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import os
from collections import defaultdict
from copy import deepcopy
from packaging.requirements import InvalidRequirement, Requirement
from ..fs import stream_file_lines, write_file_lines
from .constants import NOT_CHECKS, get_agent_requirements, get_root
from .utils import (
get_normalized_dependency,
ge... |
#!/usr/bin/env python
# coding: utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms, utils, models
from torch.autograd import Variable
import os
import sys
sys.path.append(os.path.joi... |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.forms import widgets, ModelChoiceField
from django.forms.models import ModelForm
from django.db.models.fields.related import ManyToOneRel
from django.contrib.admin.sites import site
from django.utils.html import format_html
from django.utils.e... |
import paraview
import paraview.simple
import paraview.servermanager as sm
import PVBase
import core.modules
import core.modules.module_registry
from pvconfig import QPVConfigWindow
from core.modules.vistrails_module import new_module, Module, ModuleError
from core.modules.module_registry import (registry, add_module,
... |
"""Monte Carlo value estimation and control
An interesting observation - due to the winner's curse, if our rewards are noisy
we'll frequently overestimate state values.
"""
from typing import Dict, List, Tuple, TypeVar
import numpy as np
from rl_examples.discrete import DiscreteEnvironment, State
from rl_examples.t... |
from ...errors import TarskiError
from ...fstrips import FunctionalEffect
from ...fstrips.action import AdditiveActionCost, generate_zero_action_cost
from ...fstrips.representation import is_typed_problem
from ...syntax import Interval, CompoundTerm, Tautology, BuiltinFunctionSymbol
from ... import theories
from ...syn... |
# coding: utf8
# intente algo como
@auth.requires_login()
@auth.requires_membership('Teacher')
def index():
return dict()
@auth.requires_login()
@auth.requires_membership('Teacher')
def final_practice():
assignation = request.vars['assignation']
if not assignation: redirect(URL('courses'))
final_practi... |
"""Utility to convert .ipynb files and their widgets to publicly viewable,
interactive HTML pages.
This file defines the Exporter for the NbInteract conversion utility. After
installing this package, the user can run
nbinteract some_notebook.ipynb
To export their notebook.
The above command is an alias for:
... |
import sys
import pytest
from pytest import raises
from typedpy import Structure, AllOf, AnyOf, OneOf, Integer, String, Positive, Number, NotField, Field, Array
class Foo(Structure):
s = String
class Example(Structure):
_additionalProperties = True
_required = []
a = AllOf([Number(multiplesOf=5, m... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Wraps the splicer executable from
https://github.com/kurtsiefer/qcrypto/tree/master/remotecrypto.
Copyright (c) 2020 <NAME>, S-Fifteen Instruments Pte. Ltd.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated ... |
from __future__ import print_function
import re
import os
import errno
shortcuts = {}
# regex matching on key, replacement of groups on value
# implement any other shortcuts that you want to use
#sources
shortcuts["mp([0-9]*)"] = "sqlite_file:/afs/cern.ch/cms/CAF/CMSALCA/ALCA_TRACKERALIGN/MP/MPproduction/mp{0}/jobData... |
'''ResNet in PyTorch.
For Pre-activation ResNet, see 'preact_resnet.py'.
Reference:
[1] <NAME>, <NAME>, <NAME>, <NAME>
Deep Residual Learning for Image Recognition. arXiv:1512.03385
'''
import torch
import torch.nn as nn
import torch.nn.functional as F
from lib.normalize import Normalize
from torch.autograd impo... |
import py
from pypy.rpython.lltypesystem.llmemory import *
from pypy.annotation.model import SomeAddress, SomeChar
from pypy.translator.c.test.test_genc import compile
from pypy.rlib.objectmodel import free_non_gc_object
def test_null():
def f():
return NULL - NULL
fc = compile(f, [])
def test_convert... |
# coding: utf-8
from __future__ import absolute_import, division, print_function, unicode_literals
import itertools
import os
import shlex
import sys
from pip._internal.commands import create_command
from pip._internal.utils.misc import get_installed_distributions
from .. import click, sync
from .._compat import par... |
import json
import requests
import typing
import errors
class Route(object):
"""
Model object representing a route in the MBTA API.
