id stringlengths 3 8 | content stringlengths 100 981k |
|---|---|
19759 | import rospy
MOVE_CYCLE_PERIOD = 0.01
def move_towards(target, current, step=1):
if abs(target-current) < step:
return target, True
else:
if target > current:
return current + step, False
else:
return current - step, False
def move_leg(leg, coxa=None, femur=N... |
19773 | import glob, os
import numpy as np
import tensorflow as tf
import tensorflow.contrib.graph_editor as ge
class Flownet2:
def __init__(self, bilinear_warping_module):
self.weights = dict()
for key, shape in self.all_variables():
self.weights[key] = tf.get_variable(key, shape=shape)
... |
19787 | import sys
import pytest
import aiohttp_mako
from aiohttp import web
@pytest.fixture
def app():
app = web.Application()
lookup = aiohttp_mako.setup(app, input_encoding='utf-8',
output_encoding='utf-8',
default_filters=['decode.utf8'])
tplt... |
19814 | from __future__ import print_function
import warnings
import numpy as np
C4 = 261.6 # Hz
piano_max = 4186.01 # Hz
piano_min = 27.5000 # Hz - not audible
__all__ = ['cent_per_value','get_f_min','get_f_max','FrequencyScale']
def cent_per_value(f_min, f_max, v_min, v_max):
"""
This function takes in a freque... |
19872 | import numpy as np
import h5py
import pyglib.basic.units as units
import pyglib.basic.splot as splot
'''
Equation of state.
'''
def Murnaghan(parameters, vol):
'''
Given a vector of parameters and volumes, return a vector of energies.
equation From PRB 28,5480 (1983)
'''
E0 = parameters[0]
B0... |
19885 | from dataclasses import dataclass, field
from typing import Any, Dict, List
from aiographql.client.error import GraphQLError
from aiographql.client.request import GraphQLRequestContainer
@dataclass(frozen=True)
class GraphQLBaseResponse(GraphQLRequestContainer):
json: Dict[str, Any] = field(default_factory=dict)... |
19896 | import time
from unittest import mock
import pytest
from django.contrib.auth.models import AnonymousUser
from django.core.exceptions import ValidationError
from django.db import IntegrityError
from django.http import Http404
from django.test import RequestFactory, TestCase
from django.urls import reverse
from wagtail.... |
19918 | import const
def corpora2idx(sents, ind2idx):
return [[ind2idx[w] if w in ind2idx else const.UNK for w in s] for s in sents]
|
19927 | from flask import Flask, render_template, session, redirect, url_for
app = Flask(__name__)
app.config['SECRET_KEY'] = '<PASSWORD>'
@app.route('/')
def index():
return render_template('index.html')
@app.route('/set-background/<mode>')
def set_background(mode):
session['mode'] = mode
return red... |
19947 | import os
import salt.utils.platform
from tests.support.mock import patch
from tests.support.unit import TestCase, skipIf
try:
import salt.utils.win_system as win_system
except Exception as exc: # pylint: disable=broad-except
win_system = exc
class WinSystemImportTestCase(TestCase):
"""
Simply impo... |
19957 | import logging
import os
import re
import time
import urllib
from threading import Thread
import xmlrpclib
from Queue import Queue
from flask import current_app as app, render_template, request, redirect, abort, jsonify, json as json_mod, url_for, session, Blueprint
from itsdangerous import TimedSerializer, BadTimeSi... |
19965 | expected_output = {
"ospf-statistics-information": {
"ospf-statistics": {
"dbds-retransmit": "203656",
"dbds-retransmit-5seconds": "0",
"flood-queue-depth": "0",
"lsas-acknowledged": "225554974",
"lsas-acknowledged-5seconds"... |
19970 | from .Layer import *
class Multiply(Layer):
def __init__(self, models, *args, **kwargs):
self.check_inputs(models, 2)
Layer.__init__(self, models, *args, **kwargs)
def reshape(self):
self.Y = np.zeros(self.X[0].shape)
def forward(self):
self.Y = np.multiply(self.X[0], self.X... |
19971 | from project.settings import INSTALLED_APPS, ALLOWED_HOSTS, BASE_DIR
import os
INSTALLED_APPS.append( 'webpack_loader',)
INSTALLED_APPS.append( 'app',)
ALLOWED_HOSTS.append('*',)
# STATIC_ROOT = os.path.join(BASE_DIR, 'static')
STATICFILES_DIRS = [
# os.path.join(BASE_DIR, 'static',)
os.path.join(BASE_DIR, ... |
19982 | import numpy as np
import itertools
from .contrib import compress_filter, smooth, residual_model
from .contrib import reduce_interferences
def expectation_maximization(y, x, iterations=2, verbose=0, eps=None):
r"""Expectation maximization algorithm, for refining source separation
estimates.
