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 f16lib.models.f16 as f16
import f16lib.models.llc as llc
import f16lib.models.autopilot as auto
import f16lib.models.autoairspeed as autoair
import f16lib.models.autoaltitude as autoalt
import f16lib.models.autowaypoint as awaypoint
import f16lib.models.switch as switch
import f16lib.models.autoacas as acas
impo... | new_csaf/f16lib/components.py | import f16lib.models.f16 as f16
import f16lib.models.llc as llc
import f16lib.models.autopilot as auto
import f16lib.models.autoairspeed as autoair
import f16lib.models.autoaltitude as autoalt
import f16lib.models.autowaypoint as awaypoint
import f16lib.models.switch as switch
import f16lib.models.autoacas as acas
impo... | 0.637369 | 0.232169 |
from tkinter import *
from tkinter import messagebox
window=Tk()
window.title("CALCULATOR")
f=StringVar()
s=StringVar()
def calsum():
fs=int(f.get())
ss=int(s.get())
r=fs+ss
messagebox.showinfo("output","result="+str(r))
messagebox.showinfo("confirmation page","done !!")
def calsub():
fs=int(f... | day5/calculator.py | from tkinter import *
from tkinter import messagebox
window=Tk()
window.title("CALCULATOR")
f=StringVar()
s=StringVar()
def calsum():
fs=int(f.get())
ss=int(s.get())
r=fs+ss
messagebox.showinfo("output","result="+str(r))
messagebox.showinfo("confirmation page","done !!")
def calsub():
fs=int(f... | 0.266262 | 0.085901 |
import functools
from typing import Sequence
from absl.testing import absltest
from acme.utils import tree_utils
import numpy as np
import tree
TEST_SEQUENCE = [
{
'action': np.array([1.0]),
'observation': (np.array([0.0, 1.0, 2.0]),),
'reward': np.array(1.0),
},
{
'action'... | acme/utils/tree_utils_test.py | import functools
from typing import Sequence
from absl.testing import absltest
from acme.utils import tree_utils
import numpy as np
import tree
TEST_SEQUENCE = [
{
'action': np.array([1.0]),
'observation': (np.array([0.0, 1.0, 2.0]),),
'reward': np.array(1.0),
},
{
'action'... | 0.89915 | 0.756785 |
from CommonServerPython import *
import traceback
SECTIONS_TO_KEEP = ('Threat Hunting', 'Mitigation', 'Remediation', 'Eradication')
HEADER_TRANSFORM = {'id': 'Task ID', 'name': 'Task Name', 'state': 'Task State', 'completedDate': 'Completion Time'}
''' COMMAND FUNCTION '''
def add_url_to_tasks(tasks: Dict, workpl... | Packs/DemistoRESTAPI/Scripts/SetIRProceduresMarkdown/SetIRProceduresMarkdown.py | from CommonServerPython import *
import traceback
SECTIONS_TO_KEEP = ('Threat Hunting', 'Mitigation', 'Remediation', 'Eradication')
HEADER_TRANSFORM = {'id': 'Task ID', 'name': 'Task Name', 'state': 'Task State', 'completedDate': 'Completion Time'}
''' COMMAND FUNCTION '''
def add_url_to_tasks(tasks: Dict, workpl... | 0.341692 | 0.298696 |
import arrow
from flask import request, render_template, redirect, url_for, flash, session, g
from flask_login import login_user
from flask_wtf import FlaskForm
from wtforms import StringField, validators
from app.auth.base import auth_bp
from app.config import MFA_USER_ID
from app.db import Session
from app.email_uti... | app/auth/views/recovery.py | import arrow
from flask import request, render_template, redirect, url_for, flash, session, g
from flask_login import login_user
from flask_wtf import FlaskForm
from wtforms import StringField, validators
from app.auth.base import auth_bp
from app.config import MFA_USER_ID
from app.db import Session
from app.email_uti... | 0.311741 | 0.057335 |
from __future__ import annotations
from functools import partial
from colour.characterisation import RGB_DisplayPrimaries
from colour.hints import Dict
from colour.utilities import LazyCaseInsensitiveMapping
__author__ = "Colour Developers"
__copyright__ = "Copyright (C) 2013-2022 - Colour Developers"
__license__ = ... | colour/characterisation/datasets/displays/crt/primaries.py | from __future__ import annotations
from functools import partial
from colour.characterisation import RGB_DisplayPrimaries
from colour.hints import Dict
from colour.utilities import LazyCaseInsensitiveMapping
__author__ = "Colour Developers"
__copyright__ = "Copyright (C) 2013-2022 - Colour Developers"
__license__ = ... | 0.816772 | 0.185929 |
from bleach import clean
import pandas as pd
import argparse
from sklearn.model_selection import train_test_split
import preprocessor as p # forming a separate feature for cleaned tweets
from nlpaug.augmenter.word.synonym import SynonymAug
from nlpaug.augmenter.word.back_translation import BackTranslationAug
SPLIT_PR... | preprocessing/data_prep.py | from bleach import clean
import pandas as pd
import argparse
from sklearn.model_selection import train_test_split
import preprocessor as p # forming a separate feature for cleaned tweets
from nlpaug.augmenter.word.synonym import SynonymAug
from nlpaug.augmenter.word.back_translation import BackTranslationAug
SPLIT_PR... | 0.348091 | 0.183484 |
import os
import importlib
import json
from typing import Union
from flask import Response
from flask.testing import Client
import pytest
@pytest.fixture
def app(service_module_name):
# Ensure that test configuration will be loaded
os.environ["SERVER_ENVIRONMENT"] = "test"
service_module = importlib.impo... | pytest_layab/flask.py | import os
import importlib
import json
from typing import Union
from flask import Response
from flask.testing import Client
import pytest
@pytest.fixture
def app(service_module_name):
# Ensure that test configuration will be loaded
os.environ["SERVER_ENVIRONMENT"] = "test"
service_module = importlib.impo... | 0.802556 | 0.422624 |
import itertools as it
import re
import types
from plato_pylib.shared.ucell_class import UnitCell
from plato_pylib.shared.energies_class import EnergyVals
from . import parse_xyz_files as parseXyzHelp
from ..shared import custom_errors as errorHelp
from ..shared import unit_convs as uConvHelp
import pycp2k
RYD_TO_E... | plato_pylib/parseOther/parse_cp2k_files.py |
import itertools as it
import re
import types
from plato_pylib.shared.ucell_class import UnitCell
from plato_pylib.shared.energies_class import EnergyVals
from . import parse_xyz_files as parseXyzHelp
from ..shared import custom_errors as errorHelp
from ..shared import unit_convs as uConvHelp
import pycp2k
RYD_TO_E... | 0.452052 | 0.204223 |
from copy import copy
from openpyxl.cell import Cell
from openpyxl.worksheet import Worksheet
import openpyxl
from wysiwygtemplate.dictcontext import DictExcelTemplateContext
from wysiwygtemplate.looptemplate import ExcelArchetectureTemplate
from wysiwygtemplate.pyevaluator import PyEvaluator, EmbeddedPyEvaluator
fr... | wysiwygtemplate/openpyprocessor.py | from copy import copy
from openpyxl.cell import Cell
from openpyxl.worksheet import Worksheet
import openpyxl
from wysiwygtemplate.dictcontext import DictExcelTemplateContext
from wysiwygtemplate.looptemplate import ExcelArchetectureTemplate
from wysiwygtemplate.pyevaluator import PyEvaluator, EmbeddedPyEvaluator
fr... | 0.302082 | 0.308789 |
import collections
import os
import random
from typing import Deque
import gym
import numpy as np
from cartPoleDqn import DQN
PROJECT_PATH = os.path.abspath("C:/Users/Jan/Dropbox/_Coding/UdemyAI")
MODELS_PATH = os.path.join(PROJECT_PATH, "models")
MODEL_PATH = os.path.join(MODELS_PATH, "dqn_cartpole.h5")
class Ag... | Chapter10_DeepQNetworks/5_Finish/cartPoleDqnAgent.py | import collections
import os
import random
from typing import Deque
import gym
import numpy as np
from cartPoleDqn import DQN
PROJECT_PATH = os.path.abspath("C:/Users/Jan/Dropbox/_Coding/UdemyAI")
MODELS_PATH = os.path.join(PROJECT_PATH, "models")
MODEL_PATH = os.path.join(MODELS_PATH, "dqn_cartpole.h5")
class Ag... | 0.684053 | 0.249659 |
import math
import os
import sys
import glob
import gc
import threading
from pathlib import Path
from simplygon9 import simplygon_loader
from simplygon9 import Simplygon
def LoadScene(sg: Simplygon.ISimplygon, path: str):
# Create scene importer
sgSceneImporter = sg.CreateSceneImporter()
sgSceneImporte... | Src/Python/GeometryDataCasting/GeometryDataCasting.py |
import math
import os
import sys
import glob
import gc
import threading
from pathlib import Path
from simplygon9 import simplygon_loader
from simplygon9 import Simplygon
def LoadScene(sg: Simplygon.ISimplygon, path: str):
# Create scene importer
sgSceneImporter = sg.CreateSceneImporter()
sgSceneImporte... | 0.415136 | 0.193566 |
"""Events that fire if messages are sent/updated/deleted."""