"""
# Attributes to request from the API. We want this to be the minimum set of fields that we'll need to reduce
# network cost
fields = ['color', 'text_color', ... |
import copy
import numpy as np
from ...utils import common_utils
def random_flip_along_x(gt_boxes, points):
"""
沿着x轴随机翻转
Args:
gt_boxes: (N, 7 + C), [x, y, z, dx, dy, dz, heading, [vx], [vy]]
points: (M, 3 + C)
Returns:
"""
# 随机选择是否翻转
enable = np.random.choice([False, True... |
import get_file as f
import morpher as m
import tester as t
import detector
import get_file
import time
import os
d=detector.detector()
p=10
q1=20
q2=q1/20
def EvadeHC():
C=[]
bytes=get_file.get_bytes_batch()
print(len(bytes))
for bytez in bytes:
ti=time.time()
f = open('temp/' + str(ti)... |
from Bio import SeqIO
from src.inputValueException import InputValueException
import os
import pandas as pd
import re
# calculates kmer frequencies
# k: kmer-length
# peak: peak-position, where sequences should be aligned
# selected: input files
# no_sec_peak: status (-1= no structural data available, 0= False, 1= Tr... |
from dataclasses import dataclass, field
from unidecode import unidecode
class TabelaHadoopColunaException(ValueError):
pass
TIPOS_CONVERSAO = {
'C': 'VARCHAR',
'CHAR': 'VARCHAR',
'TEXTO': 'VARCHAR',
'Alfanumérico': 'VARCHAR',
'I': 'INTEGER',
'INTEIRO': 'INTEGER',
'N': 'NUMBER',
... |
"""
Input and output for geo-specific data formats.
"""
import numpy as np
import pandas as pd
import fiona
import geoviews as gv
import dask.dataframe as dd
import xarray as xr
import cartopy.crs as ccrs
from osgeo import gdal, osr
def get_sampling(bounds, shape):
"""
Generates x/y coordinates from bounds ... |
import math
import KratosMultiphysics
import KratosMultiphysics.FluidDynamicsApplication as KratosFluid
def Factory(settings, Model):
if(type(settings) != KratosMultiphysics.Parameters):
raise Exception("expected input shall be a Parameters object, encapsulating a json string")
return ApplyOutletProces... |
################################################################################
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this... |
# This is where to save audit trail stuff
import csv
import datetime
import os
import sqlite3
MESSAGE_ARCHIVE = 'archive/messages/'
BLOCKS_ARCHIVE = 'archive/blocks/'
JOURNAL_ARCHIVE = 'archive/journals.csv'
DATABASE_ARCHIVE = 'archive/farmxero.db'
def nanoFilToFil(nanoFil):
return nanoFil*(10**-18)
#Returns tot... |
"""
Pull method tools.
"""
from __future__ import absolute_import, division
import numpy as np
from pisa.utils.log import logging, set_verbosity
__all__ = []
__author__ = '<NAME>'
__license__ = '''Copyright (c) 2014-2020, The IceCube Collaboration
Licensed under the Apache License, Version 2.0 (the "License");... |
### Import Libraries ###
import os
import pickle
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import tensorflow as tf
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.models import Model
import tensorflow_addons as tfa
import... |
"""This module defines helpers for various endpoints."""
from decimal import Decimal
from typing import Callable
import codecs
import time
import uuid
from polaris import settings
import jwt
from jwt.exceptions import InvalidTokenError
from rest_framework import status
from rest_framework.response import Response
from... |
# this program trains, and then outputs the CNN used in the javascript script.
from tensorflow.examples.tutorials.mnist import input_data
from math import floor
mnist = input_data.read_data_sets('MNIST_data', one_hot=True)
import numpy as np
import struct
import math
import tensorflow as tf
sess = tf.InteractiveSessi... |
from . import base
class LogSection(base.SectionBase):
@base.returns_single_item(base.ResponseBase)
def level(self, subsystem: str, level: str, **kwargs: base.CommonArgs):
