text stringlengths 3.07k 22.1k |
|---|
from ultrasonic import steph
distanceFromStart=0
possibleDogLocations=[True, True, True, False]
oldDistances=[]
def moveForward(distance):
global distanceFromStart
global moved
moved=True
distanceFromStart+=distance
input()
print(distanceFromStart)
#this is the value that will be returned when added to the... |
import functools
import time
import numpy as np
from numba import jit
np_nanmean = np.nanmean
np_nansum = np.nansum
def timer(func):
@functools.wraps(func)
def wrapper_timer(*args, **kwargs):
tic = time.perf_counter()
value = func(*args, **kwargs)
toc = time.perf_counter()
... |
import numpy as np
import functools
from tempfile import mkdtemp
import sys
sys.setrecursionlimit(100000)
from joblib.memory import Memory
cache_dir = mkdtemp()
memory = Memory(location=cache_dir, verbose=0)
# Old solution
# @memory.cache
def cut_rope(cs, T):
# print("-" *8 + "\nT: {}.".format(T))
# print("... |
"""
Capstone Project. Code to run on a LAPTOP (NOT the robot).
Displays the Graphical User Interface (GUI) and communicates with the robot.
Authors: Your professors (for the framework)
and <NAME>.
Winter term, 2018-2019.
"""
import mqtt_remote_method_calls as com
import tkinter
from tkinter import ttk
i... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Aug 22 21:31:09 2019
App: I-Spy-P
Use: Search IP within .txt documents, identify IPv4,
allow user to find particular IP, get GeoID from IP,
and RDAP/WhoIS from IP based on Queries
@author: beehive
"""
#/home/beehive/Documents/I-Spy-P/data/list_of_ip... |
#----------------------------------------------------------------------*/influxdb_client
# 2022.03.11 UECS
# sudo apt-get install python3-pip -y
# sudo apt-get install python3-pandas -y
# sudo apt-get install python3-influxdb -y
# sudo pip3 install influxdb-client
# sudo pip3 install xmltodict
#-----------------------... |
"""
Name - <NAME>
Lab Assignment 3
Roll No - B19130
Mobile No - +91-9351159849
"""
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.metrics import mean_squared_error
from sklearn import decomposition
# import
data = pd.read_csv('landslide_data3.csv') # loading
d... |
import torch
import json
from torch.utils.data import DataLoader, Dataset
import os
import sys
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__),
'../')))
from data_retriever import MentionSet
from reader import get_predicts
import math
def proc... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Documentation Build Configuration
Django Improved User documentation build configuration file, created by
sphinx-quickstart on Thu Aug 17 10:44:16 2017.
This file is execfile()d with the current directory set to its
containing dir.
Note that not all possible configur... |
"""
This script contains functions needed for the core functionality of gitcrawl
"""
import os
import sys
import re
import subprocess
import yaml
import json
from tqdm import tqdm
import time
import pickle
from .helpers import extract_keys, enumerate_installation_candidates, menu, choose_custom_name
def findimports_to... |
#import AYS_Environment as ays_env
import c_global.cG_LAGTPKS_Environment as c_global
import numpy as np
import pandas as pd
import sys,os
import matplotlib.pyplot as plt
from matplotlib.offsetbox import AnchoredText
pars=dict( Sigma = 1.5 * 1e8,
Cstar=5500,
a0=0.03,
aT=3.2*1e3,
... |
"""
Modifed from the original STM code https://github.com/seoungwugoh/STM
"""
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from model.propagation.modules import *
class Decoder(nn.Module):
def __init__(self):
super().__init__()
self.compress = ResBlock(1024, 512... |
import torch
import torch.nn as nn
import torch.nn.init as init
import torch.nn.functional as F
from torch.nn.parameter import Parameter
class BatchMultiHeadGraphAttention(nn.Module):
def __init__(self, n_head, f_in, f_out, attn_dropout, attn_mask=True, bias=True, attn_type="aa"):
super(BatchMultiHeadGrap... |
#!/usr/bin/env python
#===============================================================================
# @file pompcli.py
#
# @author <EMAIL>
#
# Copyright (c) 2014 Parrot S.A.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the ... |
from __future__ import annotations
import unittest
from unittest.mock import patch
from typing import Dict, Optional
from app import app
from geopy.exc import GeopyError, ConfigurationError, GeocoderServiceError
from mkad_blueprint.geo_functions import (
default_geocoder,
yandex_geocoder,
geopy_geocoder,
... |
import subprocess
import os.path