from __future__ import annotations
__all__: typing.List[str] = [
"MessageEvent",
"MessageCreateEvent",
"MessageUpdateEvent",
"MessageDeleteEvent",
"GuildMessageCreateEvent",
"GuildMessageUpdateEvent",
"GuildMessageDeleteEvent",
... | hikari/events/message_events.py | """Events that fire if messages are sent/updated/deleted."""
from __future__ import annotations
__all__: typing.List[str] = [
"MessageEvent",
"MessageCreateEvent",
"MessageUpdateEvent",
"MessageDeleteEvent",
"GuildMessageCreateEvent",
"GuildMessageUpdateEvent",
"GuildMessageDeleteEvent",
... | 0.919448 | 0.319639 |
from django.http import Http404
from django.utils.decorators import method_decorator
from django.views.decorators.cache import cache_page
import django_filters.rest_framework
from rest_framework import response, status
from rest_framework.filters import OrderingFilter, SearchFilter
from rest_framework.generics import ... | safe_transaction_service/tokens/views.py | from django.http import Http404
from django.utils.decorators import method_decorator
from django.views.decorators.cache import cache_page
import django_filters.rest_framework
from rest_framework import response, status
from rest_framework.filters import OrderingFilter, SearchFilter
from rest_framework.generics import ... | 0.50952 | 0.07333 |
import sys
import os, os.path
import shutil
from optparse import OptionParser
def get_num_of_cpu():
''' The build process can be accelerated by running multiple concurrent job processes using the -j-option.
'''
try:
platform = sys.platform
if platform == 'win32':
if 'NUMBER_OF_P... | samples/MoonWarriors/frameworks/runtime-src/proj.android/build_native.py | import sys
import os, os.path
import shutil
from optparse import OptionParser
def get_num_of_cpu():
''' The build process can be accelerated by running multiple concurrent job processes using the -j-option.
'''
try:
platform = sys.platform
if platform == 'win32':
if 'NUMBER_OF_P... | 0.092814 | 0.095181 |
__author__ = '<NAME>'
import pika
import json
from pydispatch import dispatcher
VISUAL_FACE_DETECTION = 'VISUAL_FACE_DETECTION'
VISUAL_FACE_DETECTION = 'VISUAL_FACE_DETECTION'
VISUAL_FACE_RECOGNITION ='VISUAL_FACE_RECOGNITION'
VISUAL_FACE_TRACKING = 'VISUAL_FACE_TRACKING'
VISUAL_HUMAN_TRACKING = 'VISUAL_HUMAN_TRACKING... | Data.py | __author__ = '<NAME>'
import pika
import json
from pydispatch import dispatcher
VISUAL_FACE_DETECTION = 'VISUAL_FACE_DETECTION'
VISUAL_FACE_DETECTION = 'VISUAL_FACE_DETECTION'
VISUAL_FACE_RECOGNITION ='VISUAL_FACE_RECOGNITION'
VISUAL_FACE_TRACKING = 'VISUAL_FACE_TRACKING'
VISUAL_HUMAN_TRACKING = 'VISUAL_HUMAN_TRACKING... | 0.333178 | 0.052303 |
import os
import sys
from functools import lru_cache
@lru_cache(maxsize=None)
def _get_test_folder():
"""Get path of the main test folder.
Path is assumed to be located somewhere above this file. This computation
is cached as the absolute directory of the cache isn't expected to change.
Returns:
... | foreshadow/utils/testing.py |
import os
import sys
from functools import lru_cache
@lru_cache(maxsize=None)
def _get_test_folder():
"""Get path of the main test folder.
Path is assumed to be located somewhere above this file. This computation
is cached as the absolute directory of the cache isn't expected to change.
Returns:
... | 0.615897 | 0.331147 |
from .conf import *
from gym_electric_motor.physical_systems import *
from gym_electric_motor.utils import make_module, set_state_array
from gym_electric_motor import ReferenceGenerator, RewardFunction, PhysicalSystem, ElectricMotorVisualization, \
ConstraintMonitor
from gym_electric_motor.physical_systems import P... | tests/testing_utils.py | from .conf import *
from gym_electric_motor.physical_systems import *
from gym_electric_motor.utils import make_module, set_state_array
from gym_electric_motor import ReferenceGenerator, RewardFunction, PhysicalSystem, ElectricMotorVisualization, \
ConstraintMonitor
from gym_electric_motor.physical_systems import P... | 0.858259 | 0.435181 |
from threading import Timer
from olo.database import BaseDataBase, MySQLCursor
from olo.libs.class_proxy import ClassProxy
from olo.libs.pool import Pool, ConnProxy
def create_conn(host, port, user, password, dbname, charset):
try:
from MySQLdb import connect
conn = connect( # pragma: no cover
... | olo/database/mysql.py | from threading import Timer
from olo.database import BaseDataBase, MySQLCursor
from olo.libs.class_proxy import ClassProxy
from olo.libs.pool import Pool, ConnProxy
def create_conn(host, port, user, password, dbname, charset):
try:
from MySQLdb import connect
conn = connect( # pragma: no cover
... | 0.521959 | 0.099426 |
import torch
import torch.nn as nn
from .network_builder import NetworkBuilder, A2CBuilder
from ..modules.pointnet_modules import pointnet
class A2CPNBuilder(A2CBuilder):
class Network(NetworkBuilder.BaseNetwork):
def __init__(self, params, **kwargs):
actions_num = kwargs.pop('actions_num')
... | rl_games/algos_torch/pn_network_builder.py | import torch
import torch.nn as nn
from .network_builder import NetworkBuilder, A2CBuilder
from ..modules.pointnet_modules import pointnet
class A2CPNBuilder(A2CBuilder):
class Network(NetworkBuilder.BaseNetwork):
def __init__(self, params, **kwargs):
actions_num = kwargs.pop('actions_num')
... | 0.795777 | 0.320715 |
import numpy as np
import pytest
from peleffy.forcefield.parameters import OPLS2005ParameterWrapper
from simtk import unit
FORCEFIELD_NAME = 'openff_unconstrained-1.2.0.offxml'
METHANE_OPLS_PARAMETERS = OPLS2005ParameterWrapper({
'atom_names': [' C1 ', ' H2 ', ' H3 ', ' H4 ', ' H5 '],
'atom_types': ['CT', 'H... | peleffy/tests/test_toolkits.py | import numpy as np
import pytest
from peleffy.forcefield.parameters import OPLS2005ParameterWrapper
from simtk import unit
FORCEFIELD_NAME = 'openff_unconstrained-1.2.0.offxml'
METHANE_OPLS_PARAMETERS = OPLS2005ParameterWrapper({
'atom_names': [' C1 ', ' H2 ', ' H3 ', ' H4 ', ' H5 '],
'atom_types': ['CT', 'H... | 0.775095 | 0.628464 |
import xml.etree.ElementTree as ET
from typing import Callable, Dict, List, Mapping, Sequence, TYPE_CHECKING
from chb.app.BasicBlock import BasicBlock
import chb.util.fileutil as UF
from chb.arm.ARMDictionary import ARMDictionary
from chb.arm.ARMInstruction import ARMInstruction
from chb.invariants.XXpr import XX... | chb/arm/ARMBlock.py |
import xml.etree.ElementTree as ET
from typing import Callable, Dict, List, Mapping, Sequence, TYPE_CHECKING
from chb.app.BasicBlock import BasicBlock
import chb.util.fileutil as UF
from chb.arm.ARMDictionary import ARMDictionary
from chb.arm.ARMInstruction import ARMInstruction
from chb.invariants.XXpr import XX... | 0.814348 | 0.201951 |
import functools
import itertools
import jmespath
from c7n.actions import BaseAction
from c7n.filters import ValueFilter
from c7n.filters.kms import KmsRelatedFilter
from c7n.manager import resources
from c7n.query import QueryResourceManager, TypeInfo
from c7n.tags import universal_augment
from c7n.exceptions import ... | c7n/resources/workspaces.py | import functools
import itertools
import jmespath
from c7n.actions import BaseAction
from c7n.filters import ValueFilter
from c7n.filters.kms import KmsRelatedFilter
from c7n.manager import resources
from c7n.query import QueryResourceManager, TypeInfo
from c7n.tags import universal_augment
from c7n.exceptions import ... | 0.489259 | 0.098599 |
import datetime
import decimal
import io
import os
from pathlib import Path
from tempfile import NamedTemporaryFile
import numpy as np
import pytest
import matplotlib as mpl
from matplotlib import dviread, pyplot as plt, checkdep_usetex, rcParams
from matplotlib.backends.backend_pdf import PdfPages
from matplotlib.te... | venv/Lib/site-packages/matplotlib/tests/test_backend_pdf.py | import datetime
import decimal
import io
import os
from pathlib import Path
from tempfile import NamedTemporaryFile
import numpy as np
import pytest
import matplotlib as mpl
from matplotlib import dviread, pyplot as plt, checkdep_usetex, rcParams
from matplotlib.backends.backend_pdf import PdfPages
from matplotlib.te... | 0.517327 | 0.439868 |
from typing import List
from fastapi_utils.api_model import APIMessage
from fastapi_utils.cbv import cbv
from fastapi_utils.inferring_router import InferringRouter
from fastapi import Depends, status, Response
from odmantic import ObjectId
from app.schema import DatasetPostSchema, DatasetGetSortQuery, \
DatasetTo... | app/views/datasets.py | from typing import List
from fastapi_utils.api_model import APIMessage
from fastapi_utils.cbv import cbv
from fastapi_utils.inferring_router import InferringRouter
from fastapi import Depends, status, Response
from odmantic import ObjectId
from app.schema import DatasetPostSchema, DatasetGetSortQuery, \
DatasetTo... | 0.704872 | 0.287749 |
import random
from .vbc_class import Player
from .vbc_base import compare_value, base_push, base_push_index, remain_rank_sort
from functools import cmp_to_key
from .vbc_value_probability import final_push_value, final_answer_probability
def final_set(players, set_number):
players_number = 3
winners_num... | module/vbc_F.py | import random
from .vbc_class import Player
from .vbc_base import compare_value, base_push, base_push_index, remain_rank_sort
from functools import cmp_to_key
from .vbc_value_probability import final_push_value, final_answer_probability
def final_set(players, set_number):
players_number = 3
winners_num... | 0.151122 | 0.156105 |
import sys
sys.path.append('..')
