizer import TextVectorizer
from src.mo... | 0.446495 | 0.25215 |
import os.path as osp
from itertools import product
import matplotlib
import matplotlib.colors as colors
import matplotlib.pyplot as plt
import scipy
from scipy.stats import sem
import numpy as np
import rlutils as rl
from matplotlib.collections import PatchCollection
from matplotlib.patches import Rectangle, Polygon
... | rewardpredictive/plot.py | import os.path as osp
from itertools import product
import matplotlib
import matplotlib.colors as colors
import matplotlib.pyplot as plt
import scipy
from scipy.stats import sem
import numpy as np
import rlutils as rl
from matplotlib.collections import PatchCollection
from matplotlib.patches import Rectangle, Polygon
... | 0.38318 | 0.50415 |
import asyncio
from libp2p.protocol_muxer.multiselect_client import MultiselectClient
from libp2p.protocol_muxer.multiselect import Multiselect
from libp2p.peer.id import id_b58_decode
from .network_interface import INetwork
from .notifee_interface import INotifee
from .stream.net_stream import NetStream
from .connec... | libp2p/network/swarm.py | import asyncio
from libp2p.protocol_muxer.multiselect_client import MultiselectClient
from libp2p.protocol_muxer.multiselect import Multiselect
from libp2p.peer.id import id_b58_decode
from .network_interface import INetwork
from .notifee_interface import INotifee
from .stream.net_stream import NetStream
from .connec... | 0.413004 | 0.126407 |
# Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated
# documentation files (the “Software”), to deal in the Software without restriction, including without limitation
# the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies ... | bittensor/_neuron/text/template_server/run.py |
# Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated
# documentation files (the “Software”), to deal in the Software without restriction, including without limitation
# the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies ... | 0.694406 | 0.239161 |
import numpy as np
class GridWorld:
NUM_STATES = 90
NUM_FEATURES = 3
NUM_ACTIONS = 4
def __init__(self):
# initialize empty transition and reward tables
self.p = np.zeros((30, 3, 30, 3, 4), dtype=np.float32)
self.r = np.zeros((30, 3, 4), dtype=np.float32)
# fill in ... | model_transfer/gridworld.py | import numpy as np
class GridWorld:
NUM_STATES = 90
NUM_FEATURES = 3
NUM_ACTIONS = 4
def __init__(self):
# initialize empty transition and reward tables
self.p = np.zeros((30, 3, 30, 3, 4), dtype=np.float32)
self.r = np.zeros((30, 3, 4), dtype=np.float32)
# fill in ... | 0.642545 | 0.676793 |
#--------------------
# System wide imports
# -------------------
import hashlib
import logging
# ---------------
# Airflow imports
# ---------------
from airflow.providers.sqlite.hooks.sqlite import SqliteHook
#--------------
# local imports
# -------------
# -----------------------
# Module global variables
# -... | src/airflow_actionproject/callables/streetspectra.py |
#--------------------
# System wide imports
# -------------------
import hashlib
import logging
# ---------------
# Airflow imports
# ---------------
from airflow.providers.sqlite.hooks.sqlite import SqliteHook
#--------------
# local imports
# -------------
# -----------------------
# Module global variables
# -... | 0.435661 | 0.073696 |
import matplotlib
matplotlib.rcParams = matplotlib.rc_params_from_file('../../matplotlibrc')
#================================================
#Plots for the Value Function Iteration Lab
#================================================
import numpy as np
import math
from scipy import stats as st
import discretenorm
f... | Vol2B/DynamicOpt1-Value/plots.py | import matplotlib
matplotlib.rcParams = matplotlib.rc_params_from_file('../../matplotlibrc')
#================================================
#Plots for the Value Function Iteration Lab
#================================================
import numpy as np
import math
from scipy import stats as st
import discretenorm
f... | 0.487063 | 0.615839 |
import numpy as np
from typing import Callable
class GeneticAlgorithm:
def __init__(self,
population: list,
calculate_fitness: Callable[..., float],
mutate: Callable[],
crossover: Callable[]):
self.calculate_fitness = calculate_fitness
... | genetic.py | import numpy as np
from typing import Callable
class GeneticAlgorithm:
def __init__(self,
population: list,
calculate_fitness: Callable[..., float],
mutate: Callable[],
crossover: Callable[]):
self.calculate_fitness = calculate_fitness
... | 0.730674 | 0.578746 |
"""Project class."""
from datetime import datetime
from pathlib import Path
from typing import List
from urllib.parse import quote, urlparse
from marshmallow import EXCLUDE
from renku.core.management.migrate import SUPPORTED_PROJECT_VERSION
from renku.core.metadata.database import persistent
from renku.core.models i... | renku/core/models/project.py | """Project class."""
