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import locale import os from enum import Enum, IntEnum from functools import lru_cache import gi gi.require_version("Gtk", "3.0") gi.require_version("Gdk", "3.0") gi.require_version("Notify", "0.7") from gi.repository import Gtk, Gdk, Notify from app.settings import Settings, SettingsException, IS_DARWIN # Init not...
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from abc import ABC, abstractmethod from typing import List import numpy as np from scipy.stats import t, spearmanr from scipy.special import erfinv from chemprop.uncertainty.uncertainty_calibrator import UncertaintyCalibrator from chemprop.train import evaluate_predictions class UncertaintyEvaluator(ABC): """ ...
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import hydra import hydra.utils as utils from pathlib import Path import torch import numpy as np from tqdm import tqdm import soundfile as sf from model_encoder import Encoder, Encoder_lf0 from model_decoder import Decoder_ac from model_encoder import SpeakerEncoder as Encoder_spk import os import random from glob...
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import numpy as np from nms import nms import cfg from shapely.geometry import Polygon class Averager(object): """Compute average for torch.Tensor, used for loss average.""" def __init__(self): self.reset() def add(self, v): count = v.data.numel() v = v.data.sum() self.n_...
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class ListView(Control,IComponent,IDisposable,IOleControl,IOleObject,IOleInPlaceObject,IOleInPlaceActiveObject,IOleWindow,IViewObject,IViewObject2,IPersist,IPersistStreamInit,IPersistPropertyBag,IPersistStorage,IQuickActivate,ISupportOleDropSource,IDropTarget,ISynchronizeInvoke,IWin32Window,IArrangedElement,IBindableCo...
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import torch import torch.nn as nn from fpconv.pointnet2.pointnet2_modules import PointnetFPModule, PointnetSAModule import fpconv.pointnet2.pytorch_utils as pt_utils from fpconv.base import AssemRes_BaseBlock from fpconv.fpconv import FPConv4x4_BaseBlock, FPConv6x6_BaseBlock NPOINTS = [8192, 2048, 512, 128] RADIUS =...
76574
import argparse, os import malmoenv from pathlib import Path from gameai.utils.wrappers import DownsampleObs def parse_args(): parser = argparse.ArgumentParser(description='malmoenv arguments') parser.add_argument('--mission', type=str, default='../MalmoEnv/missions/mobchase_single_agent.xml', ...
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import pytest from tests.utils.device_mock import DeviceMock @pytest.fixture() def device(): dev = DeviceMock({ 0x10: bytes.fromhex('59') }) return dev class TestEncryptionTemperature: def test_read_battery(self, device): assert device.battery == 89 def test_write_battery(self,...
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from dataclasses import dataclass import discord @dataclass(init=False) class TwitchProfile: def __init__(self, **kwargs): self.id = kwargs.get("id") self.login = kwargs.get("login") self.display_name = kwargs.get("display_name") self.acc_type = kwargs.get("acc_type") self...
76627
import pandas as pd from pandas_datareader import data start_date = '2014-01-01' end_date = '2018-01-01' SRC_DATA_FILENAME = 'goog_data.pkl' try: goog_data2 = pd.read_pickle(SRC_DATA_FILENAME) except FileNotFoundError: goog_data2 = data.DataReader('GOOG', 'yahoo', start_date, end_date) goog_data2.to_pickle(SRC...
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import random import pecan from pecan import expose, response, request _body = pecan.x_test_body _headers = pecan.x_test_headers class TestController: def __init__(self, account_id): self.account_id = account_id @expose(content_type='text/plain') def test(self): user_agent = request.he...
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import csv import os def remove_if_exist(path): if os.path.exists(path): os.remove(path) def load_metadata(path): res = {} headers = None with open(path, newline='') as csvfile: reader = csv.reader(csvfile, delimiter=',', quotechar='"') for row in reader: if head...
76674
import sys import csv from matplotlib import image as mpimg import numpy as np import scipy.misc import cv2 vert_filename = sys.argv[1] edge_filename = sys.argv[2] img_filename = sys.argv[3] output_img_filename = sys.argv[4] thresh = int(sys.argv[5]) print('reading in verts...') verts = [] with open(vert_filename, '...