r"""Changes the logging output level for a given subsystem
**This API is subject to future change or removal!**
.. code-block:: pyth... |
# Copyright (c) 2021 <NAME>
# Copyright (c) 2018 <NAME>, <NAME>, <NAME>
#
# Licensed under the MIT license: https://opensource.org/licenses/MIT
# Permission is granted to use, copy, modify, and redistribute the work.
# Full license information available in the project LICENSE file.
import sys
from multiprocessing impo... |
#!/usr/bin/python3
# Demonstration of Simple Python Fixed-Point Module
# (C)Copyright 2006-2018, <NAME>
from __future__ import print_function
import argparse, time
from collections import OrderedDict
try:
import matplotlib, numpy
import matplotlib.pyplot as plt
HAVE_MATPLOTLIB = True
except ImportError:
... |
import random
import urllib.request as urllib_request
from django.conf import settings
from django.core.exceptions import ValidationError
from django.http import JsonResponse, HttpResponseRedirect
from django.template.response import TemplateResponse
from django.urls import reverse
from django.views.decorators.cache i... |
from typing import List
import tensorflow as tf
from tensorflow.contrib.layers import fully_connected
from hotpot.model import Prediction
from hotpot.nn.layers import SequencePredictionLayer, SequenceEncoder, FixedPredictionLayer, WeightedPredictionLayer, \
get_keras_initialization
class BinaryPrediction(Predic... |
from tkinter import *
win = Tk()
win.geometry("312x324")
win.resizable(0, 0)
win.title("Calculator")
def btn_click(item):
global expression
expression = expression + str(item)
input_text.set(expression)
def bt_clear():
global expression
expression = ""
input_text.set("")
def bt_equ... |
import uuid
from sqlalchemy.exc import IntegrityError
from api.utils import get_next_answer_set_pk
from .clr import configure_celery
from celery.schedules import crontab
from celery.task import periodic_task
from app.extensions import db
from pandas_datareader import data as pdr
import pandas as pd
from datetime imp... |
import os.path
import structures as st
import numpy as np
import itertools
import csv
def genFileName(fileName_base,catIndex):
return fileName_base+'_'+str(catIndex)+'.nextflix'
#write a category list into ncat files
def dump(fileName_base,cats):
#extracting some metadata
nChannels = len(cats[0][0].channel)
pLen... |
"""Support Peewee ORM with asyncio."""
import typing as t
from contextvars import ContextVar
from collections import deque
from inspect import isawaitable
import peewee as pw
from playhouse import db_url, pool, cockroachdb as crdb
from playhouse.sqlite_ext import SqliteExtDatabase
from ._compat import aio_wait, aio_s... |
#!/usr/bin/env python
###################################################################
#
# fos_restapi.py is based on fgt_api.py by <NAME>
# refactored and packaged with ftntlib by <NAME>
#
# A Python module to access the FortiOS REST API
#
###################################################################
import... |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
"""
Fields, parameters, and coercion
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Fields are typed slots which normalize and validate values passed to
them, facilitating much more robust Operation usage.
Parameters (aka params) are the values passed to a field. Ano... |
"""
Functional API endpoints separate from static views
"""
# stdlib
import json
import asyncio as aio
from functools import wraps
from pathlib import Path
from typing import Optional
# library
from quart import Response, request
from quart_openapi.cors import crossdomain
from voluptuous import Invalid, MultipleInval... |
from functools import lru_cache
import numpy as np
import torch as th
@lru_cache(maxsize=None)
def get_kernel_area(ker_loc=(0, 0), theta_c=np.pi / 12, theta=0):
"""
Helper function to identify kernel area after rotate on the sphere.