This algorith... |
19994 | import os
import requests
from typing import Optional, List
from pydantic import Field, validator
from dbt_cloud.command.command import DbtCloudAccountCommand
from dbt_cloud.field import JOB_ID_FIELD
class DbtCloudJobRunCommand(DbtCloudAccountCommand):
"""Triggers a dbt Cloud job run and returns a status JSON res... |
20000 | from eblib import libcollect
# Create a LibCollect object
lc = libcollect.LibCollect()
# Prepare arguments for do_collect
#
# Path to the script (can be absolute or relative)
scriptname = 'plotting_data_monitor.pyw'
# Ask the resulting distribution to be placed in
# directory distrib
targetdir = 'distr... |
20038 | from fastapi import HTTPException, Query, APIRouter
from starlette.requests import Request
from starlette.status import HTTP_404_NOT_FOUND
from .models import db, Metadata
mod = APIRouter()
@mod.get("/metadata")
async def search_metadata(
request: Request,
data: bool = Query(
False,
descript... |
20057 | import numpy as np
import torch
from modules.frustum import get_box_corners_3d
from kitti_meters.util import get_box_iou_3d
__all__ = ['MeterFrustumKitti']
class MeterFrustumKitti:
def __init__(self, num_heading_angle_bins, num_size_templates, size_templates, class_name_to_class_id,
metric='iou_... |
20080 | def filter_dict(dictionary_to_filter):
return dict((k, v) for k, v in dictionary_to_filter.items() if v is not None)
|
20094 | from appJar import gui
def press(btn):
if btn == "info": app.infoBox("Title Here", "Message here...")
if btn == "error": app.errorBox("Title Here", "Message here...")
if btn == "warning": app.warningBox("Title Here", "Message here...")
if btn == "yesno": app.yesNoBox("Title Here", "Message here...")
... |
20099 | from custom_objects import FinanceCalculator
from tkinter import messagebox
class CalculationsPresenter(object):
def __init__(self, view):
self.view = view
def convert_price(self, price):
try:
converted_price = FinanceCalculator.decimal_to_treasury(price)
self.view.dis... |
20111 | import subprocess, re, sys
def get_coref_score(metric, path_to_scorer, gold=None, preds=None):
output=subprocess.check_output(["perl", path_to_scorer, metric, preds, gold]).decode("utf-8")
output=output.split("\n")[-3]
matcher=re.search("Coreference: Recall: \(.*?\) (.*?)% Precision: \(.*?\) (.*?)% F1: (.*?)%", ou... |
20120 | from string import ascii_letters
import textwrap
from fontTools.misc.testTools import getXML
from fontTools import subset
from fontTools.fontBuilder import FontBuilder
from fontTools.pens.ttGlyphPen import TTGlyphPen
from fontTools.ttLib import TTFont, newTable
from fontTools.subset.svg import NAMESPACES, ranges
impo... |
20176 | from inqry.system_specs import win_physical_disk
UNIQUE_ID_OUTPUT = """