from datetime import datetime
from pathlib import Path
from typing import List
from urllib.parse import quote, urlparse
from marshmallow import EXCLUDE
from renku.core.management.migrate import SUPPORTED_PROJECT_VERSION
from renku.core.metadata.database import persistent
from renku.core.models i... | 0.877359 | 0.179153 |
import collections, random
from numpy import array
from nltk.metrics import masi_distance, f_measure, precision, recall
from nltk.probability import FreqDist, ConditionalFreqDist
def sum_category_word_scores(categorized_words, score_fn):
word_fd = FreqDist()
category_word_fd = ConditionalFreqDist()
for category, ... | nltk_trainer/classification/scoring.py | import collections, random
from numpy import array
from nltk.metrics import masi_distance, f_measure, precision, recall
from nltk.probability import FreqDist, ConditionalFreqDist
def sum_category_word_scores(categorized_words, score_fn):
word_fd = FreqDist()
category_word_fd = ConditionalFreqDist()
for category, ... | 0.323808 | 0.306871 |
import numpy as np
import torch
from .cluster_cpu import cluster as cluster_cpu
try:
from .cluster_cuda import cluster as cluster_gpu
except ImportError:
pass
def cluster(
hashes,
lengths,
groups=None,
counts=None,
centroids=None,
distances=None,
bitcounts=None,
clusters=30,
... | language-modeling/fast_transformers/clustering/hamming/__init__.py | import numpy as np
import torch
from .cluster_cpu import cluster as cluster_cpu
try:
from .cluster_cuda import cluster as cluster_gpu
except ImportError:
pass
def cluster(
hashes,
lengths,
groups=None,
counts=None,
centroids=None,
distances=None,
bitcounts=None,
clusters=30,
... | 0.896467 | 0.645707 |
import sys
import logging
import argparse
import yaml
import subprocess
import os
RESTIC = "restic"
LVS = "lvs"
config = []
class BackupException(Exception):
pass
class Config:
def __init__(self, configFile, prune):
with open(configFile, 'r') as stream:
configYaml = yaml.safe_load(strea... | lvm-backup.py |
import sys
import logging
import argparse
import yaml
import subprocess
import os
RESTIC = "restic"
LVS = "lvs"
config = []
class BackupException(Exception):
pass
class Config:
def __init__(self, configFile, prune):
with open(configFile, 'r') as stream:
configYaml = yaml.safe_load(strea... | 0.129458 | 0.053059 |
# Python modules
import datetime
# NOC modules
from noc.sa.models.interactionlog import InteractionLog
from noc.config import config
def get_seconds(section, option):
v = config.get(section, option)
m = 1
if v.endswith("h"):
v = v[:-1]
m = 3600
elif v.endswith("d"):
v = v[:-1... | fm/handlers/event/audit.py |
# Python modules
import datetime
# NOC modules
from noc.sa.models.interactionlog import InteractionLog
from noc.config import config
def get_seconds(section, option):
v = config.get(section, option)
m = 1
if v.endswith("h"):
v = v[:-1]
m = 3600
elif v.endswith("d"):
v = v[:-1... | 0.364325 | 0.12416 |
import random
import streamlit as st
from typing import Tuple, List
from streamlit.config import _global_development_mode
MAX_GAMES = 10_000
def simulate_handle(start: float, payback_rate: float, bet: float) -> Tuple[float, int, List[float]]:
"""Run a simulation game and stop when player is broken
Parame... | app/app.py | import random
import streamlit as st
from typing import Tuple, List
from streamlit.config import _global_development_mode
MAX_GAMES = 10_000
def simulate_handle(start: float, payback_rate: float, bet: float) -> Tuple[float, int, List[float]]:
"""Run a simulation game and stop when player is broken
Parame... | 0.855881 | 0.411347 |
import csv
import json
def main():
_user_input()
raw_data = _get_data()
filter_data = _filter_json()
filtered_csv = _filter_csv(raw_data, filter_data)
_write_to_file(filtered_csv)
def _user_input():
print("Welcome to PGH Capital Projects. Now with search features!")
print("Which topic... | Week 04/Project/BG_DAT129_HW04_Project.py |
import csv
import json
def main():
_user_input()
raw_data = _get_data()
filter_data = _filter_json()
filtered_csv = _filter_csv(raw_data, filter_data)
_write_to_file(filtered_csv)
def _user_input():
print("Welcome to PGH Capital Projects. Now with search features!")
print("Which topic... | 0.073505 | 0.21308 |
r"""ICNet Semantic Segmentation architecture.
As described in http://arxiv.org/abs/1704.08545.
ICNet for Real-Time Semantic Segmentation
on High-Resolution Images
<NAME>, <NAME>, <NAME>, <NAME>, <NAME>
"""
from abc import abstractmethod
from functools import partial
import tensorflow as tf
from . import base... | segmentation/architectures/icnet_architecture.py | r"""ICNet Semantic Segmentation architecture.
As described in http://arxiv.org/abs/1704.08545.