import shutil
import time
import json
from gii.core import *
from gii.qt import *
from gii.qt.IconCache import getIcon
from gii.qt.helpers import addWidgetWithLayout, QColorF, unpackQColor
from gii.qt.dialogs import requestString, alertMessage, requestColor
from ... |
import numpy as np
from matlearn.evaluation import *
from matlearn._errors import NotTrainingError
from matlearn.preprocessing import split_train_test,polynomial
#########################################################################################################
def activation_function(z, type, derivative=False)... |
#!/bin/env python
#
# Advent of Code 2020
# Day 16
#
# author: <NAME>
# e-mail: <EMAIL>
#
import sys
from argparse import ArgumentParser
from pathlib import Path
import numpy as np
from scipy.optimize import linear_sum_assignment
import pytest
@pytest.fixture
def example_data():
test_data = """class: 1-3 or 5... |
from typing import Optional, Tuple
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.axes import Axes
from matplotlib.figure import Figure
__all__ = ["reliability_diagram", "reliability_curve"]
def reliability_diagram(
accs: np.array,
confs: np.array,
left_bins: np.array,
num_classe... |
import glob
import numpy as np
import sys
import pandas as pd
sys.path.append('./support_files/')
import summarise_bins
def load_individual_bin_summaries():
return pd.read_csv('support_files/bin_summary.csv')
def load_bin_length_summary():
return pd.read_csv('support_files/bin_stats.tsv', sep ='\t')
def... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Chapter 8: Variational Autoencoders
Github directory: https://github.com/jgvfwstone/DeepLearningEngines/tree/master/DeepLearningEnginesCode/Python/Ch08_VariationalAutoencoder
Author: <NAME>, most comments by authors, with a few added comments by JVStone
Date created: 2... |
import helper
from PIL import Image
from torchvision import datasets, transforms, models
import torch
import matplotlib.pyplot as plt
import numpy as np
from torch import optim
import time
import json
def get_train_valid_test_loader(data_dir, gpu):
train_dir = data_dir + '/train'
valid_dir = data_dir + '/val... |
import heapq
import wx
import os
from numpy import *
HuffAlphabeth = []
LZWAlphabeth = ""
class Example(wx.Frame):
def __init__(self, *args, **kwargs):
super(Example, self).__init__(*args, **kwargs)
self.args = args
self.kwargs = kwargs
self.fname=""
self.InitUI() ... |
"""
Algorithms and containers mimicking FORTRAN-style behaviour. This allows
interoperability with - or straightforward implementation of - algorithms
originally written using Fortran or MATLAB.
Examples
--------
Create a 4x4 array using Fibonacci numbers:
>>> fib_mat = fortran_array([[1, 1, 2, 3],
... ... |
# -*- coding: utf-8 -*-
"""
Zegami Ltd.
Apache 2.0
"""
from io import BytesIO
import pandas as pd
from PIL import Image
from time import time
from concurrent.futures import ThreadPoolExecutor, as_completed
from .source import Source
class Collection():
@staticmethod
def _construct_collection(client, wo... |
"""
ROS Code Commands
This file contains all the commands in ROS Code
"""
import warnings
import keyword
import importlib
import string
import pprint
import loremipsum
import colour
from.roserrors import*
def shellinput(initialtext='>> ',splitpart=' '):
try:
str(initialtext)
except BaseException:
raise Conversion... |
""" SDFG nesting transformation. """
from copy import deepcopy as dc
import networkx as nx
import dace
from dace import data as dt, memlet, sdfg as sd, subsets, Memlet, EmptyMemlet
from dace.graph import edges, nodes, nxutil
from dace.transformation import pattern_matching
from dace.properties import make_properties,... |
import os
import argparse
import random
import time
import numpy as np
import scipy.sparse as sp
import torch
import torch.nn as nn
import torch.optim as optim
from script import dataloader, utility, earlystopping
from model import models
import nni
def set_env(seed):
# Set available CUDA devices
# This o... |
import numpy as np
"""
Mapping SIP to Bin
"""
#Mapping of SIP ensemble onto a bin grid
#SIP ensemble (of one realisation) with nr_SIPs SIP defined by nEK_sip and mEK_sip
#Properties of the bin grid are specified by n10_plot, r10_plot, min10_plot
def MapSIPBin(nEK_sip,mEK_sip,nr_SIPs,n10,r10,min10):
n= n10 * r10
... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Sorting gr3 output from SCHISM in pythonic way. The script is intended to sort
a lot of max elevation results and sorting them at node based on the inundation
value.