UniqueId
--------
{256a2559-ce63-5434-1bee-3ff629daa3a7}
{4069d186-f178-856e-cff3-ba250c28446d}
{4da19f06-2e28-2722-a0fb-33c02696abcd}
50014EE20D887D66
eui.0025384161B6798A
5000C5007A75E216
500A07510F1A545C
ATA LITEONIT LMT-256M6M mSATA 256GB ... |
20202 | import os
from netmiko import ConnectHandler
from getpass import getpass
from pprint import pprint
# Code so automated tests will run properly
# Check for environment variable, if that fails, use getpass().
password = os.getenv("NETMIKO_PASSWORD") if os.getenv("NETMIKO_PASSWORD") else getpass()
my_device = {
"dev... |
20210 | import pytest
from conflow.merge import merge_factory
from conflow.node import Node, NodeList, NodeMap
def test_merge_node_node(default_config):
base = Node('base', 'node_A')
other = Node('other', 'node_B')
assert merge_factory(base, other, default_config) == other
def test_merge_node_nodelist(default_... |
20233 | import unittest
import os.path
import requests_mock
import tableauserverclient as TSC
TEST_ASSET_DIR = os.path.join(os.path.dirname(__file__), 'assets')
SIGN_IN_XML = os.path.join(TEST_ASSET_DIR, 'auth_sign_in.xml')
SIGN_IN_IMPERSONATE_XML = os.path.join(TEST_ASSET_DIR, 'auth_sign_in_impersonate.xml')
SIGN_IN_ERROR_X... |
20234 | import gym
from gym import spaces, error, utils
from gym.utils import seeding
import numpy as np
import configparser
from os import path
import matplotlib.pyplot as plt
from matplotlib.pyplot import gca
font = {'family': 'sans-serif',
'weight': 'bold',
'size': 14}
class FlockingEnv(gym.Env):
def... |
20237 | import sys,os
from torch.autograd import Variable
import torch.optim as optim
from tensorboardX import SummaryWriter
import torch
import time
import shutil
from torch.utils.data import DataLoader
import csv
from samp_net import EMDLoss, AttributeLoss, SAMPNet
from config import Config
from cadb_dataset import CADBData... |
20239 | import pygame
from pygame.mixer import music
from pystage.core.assets import SoundManager
from pystage.core._base_sprite import BaseSprite
import time
class _Sound(BaseSprite):
# Like for costumes and backdrops, we need a class structure here.
# Plus a global sound manager.
def __init__(self):
su... |
20298 | import os
import dgl
import time
import argparse
import numpy as np
import torch as th
import distutils.util
import torch.nn.functional as F
import utils
import models
import data_loader
os.environ["CUDA_VISIBLE_DEVICES"] = '0'
dev = th.device('cuda' if th.cuda.is_available() else 'cpu')
if __name__ == '__main__':
... |
20310 | from collections import namedtuple
RGB = namedtuple("RGB", "red, green, blue")
COLORS = {
"red": RGB(255, 0, 0),
"orange-deep": RGB(255, 40, 0),
"orange": RGB(255, 120, 0),
"yellow": RGB(255, 200, 0),
"yellow-acid": RGB(160, 255, 0),
"green": RGB(0, 255, 0),
"green-forest": RGB(34, 139, 34... |
20325 | from menpofit.result import (ParametricIterativeResult,
MultiScaleParametricIterativeResult)
class LucasKanadeAlgorithmResult(ParametricIterativeResult):
r"""
Class for storing the iterative result of a Lucas-Kanade Image Alignment
optimization algorithm.