Assume circle center: $\mathbf{c}=(x_c, y_c, z_c)$, radius degree: $\thet... |
r"""
test module for pair counts in s and mu bins
"""
from __future__ import absolute_import, division, print_function, unicode_literals
import numpy as np
# load pair counters
from ..npairs_s_mu import npairs_s_mu
from ....mock_observables import npairs_3d
# load comparison simple pair counters
from ..pairs import s... |
from celery.task import task
from datetime import timedelta
from corehq import toggles
from corehq.apps.formplayer_api.smsforms.api import FormplayerInterface, TouchformsError
from corehq.apps.sms.api import MessageMetadata, send_sms_to_verified_number, send_sms
from corehq.apps.sms.models import PhoneNumber
from core... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2019/4/17 13:48
# @Author : <NAME>
# @File : db.py
# @Role : ORM
from sqlalchemy import Column, String, Integer, Text, DateTime, Boolean
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import class_mapper
from datetime impor... |
from sympy import Symbol, pi, symbols, Tuple, S, sqrt, asinh
from sympy.geometry import Curve, Line, Point, Ellipse, Ray, Segment, Circle, Polygon, RegularPolygon
from sympy.utilities.pytest import raises, slow
def test_curve():
x = Symbol('x', real=True)
s = Symbol('s')
z = Symbol('z')
# this curve ... |
import cv2
import numpy as np
import mxnet as mx
# import datetime
from skimage import transform as trans
import insightface
from . import img_helper
arcface_src = np.array([
[38.2946, 51.6963],
[73.5318, 51.5014],
[56.0252, 71.7366],
[41.5493, 92.3655],
[70.7299, 92.2041] ], dtype=np.float32 ) #... |
import collections
class BigInt:
def __init__(self):
self.number = [0]
def skim(self):
carrier = 0
for i in range(0, len(self.number)):
self.number[i] += carrier
head = self.number[i] % 10
carrier = (self.number[i] - head) / 10
self.number[i] = int(head)
while carrier != 0:
... |
import json
import logging
import os
import requests
import sys
import uuid
WIT_API_HOST = os.getenv('WIT_URL', 'https://api.wit.ai')
WIT_API_VERSION = os.getenv('WIT_API_VERSION', '20160516')
DEFAULT_MAX_STEPS = 5
INTERACTIVE_PROMPT = '> '
LEARN_MORE = 'Learn more at https://wit.ai/docs/quickstart'
class WitError(Ex... |
#from .input_parser import SimulationSetup
import numpy as np
import sys
import argparse
import mcdc_tnt
import matplotlib.pyplot as plt
def flatLinePlot(x, y, lab):
for i in range(y.size):
xx = x[i:i+2]
yy = [y[i], y[i]]
plt.plot(xx, yy, label=lab)
def run(input_file, output_file=None, ha... |
from __future__ import print_function
import numpy as np
def get_multi_metric(pred, gt, eval_label_list=None, rm_bg=False, verbose=True):
"""
implemented iou, dice, recall, precision metrics for each label of each instance in batch
:param pred: predicted(warpped) label map Bx....
:param gt: ground ... |
import multiprocessing
try:
from io import StringIO
except ImportError:
from io import StringIO
from contextlib import closing
import logging
import connection
from sink.backends.postgis import dump_schema, dump_indices, dump_statistics
from sink.backends.postgis_copy import dump_data
class CopyFromMessage(... |
import requests
import csv
import json
import time
import datetime
MAX_Page=500
cook='BIGipServerPool_app_chinabond_www=715265290.37151.0000; _pk_ses.1.0170=*; JSESSIONID=6DFA29606BC69B7DD491CA942FB2B940; _pk_id.1.0170=10c297c0f24dfa37.1546921738.4.1547037018.1547036258.'
headers = {
'Cookie':cook,
... |
import torch
import config
import torch.nn as nn
ALEXNET = "ALEXNET"
DENSENET121 = "DENSENET121"
VGG13 = "VGG13"
VGG13BN = "VGG13BN"
VGG11BN = 'VGG11BN'
RESNET50 = "RESNET50"
RESNET101 = "RESNET101"
INCEPTION_V3 = 'INVEPTION_V3'
# MVCNN functions
class conv_2d(nn.Module):
def __init__(self, in_ch, out_ch, kern... |
#!/usr/bin/env python3
import re
import socket
import ssl
import sys
import threading
import time
import config
import debug
import twitch
import utility
COMMANDS = [
# [r"!discord", "the official discord: ____"]
]
TWITCH_MSG = re.compile(r"(:tmi\.twitch\.tv \w+ \w+ :|:\w+.tmi\.twitch\.tv \w+ \w+ |:\w+!\w+@\w+\... |
import os
from typing import Optional
import numpy as np
import tensorflow as tf
from sklearn import preprocessing
from fedot.core.data.data import InputData, OutputData
from fedot.core.log import Log, default_log
from fedot.core.operations.evaluation. \
operation_implementations.implementation_interfaces import ... |
from manimlib.imports import *
from math import *
class fr(ThreeDScene):
CONFIG = {
"kone": None,
"rate": None,
"lines": [],
"pointt": None,
}
def construct(self):
axes = ThreeDAxes(z_min = 0, z_max = 8,)
circle = Circle()
sphere = ParametricSurface(
... |
import dgl
import math
import torch as th
import torch.nn as nn
import torch.nn.functional as F
from dgl.nn.pytorch import GraphConv, EdgeWeightNorm
from ..utils import transform_relation_graph_list
from . import BaseModel, register_model
@register_model('GTN')
class GTN(BaseModel):
@classmethod
def build_mod... |
import tensorflow as tf
import tensorflow.contrib.slim as slim
import slim_model
import data_loader
import numpy as np
import datetime
import time
import os
FLAGS = tf.app.flags.FLAGS
tf.app.flags.DEFINE_string('summary_dir', './summary', 'path to store summary')
tf.app.flags.DEFINE_string(
'CKPT_RES50', './pretr... |
import requests
import pymongo
import time
from multiprocessing import Pool
import requests
from fake_useragent import UserAgent
import time
from random import randint
API_KEY_TOKEN = 'TOKEN'
BASE_URL = "https://api.telegram.org/bot{}/sendMessage".format(API_KEY_TOKEN)
temp_user_agent = UserAgent(verify_ssl=Fal... |
from __future__ import (absolute_import, division,
print_function, unicode_literals)
from builtins import *
"""
qutip_conv
==========
QuTiP / tncontract conversions.