import specrel.geom as geom
import specrel.graphics.companim as canim
import specrel.spacetime.physical as phy
import specrel.visualize as vis
# Planets
origin = 0
planetdist = 1
x_planet = origin + planetdist
earth = phy.MovingObject(origin,
draw_options={'color': 'blue', 'marker... | examples/9-twinparadox.py | import sys
sys.path.append('..')
import specrel.geom as geom
import specrel.graphics.companim as canim
import specrel.spacetime.physical as phy
import specrel.visualize as vis
# Planets
origin = 0
planetdist = 1
x_planet = origin + planetdist
earth = phy.MovingObject(origin,
draw_options={'color': 'blue', 'marker... | 0.538983 | 0.338241 |
import os
import itertools
import logging as L
import numpy as np
from perf_compare import execute
L.basicConfig(format='%(levelname)s:%(message)s', level=L.DEBUG)
class Autotune():
def __init__(self, template_list, key_values, cmd):
"""
template_list: ['GroupCOOSparseMatrix.h.t', 'cnnBench2.cu.t... | src/autotune.py | import os
import itertools
import logging as L
import numpy as np
from perf_compare import execute
L.basicConfig(format='%(levelname)s:%(message)s', level=L.DEBUG)
class Autotune():
def __init__(self, template_list, key_values, cmd):
"""
template_list: ['GroupCOOSparseMatrix.h.t', 'cnnBench2.cu.t... | 0.13852 | 0.190667 |
from collections import OrderedDict
import pytest
from fiona_settings import CRS, Settings, Driver, Geometry, Type
class Collection:
def __init__(
self,
driver: Driver = Driver.GeoJSON,
schema: dict = None,
crs: CRS = CRS.WGS84,
encoding: str = "utf-8",
):
sel... | test/test_settings.py | from collections import OrderedDict
import pytest
from fiona_settings import CRS, Settings, Driver, Geometry, Type
class Collection:
def __init__(
self,
driver: Driver = Driver.GeoJSON,
schema: dict = None,
crs: CRS = CRS.WGS84,
encoding: str = "utf-8",
):
sel... | 0.808219 | 0.441854 |
from unittest import mock
import pytest
from h_matchers import Any
from h.traversal.group import GroupContext
from h.views.admin import groups
from h.views.admin.groups import GroupCreateViews, GroupEditViews
class FakeForm:
appstruct = None
def set_appstruct(self, appstruct):
self.appstruct = apps... | tests/h/views/admin/groups_test.py | from unittest import mock
import pytest
from h_matchers import Any
from h.traversal.group import GroupContext
from h.views.admin import groups
from h.views.admin.groups import GroupCreateViews, GroupEditViews
class FakeForm:
appstruct = None
def set_appstruct(self, appstruct):
self.appstruct = apps... | 0.773302 | 0.341322 |
import numpy as np
class Graph():
def __init__(self , path , graph = dict() , circle = list()):
self.data = np.loadtxt(path , delimiter= "," , dtype=np.int16)
self.data = self.data[np.argsort(self.data[:,0])]
self.graph = graph
self.circlePath = circle
self.tempPath ... | Main.py | import numpy as np
class Graph():
def __init__(self , path , graph = dict() , circle = list()):
self.data = np.loadtxt(path , delimiter= "," , dtype=np.int16)
self.data = self.data[np.argsort(self.data[:,0])]
self.graph = graph
self.circlePath = circle
self.tempPath ... | 0.048869 | 0.121607 |
import os
import re
import test.support
import time
import unittest
import urllib.request
from http.cookiejar import time2isoz, http2time, iso2time, time2netscape, parse_ns_headers, join_header_words, split_header_words, Cookie, CookieJar, DefaultCookiePolicy, LWPCookieJar, MozillaCookieJar, LoadError, lwp_cookie_str, ... | code/tmp_rtrip/test/test_http_cookiejar.py | import os
import re
import test.support
import time
import unittest
import urllib.request
from http.cookiejar import time2isoz, http2time, iso2time, time2netscape, parse_ns_headers, join_header_words, split_header_words, Cookie, CookieJar, DefaultCookiePolicy, LWPCookieJar, MozillaCookieJar, LoadError, lwp_cookie_str, ... | 0.421076 | 0.272164 |
import pandas as pd
import numpy as np
import keras
from keras.models import Sequential
from keras.layers import Dense
from sklearn.cross_validation import train_test_split
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
from keras.utils import np_utils
import pickle
data = pd.read_csv("C:/pr... | final_running_model.py | import pandas as pd
import numpy as np
import keras
from keras.models import Sequential
from keras.layers import Dense
from sklearn.cross_validation import train_test_split
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
from keras.utils import np_utils
import pickle
data = pd.read_csv("C:/pr... | 0.531453 | 0.181155 |
from datetime import datetime, timedelta
import pandas as pd
class TuDataModel:
"""
Class Terminal Unit, never modify any variable direct. The idea is that all gets managed via functions
"""
def __init__(self, name):
"""
Constructor of the Tu as a holder for all the TG Tu Dat... | tu_data_model.py | from datetime import datetime, timedelta
import pandas as pd
class TuDataModel:
"""
Class Terminal Unit, never modify any variable direct. The idea is that all gets managed via functions
"""
def __init__(self, name):
"""
Constructor of the Tu as a holder for all the TG Tu Dat... | 0.750827 | 0.346458 |
import cv2
import time
import argparse
import os
import torch
import posenet
parser = argparse.ArgumentParser()
parser.add_argument('--model', type=int, default=101)
parser.add_argument('--scale_factor', type=float, default=1.0)
parser.add_argument('--notxt', action='store_true')
parser.add_argument('--image_dir', t... | code/posenet-py-torch/image_demo.py | import cv2
import time
import argparse
import os
import torch
import posenet
parser = argparse.ArgumentParser()
parser.add_argument('--model', type=int, default=101)
parser.add_argument('--scale_factor', type=float, default=1.0)
parser.add_argument('--notxt', action='store_true')
parser.add_argument('--image_dir', t... | 0.460289 | 0.116991 |
import numpy as np
from deep_filters.core.filters import filters
from keras.preprocessing.image import load_img, img_to_array
def load_array_image(paths, mode, kernel=(128, 128), img_filter='zoom', channels=3, model=None, zoom_learn=2, resize=False, **kwargs):
"""
3 channels as 3 batch datas
:param path:... | deep_filters/core/images.py | import numpy as np
from deep_filters.core.filters import filters
from keras.preprocessing.image import load_img, img_to_array
def load_array_image(paths, mode, kernel=(128, 128), img_filter='zoom', channels=3, model=None, zoom_learn=2, resize=False, **kwargs):
"""
3 channels as 3 batch datas
:param path:... | 0.627267 | 0.46721 |
from flask import Flask, request, jsonify
from flask_cors import CORS, cross_origin
import socket
import psycopg2
import json
from google.oauth2 import id_token
from google.auth.transport import requests as requests_google
import requests
print('starting server')
#initialize app
app = Flask(__name__)
CORS(app)
#func... | app.py | from flask import Flask, request, jsonify
from flask_cors import CORS, cross_origin
import socket
import psycopg2
import json
from google.oauth2 import id_token
from google.auth.transport import requests as requests_google
import requests
print('starting server')
#initialize app
app = Flask(__name__)
CORS(app)
#func... | 0.195287 | 0.072571 |
import locale
import sys
from collections import OrderedDict
from io import StringIO
import numpy as np
import pandas as pd
from .. import dp_logging
from . import data_utils
logger = dp_logging.get_child_logger(__name__)
class BaseData(object):
"""
Abstract class for data loading and saving
"""
d... | dataprofiler/data_readers/base_data.py | import locale
import sys
from collections import OrderedDict
from io import StringIO
import numpy as np
import pandas as pd
from .. import dp_logging
from . import data_utils
logger = dp_logging.get_child_logger(__name__)
class BaseData(object):
"""
Abstract class for data loading and saving
"""
d... | 0.483892 | 0.45302 |
from __future__ import absolute_import
import logging
import os
import time
import click
import cachetools
import functools
import itertools
import re
from pathlib import Path
import pandas as pd
try:
import cPickle as pickle
except ImportError:
import pickle
from datacube.ui import click as dc_ui
from data... | datacube/ui/task_app.py | from __future__ import absolute_import
import logging
import os
import time
import click
import cachetools