Parameters
-... |
20358 | from setuptools import setup, find_packages
version = {}
with open("nltools/version.py") as f:
exec(f.read(), version)
with open("requirements.txt") as f:
requirements = f.read().splitlines()
extra_setuptools_args = dict(tests_require=["pytest"])
setup(
name="nltools",
version=version["__version__"]... |
20366 | from detectron2 import model_zoo
from detectron2.engine import DefaultPredictor
from detectron2.config import get_cfg
from detectron2.utils.visualizer import Visualizer
from detectron2.data import MetadataCatalog
import torch
import numpy as np
import cv2
class Model:
def __init__(self,confidence_thresh=0.6):
... |
20367 | from setuptools import setup
setup(
name="example-advanced-package", version="0.0.0", packages=[],
)
|
20368 | from distutils.core import setup
setup(
name='pyASA',
packages=['pyASA'],
version='0.1.0',
description='Wrapper for the Cisco ASA REST API',
author='xpac',
author_email='<EMAIL>',
url='https://github.com/xpac1985/pyASA',
download_url='https://github.com/xpac1985/pyASA/tarball/0.1.0',
... |
20376 | def _recipes_pil_prescript(plugins):
try:
import Image
have_PIL = False
except ImportError:
from PIL import Image
have_PIL = True
import sys
def init():
if Image._initialized >= 2:
return
if have_PIL:
try:
impor... |
20397 | import torch
import numpy as np
PAD_TOKEN_INDEX = 0
def pad_masking(x, target_len):
# x: (batch_size, seq_len)
batch_size, seq_len = x.size()
padded_positions = x == PAD_TOKEN_INDEX # (batch_size, seq_len)
pad_mask = padded_positions.unsqueeze(1).expand(batch_size, target_len, seq_len)
return pa... |
20441 | from __future__ import unicode_literals
from django.utils.translation import ugettext_lazy as _
from common import MayanAppConfig
from .licenses import * # NOQA
class MIMETypesApp(MayanAppConfig):
name = 'mimetype'
verbose_name = _('MIME types')
def ready(self, *args, **kwargs):
super(MIMETyp... |
20474 | from base import BaseDataSet, BaseDataLoader
from utils import pallete
import numpy as np
import os
import scipy
import torch
from PIL import Image
import cv2
from torch.utils.data import Dataset
from torchvision import transforms
import json
class VOCDataset(BaseDataSet):
def __init__(self, **kwargs):
sel... |
20488 | import torch
import numpy as np
import torch.nn as nn
from torch.utils.data import Dataset, DataLoader
def binary_reg(x: torch.Tensor):
# forward: f(x) = (x>=0)
# backward: f(x) = sigmoid
a = torch.sigmoid(x)
b = a.detach()
c = (x.detach() >= 0).float()
return a - b + c
class HIN2vec(nn.Module... |
20491 | SECRET_KEY = None
DB_HOST = "localhost"
DB_NAME = "kido"
DB_USERNAME = "kido"
DB_PASSWORD = "<PASSWORD>"
COMPRESSOR_DEBUG = False
COMPRESSOR_OFFLINE_COMPRESS = True
|
20493 | import torch
import torch.nn as nn
import torch.nn.functional as F
def soft_dice_score(
output: torch.Tensor, target: torch.Tensor, smooth: float = 0.0, eps: float = 1e-7, dims=None) -> torch.Tensor:
assert output.size() == target.size()
if dims is not None:
intersection = torch.sum(output * t... |
20494 | import inspect
import re
from functools import update_wrapper
from typing import Optional
def is_interactive() -> bool:
try:
_ = get_ipython().__class__.__name__ # type: ignore
return True
except NameError:
return False
def get_attr_docstring(class_type, attr_name) -> Optional[str]:... |
20498 | import logging
import inspect
import re
from collections import OrderedDict
from gremlinpy.gremlin import Gremlin, Param, AS
from .entity import (_Entity, Vertex, Edge, GenericVertex, GenericEdge,
ENTITY_MAP)
from .exception import (AstronomerQueryException, AstronomerMapperException)
from .traversal import Trav... |