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import torch from hypothesis import given from hypothesis import strategies as st from subset_samplers import ConstructiveRandomSampler from subset_samplers import ExhaustiveSubsetSampler from subset_samplers import ProportionalConstructiveRandomSampler from subset_samplers import RandomProportionSubsetSampler from su...
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import tensorflow as tf import numpy as np def batches(l, n): """Yield successive n-sized batches from l, the last batch is the left indexes.""" for i in range(0, l, n): yield range(i,min(l,i+n)) class Deep_Autoencoder(object): def __init__(self, sess, input_dim_list=[7,64,64,7],transfer_function...
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from .component import Component class Location(Component): NAME = "location" def __init__(self): super().__init__() # TODO THIS HOLDS ALL THE INFORMATION NEEDED TO LOCATE SOMETHING self.local_x = 0 self.local_y = 0 self.global_x = 0 self.global_y = 0 s...
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from time import time import os from random import gauss import sys import numpy as np from keras.models import Sequential, load_model from keras.layers import Dense, Activation from Bio.SeqIO import SeqRecord from Bio import SeqIO, Seq from advntr.sam_utils import get_id_of_reads_mapped_to_vntr_in_bamfile, make_bam...
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from django.conf import settings def get_user_model_name(): """ Returns the app_label.object_name string for the user model. """ return getattr(settings, "AUTH_USER_MODEL", "auth.User")
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import os PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) MODEL_PATH = os.path.join(PROJECT_ROOT, 'models') DATA_PATH = os.path.join(PROJECT_ROOT, 'data')
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import FWCore.ParameterSet.Config as cms from CondCore.DBCommon.CondDBCommon_cfi import * PoolDBESSourcebtagMuJetsWpNoTtbar = cms.ESSource("PoolDBESSource", CondDBCommon, toGet = cms.VPSet( # # working points # cms.PSet( record = cms.stri...
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from simple_NER.utils.log import LOG from simple_NER.rules import RuleNER from simple_NER import Entity from os.path import expanduser, isdir, join from os import makedirs try: from padatious import IntentContainer except ImportError: LOG.error("padatious not found, run") LOG.error("pip install fann2==1.0....
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from dataclasses import dataclass from dbt.adapters.sqlserver import (SQLServerConnectionManager, SQLServerCredentials) @dataclass class SynapseCredentials(SQLServerCredentials): @property def type(self): return "synapse" class SynapseConnectionManager(SQLServerCon...
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import pytest from webbpsf import wfirst from numpy import allclose def test_WFI_psf(): """ Just test that instantiating WFI works and can compute a PSF without raising any exceptions """ wi = wfirst.WFI() wi.calc_psf(fov_pixels=4) def test_WFI_filters(): wi = wfirst.WFI() filter_lis...
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from typing import Optional, List from platypush.message.response import Response class PrinterResponse(Response): def __init__(self, *args, name: str, printer_type: int, info: str, uri: str, state: int, ...
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from ubinascii import hexlify from bitcoin import bip32, bip39, script # NETWORKS contains all constants for HD keys and addresses from bitcoin.networks import NETWORKS # we will use testnet: network = NETWORKS["test"] entropy = b'\x64\xd3\xe4\xa0\xa3\x87\xe2\x80\x21\xdf\x55\xa5\x1d\x45\x4d\xcf' recovery_phrase = bip...
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from manim import * from manim_ml.neural_network.layers import TripletLayer, triplet from manim_ml.neural_network.layers.feed_forward import FeedForwardLayer from manim_ml.neural_network.neural_network import NeuralNetwork config.pixel_height = 720 config.pixel_width = 1280 config.frame_height = 6.0 config.frame_width...
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import typing from pycspr.crypto import KeyAlgorithm from pycspr.factory import create_public_key from pycspr.serialisation.cl_type_from_bytes import decode as cl_type_from_bytes from pycspr.serialisation.cl_value_from_bytes import decode as cl_value_from_bytes from pycspr.types import Timestamp from pycspr.types impo...
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import re from os import environ import boto3 import pytest from botocore.exceptions import ClientError from moto import mock_efs from tests.test_efs.junk_drawer import has_status_code ARN_PATT = r"^arn:(?P<Partition>[^:\n]*):(?P<Service>[^:\n]*):(?P<Region>[^:\n]*):(?P<AccountID>[^:\n]*):(?P<Ignore>(?P<ResourceType...