import functools
import itertools
import re
from pathlib import Path
import pandas as pd
try:
import cPickle as pickle
except ImportError:
import pickle
from datacube.ui import click as dc_ui
from data... | 0.574037 | 0.104981 |
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
class Config(object):
"""
配置参数
"""
def __init__(self, dataset):
self.model_name = 'DPCNN'
self.class_list = [x.strip() for x in open(
dataset + '/data/class.txt', encoding='utf-8').readlin... | src/DL/models/DPCNN.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
class Config(object):
"""
配置参数
"""
def __init__(self, dataset):
self.model_name = 'DPCNN'
self.class_list = [x.strip() for x in open(
dataset + '/data/class.txt', encoding='utf-8').readlin... | 0.714329 | 0.305185 |
import datetime as dt
from ravenpy.models import GR4JCN
from ravenpy.utilities.testdata import get_local_testdata
"""
Test to perform a hindcast using Caspar data on THREDDS.
Currently only runs GEPS, eventually will run GEPS, GDPS, REPS and RDPS.
To do so will need to add the actual data from Caspar, currently being... | tests/test_hindcasting.py | import datetime as dt
from ravenpy.models import GR4JCN
from ravenpy.utilities.testdata import get_local_testdata
"""
Test to perform a hindcast using Caspar data on THREDDS.
Currently only runs GEPS, eventually will run GEPS, GDPS, REPS and RDPS.
To do so will need to add the actual data from Caspar, currently being... | 0.581897 | 0.602383 |
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as cp
from fairseq.incremental_decoding_utils import with_incremental_state
@with_incremental_state
class MaskedConvolution(nn.Conv2d):
""" 2d convolution with masked kernel """
def __init__(self,
... | examples/pervasive/modules/masked_convolution.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as cp
from fairseq.incremental_decoding_utils import with_incremental_state
@with_incremental_state
class MaskedConvolution(nn.Conv2d):
""" 2d convolution with masked kernel """
def __init__(self,
... | 0.916044 | 0.39636 |
import zmq.green as zmq
import gevent
from gevent.queue import PriorityQueue
import yaml
from .. import messages
from itertools import count
import logging
logger = logging.getLogger('ansible_automata.connectors.zmq')
class ZMQEventChannel(object):
def __init__(self, fsm_registry, connector_registry, configurat... | ansible_automata/connectors/zmq.py | import zmq.green as zmq
import gevent
from gevent.queue import PriorityQueue
import yaml
from .. import messages
from itertools import count
import logging
logger = logging.getLogger('ansible_automata.connectors.zmq')
class ZMQEventChannel(object):
def __init__(self, fsm_registry, connector_registry, configurat... | 0.207616 | 0.049797 |
import config
import awb
import csv
import json
import requests
import re
emapping = {
"ekialdeko-nafarra": "Q752",
"erronkarikoa": "Q753",
"zaraitzukoa": "Q754",
"erdialdekoa-gipuzkera": "Q755",
"erdigunekoa-g": "Q756",
"beterrikoa": "Q757",
"tolosaldekoa": "Q758",
"sartaldekoa-g": "Q759",
"goierrikoa": "Q760",
"urol... | herriak_ahotsak_parsehtml.py | import config
import awb
import csv
import json
import requests
import re
emapping = {
"ekialdeko-nafarra": "Q752",
"erronkarikoa": "Q753",
"zaraitzukoa": "Q754",
"erdialdekoa-gipuzkera": "Q755",
"erdigunekoa-g": "Q756",
"beterrikoa": "Q757",
"tolosaldekoa": "Q758",
"sartaldekoa-g": "Q759",
"goierrikoa": "Q760",
"urol... | 0.052619 | 0.247822 |
class TrieNode:
# Initialize your data structure here.
def __init__(self):
# reference to related trie node
self.children = {}
# flag to determine if this node represents a word ending
self.word_end = False
def add(self, char):
self.children[char] = TrieNode()
class Trie:
def __init__(self):
self.ro... | Word_Search 2.py | class TrieNode:
# Initialize your data structure here.
def __init__(self):
# reference to related trie node
self.children = {}
# flag to determine if this node represents a word ending
self.word_end = False
def add(self, char):
self.children[char] = TrieNode()
class Trie:
def __init__(self):
self.ro... | 0.511961 | 0.481515 |
import pymysql
# 打开数据库连接
db = pymysql.connect("localhost", "root", "root", "api_dev", use_unicode=True, charset="utf8")
# 使用cursor()方法获取操作游标
cursor = db.cursor()
try:
# 执行SQL语句
cursor.execute("SELECT id, tags FROM problem")
# 获取所有记录列表
results = cursor.fetchall()
for row in results:
id =... | reformat.py |
import pymysql
# 打开数据库连接
db = pymysql.connect("localhost", "root", "root", "api_dev", use_unicode=True, charset="utf8")
# 使用cursor()方法获取操作游标
cursor = db.cursor()
try:
# 执行SQL语句
cursor.execute("SELECT id, tags FROM problem")
# 获取所有记录列表
results = cursor.fetchall()
for row in results:
id =... | 0.109319 | 0.186447 |
import numpy as np
import cv2
from pyquaternion import Quaternion
from Quaternion import Quat
import timeit
from scipy import stats
# seek_time = 40
source = 'france' #'own', 'france'
topic_dict = {'paris':'paris.mp4', 'diving':'ocean40.webm', 'venise':'venise.webm', 'roller':'roller65.webm',
'timelap... | utils/get_fixation.py | import numpy as np
import cv2
from pyquaternion import Quaternion
from Quaternion import Quat
import timeit
from scipy import stats
# seek_time = 40
source = 'france' #'own', 'france'
topic_dict = {'paris':'paris.mp4', 'diving':'ocean40.webm', 'venise':'venise.webm', 'roller':'roller65.webm',
'timelap... | 0.428473 | 0.322446 |
import csv
import datetime
import shutil
import sys
from functools import partial
import click
from dateutil import tz
from psycopg2._range import Range
from functools import singledispatch
from datacube.ui import click as ui
from datacube.ui.click import CLICK_SETTINGS
PASS_INDEX = ui.pass_index('datacube-search')
... | datacube/scripts/search_tool.py | import csv
import datetime
import shutil
import sys
from functools import partial
import click
from dateutil import tz
from psycopg2._range import Range
from functools import singledispatch
from datacube.ui import click as ui
from datacube.ui.click import CLICK_SETTINGS
PASS_INDEX = ui.pass_index('datacube-search')
... | 0.382718 | 0.168241 |
from typing import List, Tuple
import torch
import torch.nn as nn
from OpenMatch.modules.embedders import Embedder
from OpenMatch.modules.encoders import Conv1DEncoder
from OpenMatch.modules.matchers import KernelMatcher
class ConvKNRM(nn.Module):
def __init__(
self,
vocab_size: int,
embe... | OpenMatch/models/conv_knrm.py | from typing import List, Tuple
import torch
import torch.nn as nn
from OpenMatch.modules.embedders import Embedder
from OpenMatch.modules.encoders import Conv1DEncoder
from OpenMatch.modules.matchers import KernelMatcher
class ConvKNRM(nn.Module):
def __init__(
self,
vocab_size: int,
embe... | 0.947491 | 0.376251 |
# <markdowncell>
# # netCDF File Visualization Case Study
#
# I was asked by a colleague to visualize data contained within this [netCDF file](https://motherlode.ucar.edu/repository/entry/show/RAMADDA/Unidata/Staff/Julien+Chastang/netcdf-explore?entryid=c7239224-d3fe-45d8-b100-43ae043824c3) ([OPeNDAP link](https://m... | Siphon/casestudy.py |
# <markdowncell>
# # netCDF File Visualization Case Study
#
# I was asked by a colleague to visualize data contained within this [netCDF file](https://motherlode.ucar.edu/repository/entry/show/RAMADDA/Unidata/Staff/Julien+Chastang/netcdf-explore?entryid=c7239224-d3fe-45d8-b100-43ae043824c3) ([OPeNDAP link](https://m... | 0.766643 | 0.656459 |
import sqlite3
import logging
from weight_unit import WeightUnit
class Database:
weight_units = []
def __init__(self, path):
self.db = sqlite3.connect(path)
cursor = self.db.cursor()
for row in cursor.execute('SELECT id, name, language_id FROM nutrition_weightunit'):
self.... | database.py | import sqlite3
import logging
from weight_unit import WeightUnit
class Database:
weight_units = []
def __init__(self, path):
self.db = sqlite3.connect(path)
cursor = self.db.cursor()
for row in cursor.execute('SELECT id, name, language_id FROM nutrition_weightunit'):
self.... | 0.34798 | 0.146423 |
# General-purpose Python library imports
import os
import sys
import unittest
# Third-party libraries
import boto.s3.connection
import boto.s3.key
from flexmock import flexmock
# Walrus storage import, the library that we're testing here
lib = os.path.dirname(__file__) + os.sep + ".."