ICNet for Real-Time Semantic Segmentation
on High-Resolution Images
<NAME>, <NAME>, <NAME>, <NAME>, <NAME>
"""
from abc import abstractmethod
from functools import partial
import tensorflow as tf
from . import base... | 0.94831 | 0.341857 |
import typing as t
from toollib.validator import Attr
class Arg:
def __init__(self,
*name_or_flags: str,
action: str = None,
nargs: t.Union[int, str] = None,
const: t.Any = None,
default: t.Any = None,
type: typ... | toollib/tcli/option.py | import typing as t
from toollib.validator import Attr
class Arg:
def __init__(self,
*name_or_flags: str,
action: str = None,
nargs: t.Union[int, str] = None,
const: t.Any = None,
default: t.Any = None,
type: typ... | 0.693161 | 0.118385 |
import unittest
import torch
from torch import nn
import torch_testing as tt
from all.core import State
from all.approximation.feature_network import FeatureNetwork
STATE_DIM = 2
class TestFeatureNetwork(unittest.TestCase):
def setUp(self):
torch.manual_seed(2)
self.model = nn.Sequential(nn.Linea... | all/approximation/feature_network_test.py | import unittest
import torch
from torch import nn
import torch_testing as tt
from all.core import State
from all.approximation.feature_network import FeatureNetwork
STATE_DIM = 2
class TestFeatureNetwork(unittest.TestCase):
def setUp(self):
torch.manual_seed(2)
self.model = nn.Sequential(nn.Linea... | 0.837188 | 0.684254 |
from nl_open_data.config import config
from prefect import task, Flow, unmapped, Parameter
from prefect.run_configs import LocalRun
from prefect.storage import GCS
from prefect.executors import DaskExecutor
import nl_open_data.tasks as nlt
with Flow("statline-catalogs") as st_catalogs_flow:
catalog_urls = Parame... | nl_open_data/flows/register/register_statline_catalog_flow.py | from nl_open_data.config import config
from prefect import task, Flow, unmapped, Parameter
from prefect.run_configs import LocalRun
from prefect.storage import GCS
from prefect.executors import DaskExecutor
import nl_open_data.tasks as nlt
with Flow("statline-catalogs") as st_catalogs_flow:
catalog_urls = Parame... | 0.107689 | 0.212395 |
ANSIBLE_METADATA = {'metadata_version': '1.1',
'status': ['preview'],
'supported_by': 'community'}
DOCUMENTATION = '''
---
module: alicloud_security_group_facts
version_added: "2.4"
short_description: Gather facts on security group of Alibaba Cloud ECS.
description:
- This... | lib/ansible/modules/cloud/alicloud/alicloud_security_group_facts.py |
ANSIBLE_METADATA = {'metadata_version': '1.1',
'status': ['preview'],
'supported_by': 'community'}
DOCUMENTATION = '''
---
module: alicloud_security_group_facts
version_added: "2.4"
short_description: Gather facts on security group of Alibaba Cloud ECS.
description:
- This... | 0.562056 | 0.22289 |
import numpy as np
import pytest
from dirty_cat import target_encoder
def test_target_encoder():
lambda_ = target_encoder.lambda_
X1 = np.array(['Red',
'red',
'green',
'blue',
'green',
'green',
'... | dirty_cat/test/test_target_encoder.py | import numpy as np
import pytest
from dirty_cat import target_encoder
def test_target_encoder():
lambda_ = target_encoder.lambda_
X1 = np.array(['Red',
'red',
'green',
'blue',
'green',
'green',
'... | 0.596668 | 0.51251 |
import logging
import os
import subprocess
import warnings
from builtins import object
from collections import defaultdict
from typing import DefaultDict, List, Optional, Tuple
from bs4 import BeautifulSoup
from IPython.display import DisplayHandle, display
from wand.color import Color
from wand.drawing import Drawing... | src/fonduer/utils/visualizer.py | import logging
import os
import subprocess
import warnings
from builtins import object
from collections import defaultdict
from typing import DefaultDict, List, Optional, Tuple
from bs4 import BeautifulSoup
from IPython.display import DisplayHandle, display
from wand.color import Color
from wand.drawing import Drawing... | 0.90165 | 0.229967 |
from multiprocessing.pool import Pool
import tables
from phd.satellite.geant4_server import DetectorMode, Geant4Server
import numpy as np
from phd.satellite.run import request_generator
from phd.satellite.satellite_pb2 import Run
from phd.satellite.single_processing import load_likelihood_factory
from phd.satellite.pr... | python/simulation_scripts/satellite/test_recontruction.py | from multiprocessing.pool import Pool
import tables
from phd.satellite.geant4_server import DetectorMode, Geant4Server
import numpy as np
from phd.satellite.run import request_generator
from phd.satellite.satellite_pb2 import Run
from phd.satellite.single_processing import load_likelihood_factory
from phd.satellite.pr... | 0.471953 | 0.348617 |
from keras.models import Model
from keras.layers import Activation, Concatenate, Dense, Flatten, Input
from keras.layers import LeakyReLU, Reshape
from keras.layers import Conv2D, UpSampling2D
from keras.layers import BatchNormalization
def cs_generator(scene_size, modis_var_dim, noise_dim):
f = 256
start_dim... | csmodiscgan/src/models.py | from keras.models import Model
from keras.layers import Activation, Concatenate, Dense, Flatten, Input
from keras.layers import LeakyReLU, Reshape
from keras.layers import Conv2D, UpSampling2D
from keras.layers import BatchNormalization
def cs_generator(scene_size, modis_var_dim, noise_dim):
f = 256
start_dim... | 0.952627 | 0.694743 |
from datetime import datetime
import yaml
class DataValidator:
def __init__(self):
self.master_config = 'etc/weatherman.yml'
with open(self.master_config) as ycf:
self.config = yaml.load(ycf, Loader=yaml.FullLoader)
def is_datetime(self, datetime_str):
"""
Is the ... | weatherman/data_validator.py | from datetime import datetime
import yaml
class DataValidator:
def __init__(self):
self.master_config = 'etc/weatherman.yml'
with open(self.master_config) as ycf:
self.config = yaml.load(ycf, Loader=yaml.FullLoader)
def is_datetime(self, datetime_str):
"""
Is the ... | 0.517083 | 0.262505 |
import os, time
"""
Modify following configurations to adapt to your environment.