Functionality for converting between `qutip.Qobj` and `Tensor`.
Requires `qutip`.
"""
import numpy as np
import qutip as qt... |
import numpy as np
from collections import Counter
import sys
sys.path.append('../..')
from LIB.EVAL.meteor import Meteor
from LIB.EVAL.bleu import compute_bleu, diverse_bleu
from LIB.EVAL.rouge import compute_rouge_L
def convert_to_words(map_to_orig, question):
"""convert bert word pieces to normal tokens"""
... |
import argparse
import time
import torch
import torch.nn.functional as F
import torch.optim as optim
import numpy as np
from models import GCN
from sampler import Sampler_FastGCN, Sampler_ASGCN
from utils import load_data, get_batches, accuracy
from utils import sparse_mx_to_torch_sparse_tensor
def get_args():
... |
from typing import List, Tuple
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from IPython.display import display
from scipy import stats
def cat_data(df: pd.DataFrame, col_name: str) -> None:
"""Display some useful attributes of a categorical feature."""
print(f"Data type: {df[col_na... |
# SPDX-FileCopyrightText: 2014-2020 <NAME>
#
# SPDX-License-Identifier: MIT
# -*- coding: utf-8 -*-
from __future__ import division, print_function
import pytest
import sys
import numpy as np
from symfit import (
Fit, Parameter, Variable, Model, GradientModel
)
from symfit.core.minimizers import BFGS, Differenti... |
"""Group of functions which produce heatmap of accumulated frequency counts.
To run these functions the user will need a videofile (.tif format).
WARNING: Extremely large video files (>1500 frames) or videos with
high pixel resolution (512x512 array or greater) may take a couple of
minutes to run depending on your com... |
import utils
class Prob(object):
"""Problem space with layer dimension, stride and dilation defined.
Attributes:
prob: A layer dimemsion dictionary.
R, S represent the weight filter width and height.
P, Q represent the output feature map width and height.
C re... |
"""
Shogun demo
<NAME>
"""
import numpy as np
import matplotlib as mpl
import pylab
import util
from scipy import linalg
from modshogun import QDA
from modshogun import RealFeatures, MulticlassLabels
# colormap
cmap = mpl.colors.LinearSegmentedColormap('color_classes',
{'red': [(0, 1, 1),
(1, .7, .7)],
'... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Date : 2018-11-05 11:30:01
# @Author : <NAME> (<EMAIL>)
# @Link : http://cs.ucsb.edu/~bolunwang
import os
import time
import numpy as np
import random
import tensorflow
from tensorflow import set_random_seed
random.seed(123)
np.random.seed(123)
set_random_seed(1... |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import json
import os
import yaml
from redis import Redis
"""Load from files"""
def load_cluster_details(cluster_name: str) -> dict:
with open(os.path.expanduser(f"~/.maro/clusters/{cluster_name}/details.yml"), 'r') as fr:
cluste... |
"""
.. module:: cosmo_hammer
:synopsis: Invoke the Cosmo Hammer
.. moduleauthor:: <NAME> <<EMAIL>>
This module interface Monte Python with the CosmoHammer, available
`publicly <http://www.astro.ethz.ch/refregier/research/Software/cosmohammer>`_
and developped by <NAME> and <NAME>, who helped me a lot
creating this... |
"""
Copyright (c) Microsoft Corporation.