sys.path.append(lib)
from magi... | tests/test_walrus_storage.py | # General-purpose Python library imports
import os
import sys
import unittest
# Third-party libraries
import boto.s3.connection
import boto.s3.key
from flexmock import flexmock
# Walrus storage import, the library that we're testing here
lib = os.path.dirname(__file__) + os.sep + ".."
sys.path.append(lib)
from magi... | 0.39222 | 0.184529 |
__author__ = "<NAME>"
__all__ = ["TimeSeriesForest"]
import numpy as np
import pandas as pd
import math
from sklearn.ensemble.forest import ForestClassifier
from sklearn.tree import DecisionTreeClassifier
from numpy import random
from copy import deepcopy
from sklearn.utils.multiclass import class_distribution
from sk... | sktime/classifiers/interval_based/tsf.py | __author__ = "<NAME>"
__all__ = ["TimeSeriesForest"]
import numpy as np
import pandas as pd
import math
from sklearn.ensemble.forest import ForestClassifier
from sklearn.tree import DecisionTreeClassifier
from numpy import random
from copy import deepcopy
from sklearn.utils.multiclass import class_distribution
from sk... | 0.853577 | 0.523299 |
from msrest.pipeline import ClientRawResponse
from .. import models
class CustomVisionPredictionClientOperationsMixin(object):
def classify_image(
self, project_id, published_name, image_data, application=None, custom_headers=None, raw=False, **operation_config):
"""Classify an image and sav... | sdk/cognitiveservices/azure-cognitiveservices-vision-customvision/azure/cognitiveservices/vision/customvision/prediction/operations/_custom_vision_prediction_client_operations.py |
from msrest.pipeline import ClientRawResponse
from .. import models
class CustomVisionPredictionClientOperationsMixin(object):
def classify_image(
self, project_id, published_name, image_data, application=None, custom_headers=None, raw=False, **operation_config):
"""Classify an image and sav... | 0.861115 | 0.233499 |
"""Test Loan - setcollateraltoken."""
from test_framework.test_framework import DefiTestFramework
from test_framework.authproxy import JSONRPCException
from test_framework.util import assert_equal
from decimal import Decimal
import calendar
import time
class LoanSetCollateralTokenTest (DefiTestFramework):
def s... | test/functional/feature_loan_setcollateraltoken.py | """Test Loan - setcollateraltoken."""
from test_framework.test_framework import DefiTestFramework
from test_framework.authproxy import JSONRPCException
from test_framework.util import assert_equal
from decimal import Decimal
import calendar
import time
class LoanSetCollateralTokenTest (DefiTestFramework):
def s... | 0.662141 | 0.405625 |
import numpy as np
from scipy.spatial.distance import pdist, squareform
class GaussianProcess:
"""
The crop yield Gaussian process
"""
def __init__(self, sigma=1, r_loc=0.5, r_year=1.5, sigma_e=0.32, sigma_b=0.01):
self.sigma = sigma
self.r_loc = r_loc
self.r_year = r_year
... | cyp/models/gp.py | import numpy as np
from scipy.spatial.distance import pdist, squareform
class GaussianProcess:
"""
The crop yield Gaussian process
"""
def __init__(self, sigma=1, r_loc=0.5, r_year=1.5, sigma_e=0.32, sigma_b=0.01):
self.sigma = sigma
self.r_loc = r_loc
self.r_year = r_year
... | 0.877437 | 0.649676 |
import abc
import copy
import inspect
import re
import six
import yaql
from yaql import exceptions as yaql_exc
from highlander import exceptions as exc
from highlander.openstack.common import log as logging
from highlander import yaql_utils
LOG = logging.getLogger(__name__)
class Evaluator(object):
"""Expres... | highlander/expressions.py |
import abc
import copy
import inspect
import re
import six
import yaql
from yaql import exceptions as yaql_exc
from highlander import exceptions as exc
from highlander.openstack.common import log as logging
from highlander import yaql_utils
LOG = logging.getLogger(__name__)
class Evaluator(object):
"""Expres... | 0.478041 | 0.480357 |
import os
from os import path
import numpy as np
from scipy.io import loadmat
import torch
from subprocess import call
from shutil import copy, move
from tqdm import tqdm
from tempfile import TemporaryDirectory
import h5py
import PIL.Image
import PIL.ImageDraw
import PIL.ImageOps
import PIL.ImageFilter
import PIL.Image... | src/margipose/data/mpi_inf_3dhp/preprocess.py | import os
from os import path
import numpy as np
from scipy.io import loadmat
import torch
from subprocess import call
from shutil import copy, move
from tqdm import tqdm
from tempfile import TemporaryDirectory
import h5py
import PIL.Image
import PIL.ImageDraw
import PIL.ImageOps
import PIL.ImageFilter
import PIL.Image... | 0.521715 | 0.24834 |
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('wmdadict', '0029_auto_20170917_2049'),
]
operations = [
migrations.RemoveField(
model_name='bmdwfield',... | wmdadict/migrations/0030_auto_20170917_2104.py | from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('wmdadict', '0029_auto_20170917_2049'),
]
operations = [
migrations.RemoveField(
model_name='bmdwfield',... | 0.580352 | 0.073165 |
from math import acos
class Vector:
"""3D Vector. Could be used as 2D."""
def __init__(self, x: float = 0, y: float = 0, z: float = 0):
self.data = [x, y, z]
def __add__(self, other):
return Vector(*(self.data[i] + other.data[i] for i in range(3)))
def __iadd__(self, other):
... | physicslib/vector.py | from math import acos
class Vector:
"""3D Vector. Could be used as 2D."""