20506 | class InterpreterException(Exception):
def __init__(self, message):
self.message = message
def __str__(self):
return self.message
class SymbolNotFound(InterpreterException):
pass
class UnexpectedCharacter(InterpreterException):
pass
class ParserSyntaxError(InterpreterException):
... |
20520 | import cv2
import ProcessWithCV2
img1 = cv2.imread("D:/py/chinese/7.png")
img2 = cv2.imread("D:/py/chinese/8.png")
a = ProcessWithCV2.dHash(img1, img2, 1)
print(a)
|
20540 | from django.conf.urls.defaults import patterns, url
urlpatterns = patterns(
'popcorn_gallery.tutorials.views',
url(r'^(?P<slug>[\w-]+)/$', 'object_detail', name='object_detail'),
url(r'^$', 'object_list', name='object_list'),
)
|
20547 | from distutils.spawn import find_executable
from os import path
import click
from .settings import (
BASE_DEVELOPMENT_REQUIREMENTS_FILENAME,
BASE_REQUIREMENTS_FILENAME,
DEVELOPMENT_REQUIREMENTS_FILENAME,
REQUIREMENTS_FILENAME,
)
from .util import print_and_run
def _ensure_pip_tools_installed():
... |
20601 | import sys
sys.path.append("../../configs")
#../../configs
from path import EXP_PATH
import numpy as np
DECAY_PARAMS_DICT =\
{
'stair' :
{
128 :{
'a1': {'initial_lr' : 1e-5, 'decay_steps' : 50000, 'decay_rate' : 0.3},
'a2' : {'initial_lr' : 3e-4, 'decay_step... |
20613 | from aiohttp.test_utils import TestClient
import pytest
import typing
import unittest.mock
from rolling.kernel import Kernel
from rolling.model.character import CharacterModel
from rolling.model.character import MINIMUM_BEFORE_EXHAUSTED
from rolling.server.document.affinity import AffinityDirectionType
from rolling.se... |
20623 | from contextlib import contextmanager
import pytest
from sai import SaiObjType
@contextmanager
def config(npu):
topo_cfg = {
"lo_rif_oid": None,
"cpu_port_oid": None,
}
# Create Loopback RIF
lo_rif_oid = npu.create(SaiObjType.ROUTER_INTERFACE,
[
... |
20628 | import time
import textwrap
import math
import binascii
from inkfish.create_discriminant import create_discriminant
from inkfish.classgroup import ClassGroup
from inkfish.iterate_squarings import iterate_squarings
from inkfish import proof_wesolowski
from inkfish.proof_of_time import (create_proof_of_time_nwesolowski,... |
20668 | import openmoc
import openmc.openmoc_compatible
import openmc.mgxs
import numpy as np
import matplotlib
# Enable Matplotib to work for headless nodes
matplotlib.use('Agg')
import matplotlib.pyplot as plt
plt.ioff()
opts = openmoc.options.Options()
openmoc.log.set_log_level('NORMAL')
##############################... |
20705 | import os
import sys
import signal
import asyncio
import json
import time
import traceback
import typing
import socket
import re
import select
import websockets
if sys.platform != "win32":
import termios
import tty
else:
import msvcrt
import win32api
from .. import api
from ..shared import constants, ... |
20717 | from typing import Optional, Sequence
import torch
from ...gpu import Device
from ...models.encoders import EncoderFactory
from ...models.optimizers import OptimizerFactory
from ...models.q_functions import QFunctionFactory
from ...preprocessing import ActionScaler, RewardScaler, Scaler
from ...torch_utility import T... |
20769 | import io
import zlib
import numpy as np
def maybe_compress(str, compress):
return zlib.compress(str) if compress else str
def maybe_decompress(str, decompress):
return zlib.decompress(str) if decompress else str
def serialize_numpy(arr: np.ndarray, compress: bool = False) -> str:
"""Serializes numpy... |
20851 | import numpy as np
from matplotlib import _api
from .axes_divider import make_axes_locatable, Size