Licensed under the MIT license.
some functions are modified from HuggingFace
(https://github.com/huggingface/transformers)
copied/modified from HERO
(https://github.com/linjieli222/HERO)
"""
import torch
from torch import nn
import logging
logger = logging.getLogger(__name__)
... |
import math
from datetime import datetime
try:
from zoneinfo import ZoneInfo
except ImportError:
from backports.zoneinfo import ZoneInfo
TIME_UNIT_MAP = {
'seconds': {
'label': 's',
'divisor': 1,
'threshold': 60,
},
'minutes': {
'label': 'm',
'divisor': 60,
... |
# Copyright 2013, Couchbase, Inc.
# All Rights Reserved
#
# Licensed under the Apache License, Version 2.0 (the "License")
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law... |
import transformers
import tensorflow as tf
import os
import numpy as np
import argparse
from datetime import datetime
def _int64_feature(value):
"""Wrapper for inserting int64 features into Example proto."""
if not isinstance(value, list):
value = [value]
return tf.train.Feature(int64_list=tf.tra... |
from copy import deepcopy
from sklearn.cross_validation import StratifiedKFold, StratifiedShuffleSplit
from xgboost.sklearn import XGBClassifier
import numpy as np
N_FOLDS = 5
CV_NUM = 1
EVAL_METRIC = "error"
EARLY_STOPPING_ROUNDS = 100
N_ESTIMATORS = 1000000
OBJECTIVE = "binary:logistic"
GET_BEST_SCORE_INDEX = np.arg... |
import numpy as np
import math
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from src.coordinate_system_transformations import transform_2D_to_3D
from src.calculate_optic_axis import calculate_optic_axis_unit_vector, calculate_r, calculate_p
from src.calculate_visual_axis import calculate_vi... |
import gc
import syslog
import logging
import importlib.util
import regex
from Global import *
import TaskScheduling
def GetModule(PATH):
_spec= importlib.util.spec_from_file_location("MOD", PATH)
_result= importlib.util.module_from_spec(_spec)
_spec.loader.exec_module(_result)
return _result
def... |
"""
examples/lego-3d.py
Copyright (c) 2020, <NAME> - <EMAIL>
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice, this
lis... |
from __future__ import print_function
import json
import kalman_filter
import param_estimation
import os.path
import numpy
import time
def fit_and_filter_from_dir(dirname, trap, method='em', smooth_param=150.0):
# data_filename = '../examples/data/2019_05_08_experiment/all_traps_final_analysis_output.json'
#... |
"""Flow instructions to be executed.
The flow instructions associated with a flow table entry are executed when a
flow matches the entry.
"""
# System imports
from enum import IntEnum
# Local source tree imports
from pyof.foundation.base import GenericStruct
from pyof.foundation.basic_types import (
FixedTypeList... |
# Copyright 2014 Huawei Technologies Co. Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed... |
import json
import csv
import re
from utils import untokenize, convert_REC_ID_to_DD_ID
from tqdm import tqdm
# Load original DailyDialog data
DD_data = json.load(open('TLiDB_DailyDialog/TLiDB_DailyDialog.json', 'r'))
def get_DD_datum_from_RECCON_ID(REC_ID, original_DD_data):
id = re.search(f"dailydialog_(.*?)_utt... |
# Some useful packages
from typing import Union, Tuple
import time
import numpy as np
import pandas as pd
import pprint
# Tensorflow
import tensorflow as tf
import tensorflow_datasets as tfds
# Importing the HPOptimizer and the RandomHpSearch from the AutoMLpy package.
from AutoMLpy import HpOptimizer, RandomHpSearch... |
# Copyright 2017 The Sonnet Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... |
import copy
from argparse import Namespace
from typing import List
from ... import __default_host__
from ...enums import SchedulerType, SocketType, PeaRoleType
from ...helper import random_port, get_random_identity, get_public_ip, get_internal_ip, is_valid_local_config_source
def _set_peas_args(args: Namespace, head... |
#!/bin/python3.8
"""
DecisionTreeClassifier is a class capable of performing multi-class classification on a dataset.