def __init__(self, x: float = 0, y: float = 0, z: float = 0):
self.data = [x, y, z]
def __add__(self, other):
return Vector(*(self.data[i] + other.data[i] for i in range(3)))
def __iadd__(self, other):
... | 0.91507 | 0.696688 |
from nuaal.connections.api import RestBase
from nuaal.definitions import DATA_PATH
from nuaal.utils import check_path
import json
import os
import requests
class Cisco_NX_API(RestBase):
def __init__(self, ip, username, password, verify_ssl=False, DEBUG=False):
super(Cisco_NX_API, self).__init__(url="https:... | nuaal/connections/api/nxos/NxOsBase.py | from nuaal.connections.api import RestBase
from nuaal.definitions import DATA_PATH
from nuaal.utils import check_path
import json
import os
import requests
class Cisco_NX_API(RestBase):
def __init__(self, ip, username, password, verify_ssl=False, DEBUG=False):
super(Cisco_NX_API, self).__init__(url="https:... | 0.365457 | 0.106087 |
import argparse
import collections
import gzip
import json
from pprint import pformat
import re
import tqdm
def main():
p = argparse.ArgumentParser()
p.add_argument("-o", "--output-file", help="json file output path")
p.add_argument("-v", "--verbose", action="store_true")
p.add_argument("gangstr_spec"... | str_analysis/convert_gangstr_spec_to_expansion_hunter_variant_catalog.py | import argparse
import collections
import gzip
import json
from pprint import pformat
import re
import tqdm
def main():
p = argparse.ArgumentParser()
p.add_argument("-o", "--output-file", help="json file output path")
p.add_argument("-v", "--verbose", action="store_true")
p.add_argument("gangstr_spec"... | 0.214034 | 0.197367 |
import os
import pickle
import numpy as np
import sklearn.metrics
from itertools import islice, zip_longest
import numpy as np
from IPython.display import HTML, Markdown
from bing_maps import *
import pandas as pd
import mapswipe
from pathlib import Path
from collections import defaultdict, namedtuple
import bing_ma... | mapswipe_analysis.py | import os
import pickle
import numpy as np
import sklearn.metrics
from itertools import islice, zip_longest
import numpy as np
from IPython.display import HTML, Markdown
from bing_maps import *
import pandas as pd
import mapswipe
from pathlib import Path
from collections import defaultdict, namedtuple
import bing_ma... | 0.535584 | 0.219317 |
import pandas as pd
import matplotlib.pyplot as plt
# parameters
# ---
# which subset
subset = 'survey_only'
rho = 1700
# where are the samples and where to put results
dir_results = '../../results/neutral_data_fitm/'
# where to find the island area and richness data
fname_area = '../../data/processed/island_area.... | scripts/neutral_data_fitm/plot_sample.py |
import pandas as pd
import matplotlib.pyplot as plt
# parameters
# ---
# which subset
subset = 'survey_only'
rho = 1700
# where are the samples and where to put results
dir_results = '../../results/neutral_data_fitm/'
# where to find the island area and richness data
fname_area = '../../data/processed/island_area.... | 0.407098 | 0.529811 |
def main():
"""
Say we have a produces an assignment between true detections within images
and some set of predictions.
"""
import numpy as np
import ubelt as ub
# Create demo detection metrics
from kwcoco.metrics import DetectionMetrics
dmet = DetectionMetrics.demo(
nimgs=1... | when_is_grouping_better.py | def main():
"""
Say we have a produces an assignment between true detections within images
and some set of predictions.
"""
import numpy as np
import ubelt as ub
# Create demo detection metrics
from kwcoco.metrics import DetectionMetrics
dmet = DetectionMetrics.demo(
nimgs=1... | 0.667581 | 0.572364 |
import secrets
from copy import copy
from datetime import datetime
from enum import Enum
from typing import TYPE_CHECKING, List, Optional, Tuple, Union
import flask
from sqlalchemy import and_, func
from sqlalchemy.dialects.postgresql import ARRAY, INET
from sqlalchemy.ext.declarative import declared_attr
from werkzeu... | core/users/models.py | import secrets
from copy import copy
from datetime import datetime
from enum import Enum
from typing import TYPE_CHECKING, List, Optional, Tuple, Union
import flask
from sqlalchemy import and_, func
from sqlalchemy.dialects.postgresql import ARRAY, INET
from sqlalchemy.ext.declarative import declared_attr
from werkzeu... | 0.803135 | 0.136033 |
import sys, os, fcntl, termios
##################################################################
# Establish a serial-port connection w. required settings.
##################################################################
def openSerial(self, portName="/dev/ttyS0"):
# The open attempt may fail on account o... | snippets/serial/serial.py | import sys, os, fcntl, termios
##################################################################
# Establish a serial-port connection w. required settings.
##################################################################
def openSerial(self, portName="/dev/ttyS0"):
# The open attempt may fail on account o... | 0.241221 | 0.117167 |
from typing import Dict, Any, List, Tuple, Optional
import copy
class ShieldBoosterVariant(object):
def __init__(self):
# no need for private attributes, we are handing out deep copies
self.engineering = ""
self.experimental = ""
self.shield_strength_bonus = 0
sel... | ShieldBoosterVariant.py | from typing import Dict, Any, List, Tuple, Optional
import copy
class ShieldBoosterVariant(object):
def __init__(self):
# no need for private attributes, we are handing out deep copies
self.engineering = ""
self.experimental = ""
self.shield_strength_bonus = 0
sel... | 0.879581 | 0.205874 |
import tensorrt as trt
import numpy as np
from scipy.io.wavfile import write
import time
import torch
import argparse
import sys
sys.path.append('./')
from common.utils import to_gpu, get_mask_from_lengths
from tacotron2.text import text_to_sequence
from inference import MeasureTime, prepare_input_sequence, load_and... | demo/Tacotron2/trt/inference_trt.py |
import tensorrt as trt
import numpy as np
from scipy.io.wavfile import write
import time
import torch
import argparse
import sys
sys.path.append('./')
from common.utils import to_gpu, get_mask_from_lengths
from tacotron2.text import text_to_sequence
from inference import MeasureTime, prepare_input_sequence, load_and... | 0.589362 | 0.184327 |
import unittest
from io import BytesIO
try:
# Python 2
import cPickle as pickle
except ImportError:
# Python 3
import pickle
from icarus.util import Tree
class TestTree(unittest.TestCase):
@classmethod
def setUpClass(cls):
pass
@classmethod
def tearDownClass(cls):
pa... | icarus/test/test_tree.py | import unittest
from io import BytesIO
try:
# Python 2
import cPickle as pickle
except ImportError:
# Python 3
import pickle
from icarus.util import Tree
class TestTree(unittest.TestCase):
@classmethod
def setUpClass(cls):
pass
@classmethod
def tearDownClass(cls):
pa... | 0.699254 | 0.58436 |
from django.db import models
class ProductFamily(models.Model):
product_family_id = models.FloatField(primary_key=True, db_column="produkt_familie_id")
description = models.CharField(max_length=50, db_column="bezeichnung")
slug = models.SlugField(default="test")
class Meta:
ordering = ('descr... | product/models.py | from django.db import models
class ProductFamily(models.Model):
product_family_id = models.FloatField(primary_key=True, db_column="produkt_familie_id")
description = models.CharField(max_length=50, db_column="bezeichnung")
slug = models.SlugField(default="test")
class Meta:
ordering = ('descr... | 0.618435 | 0.138171 |
import copy
import json
import pytest
import pathlib
import urllib.request
from unittest.mock import patch, MagicMock, mock_open
from o3de import manifest, download, utils
TEST_O3DE_MANIFEST_JSON_PAYLOAD = '''
{
"o3de_manifest_name": "testuser",
"origin": "C:/Users/testuser/.o3de",
"default_engines_folde... | scripts/o3de/tests/test_download.py |
import copy
import json
import pytest
import pathlib
import urllib.request
from unittest.mock import patch, MagicMock, mock_open
from o3de import manifest, download, utils
TEST_O3DE_MANIFEST_JSON_PAYLOAD = '''
{
"o3de_manifest_name": "testuser",
"origin": "C:/Users/testuser/.o3de",
"default_engines_folde... | 0.208904 | 0.268606 |
from pirates.piratesbase.PiratesGlobals import *
from direct.interval.IntervalGlobal import *
from direct.distributed.ClockDelta import *
from pirates.piratesbase import PiratesGlobals
from direct.distributed import DistributedObject
from pirates.piratesbase import PLocalizer
from direct.gui.DirectGui import *
from pan... | pirates/destructibles/DistributedBarrel.py | from pirates.piratesbase.PiratesGlobals import *
from direct.interval.IntervalGlobal import *
from direct.distributed.ClockDelta import *
from pirates.piratesbase import PiratesGlobals
from direct.distributed import DistributedObject
from pirates.piratesbase import PLocalizer
from direct.gui.DirectGui import *
from pan... | 0.483648 | 0.085518 |
import sys
import argparse
from closeio_api import Client as CloseIO_API, APIError
from datetime import datetime, timedelta
import time
from dateutil import tz
import csv
reload(sys)
sys.setdefaultencoding('utf-8')
parser = argparse.ArgumentParser(description='Get Time To Respond Metrics From Org')
parser.add_argumen... | scripts/time_to_respond_report.py | import sys
import argparse
from closeio_api import Client as CloseIO_API, APIError
from datetime import datetime, timedelta
import time
from dateutil import tz
import csv
reload(sys)
sys.setdefaultencoding('utf-8')
parser = argparse.ArgumentParser(description='Get Time To Respond Metrics From Org')
parser.add_argumen... | 0.192767 | 0.158142 |
from __future__ import print_function, absolute_import, division
from .pokerth_pb2 import PokerTHMessage
__author__ = '<NAME>'
__copyright__ = '<NAME>'
def makeSizeBytes(n):
"""
Create a 4 bytes string that encodes the number ``n``.