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import numpy as np from scipy.optimize import least_squares from scipy.special import gamma from scipy.stats import gengamma from percentile_3_moments_first_guess import percentile_3_moments_first_guess from tqdm import trange import sys def percentile_3_moments(trA,trAsq,trAcub,proba,MaxFunEvals): """ percentile_3...
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from setuptools import setup, find_packages VERSION_NUMBER = '0.1.0' with open('requirements.txt', 'rb') as handle: REQUIREMENTS = [ x.decode('utf8') for x in handle.readlines() ] with open('dev_requirements.txt', 'rb') as handle: TEST_REQUIREMENTS = [ x.decode('utf8') for x in handle.r...
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import json from os import write w = open("json.txt","r",encoding="utf-8") f = open("dict.txt","w",encoding="utf-8") arr = json.load(w) s = dict() f.write('{') for item in arr: s[item["value"]] = item["key"] print(s) for key in s: f.write('"'+str(key)+'"'+':') f.write('"'+str(s[key])+'"'+',\n') f.write("}"...
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import ee # Initialize the GEE API # try: # ee.Initialize() # except Exception as ee: # ee.Authenticate() # ee.Initialize() # geemap:A Python package for interactive mapping with Google Earth Engine, ipyleaflet, and ipywidgets # Documentation: https://geemap.org import geemap from geemap import ml import p...
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from __future__ import absolute_import, division, print_function, unicode_literals import fractions import math from six.moves import xrange # http://stackoverflow.com/questions/4798654/modular-multiplicative-inverse-function-in-python # from https://en.wikibooks.org/wiki/Algorithm_Implementation/Mathematics/Extende...
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from typing import TYPE_CHECKING, Any, Dict, List, Optional from app import errors if TYPE_CHECKING: from app.database.database import Database class Autoredeem: def __init__(self, db: "Database"): self.db = db async def get( self, guild_id: int, user_id: int ) -> Optional[Dict[str,...
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import os,sys from scipy.stats.stats import pearsonr import numpy as np try: bacteriaF = sys.argv[1] phageF = sys.argv[2] except: sys.exit(sys.argv[0] + " <bacterial file> <phage file>") bact={} with open(bacteriaF, 'r') as bin: l=bin.readline() bactheaders = l.strip().split("\t") for l in ...
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import sys sys.path.append('../') import tensorflow as tf from google.cloud import storage from tempfile import TemporaryDirectory import os from mreserve.lowercase_encoder import get_encoder import argparse from PIL import Image import numpy as np from io import BytesIO import random encoder = get_encoder() class GC...
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import os.path as osp import random import numpy as np import pytest from numpy.testing import assert_array_almost_equal, assert_array_equal from mmaction.core import (ActivityNetLocalization, average_recall_at_avg_proposals, confusion_matrix, get_weighted_score, ...
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import numpy as np import sys import os import pytest from knnFeat import _distance sys.path.append(os.getcwd()) @pytest.mark.success def test_distance(): a = np.array([0, 0]) b = np.array([3, 4]) expected = _distance(a, b) actual = 5 assert expected == actual
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class BaseSubmission: def __init__(self, team_name, player_names): self.team_name = team_name self.player_names = player_names def get_actions(self, obs): ''' Overview: You must implement this function. ''' raise NotImplementedError
77404
from plex_database.core import db from plex_database.models.directory import Directory from plex_database.models.media_item import MediaItem from peewee import * class MediaPart(Model): class Meta: database = db db_table = 'media_parts' media_item = ForeignKeyField(MediaItem, null=True, rela...
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import numpy as np import time import math # from cassie_env import CassieEnv from cassiemujoco import * from trajectory.trajectory import CassieTrajectory import matplotlib.pyplot as plt from matplotlib import style from matplotlib.animation import FuncAnimation import matplotlib.animation as animation from mpl_too...
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import pytest from wemake_python_styleguide.violations.complexity import ( TooDeepAccessViolation, ) from wemake_python_styleguide.visitors.ast.complexity.access import ( AccessVisitor, ) # boundary expressions subscript_access = 'my_matrix[0][0][0][0]' attribute_access = 'self.attr.inner.wrapper.value' mixed...