"""
test_cases_dir = '../testcases/semantic/'
# test_cases_dir = '../testcases/codegen/'
# test_cases_dir = '../testcases/optim/'
compile_cmd = "bash ../build.bash"
execute_cmd = "bash ../semantic.bash"
excluded_test_cases = ["foo.... | tools/local_judge.py |
import os, time
"""
Modify following configurations to adapt to your environment.
"""
test_cases_dir = '../testcases/semantic/'
# test_cases_dir = '../testcases/codegen/'
# test_cases_dir = '../testcases/optim/'
compile_cmd = "bash ../build.bash"
execute_cmd = "bash ../semantic.bash"
excluded_test_cases = ["foo.... | 0.27406 | 0.229093 |
import numpy as np
if True: # Include project path
import sys
import os
ROOT = os.path.dirname(os.path.abspath(__file__))+"/../"
CURR_PATH = os.path.dirname(os.path.abspath(__file__))+"/"
sys.path.append(ROOT)
import utils.lib_commons as lib_commons
from utils.lib_skeletons_io import load... | src/s3_preprocess_features.py | import numpy as np
if True: # Include project path
import sys
import os
ROOT = os.path.dirname(os.path.abspath(__file__))+"/../"
CURR_PATH = os.path.dirname(os.path.abspath(__file__))+"/"
sys.path.append(ROOT)
import utils.lib_commons as lib_commons
from utils.lib_skeletons_io import load... | 0.311008 | 0.209955 |
import numpy as np
import pandas as pd
import plotly.figure_factory as ff
import cufflinks as cf
from . import tools
cf.go_offline()
def distplot1d(ss: pd.Series, bins=10, hist=True, kde=True, rug=True, color=None,
as_figure=False, legend=True, title=True, grid=True, figsize=None, **kwargs):
ss = ... | mplotly/mplotly.py | import numpy as np
import pandas as pd
import plotly.figure_factory as ff
import cufflinks as cf
from . import tools
cf.go_offline()
def distplot1d(ss: pd.Series, bins=10, hist=True, kde=True, rug=True, color=None,
as_figure=False, legend=True, title=True, grid=True, figsize=None, **kwargs):
ss = ... | 0.68941 | 0.400544 |
from caribou.settings.setting_types import *
from gi.repository import GObject
from gi.repository import Gdk
from gi.repository import Gtk
class AbstractPreferencesUI:
def populate_settings(self, settings_manager):
if getattr(self, "notebook", None) is None:
self.notebook = Gtk.Notebook()
... | stdlib2-src/dist-packages/caribou/settings/preferences_window.py |
from caribou.settings.setting_types import *
from gi.repository import GObject
from gi.repository import Gdk
from gi.repository import Gtk
class AbstractPreferencesUI:
def populate_settings(self, settings_manager):
if getattr(self, "notebook", None) is None:
self.notebook = Gtk.Notebook()
... | 0.570571 | 0.130895 |
import torch
import torch.nn as nn
from torch import autograd
import torch.nn.functional as F
import numpy as np
class NaturalGradientDescentVelNet(nn.Module):
"""
taskmap_fcn: map to a latent space
grad_taskmap_fcn: jacobian of the map
grad_potential_fcn: gradient of a potential fcn defined on the mapped space
... | euclideanizing_flows/flows.py | import torch
import torch.nn as nn
from torch import autograd
import torch.nn.functional as F
import numpy as np
class NaturalGradientDescentVelNet(nn.Module):
"""
taskmap_fcn: map to a latent space
grad_taskmap_fcn: jacobian of the map
grad_potential_fcn: gradient of a potential fcn defined on the mapped space
... | 0.903341 | 0.638892 |
import time
import numpy as np
from scipy.sparse import coo_matrix
from implicit.approximate_als import FaissAlternatingLeastSquares
from implicit.nearest_neighbours import bm25_weight
from implicit.datasets.movielens import get_movielens
def experiment(B, K1, conf, variant='20m', min_rating=3.0):
# read in the i... | ch04-recommending-products-and-services/movielens.py | import time
import numpy as np
from scipy.sparse import coo_matrix
from implicit.approximate_als import FaissAlternatingLeastSquares
from implicit.nearest_neighbours import bm25_weight
from implicit.datasets.movielens import get_movielens
def experiment(B, K1, conf, variant='20m', min_rating=3.0):
# read in the i... | 0.49707 | 0.476275 |
import subprocess
def collect():
filter_keys = ['Manufacturer', 'Serial Number', 'Product Name', 'UUID', 'Wake-up Type']
raw_data = {}
for key in filter_keys:
try:
res = subprocess.Popen("sudo dmidecode -t system|grep '%s'" % key,
stdout=subprocess.... | Client/plugins/collect_linux_info.py |
import subprocess
def collect():
filter_keys = ['Manufacturer', 'Serial Number', 'Product Name', 'UUID', 'Wake-up Type']
raw_data = {}
for key in filter_keys:
try:
res = subprocess.Popen("sudo dmidecode -t system|grep '%s'" % key,
stdout=subprocess.... | 0.229708 | 0.172381 |
import tensorflow as tf
from tensorflow_probability.python.internal import special_math
from tensorflow_probability import distributions as tfd
import tensorflow_probability as tfp
from tensorflow_probability import bijectors as tfb
from tensorflow_probability.python.internal import tensor_util
import numpy as np
cla... | careless/utils/distributions.py | import tensorflow as tf
from tensorflow_probability.python.internal import special_math