:param n: integer
:return: 4 bytes string
"""
return str(b... | pokerthproto/transport.py | from __future__ import print_function, absolute_import, division
from .pokerth_pb2 import PokerTHMessage
__author__ = '<NAME>'
__copyright__ = '<NAME>'
def makeSizeBytes(n):
"""
Create a 4 bytes string that encodes the number ``n``.
:param n: integer
:return: 4 bytes string
"""
return str(b... | 0.887449 | 0.463323 |
import torch
import torch.nn as nn
from torch.distributions import Normal, Categorical
def init_weights(module: nn.Module, gain=1.414):
for m in module.modules():
if isinstance(m, (nn.Linear, nn.Conv2d)):
torch.nn.init.zeros_(m.bias)
torch.nn.init.orthogonal_(m.weight, gain)
... | pbrl/policy/base.py | import torch
import torch.nn as nn
from torch.distributions import Normal, Categorical
def init_weights(module: nn.Module, gain=1.414):
for m in module.modules():
if isinstance(m, (nn.Linear, nn.Conv2d)):
torch.nn.init.zeros_(m.bias)
torch.nn.init.orthogonal_(m.weight, gain)
... | 0.935693 | 0.502686 |
from __future__ import division
import time
import torch
import torch.nn as nn
from torch.autograd import Variable
import numpy as np
import cv2
from util import *
import argparse
import os
import os.path as osp
from darknet import Darknet
import pickle as pkl
import pandas as pd
import random
def arg_parse():
... | detect.py | from __future__ import division
import time
import torch
import torch.nn as nn
from torch.autograd import Variable
import numpy as np
import cv2
from util import *
import argparse
import os
import os.path as osp
from darknet import Darknet
import pickle as pkl
import pandas as pd
import random
def arg_parse():
... | 0.50415 | 0.225758 |
import ctypes
import os
import shutil
import cv2
import glob
import subprocess
import signal
from pydub import AudioSegment
from collections import defaultdict
from tqdm import tqdm
from multiprocessing import Process, Queue, Value, Pipe
from queue import Empty
from logging import getLogger, StreamHandler, Formatter, F... | mitsuba.py | import ctypes
import os
import shutil
import cv2
import glob
import subprocess
import signal
from pydub import AudioSegment
from collections import defaultdict
from tqdm import tqdm
from multiprocessing import Process, Queue, Value, Pipe
from queue import Empty
from logging import getLogger, StreamHandler, Formatter, F... | 0.107455 | 0.095055 |
# @Time : 11/24/18 12:29 PM
# @Author : <NAME>
# @File : multimodal_gan.py
from random import sample
import numpy as np
# installed packages and modules
from keras.layers import (Dense, Conv1D, MaxPool1D, Flatten,
Dropout, Input, Activation, BatchNormalization,
... | DMMFF/multimodal_gan.py |
# @Time : 11/24/18 12:29 PM
# @Author : <NAME>
# @File : multimodal_gan.py
from random import sample
import numpy as np
# installed packages and modules
from keras.layers import (Dense, Conv1D, MaxPool1D, Flatten,
Dropout, Input, Activation, BatchNormalization,
... | 0.822332 | 0.532668 |
import lldb
from intelpt_testcase import *
from lldbsuite.test.lldbtest import *
from lldbsuite.test import lldbutil
from lldbsuite.test.decorators import *
class TestTraceLoad(TraceIntelPTTestCaseBase):
mydir = TestBase.compute_mydir(__file__)
NO_DEBUG_INFO_TESTCASE = True
def testLoadTrace(self):
... | lldb/test/API/commands/trace/TestTraceLoad.py | import lldb
from intelpt_testcase import *
from lldbsuite.test.lldbtest import *
from lldbsuite.test import lldbutil
from lldbsuite.test.decorators import *
class TestTraceLoad(TraceIntelPTTestCaseBase):
mydir = TestBase.compute_mydir(__file__)
NO_DEBUG_INFO_TESTCASE = True
def testLoadTrace(self):
... | 0.525856 | 0.378143 |
import sys
from PyQt5.QtCore import Qt, QRectF, QPointF
from PyQt5.QtGui import QPixmap, QTransform, QBrush, QColor, QPen
from PyQt5.QtWidgets import QApplication, QMainWindow, QWidget, QVBoxLayout, QGraphicsView, QGraphicsScene, QGraphicsPixmapItem, QSizePolicy, QSpacerItem, QGraphicsObject
class MouseBrushObject(... | temp.py | import sys
from PyQt5.QtCore import Qt, QRectF, QPointF
from PyQt5.QtGui import QPixmap, QTransform, QBrush, QColor, QPen
from PyQt5.QtWidgets import QApplication, QMainWindow, QWidget, QVBoxLayout, QGraphicsView, QGraphicsScene, QGraphicsPixmapItem, QSizePolicy, QSpacerItem, QGraphicsObject
class MouseBrushObject(... | 0.401805 | 0.266184 |
import unittest
import numpy as np
from openvino.tools.mo.ops.ctc_loss import CTCLoss
from openvino.tools.mo.front.common.partial_infer.utils import int64_array
from openvino.tools.mo.graph.graph import Node
from unit_tests.utils.graph import build_graph
nodes_attributes = {'logits': {'kind': 'op'},
... | tools/mo/unit_tests/mo/ops/ctc_loss_test.py |
import unittest
import numpy as np
from openvino.tools.mo.ops.ctc_loss import CTCLoss
from openvino.tools.mo.front.common.partial_infer.utils import int64_array
from openvino.tools.mo.graph.graph import Node
from unit_tests.utils.graph import build_graph
nodes_attributes = {'logits': {'kind': 'op'},
... | 0.699254 | 0.348673 |
import errno
import logging
# Import Salt libs
import salt.modules.cmdmod
import salt.utils.files
import salt.utils.path
import salt.utils.platform
__virtualname__ = "iscsi"
# Get logging started
log = logging.getLogger(__name__)
def __virtual__():
if __opts__.get("iscsi_grains", False) is False:
retu... | salt/grains/iscsi.py |
import errno
import logging
# Import Salt libs
import salt.modules.cmdmod
import salt.utils.files
import salt.utils.path
import salt.utils.platform
__virtualname__ = "iscsi"
# Get logging started
log = logging.getLogger(__name__)
def __virtual__():
if __opts__.get("iscsi_grains", False) is False:
retu... | 0.360264 | 0.047492 |
import treetensor.torch as ttorch
from .base import choose_mark
# noinspection DuplicatedCode,PyUnresolvedReferences
class TestTorchTensorAutograd:
@choose_mark()
def test_requires_grad(self):
tt1 = ttorch.tensor({
'a': [2, 3, 4.0],
'b': {'x': [[5, 6], [7, 8.0]]}
}, req... | test/torch/tensor/test_autograd.py | import treetensor.torch as ttorch
from .base import choose_mark
# noinspection DuplicatedCode,PyUnresolvedReferences
class TestTorchTensorAutograd:
@choose_mark()
def test_requires_grad(self):
tt1 = ttorch.tensor({
'a': [2, 3, 4.0],
'b': {'x': [[5, 6], [7, 8.0]]}
}, req... | 0.479991 | 0.606964 |
import re
import sys
import time
from unittest.case import SkipTest
import mock
import pytest
import six
from ddtrace.constants import ANALYTICS_SAMPLE_RATE_KEY
from ddtrace.constants import ENV_KEY
from ddtrace.constants import ERROR_MSG
from ddtrace.constants import ERROR_STACK
from ddtrace.constants import ERROR_T... | tests/tracer/test_span.py | import re
import sys
import time
from unittest.case import SkipTest
import mock
import pytest
import six
from ddtrace.constants import ANALYTICS_SAMPLE_RATE_KEY
from ddtrace.constants import ENV_KEY
from ddtrace.constants import ERROR_MSG
from ddtrace.constants import ERROR_STACK
from ddtrace.constants import ERROR_T... | 0.428473 | 0.479747 |
import asyncio
import email.header
import email.message
import email.mime.multipart
import email.mime.text
import socket
import ssl
import sys
import traceback
from pathlib import Path
import hypothesis
import pytest
from aiosmtplib import SMTP, SMTPStatus
from aiosmtplib.sync import shutdown_loop
from .smtpd import... | tests/conftest.py | import asyncio
import email.header
import email.message
import email.mime.multipart
import email.mime.text
import socket
import ssl
import sys
import traceback
from pathlib import Path
import hypothesis
import pytest
from aiosmtplib import SMTP, SMTPStatus
from aiosmtplib.sync import shutdown_loop
from .smtpd import... | 0.315841 | 0.121295 |
"""Client and server classes corresponding to protobuf-defined services."""
import grpc
from . import poi_pb2 as poi_dot_poi__pb2
class PoiServiceStub(object):
"""
Allow users to get poi information
"""
def __init__(self, channel):
"""Constructor.