from .mpl_axes import Axes
@_api.delete_parameter("3.3", "add_all")
def make_rgb_axes(ax, pad=0.01, axes_class=None, add_all=True, **kwargs):
"""
Parameters
----------
pad : float
Fraction of th... |
20929 | import numpy as np
import os,sys,time
import torch
import torch.nn.functional as torch_F
import collections
from easydict import EasyDict as edict
import util
class Pose():
def __call__(self,R=None,t=None):
assert(R is not None or t is not None)
if R is None:
if not isinstance(t,torch... |
20935 | import logging, time, os
class Config:
def __init__(self, data_prefix):
# data_prefix = r'../data/'
self.data_prefix = data_prefix
self._multiwoz_damd_init()
def _multiwoz_damd_init(self):
self.vocab_path_train = self.data_prefix + '/multi-woz-processed/vocab'
self.data... |
20957 | try:
import pathlib
except ImportError as e:
try:
import pathlib2 as pathlib
except ImportError:
raise e
def name_to_asserted_group_path(name):
path = pathlib.PurePosixPath(name)
if path.is_absolute():
raise NotImplementedError(
"Absolute paths are currently not... |
20959 | def bubblesort(L):
keepgoing = True
while keepgoing:
keepgoing = False
for i in range(len(L)-1):
if L[i]>L[i+1]:
L[i], L[i+1] = L[i+1], L[i]
keepgoing = True
|
20993 | import numpy as np
import pytest
from arbol import aprint
from dexp.processing.utils.normalise import Normalise
from dexp.utils.backends import Backend
from dexp.utils.testing.testing import execute_both_backends
@execute_both_backends
@pytest.mark.parametrize(
"dexp_nuclei_background_data",
[dict(length_xy=... |
20996 | from ..utils import AnalysisException
from .expressions import Expression
class Literal(Expression):
def __init__(self, value):
super().__init__()
self.value = value
def eval(self, row, schema):
return self.value
def __str__(self):
if self.value is True:
retur... |
21014 | from .layer_send import AxolotlSendLayer
from .layer_control import AxolotlControlLayer
from .layer_receive import AxolotlReceivelayer
|
21035 | from .mem_bank import RGBMem, CMCMem
from .mem_moco import RGBMoCo, CMCMoCo
def build_mem(opt, n_data):
if opt.mem == 'bank':
mem_func = RGBMem if opt.modal == 'RGB' else CMCMem
memory = mem_func(opt.feat_dim, n_data,
opt.nce_k, opt.nce_t, opt.nce_m)
elif opt.mem == '... |
21043 | import pyblaze.nn.data.extensions
from .noise import NoiseDataset, LabeledNoiseDataset
from .zip import ZipDataLoader
from .transform import TransformDataset
|
21059 | from functools import partial
from typing import Callable
from typing import TYPE_CHECKING
from ...config import Conf
from .menu import Menu, MenuEntry, MenuSeparator
if TYPE_CHECKING:
from ...ui.views.disassembly_view import DisassemblyView
class DisasmInsnContextMenu(Menu):
"""
Dissembly Instruction's ... |
21079 | class AnalyticalModelStick(AnalyticalModel,IDisposable):
"""
An element that represents a stick in the structural analytical model.
Could be one of beam,brace or column type.
"""
def Dispose(self):
""" Dispose(self: Element,A_0: bool) """
pass
def GetAlignmentMethod(self,selector):
"""
GetA... |
21090 | import doctest
from nose.tools import assert_equal, assert_true
from corehq.apps.fixtures.models import (
FieldList,
FixtureDataItem,
FixtureItemField,
)
from custom.abt.reports import fixture_utils
from custom.abt.reports.fixture_utils import (
dict_values_in,
fixture_data_item_to_dict,
)
def t... |
21182 | import os
import sys
from dataclasses import dataclass
import click
import numpy as np
import xgboost as xgb
from rich import print, traceback
WD = os.path.dirname(__file__)
@click.command()
@click.option('-i', '--input', required=True, type=str, help='Path to data file to predict.')