from tensorflow_probability import distributions as tfd
import tensorflow_probability as tfp
from tensorflow_probability import bijectors as tfb
from tensorflow_probability.python.internal import tensor_util
import numpy as np
cla... | 0.951953 | 0.839734 |
import logging
import numpy as np
import pandas as pd
import scipy.signal as signal
from import_data import import_data
from extract_data import extract_time_data
from extract_data import extract_template_data
logging.basicConfig(filename='hrmonitorlog.txt', format='%(levelname)s \
%(asctime)s %(message)s', datefmt='%m... | mean_hr_bpm.py | import logging
import numpy as np
import pandas as pd
import scipy.signal as signal
from import_data import import_data
from extract_data import extract_time_data
from extract_data import extract_template_data
logging.basicConfig(filename='hrmonitorlog.txt', format='%(levelname)s \
%(asctime)s %(message)s', datefmt='%m... | 0.523908 | 0.445409 |
import config
import customer_details
import no_found
def show_customers(bit):
conn,cursor=config.connect_to_database()
sql="select * from customers where hasAcc='%s'"%bit
try:
cursor.execute(sql)
results=cursor.fetchall()
row_num=cursor.rowcount
bit=int(bit)
if bit==0:
flag="New customers"
cust_id="... | admin_show_customers.py | import config
import customer_details
import no_found
def show_customers(bit):
conn,cursor=config.connect_to_database()
sql="select * from customers where hasAcc='%s'"%bit
try:
cursor.execute(sql)
results=cursor.fetchall()
row_num=cursor.rowcount
bit=int(bit)
if bit==0:
flag="New customers"
cust_id="... | 0.043003 | 0.106133 |
import math
import cairo
import poppler
import lmcore
import datetime
import sys
import getopt
today = datetime.date.today()
year = today.strftime('%Y')
A4_size_mm = [210.0, 297.0]
def mm_to_inch(iterable):
return [i * 0.0393700787 for i in iterable]
def inch_to_point(iterable):
return [i * 72.0 for i in it... | bibgen.py | import math
import cairo
import poppler
import lmcore
import datetime
import sys
import getopt
today = datetime.date.today()
year = today.strftime('%Y')
A4_size_mm = [210.0, 297.0]
def mm_to_inch(iterable):
return [i * 0.0393700787 for i in iterable]
def inch_to_point(iterable):
return [i * 72.0 for i in it... | 0.220007 | 0.245865 |
import json
from typing import Dict, List, NewType
from google.appengine.ext import ndb
from backend.common.consts.api_version import ApiMajorVersion
from backend.common.models.award import Award
from backend.common.models.event import Event
from backend.common.models.team import Team
from backend.common.queries.dict... | src/backend/common/queries/dict_converters/award_converter.py | import json
from typing import Dict, List, NewType
from google.appengine.ext import ndb
from backend.common.consts.api_version import ApiMajorVersion
from backend.common.models.award import Award
from backend.common.models.event import Event
from backend.common.models.team import Team
from backend.common.queries.dict... | 0.612078 | 0.179872 |
import string
import unittest
from enigma import Reflector, Rotor, RotorMechanism
class TestRotorMechanism(unittest.TestCase):
"""Test class for enigma's rotor mechanism."""
def get_rotors(self, settings):
"""Return rotor set."""
return [Rotor(**setting) for setting in settings]
def ge... | tests/test_rotor/test_rotor_mechanism.py |
import string
import unittest
from enigma import Reflector, Rotor, RotorMechanism
class TestRotorMechanism(unittest.TestCase):
"""Test class for enigma's rotor mechanism."""
def get_rotors(self, settings):
"""Return rotor set."""
return [Rotor(**setting) for setting in settings]
def ge... | 0.864038 | 0.459319 |
import math
import itertools
import collections
import numpy
from ..dataset.dataset import DataSet
from ..statistics.random import RandomState
# Disable variable name nagging since these are mostly math functions
# pylint: disable=invalid-name
def new_labels(samples: int = 1024, random_seed: int = None, key: str ... | bananas/sampledata/synthetic.py |
import math
import itertools
import collections
import numpy
from ..dataset.dataset import DataSet
from ..statistics.random import RandomState
# Disable variable name nagging since these are mostly math functions
# pylint: disable=invalid-name
def new_labels(samples: int = 1024, random_seed: int = None, key: str ... | 0.528533 | 0.561696 |
import typing as t
import numpy as np
def bootstrap(
samples: np.ndarray,
num_resamples: int = 256,
random_state: t.Optional[int] = None,
) -> np.ndarray:
"""Generator of bootstraps ``samples``.
Arguments
---------
samples : :obj:`np.ndarray`
Population to draw samples from.
... | confidence_intervals/bootstrap.py | import typing as t
import numpy as np
def bootstrap(
samples: np.ndarray,
num_resamples: int = 256,
random_state: t.Optional[int] = None,
) -> np.ndarray:
"""Generator of bootstraps ``samples``.
Arguments
---------
samples : :obj:`np.ndarray`
Population to draw samples from.