Args:
channel: A grpc.C... | mavsdk/poi_pb2_grpc.py | """Client and server classes corresponding to protobuf-defined services."""
import grpc
from . import poi_pb2 as poi_dot_poi__pb2
class PoiServiceStub(object):
"""
Allow users to get poi information
"""
def __init__(self, channel):
"""Constructor.
Args:
channel: A grpc.C... | 0.756537 | 0.17172 |
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Utility script that directly loads in data from another place to
the MephistoDB under a specified task run, using MockRequester and
MockWor... | mephisto/scripts/local_db/load_data_to_mephisto_db.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Utility script that directly loads in data from another place to
the MephistoDB under a specified task run, using MockRequester and
MockWor... | 0.590543 | 0.214362 |
import ast
import json
import os
import glob
import sys
import requests
import inspect
from clebear.configs import cfg
from requests_toolbelt import MultipartEncoder
def load_module(file_path, module_name=None):
"""
Load a module by name and search path
This function should work with python 2.7 and 3.x
... | clebear/core/utils.py | import ast
import json
import os
import glob
import sys
import requests
import inspect
from clebear.configs import cfg
from requests_toolbelt import MultipartEncoder
def load_module(file_path, module_name=None):
"""
Load a module by name and search path
This function should work with python 2.7 and 3.x
... | 0.331985 | 0.175503 |
import functools
from . import basic_type
from .schema_dsl_common import *
def _check_object_type(input_object, path):
if not isinstance(input_object, dict):
raise TypeError(get_message(path, 'Should be an object'))
def _validate_outgoing_object(input_object, path):
if input_object is None:
... | python3/src/json_outgoing.py | import functools
from . import basic_type
from .schema_dsl_common import *
def _check_object_type(input_object, path):
if not isinstance(input_object, dict):
raise TypeError(get_message(path, 'Should be an object'))
def _validate_outgoing_object(input_object, path):
if input_object is None:
... | 0.512205 | 0.11928 |
from __future__ import absolute_import
import ctypes
import platform
import pkg_resources
if platform.system() == "Windows":
name = "awkward.dll"
elif platform.system() == "Darwin":
name = "libawkward.dylib"
else:
name = "libawkward.so"
libpath = pkg_resources.resource_filename("awkward1", name)
lib = c... | src/awkward1/_libawkward.py |
from __future__ import absolute_import
import ctypes
import platform
import pkg_resources
if platform.system() == "Windows":
name = "awkward.dll"
elif platform.system() == "Darwin":
name = "libawkward.dylib"
else:
name = "libawkward.so"
libpath = pkg_resources.resource_filename("awkward1", name)
lib = c... | 0.313735 | 0.057019 |
import sys
import numpy as np
from datetime import datetime
from sklearn.metrics import accuracy_score
from sklearn.neighbors import KNeighborsClassifier
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.linear_model import LogisticRegression
from sklearn.ensemble import RandomForestClas... | utils.py | import sys
import numpy as np
from datetime import datetime
from sklearn.metrics import accuracy_score
from sklearn.neighbors import KNeighborsClassifier
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.linear_model import LogisticRegression
from sklearn.ensemble import RandomForestClas... | 0.686685 | 0.551936 |
import json
from package.decorator_csrf_setting import my_csrf_decorator
from package.request_method_limit import post_limit, login_limit
from package.response_data import get_res_json
from package.session_manage import set_user_session, clear_session, is_logined
from .models import UserModel
from .forms import Registe... | user/views.py | import json
from package.decorator_csrf_setting import my_csrf_decorator
from package.request_method_limit import post_limit, login_limit
from package.response_data import get_res_json
from package.session_manage import set_user_session, clear_session, is_logined
from .models import UserModel
from .forms import Registe... | 0.219672 | 0.077622 |
import numpy as np
import pytest
from pandas import (
CategoricalIndex,
DatetimeIndex,
Index,
Int64Index,
NaT,
Period,
PeriodIndex,
Timedelta,
UInt64Index,
period_range,
)
import pandas._testing as tm
class TestPeriodIndexAsType:
@pytest.mark.parametrize("dtype", [float, "... | pandas/tests/indexes/period/methods/test_astype.py | import numpy as np
import pytest
from pandas import (
CategoricalIndex,
DatetimeIndex,
Index,
Int64Index,
NaT,
Period,
PeriodIndex,
Timedelta,
UInt64Index,
period_range,
)
import pandas._testing as tm
class TestPeriodIndexAsType:
@pytest.mark.parametrize("dtype", [float, "... | 0.559531 | 0.718416 |
import tensorflow as tf
from detection.models.backbones import resnet
from detection.models.necks import fpn
from detection.models.rpn_heads import rpn_head
from detection.models.bbox_heads import bbox_head
from detection.models.roi_extractors import roi_align
from detection.models.detectors.test_mixins import RPNTest... | detection/models/detectors/faster_rcnn.py | import tensorflow as tf
from detection.models.backbones import resnet
from detection.models.necks import fpn
from detection.models.rpn_heads import rpn_head
from detection.models.bbox_heads import bbox_head
from detection.models.roi_extractors import roi_align
from detection.models.detectors.test_mixins import RPNTest... | 0.697094 | 0.180865 |
import os
import glob
from netCDF4 import Dataset as open_ncfile
import matplotlib.pyplot as plt
import numpy as np
import datetime
import pickle
# -- Read result
emerge = pickle.load( open( "/home/ysilvy/Density_bining/Yona_analysis/data/percentage_emergence_medians_meanhistNat.pkl", "rb" ) )
# -- Median and range
m... | fig3b.py | import os
import glob
from netCDF4 import Dataset as open_ncfile
import matplotlib.pyplot as plt
import numpy as np
import datetime
import pickle
# -- Read result
emerge = pickle.load( open( "/home/ysilvy/Density_bining/Yona_analysis/data/percentage_emergence_medians_meanhistNat.pkl", "rb" ) )
# -- Median and range
m... | 0.47025 | 0.409929 |
import os
import sys
import cv2
import numpy as np
#PYCAFFE_DIR = '/home/kevin/Development/caffe3/python'
PYCAFFE_DIR = '/usr/local/opt/caffe-2015-07/python'
def _create_net(specfile, modelfile):
if not PYCAFFE_DIR in sys.path:
sys.path.insert(0, PYCAFFE_DIR)
import caffe
return caffe.Net(specfil... | deep/__init__.py | import os
import sys
import cv2
import numpy as np
#PYCAFFE_DIR = '/home/kevin/Development/caffe3/python'
PYCAFFE_DIR = '/usr/local/opt/caffe-2015-07/python'
def _create_net(specfile, modelfile):
if not PYCAFFE_DIR in sys.path:
sys.path.insert(0, PYCAFFE_DIR)
import caffe
return caffe.Net(specfil... | 0.396652 | 0.161849 |
import logging
import itertools
from data.logs_model.datatypes import AggregatedLogCount, LogEntriesPage
from data.logs_model.interface import ActionLogsDataInterface
from data.logs_model.shared import SharedModel
logger = logging.getLogger(__name__)
def _merge_aggregated_log_counts(*args):
""" Merge two lists of... | data/logs_model/combined_model.py | import logging
import itertools
from data.logs_model.datatypes import AggregatedLogCount, LogEntriesPage
from data.logs_model.interface import ActionLogsDataInterface
from data.logs_model.shared import SharedModel
logger = logging.getLogger(__name__)
def _merge_aggregated_log_counts(*args):
""" Merge two lists of... | 0.593374 | 0.168891 |
# Import libraries
from absl import logging
import tensorflow as tf
from official.vision.beta.ops import spatial_transform_ops
# The fixed NAS-FPN architecture discovered by NAS.
# Each element represents a specification of a building block:
# (block_level, combine_fn, (input_offset0, input_offset1), is_output).
N... | official/vision/beta/modeling/decoders/nasfpn.py | # Import libraries
from absl import logging
import tensorflow as tf
from official.vision.beta.ops import spatial_transform_ops
# The fixed NAS-FPN architecture discovered by NAS.
# Each element represents a specification of a building block:
# (block_level, combine_fn, (input_offset0, input_offset1), is_output).
N... | 0.930324 | 0.44746 |
import requests
import re
import uuid
from flask import current_app
from app.book.models import Book, SearchableBookMapping, searchable_book_index, searchable_book_doc_type
from app.search import services as es_service
def check_connection():
if not es_service.check_connection():
raise ValueError("Connect... | api/app/book/services.py | import requests
import re
import uuid
from flask import current_app
from app.book.models import Book, SearchableBookMapping, searchable_book_index, searchable_book_doc_type
from app.search import services as es_service
def check_connection():
if not es_service.check_connection():
raise ValueError("Connect... | 0.304869 | 0.310054 |