As with other classifiers, DecisionTreeClassifier takes as input two arrays: an array X, sparse
or dense, of shape(n_samples, n_features) holding the training samples, and an array Y of int... |
#!/usr/bin/python3
# Posix and Windows
# Version 0.9, Python 3.6, 2018-07-03, <NAME>
import sys
import os
import argparse
from fnmatch import fnmatch
FILE_CHUNK_SIZE = 512*1024
def file_content_diff(fno, fnb):
with open(fno, 'rb') as f1:
with open(fnb, 'rb') as f2:
while True:
b1 = f1.... |
import argparse
import random
from setup_dataset_utils import *
def get_ecef_origin():
"""Shift the origin to make the value of coordinates in ECEF smaller and increase training stability"""
# Warning: this is dataset specific!
ori_lon, ori_lat, ori_alt = 7.065, 46.3705, 1410
ori_x, ori_y, ori_z = pyp... |
import os
import re
# Dictionary to get a config class based on key. This is automatically
# populated on class creation by ConfigMeta. Keys are the name of the class
# before Config suffix in uppercase
CONFIGS = {}
def first_key(d):
"""
Gets the first key of a dictionary
:param d: Dictionary
:return... |
#
# This file is part of pyasn1-modules software.
#
# Created by <NAME>
# Copyright (c) 2019, Vigil Security, LLC
# License: http://snmplabs.com/pyasn1/license.html
#
import sys
from pyasn1.codec.der.decoder import decode as der_decode
from pyasn1.codec.der.encoder import encode as der_encode
from pyasn1_modules imp... |
import torch
import torch.nn as nn
from math import log2
from utils import *
class Generator(nn.Module):
def __init__(self, opt):
super(Generator, self).__init__()
act_down = nn.LeakyReLU(0.2, inplace=True)
act_up = nn.ReLU(inplace=True)
image_height = opt.image_height
inpu... |
#!/usr/bin/python -OOOO
# vim: set fileencoding=utf8 shiftwidth=4 tabstop=4 textwidth=80 foldmethod=marker :
# Copyright (c) 2010, <NAME>. All rights reserved.
# For licensing, see LICENSE file included in the package.
"""
BSON serialization and deserialization logic.
Specifications taken from: http://bsonspec.org/#/sp... |
# Copyright 2017 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in wri... |
import os
import pickle
from typing import List, Tuple
import numpy as np
import torch
import torchvision.transforms as transforms
from PIL import Image
from randaugment import RandAugment # https://github.com/jizongFox/pytorch-randaugment
from torch.utils.data import DataLoader, Dataset
class CIFAR10(Dataset):
... |
from model import create_model
from constants import BOARD_DIM, MAX_TRAINING_SIZE, NO_OF_GAMES, SAVE_DATA_EVERY, SELF_PLAY_C_PUCT, SELF_PLAY_MCTS_ITERS, UPDATE_MODEL_EVERY
from helper_methods import dihedral_trans, load_model, load_training_data
from apple_chess import Board
from model_path_management import best_m... |
import tensorflow as tf
import tensorflow.keras as keras
from tensorflow.keras import layers
from tf_package.ConvModel.encoder import vgg16, resnet50
def crop(o1, o2, i):
"""裁剪o1和o2至相同的尺寸，裁剪的宽和高取两个特征图的最小值"""
o_shape2 = keras.Model(i, o2).output_shape
output_height2 = o_shape2[1]
output_wid... |
import importlib
import inspect
import itertools
import warnings
from typing import Any, Callable, Dict, Tuple, Union
from torch import _C
from torch.onnx import _constants, errors
__all__ = [
"get_op_supported_version",
"get_ops_in_version",
"get_registered_op",
"is_registered_op",
"is_registered... |
import click
import json
import pandas as pd
from requests.exceptions import HTTPError
from os import environ
from os.path import join, dirname
from os import makedirs
from .. import (
Knex,
User,
Organization,
)
from .utils import use_common_state
@click.group('upload')
def cli_upload():
pass
ov... |
# Copyright 2018 The TensorFlow Probability Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law o... |
from django.views.generic import TemplateView
from django.shortcuts import render, redirect, get_object_or_404
from django.http import JsonResponse
from django.template.loader import render_to_string
import win32com.client, datetime, pythoncom, os, re, openpyxl
from django.utils import timezone
from payments.models im... |
"""Tests for the Roku component."""
import re
from socket import gaierror as SocketGIAError
from homeassistant.components.roku.const import DOMAIN
from homeassistant.components.ssdp import (
ATTR_SSDP_LOCATION,
ATTR_UPNP_FRIENDLY_NAME,
ATTR_UPNP_SERIAL,
)
from homeassistant.const import CONF_HOST, CONF_ID,... |
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