... | 0.842183 | 0.775286 |
"""Generated protocol buffer code."""
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_insertion_point(imports)
_sym_db = _symbol_databas... | python/discodisco/generated/proto/grpc/remote_pb2.py | """Generated protocol buffer code."""
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_insertion_point(imports)
_sym_db = _symbol_databas... | 0.331012 | 0.074265 |
from dataclasses import dataclass
'''
@property is getter method
getter use: Class.attribute
@attribute.setter is setter method
setter use: Class.attribute = attribute
dataclass(frozen=True) is immutable
'''
@dataclass
class SettingsModel:
'''
Data class for settings objects
'''
_dialect: str
... | big_teacher/src/model/DataModel.py | from dataclasses import dataclass
'''
@property is getter method
getter use: Class.attribute
@attribute.setter is setter method
setter use: Class.attribute = attribute
dataclass(frozen=True) is immutable
'''
@dataclass
class SettingsModel:
'''
Data class for settings objects
'''
_dialect: str
... | 0.725843 | 0.098686 |
import os
import time
import analogio
import board
import busio
import displayio
import neopixel
import sdcardio
import storage
import adafruit_ili9341
import adafruit_ov5640
# Release any resources currently in use for the displays
displayio.release_displays()
spi = busio.SPI(MOSI=board.LCD_MOSI, cl... | py/adafruit-circuitpython-bundle-7.x-mpy-20211104/examples/ov5640_sdcard_kaluga_1_3.py | import os
import time
import analogio
import board
import busio
import displayio
import neopixel
import sdcardio
import storage
import adafruit_ili9341
import adafruit_ov5640
# Release any resources currently in use for the displays
displayio.release_displays()
spi = busio.SPI(MOSI=board.LCD_MOSI, cl... | 0.275909 | 0.086362 |
# automate the tasks of managing a file-based postfix virtual alias / mailbox server
# written by masenf
# one day hack, the Version
import argparse
import base64
import difflib
import logging
import pwd
import os
import random
import shutil
import sys
import tempfile
import time
from subprocess import check_output, ... | mailtool.py |
# automate the tasks of managing a file-based postfix virtual alias / mailbox server
# written by masenf
# one day hack, the Version
import argparse
import base64
import difflib
import logging
import pwd
import os
import random
import shutil
import sys
import tempfile
import time
from subprocess import check_output, ... | 0.336658 | 0.082809 |
from django.db import models
from django.shortcuts import reverse
from users.models import Achievement
class Page(models.Model):
class Permissions(models.IntegerChoices):
PUBLIC = 0, 'Public'
USER = 1, 'Logged In'
MEMBER = 2, 'Member'
EX_EXEC = 3, 'Ex-Exec'
EXEC = 4, 'Exec... | pages/models.py | from django.db import models
from django.shortcuts import reverse
from users.models import Achievement
class Page(models.Model):
class Permissions(models.IntegerChoices):
PUBLIC = 0, 'Public'
USER = 1, 'Logged In'
MEMBER = 2, 'Member'
EX_EXEC = 3, 'Ex-Exec'
EXEC = 4, 'Exec... | 0.547222 | 0.082143 |
print("Part 1")
print("")
print_me = 10
for i in range(9):
string = ""
for j in range(i+1):
string += str(print_me) + " "
print_me += 1
print(string)
print("")
print("Part 2")
print("")
n = int(input("How large of a box? "))
border = 'o'*2*n
inner = 'o' + ' '*(2*n-2) + 'o'
p... | Exercises/5/main.py | print("Part 1")
print("")
print_me = 10
for i in range(9):
string = ""
for j in range(i+1):
string += str(print_me) + " "
print_me += 1
print(string)
print("")
print("Part 2")
print("")
n = int(input("How large of a box? "))
border = 'o'*2*n
inner = 'o' + ' '*(2*n-2) + 'o'
p... | 0.23793 | 0.10004 |
from typing import Tuple, Any, Callable, Optional, Dict, Type
from ax.core.runner import Runner
from ax.runners.synthetic import SyntheticRunner
from ax.storage.json_store.encoders import runner_to_dict
from ax.storage.json_store.registry import CORE_ENCODER_REGISTRY, CORE_DECODER_REGISTRY
from ax.utils.common.logger... | ax/storage/runner_registry.py |
from typing import Tuple, Any, Callable, Optional, Dict, Type
from ax.core.runner import Runner
from ax.runners.synthetic import SyntheticRunner
from ax.storage.json_store.encoders import runner_to_dict
from ax.storage.json_store.registry import CORE_ENCODER_REGISTRY, CORE_DECODER_REGISTRY
from ax.utils.common.logger... | 0.714628 | 0.389169 |
import logging
import tempfile
from pathlib import Path
from typing import List, Dict, Optional, Union
from torch.profiler import profile
from ray import train
from ray.train.callbacks import TrainingCallback
from ray.train.callbacks.logging import TrainCallbackLogdirManager
from ray.train.callbacks.results_preproces... | python/ray/train/callbacks/profile.py | import logging
import tempfile
from pathlib import Path
from typing import List, Dict, Optional, Union
from torch.profiler import profile
from ray import train
from ray.train.callbacks import TrainingCallback
from ray.train.callbacks.logging import TrainCallbackLogdirManager
from ray.train.callbacks.results_preproces... | 0.882441 | 0.175044 |