This script was developed to tackle the problem of sorting the storm track
developed in Kerry Hydro sim... |
import math
import taichi as ti
import numpy as np
objects = []
springs = []
l_thigh_init_ang = 10
l_calf_init_ang = -10
r_thigh_init_ang = 10
r_calf_init_ang = -10
initHeight = 0.15
hip_pos = [0.3, 0.5 + initHeight]
thigh_half_length = 0.11
calf_half_length = 0.11
foot_half_length = 0.08
half_hip_length = 0.08
d... |
#!/usr/bin/python
DOCUMENTATION = """
---
module: comware_ospf
short_description: Manage ospf
description:
-
version_added: 1.0
category: Feature (RW)
author: hanyangyang
notes:
options:
ospfname:
description:
- Instance name.(1~65535)
required: true
default: null
... |
# Copyright (C) GRyCAP - I3M - UPV
#
# 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 writing... |
# -*- coding: utf-8 -*-
# MIT License
# Copyright (c) 2021 Arthur
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy... |
import numpy as np
import os
def vol(ftraj='atoms.traj'):
from ase.io import read
a=read(ftraj,':')
v=a[-1].get_volume()
with open('vol','w') as f:
f.write(str(v))
return v
# do eos fitting and Debye model for one functional and save results in files
def eos_gpaw(ev='e-v.dat',struc='rel.... |
#!/usr/bin/env python
"""
A tool to analyze files of shape (16, 1, 67108864) or similarly short-but-very-wide dimensions.
Reports which columns are "interesting".
"""
import cp
import json
import os
import random
import sys
import time
from h5_file import H5File
from hit_info import group_hit_windows
from hit_map imp... |
#!/usr/bin/python
# -*- coding: utf-8 -*-
#
# Copyright (C) 2018 Huawei
# GNU General Public License v3.0+ (see COPYING or
# https://www.gnu.org/licenses/gpl-3.0.txt)
from __future__ import absolute_import, division, print_function
__metaclass__ = type
#################################################################... |
from numpy.core.fromnumeric import size
import pandas as pd
import numpy as np
import torch
#file = "conceptnet-5.7.0-rel.csv"
def conceptnet_to_dict(csv_path):
data = pd.read_csv(csv_path, delimiter=',')
data['start'] = data['start'].apply(lambda str: str.split("en/")[1].split("/")[0])
data['end']... |
import socket
from datetime import timedelta
from email.utils import parsedate_to_datetime
import requests
from azure.identity import ClientSecretCredential
from azure.mgmt.cdn import CdnManagementClient
from azure.mgmt.cdn.models import PurgeParameters
from celery.utils.log import get_task_logger
from django.conf imp... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# from "Starfield" (<NAME>)
# Video: https://youtu.be/17WoOqgXsRM
import sys
import os
from PyQt5.QtWidgets import *
from PyQt5.QtGui import *
from PyQt5.QtCore import *
import random
def mapFromTo(x, a, b, c, d):
"""map() function of javascript"""
y = (float(x... |
import numpy as np
from constants import cgs_constants
from numpy import exp, sin, einsum
pi = np.pi
q = cgs_constants['q']
c = cgs_constants['c']
## Convert units to cgs from mks
class field_solver_2D(object):
def __init__(self):
self.name = '2-d electrostatic field solver'
def compute_mode_coefficients(s... |
#Begin Imports
import sys
import math
#End Imports
#Begin Util Code
def log(x):
print(x, file=sys.stderr)
# Cells
FLOOR_CELL = "."
EMPTY_TABLE = "#"
DISHWASHER = "D"
WINDOW = "W"
BLUEBERRIES_CRATE = "B"
ICE_CREAM_CRATE = "I"
STRAWBERRIES_CRATE = "S"
DOUGH_CRATE = "H"
CHOPPED_BOARD = "C"
OVEN = "O"
# Items
NO... |
# Copyright (c) 2012, GPy authors (see AUTHORS.txt).
# Licensed under the BSD 3-clause license (see LICENSE.txt)
import numpy as np
from ..core.parameterization import Parameterized, Param
from paramz.transformations import Logexp
import sys
class WarpingFunction(Parameterized):
"""
abstract function for war... |
import sys
import toml
import collections
import math
from dataclasses import dataclass
sys.path.insert(0, "../wrapper")
from wave import Wave
from asv import Asv_propeller, Asv_specification, Asv_dynamics, Asv
from geometry import Dimensions
from rudder_controller_pid import Rudder_controller
from cyclone import Cyclo... |
"""Create a tessellation from a list of qubits."""
from __future__ import annotations
from typing import List, Callable, Tuple, Iterable
import itertools
import functools
from . import exceptions
from .vector import Vector
class Tessellation:
"""Describes how to partition the lattice into cells.