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import logging import numpy as np from numpy.linalg import norm from scipy.stats import moment from scipy.special import cbrt def common_usr(molecule, ctd=None, cst=None, fct=None, ftf=None, atoms_type=None): """Function used in USR and USRCAT function Parameters ---------- molecule : oddt.toolkit.M...
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import ui, console import os import math def save_action(sender): with open('image_file.png', 'wb') as fp: fp.write(img.to_png()) console.hud_alert('image saved in the file image_file.png') def showimage_action(sender): img.show() def make_polygon(num_sides, x=0, y=0, radius=100, phase=0...
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import torch from .. import utils MODULE = torch FP16_FUNCS = [ # Low level functions wrapped by torch.nn layers. # The wrapper layers contain the weights which are then passed in as a parameter # to these functions. 'conv1d', 'conv2d', 'conv3d', 'conv_transpose1d', 'conv_transpose2d'...
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import re import uuid from subprocess import run from tempfile import NamedTemporaryFile from typing import List, Optional import conda_pack import yaml from ...utils import logger from ..constants import MLServerEnvDeps, MLServerRuntimeEnvDeps from ..metadata import ModelFramework def _get_env(conda_env_file_path:...
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from insightconnect_plugin_runtime.exceptions import PluginException from json import JSONDecodeError import requests from requests.auth import HTTPBasicAuth from urllib.parse import urlsplit class EasyVistaApi: def __init__(self, client_login: dict, account: int, url: str): self.base_url = f"{self.split_...
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from unittesting import DeferrableTestCase from GitSavvy.tests.parameterized import parameterized as p from GitSavvy.core.commands.log_graph import describe_graph_line examples = [ ( "|", {}, None ), ( "● a3062b2 (HEAD -> optimize-graph-render, origin/optimize-graph-render...
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from __future__ import annotations from typing import TYPE_CHECKING import random from enum import Enum from configuration import config from src.genotype.mutagen.option import Option from src.genotype.neat.gene import Gene if TYPE_CHECKING: pass class NodeType(Enum): INPUT = 0 HIDDEN = 1 OUTPUT =...
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import random import pygame from . import map_generator, traps from .pathfinder import Pathfinder from .tile import Tile TILE_SIZE = 16 BARRIER_SIZE = 10 def grid_walk(start, end): start = list(start) dx = end[0] - start[0] dy = end[1] - start[1] nx = abs(dx) ny = abs(dy) sign_x = 1 if dx >...
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import cv2 import tensorflow as tf import numpy as np OUTPUT_PATH = "../events/" NUM_FILTERS = 10 FILTER_SIZE = (3, 3) STRIDES = (1, 1) def nn(input_node): with tf.variable_scope('nn'): w = tf.get_variable( name='weight', shape=[FILTER_SIZE[0], FILTER_SIZE[1], 3, NUM_FILTERS], ...
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import csv class Characters: def getBrawlersID(): BrawlersID = [] with open('Logic/Files/assets/csv_logic/characters.csv') as csv_file: csv_reader = csv.reader(csv_file, delimiter=',') line_count = 0 for row in csv_reader: if line_count == 0 or ...
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from io import BytesIO from PIL import Image, ImageDraw from flask import send_file from utils.endpoint import Endpoint, setup from utils.textutils import wrap, render_text_with_emoji @setup class SneakyFox(Endpoint): params = ['text'] def generate(self, avatars, text, usernames, kwargs): base = Im...
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from unittest import TestCase from pypika import ( Table, functions as fn, ) import fireant as f from fireant.tests.dataset.mocks import test_database test_table = Table("test") ds = f.DataSet( table=test_table, database=test_database, fields=[ f.Field("date", definition=test_table.date, ...
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import torch import json from os import PathLike from typing import List, Tuple, Union, Optional from allennlp.common.file_utils import cached_path from allennlp.data import Vocabulary from allennlp.data.tokenizers.tokenizer import Tokenizer def _convert_word_to_ids_tensor(word, tokenizer, vocab, namespace, all_case...
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from util.fsm import StateMachine if __name__ == "__main__": machine = StateMachine('status', ["off", "fleft", "left", "bleft", "fright", "right", "bright"], "left") machine.create_trans("left", "fleft", "otherleft") print machine.process("otherleft") #>>> states = ["off", "f...