@click.option('-m', '--model', ... |
21212 | import unittest
import os
import json
import pandas as pd
import numpy as np
class TestingExercise2_07(unittest.TestCase):
def setUp(self) -> None:
ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
with open(os.path.join(ROOT_DIR, '..', 'dtypes.json'), 'r') as jsonfile:
self.dtyp =... |
21227 | from setuptools import setup
import src
setup(name='lsankidb',
version=src.__version__,
install_requires=['AnkiTools'],
description='"ls" for your local Anki database.',
#FIXME this duplicates README.md
long_description="""
.. image:: https://cdn.jsdelivr.net/gh/AurelienLourot/lsankidb@c... |
21232 | from stix_shifter_utils.modules.base.stix_transmission.base_delete_connector import BaseDeleteConnector
class DeleteConnector(BaseDeleteConnector):
def __init__(self, api_client):
self.api_client = api_client
def delete_query_connection(self, search_id):
return {"success": True}
|
21413 | import sys
output=sys.argv[1]
input_list=(sys.argv[2:])
EXP={}
header=[]
for input_file in input_list:
fi=open(input_file)
header=header+fi.readline().replace('"','').rstrip().split()
for line in fi:
seq=line.replace('"','').rstrip().split()
if seq[0] in EXP:
EXP[s... |
21454 | from simcse import SimCSE
from esimcse import ESimCSE
from promptbert import PromptBERT
from sbert import SBERT
from cosent import CoSent
from config import Params
from log import logger
import torch
from transformers import AutoTokenizer
class SimCSERetrieval(object):
def __init__(self, pretrained_model_path, si... |
21458 | import random
import requests
import time
HOSTS = [
'us-east-1',
'us-west-1',
'eu-west-1',
]
VEHICLES = [
'bike',
'scooter',
'car',
]
if __name__ == "__main__":
print(f"starting load generator")
time.sleep(15)
print('done sleeping')
while True:
host = HOSTS[random.rand... |
21460 | from django.contrib import admin
from . import models
class ReadOnlyAdminMixin():
def get_readonly_fields(self, request, obj=None):
return list(set(
[field.name for field in self.opts.local_fields] +
[field.name for field in self.opts.local_many_to_many]
))
class ReadOnl... |
21478 | from pymp3decoder import Decoder
import contextlib
import os
import math
import pyaudio
CHUNK_SIZE = 4096
def take_chunk(content):
""" Split a buffer of data into chunks """
num_blocks = int(math.ceil(1.0*len(content)/CHUNK_SIZE))
for start in range(num_blocks):
yield content[CHUNK_SIZE*start:... |
21519 | import re
from . import tables
from .instr import Instruction
from .instr.nop import *
from .instr.alu import *
from .instr.bcd import *
from .instr.bit import *
from .instr.flag import *
from .instr.mov import *
from .instr.smov import *
from .instr.ld_st import *
from .instr.stack import *
from .instr.jmp import *
f... |
21524 | from unittest import TestCase
from schemer import Schema, Array, ValidationException
from dusty.schemas.base_schema_class import DustySchema, DustySpecs
from ...testcases import DustyTestCase
class TestDustySchemaClass(TestCase):
def setUp(self):
self.base_schema = Schema({'street': {'type': basestring},... |
21546 | import torch
from torch.autograd import Function
class Identity(Function):
@staticmethod
def forward(ctx, x, name):
ctx.name = name
return x.clone()
def backward(ctx, grad):
import pydevd
pydevd.settrace(suspend=False, trace_only_current_thread=True)
grad_temp = gr... |
21568 | import FWCore.ParameterSet.Config as cms
# This modifier sets replaces the default pattern recognition with mkFit for tobTecStep
trackingMkFitTobTecStep = cms.Modifier()
|
21590 | from plugin.scrobbler.core import SessionEngine, SessionHandler
@SessionEngine.register
class PlayingHandler(SessionHandler):
__event__ = 'playing'
__src__ = ['create', 'pause', 'stop', 'start']
__dst__ = ['start', 'stop']
@classmethod
def process(cls, session, payload):
# Handle media c... |
21625 | import argparse
from os import listdir, path
import numpy as np
def convert(main_folder, output):
ret = []
for label, class_folder in listdir(main_folder):