import os
import yaml
import zipfile
import shutil
import lmctl.files as files
import lmctl.project.handlers.interface as handlers_api
import lmctl.project.validation as project_validation
import lmctl.utils.descriptors as descriptor_utils
from .brent_content import BrentResourcePackageContentTree, BrentPkgContentTree
... | lmctl/project/handlers/brent/brent_src.py | import os
import yaml
import zipfile
import shutil
import lmctl.files as files
import lmctl.project.handlers.interface as handlers_api
import lmctl.project.validation as project_validation
import lmctl.utils.descriptors as descriptor_utils
from .brent_content import BrentResourcePackageContentTree, BrentPkgContentTree
... | 0.5144 | 0.122471 |
from collections import namedtuple
from collections.abc import Mapping, Set
from pypyr.dsl import SpecialTagDirective
from pypyr.errors import KeyInContextHasNoValueError, KeyNotInContextError
from pypyr.formatting import RecursiveFormatter
from pypyr.moduleloader import _ChainMapPretendDict
from pypyr.utils import as... | pypyr/context.py | from collections import namedtuple
from collections.abc import Mapping, Set
from pypyr.dsl import SpecialTagDirective
from pypyr.errors import KeyInContextHasNoValueError, KeyNotInContextError
from pypyr.formatting import RecursiveFormatter
from pypyr.moduleloader import _ChainMapPretendDict
from pypyr.utils import as... | 0.906266 | 0.360095 |
import sys
import operator
class UnionFind():
def __init__(self, n_nodes):
"""
Union-Find data structure initialization sets each node to be its own
parent (so that each node is in its own set/connected component), and
to also have rank 0.
Input - n_nodes: no of nodes
... | hackerrank/2017/w28/frndshp/frndshp.py | import sys
import operator
class UnionFind():
def __init__(self, n_nodes):
"""
Union-Find data structure initialization sets each node to be its own
parent (so that each node is in its own set/connected component), and
to also have rank 0.
Input - n_nodes: no of nodes
... | 0.344333 | 0.472866 |
import DistributedLawnDecor
from direct.directnotify import DirectNotifyGlobal
from direct.showbase.ShowBase import *
from direct.interval.IntervalGlobal import *
import GardenGlobals
from toontown.toonbase import TTLocalizer
from toontown.estate import PlantingGUI
from toontown.estate import PlantTreeGUI
from toontown... | v1.0.0.test/toontown/estate/DistributedGardenPlot.py | import DistributedLawnDecor
from direct.directnotify import DirectNotifyGlobal
from direct.showbase.ShowBase import *
from direct.interval.IntervalGlobal import *
import GardenGlobals
from toontown.toonbase import TTLocalizer
from toontown.estate import PlantingGUI
from toontown.estate import PlantTreeGUI
from toontown... | 0.375363 | 0.143218 |
import sys
from zlib import crc32
from depthcharge import log
from depthcharge.hunter import ReverseCRC32Hunter
THE_RAVEN = b"""
Once upon a midnight dreary, while I pondered, weak and weary,
Over many a quaint and curious volume of forgotten lore--
While I nodded, nearly napping, suddenly there came a tapping,
... | python/examples/reverse_crc32_algo_poc.py |
import sys
from zlib import crc32
from depthcharge import log
from depthcharge.hunter import ReverseCRC32Hunter
THE_RAVEN = b"""
Once upon a midnight dreary, while I pondered, weak and weary,
Over many a quaint and curious volume of forgotten lore--
While I nodded, nearly napping, suddenly there came a tapping,
... | 0.232746 | 0.35516 |
import matplotlib
matplotlib.use('agg')
import os
import sys
import yt
import matplotlib.pyplot as plt
import numpy as np
from functools import reduce
from mpl_toolkits.axes_grid1 import ImageGrid
# assume that our data is in CGS
from yt.units import cm, amu
from yt.frontends.boxlib.api import LogiDataset
from yt.v... | Exec/science/massive_star/analysis/massive_star_composition.py |
import matplotlib
matplotlib.use('agg')
import os
import sys
import yt
import matplotlib.pyplot as plt
import numpy as np
from functools import reduce
from mpl_toolkits.axes_grid1 import ImageGrid
# assume that our data is in CGS
from yt.units import cm, amu
from yt.frontends.boxlib.api import LogiDataset
from yt.v... | 0.318909 | 0.55652 |
from __future__ import print_function, division, absolute_import
from ..rna import (
load_cufflinks_fpkm_dict,
load_transcript_fpkm_dict_from_gtf
)
def add_rna_args(arg_parser):
rna_group = arg_parser.add_argument_group(
title="RNA-Seq",
description="Transcript and gene abundance quantific... | topiary/cli/rna.py | from __future__ import print_function, division, absolute_import
from ..rna import (
load_cufflinks_fpkm_dict,
load_transcript_fpkm_dict_from_gtf
)
def add_rna_args(arg_parser):
rna_group = arg_parser.add_argument_group(
title="RNA-Seq",
description="Transcript and gene abundance quantific... | 0.71113 | 0.248039 |
import argparse
def str2bool(v):
if isinstance(v, bool):
return v
# pylint: disable=no-else-return
if v.lower() in ("yes", "true", "t", "y", "1"):
return True
elif v.lower() in ("no", "false", "f", "n", "0"):