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import torch import numpy as np from onnx import numpy_helper from thop.vision.basic_hooks import zero_ops from .counter import counter_matmul, counter_zero_ops,\ counter_conv, counter_mul, counter_norm, counter_pow,\ counter_sqrt, counter_div, counter_softmax, counter_avgpool def onnx_counter_matmul(diction,...
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from torch import nn class FeedForwardNet(nn.Module): def __init__(self, inp_dim, hidden_dim, outp_dim, n_layers, nonlinearity, dropout=0): super().__init__() layers = [] d_in = inp_dim for i in range(n_layers): module = nn.Linear(d_in, hidden_dim) self.rese...
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from toga_winforms.libs import WinForms from .base import Widget class Tree(Widget): def create(self): self.native = WinForms.TreeView() def row_data(self, item): self.interface.factory.not_implemented('Tree.row_data()') def on_select(self, selection): self.interface.factory.not...
78001
import logging from ...util import none_or from .collection import Collection logger = logging.getLogger("mw.database.collections.pages") class Pages(Collection): def get(self, page_id=None, namespace_title=None, rev_id=None): """ Gets a single page based on a legitimate identifier of the page. ...
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from rxbp.flowables.controlledzipflowable import ControlledZipFlowable from rxbp.indexed.selectors.bases.numericalbase import NumericalBase from rxbp.subscriber import Subscriber from rxbp.testing.testcasebase import TestCaseBase from rxbp.testing.testflowable import TestFlowable from rxbp.testing.tobserver import TObs...
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from dataclasses import dataclass from apischema.json_schema import deserialization_schema @dataclass class Bar: baz: str @dataclass class Foo: bar1: Bar bar2: Bar assert deserialization_schema(Foo, all_refs=False) == { "$schema": "http://json-schema.org/draft/2020-12/schema#", "$defs": { ...
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import grpc import time from bettermq_pb2 import * from bettermq_pb2_grpc import * host = '127.0.0.1:8404' with grpc.insecure_channel(host) as channel: client = PriorityQueueStub(channel) i = 1 while True: req = DequeueRequest( topic = "root", count = 1, ) i...
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import numpy as np def prefix_search(mat: np.ndarray, chars: str) -> str: """Prefix search decoding. See dissertation of Graves, p63-66. Args: mat: Output of neural network of shape TxC. chars: The set of characters the neural network can recognize, excluding the CTC-blank. Returns:...
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from struct import Struct def read_records(format, f): record_struct = Struct(format) chunks = iter(lambda: f.read(record_struct.size), b'') return (record_struct.unpack(chunk) for chunk in chunks) # Example if __name__ == '__main__': with open('data.b','rb') as f: for rec in read_records('<id...
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from typing import Dict, List from dataclasses import dataclass, field import tvm from tvm import relay import pickle import random import numpy as np import random from copy import deepcopy from .tvmpass import PassDependenceGraph, PassNode # TODO: Add parameters. # TODO: Add more passes. _RELAY_FUNCTION_HARD_PASSE...
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import json import os import unittest import shutil from satstac import __version__, Catalog, STACError, Item testpath = os.path.dirname(__file__) class Test(unittest.TestCase): path = os.path.join(testpath, 'test-catalog') @classmethod def tearDownClass(cls): """ Remove test files """ ...
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load("@bazel_skylib//lib:dicts.bzl", _dicts = "dicts") load( "//rules/scala_proto:private/core.bzl", _scala_proto_library_implementation = "scala_proto_library_implementation", _scala_proto_library_private_attributes = "scala_proto_library_private_attributes", ) scala_proto_library = rule( attrs = _dic...
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import math from OpenGL.GL import * from OpenGL.GLUT import * from OpenGL.GLU import * """ Turtle drawings Once the functions reset(), turn(), turnTo() and forw() there is a possibility to program a path. In essence this is very similar to using polar coordinates relative to the last set point. Meaning you define t...
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import os from unittest import mock import pytest from kubernetes.client.exceptions import ApiException from task_processing.plugins.kubernetes.kube_client import ExceededMaxAttempts from task_processing.plugins.kubernetes.kube_client import KubeClient def test_KubeClient_no_kubeconfig(): with mock.patch( ...
78223
from joerd.util import BoundingBox import joerd.download as download import joerd.check as check import joerd.srs as srs import joerd.mask as mask from joerd.mkdir_p import mkdir_p from shutil import copyfileobj import os.path import os import requests import logging import re import tempfile import sys import tracebac...