class_folder_path = path.join(main_folder, class_folder)
for img_name in listdir(class_folder_path):
image_path = path.join... |
21642 | import os
from sys import platform
def say_beep(n: int):
for i in range(0, n):
if platform == "darwin":
os.system("say beep")
|
21653 | import simplejson as json
from .telegram_field import TelegramField
class WTelegramHeader(object):
def __init__(self):
# self._startField = TelegramField()
self._lField = TelegramField()
self._cField = TelegramField()
# self._crcField = TelegramField()
# self._stopField = T... |
21669 | from box.parser import Parser
from box.generator import Generator
import os
class Importer:
def __init__(self, path):
# Path to directory containing function graphs to import
self.path = os.path.abspath(path)
# { "FunctionName": <Generator>, ... }
self.function_declarations = {}
... |
21681 | import json
from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter, FileType
from pathlib import Path
def main():
parser = ArgumentParser(description='Collect markdown files, and write JSON.',
formatter_class=ArgumentDefaultsHelpFormatter)
project_path = Path(__file__).... |
21704 | import torch
import torch.nn as nn
class voxel_match_loss(nn.Module):
def __init__(self):
super().__init__()
self.criterion=nn.MSELoss()
def forward(self,output,label):
positive_mask=torch.zeros(label.shape).cuda()
positive_mask=torch.where(label>0.2,torch.ones_like(positive_mas... |
21736 | import functools
from flask import Blueprint
from flask import render_template
from flask import g
from flask import redirect
from flask import url_for
from flask import flash
from mflac.vuln_app.db import get_db
bp = Blueprint("admin", __name__, url_prefix="/admin")
def admin_required(view):
@functools.wraps(... |
21772 | from __future__ import absolute_import
from __future__ import print_function
import os
import sys
from conversion_imagenet import TestModels
from conversion_imagenet import is_paddle_supported
def get_test_table():
return { 'paddle' : {
'resnet50' : [
TestModels.onnx_emit,
... |
21790 | import numpy as np
from matplotlib import pyplot as plt
"""
https://stackoverflow.com/questions/42750910/convert-rgb-image-to-index-image/62980021#62980021
convert semantic labels from RGB coding to index coding
Steps:
1. define COLORS (see below)
2. hash colors
3. run rgb2index(segmentation_rgb)
see example below
T... |
21827 | from .model import KerasModel
import keras
from keras.models import Sequential
from keras.layers import Dense, Activation, Flatten
from keras.layers import BatchNormalization, Dropout, Conv2D, MaxPooling2D
import kapre
from kapre.utils import Normalization2D
from kapre.time_frequency import Spectrogram
class CNN_STF... |
21838 | import heterocl as hcl
hcl.init()
target = hcl.Platform.xilinx_zc706
initiation_interval = 4
a = hcl.placeholder((10, 20), name="a")
b = hcl.placeholder((10, 20), name="b")
c = hcl.placeholder((10, 20), name="c")
d = hcl.placeholder((10, 20), name="d")
e = hcl.placeholder((10, 20), name="e")
def add_mul(a, b, c, d,... |
21936 | DILAMI_WEEKDAY_NAMES = {
0: "شمبه",
1: "یکشمبه",
2: "دۊشمبه",
3: "سۊشمبه",
4: "چارشمبه",
5: "پئنشمبه",
6: "جۊمه",
}
DILAMI_MONTH_NAMES = {
0: "پنجيک",
1: "نؤرۊز ما",
2: "کۊرچ ٚ ما",
3: "أرئه ما",
4: "تیر ما",
5: "مۊردال ما",
6: "شریرما",
7: "أمیر ما",
8: ... |
22008 | from __future__ import with_statement
from contextlib import contextmanager
from test import TemplateTest, eq_, raises, template_base, mock
import os
from mako.cmd import cmdline
class CmdTest(TemplateTest):
@contextmanager
def _capture_output_fixture(self, stream="stdout"):
with mock.patch("sys.%s" % ... |
22010 | from LightPipes import *
import matplotlib.pyplot as plt
def TheExample(N):
fig=plt.figure(figsize=(11,9.5))
ax1 = fig.add_subplot(221)
ax2 = fig.add_subplot(222)
ax3 = fig.add_subplot(223)
ax4 = fig.add_subplot(224)
labda=1000*nm;
size=10*mm;
f1=10*m
f2=1.11111111*m
z=1.0*... |
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