return False
else:
raise argparse.ArgumentTypeError("Bool... | cloudiscovery/shared/parameters.py | import argparse
def str2bool(v):
if isinstance(v, bool):
return v
# pylint: disable=no-else-return
if v.lower() in ("yes", "true", "t", "y", "1"):
return True
elif v.lower() in ("no", "false", "f", "n", "0"):
return False
else:
raise argparse.ArgumentTypeError("Bool... | 0.508788 | 0.124505 |
import argparse
import http.server
import logging
import os
import re
import shutil
import sys
from http import HTTPStatus
sys.path.append(
os.path.dirname(
os.path.dirname(
os.path.abspath(__file__)
)
)
)
import mdlight.index.tree
from mdlight.index.pages import MarkdownPage... | mdlight/server.py | import argparse
import http.server
import logging
import os
import re
import shutil
import sys
from http import HTTPStatus
sys.path.append(
os.path.dirname(
os.path.dirname(
os.path.abspath(__file__)
)
)
)
import mdlight.index.tree
from mdlight.index.pages import MarkdownPage... | 0.320396 | 0.061734 |
import logging
from abc import ABC
from typing import Mapping, List
from tqdm import tqdm
from codeprep.preprocess.codestructure import CodeBaseStructure
from codeprep.preprocess.tokens import TokenSequence
from langmodels.evaluation.characteristics import characterize_token
from langmodels.evaluation.dataloader impo... | langmodels/evaluation/metrics.py | import logging
from abc import ABC
from typing import Mapping, List
from tqdm import tqdm
from codeprep.preprocess.codestructure import CodeBaseStructure
from codeprep.preprocess.tokens import TokenSequence
from langmodels.evaluation.characteristics import characterize_token
from langmodels.evaluation.dataloader impo... | 0.842248 | 0.173393 |
from __future__ import print_function
import numpy as np
import pytest
import kernel_tuner
from .context import skip_if_no_cuda
@pytest.fixture
def env():
kernel_string = """
__global__ void vector_add(float *c, float *a, float *b, int n) {
int i = blockIdx.x * block_size_x + threadIdx.x;
i... | test/test_runners.py | from __future__ import print_function
import numpy as np
import pytest
import kernel_tuner
from .context import skip_if_no_cuda
@pytest.fixture
def env():
kernel_string = """
__global__ void vector_add(float *c, float *a, float *b, int n) {
int i = blockIdx.x * block_size_x + threadIdx.x;
i... | 0.680454 | 0.539165 |
import os
from ..run import run
from ..utils import BuildConfig
from ..utils import add_coverage_argument
from ..utils import add_jobs_argument
from ..utils import add_no_ccache_argument
from ..utils import add_optimize_argument
from ..utils import add_unsafe_argument
from ..utils import add_url_argument
from ..utils ... | mys/cli/subparsers/test.py | import os
from ..run import run
from ..utils import BuildConfig
from ..utils import add_coverage_argument
from ..utils import add_jobs_argument
from ..utils import add_no_ccache_argument
from ..utils import add_optimize_argument
from ..utils import add_unsafe_argument
from ..utils import add_url_argument
from ..utils ... | 0.23467 | 0.070528 |
import random
import ray
from typing import List, Type
import gym
import hydra
import matplotlib.pyplot as plt
import numpy as np
from cmaes import CMA
from matplotlib import animation
from omegaconf.dictconfig import DictConfig
from scipy.sparse.csr import csr_matrix
from torch import optim
from tqdm import tqdm
cl... | esn_rl/dqn_esn.py | import random
import ray
from typing import List, Type
import gym
import hydra
import matplotlib.pyplot as plt
import numpy as np
from cmaes import CMA
from matplotlib import animation
from omegaconf.dictconfig import DictConfig
from scipy.sparse.csr import csr_matrix
from torch import optim
from tqdm import tqdm
cl... | 0.864711 | 0.568595 |
import requests
from asyncio.tasks import sleep
from cogs.dbc import DaedalusBaseCog
from core.utils import yaml, dprint, print_exc
from discord.colour import Colour
from discord.embeds import Embed
from discord.ext import commands
from discord.ext.commands.cooldowns import BucketType
from random import randi... | src/cogs/games.py | import requests
from asyncio.tasks import sleep
from cogs.dbc import DaedalusBaseCog
from core.utils import yaml, dprint, print_exc
from discord.colour import Colour
from discord.embeds import Embed
from discord.ext import commands
from discord.ext.commands.cooldowns import BucketType
from random import randi... | 0.29381 | 0.111919 |
from unittest import TestCase
import os, sys
# 3rd party lib support
if sys.version_info[0] == 3:
from pathlib import Path
else:
from pathlib2 import Path
ModuleNotFoundError = ImportError
# local lib imports
try:
from pylightxl import pylightxl as xl
except ModuleNotFoundError:
sys.path.append('... | test/test_readxl.py | from unittest import TestCase
import os, sys
# 3rd party lib support
if sys.version_info[0] == 3:
from pathlib import Path
else:
from pathlib2 import Path
ModuleNotFoundError = ImportError
# local lib imports
try:
from pylightxl import pylightxl as xl
except ModuleNotFoundError:
sys.path.append('... | 0.372619 | 0.413596 |