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import logging from functools import wraps from celery import states from . import events from .application import celery_application from .events import RUNTIME_METADATA_ATTR winnow_task_logger = logging.getLogger(__name__) class WinnowTask(celery_application.Task): def update_metadata(self, meta=None, task_i...
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import os from gitaccount.gitaccounthelpers.gitaccounthelpers import ( get_repos_from_url, clone, pull, already_cloned, get_gists_from_url) class GitAccount: """GitAccount class provides clone_repos and update_repos methods""" def __init__(self, account_type, userName): self._userName = userNa...
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from backend.serializers.user_model_serializer import UserModelDetailSerializer def jwt_response_payload_handler(token, user=None, request=None): return { 'token': token, 'user': UserModelDetailSerializer(user, context={'request':request}).data }
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from lyrebird import application from .. import checker class CustomDecoder: def __call__(self, rules=None, *args, **kw): def func(origin_func): func_type = checker.TYPE_DECODER if not checker.scripts_tmp_storage.get(func_type): checker.scripts_tmp_storage[func_typ...
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from mongoengine import Document, IntField, DoesNotExist, MultipleObjectsReturned, StringField class SwapTrackerObject(Document): nonce = IntField(required=True) src = StringField(required=True, unique=True) @classmethod def last_processed(cls, src: str): """ Returns last processed co...
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from bge import logic class HeartContainer: def __init__(self, startHeart, maxHeart): self.isLow = False # if heartContainer not exist init then if not 'heartContainer' in logic.globalDict['Player']: logic.globalDict['Player']['heartContainer'] = {'heart' : startHeart, 'maxHeart' : maxHeart} def calculLow...
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class Token: TOP_LEFT = "┌" TOP_RIGHT = "┐" BOTTOM_LEFT = "└" BOTTOM_RIGHT = "┘" HORIZONTAL = "─" BOX_START = TOP_LEFT + HORIZONTAL VERTICAL = "│" INPUT_PORT = "┼" OUTPUT_PORT = "┼" FUNCTION = "ƒ" COMMENT = "/*...*/" SINGLE_QUOTE = "'" DOUBLE_QUOTE = '"' LEFT_PARE...
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class IndexingError(Exception): """Exception raised for errors in the indexing flow. Attributes: type -- One of 'user', 'user_replica_set', 'user_library', 'tracks', 'social_features', 'playlists' blocknumber -- block number of error blockhash -- block hash of error txhash -- tr...
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import itertools import logging import numpy as np import pandas as pd import scipy.stats def create_regression_dataset(metafeatures, experiments): X = [] X_indices = [] Y = [] for dataset_name in experiments: experiment = experiments[dataset_name] mf = metafeatures.loc[dataset_name] ...
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from dataclasses import dataclass from typing import Tuple from manim import config from manim import DEFAULT_MOBJECT_TO_EDGE_BUFFER from manim import DEFAULT_MOBJECT_TO_MOBJECT_BUFFER from manim import DOWN from manim import LEFT from manim import Mobject from manim import np from manim import ORIGIN from manim impor...
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import unittest import numpy as np from audiomentations.augmentations.transforms import Mp3Compression from audiomentations.core.composition import Compose class TestMp3Compression(unittest.TestCase): def test_apply_mp3_compression_pydub(self): sample_len = 44100 samples_in = np.random.normal(0,...
78614
from . import mysqldb from physical.models import Instance class MySQLPercona(mysqldb.MySQL): def get_default_instance_type(self): return Instance.MYSQL_PERCONA @classmethod def topology_name(cls): return ['mysql_percona_single'] class MySQLPerconaFOXHA(mysqldb.MySQLFOXHA): def ge...
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import argparse import configparser import torch import os import numpy as np import matplotlib.animation as animation import matplotlib.pyplot as plt from model import ValueNetwork from env import ENV from train import run_one_episode def visualize(model_config, env_config, weight_path, case, save): state_dim = ...
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import ast from amqp import ChannelError from kombu import Connection from kombu.common import uuid, maybe_declare from mock import patch, ANY from cell.actors import Actor, ActorProxy from cell.exceptions import WrongNumberOfArguments from cell.results import AsyncResult from cell.tests.utils import Case, Mock, with_...
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from datetime import datetime from mongoengine import DateTimeField, Document, UUIDField from mongoengine.fields import DictField, ListField, ReferenceField from vim_adaptor.models.vims import BaseVim class ServiceInstance(Document): """ Document class to store data related to a service instance """ ...
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import base64 import urllib2 import json import os import logging from celery import task from django.conf import settings from django.utils.timezone import now from github.GithubObject import NotSet from github import Github, GithubException, InputGitTreeElement from ide.git import git_auth_check, get_github from id...
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import json import sys def main(): argv_file = sys.argv[1] with open(argv_file, "wt") as fp: json.dump(sys.argv, fp) sys.exit(0) if __name__ == "__main__": main()
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import asyncio import json import signal from callosum.rpc import Peer from callosum.ordering import ( KeySerializedAsyncScheduler, ) from callosum.lower.zeromq import ZeroMQAddress, ZeroMQRPCTransport async def handle_echo(request): print('echo start') await asyncio.sleep(1) print('echo done') r...
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from collections import OrderedDict as odict import time import numpy as np from .json_encoder import JsonNumEncoder import os class Profiler: """This class provides a very simple yet light implementation of function profiling. It is very easy to use: >>> profiler.reset() >>> profiler.start("...
78829
import math import hashlib import zlib from bitarray import bitarray from globals import G class BFsignature(): def __init__(self, total_chunks): self.total_chunks = total_chunks if self.total_chunks > 0: self.cal_m() #print("bf size = ",self.m) else: #lo...
78857
from typing import List, TYPE_CHECKING from cloudfoundry_client.json_object import JsonObject if TYPE_CHECKING: from cloudfoundry_client.client import CloudFoundryClient class ResourceManager(object): def __init__(self, target_endpoint: str, client: "CloudFoundryClient"): self.target_endpoint = targ...
78935
from aiogram import types from .dataset import PHOTO photo = types.PhotoSize(**PHOTO) def test_export(): exported = photo.to_python() assert isinstance(exported, dict) assert exported == PHOTO def test_file_id(): assert isinstance(photo.file_id, str) assert photo.file_id == PHOTO['file_id'] d...
78954
from yo_fluq_ds__tests.common import * import numpy as np class MiscMethodsTests(TestCase): def test_pairwise(self): result = Query.args(1,2,3).feed(fluq.pairwise()).to_list() self.assertListEqual([(1,2),(2,3)],result) def test_strjoin(self): result = Query.args(1,2,3).feed(fluq.strjoi...
78961
from direct.directnotify import DirectNotifyGlobal from direct.distributed.DistributedObjectUD import DistributedObjectUD class AwardManagerUD(DistributedObjectUD): notify = DirectNotifyGlobal.directNotify.newCategory('AwardManagerUD')
78971
from motion import * if __name__ == '__main__': from time import sleep buf = [] buf_len = 5 last_avg = 0 threshold = 0.02 lsm = accelcomp() while True: lsm.getAccel() buf.append(lsm.accel[X] + lsm.accel[Y] + lsm.accel[Z]) buf = buf[-buf_len:] avg = reduce...
79012
from typing import List class Solution: def numPairsDivisibleBy60(self, time: List[int]) -> int: mods = [0] * 60 for t in time: mods[t % 60] += 1 cnt = sum(mods[i] * mods[60 - i] for i in range(1, 30)) for i in [0, 30]: cnt += mods[i] * (mods[i] - 1) // 2 ...
79025
from abc import abstractmethod import numpy as np from pymoo.core.population import Population # --------------------------------------------------------------------------------------------------------- # Survival # ----------------------------------------------------------------------------------------------------...
79078
import json import logging from pprint import pformat from typing import Any, Dict, Set import pydantic from models_library.projects_nodes import NodeID from models_library.utils.nodes import compute_node_hash from packaging import version from ..node_ports_common.dbmanager import DBManager from ..node_ports_common.e...
79101
import warnings from random import randint from unittest import TestCase from .models import ( ColumnFamilyTestModel, ColumnFamilyIndexedTestModel, ClusterPrimaryKeyModel, ForeignPartitionKeyModel, DictFieldModel ) from .util import ( connect_db, destroy_db, create_model ) class Colu...