This is a l... |
# -*- coding: utf-8 -*-
###########################################################################
## Python code generated with wxFormBuilder (version Oct 26 2018)
## http://www.wxformbuilder.org/
##
## PLEASE DO *NOT* EDIT THIS FILE!
###########################################################################
impor... |
# coding: utf-8
"""
サービスを実装する
"""
import datetime
from repository import openweathermap
from service import graph_creator
from service import slack_uploader
from service import slack_messenger
from service import os_manager
import json
def make_help_message():
attachments = [{
'fallback': 'tenkibot',
... |
from __future__ import division, print_function, absolute_import
import time
import datetime
import sys
import traceback
import socket
import threading
import os
import signal
import atexit
import platform
import random
import math
from .runtime import min_version, runtime_info, register_signal
from .utils import tim... |
from __future__ import division, print_function, unicode_literals
import functools
import tensorflow as tf
tf.logging.set_verbosity(tf.logging.ERROR) # Remove tf warnings
import numpy as np
from time import time
import os, shutil, random
NUM_CLASSES = 10
def CNN_withnoise(images, param_placeholders, scopes_list,laye... |
import sys
from argparse import ArgumentParser
from importlib import import_module
from typing import Any
from .recorder import TestRecorder, DefaultTestRecorder
from .runner import TestRunner, DefaultTestRunner, StopStrategy, RetryStrategy
from .task import TestTask, DefaultTestTask
class TestAuto:
def __init_... |
from typing import Dict
from typing import List
from typing import Optional
from typing import Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
from tkdet.config import configurable
from tkdet.layers import ShapeSpec
from tkdet.layers import cat
from tkdet.layers import smooth_l1_loss
from tkd... |
from tkinter import *
from copy import deepcopy
import random
class Move:
def __init__(self, x, y, p):
self.x = x
self.y = y
self.p = p
class Moves:
def __init__(self):
self.moves = []
def add(self, move: Move):
self.moves.append(move)
def getMoves(self):
... |
import numpy as np
import pandas as pd
from pandasgui import show
class CO2_Simulation(object):
def __init__(self, *args, **kwargs):
self.name = kwargs.get('name', f'Unnamed Simulation') # zone volume in m³
self.volume = kwargs.get('volume', 5 * 5 * 3) # zone... |
from collections import OrderedDict
import torch
from torchvision import models
from torchvision.ops import FeaturePyramidNetwork
from dvmvs.config import Config
from dvmvs.convlstm import MVSLayernormConvLSTMCell
from dvmvs.layers import conv_layer, depth_layer_3x3
fpn_output_channels = 32
hyper_channels = 32
cla... |
import tensorflow as tf
import tensorflow.contrib.slim as slim
import tensorflow.contrib.slim.nets as nets
import numpy as np
import os
import PIL
import matplotlib.pyplot as plt
os.environ["CUDA_VISIBLE_DEVICES"] = "3,2"
plt.switch_backend('agg')
_BATCH_SIZE = 50
X = tf.placeholder(tf.float32, [_BATCH_SIZE, 299, 299... |
#!/usr/bin/env python3
# Copyright (c) 2019 Cisco and/or its affiliates.
# 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... |
"""
Copyright 2017-2018 yhenon (https://github.com/yhenon/)
Copyright 2017-2018 Fizyr (https://fizyr.com)
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-... |
#!/usr/bin/env python
# coding: utf-8 (see https://www.python.org/dev/peps/pep-0263/)
from __future__ import unicode_literals
from __future__ import print_function
import argparse
import sys
import os
from operator import itemgetter
# Django imports
from django.core.management.base import BaseCommand, CommandError
fr... |
from typing import Tuple, Union, Iterable, List, Callable, Dict, Optional
import time
from abc import abstractmethod
import numpy as np
from tqdm import tqdm
from nnuncert.models.dnnc._sampling import genbeta, genbeta2, gentau, gentau2, genlambda
from nnuncert.models.dnnc._func_deriv import compdS, compdS2
from nnun... |
import bpy
import os
import re
from . import utils
from itertools import chain
from importlib import import_module
# (Pattern, Prefix, Fade, Outline, DoubleSided, Normal)
def gen_mat_pattern(pattern, fade=False, outline=False, doubleSided=False, prefix=None, normal=False):
return (re.compile(pattern), prefix, fade, ... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Nov 2 15:25:17 2018
@author: chris
"""
#%%
import os
base_path = 'C:\\Users\\sheld\\Desktop\\比赛\\knowledge_graph'
file_path = os.path.join(base_path, 'rawdata', 'ruijin_round1_train2_20181022', '0.txt')
file_ano_path = os.path.join(base_path, 'rawdata... |
# Copyright (c) 2015 OpenStack Foundation.
# 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... |
import maml_rl.envs
import gym
import numpy as np
import torch
import json
import sys
import pickle
import time
import timeit
from maml_rl.metalearner import MetaLearner
from maml_rl.policies import CategoricalMLPPolicy, NormalMLPPolicy
from maml_rl.baseline import LinearFeatureBaseline
from maml_rl.sampler import Batc... |
from flask import (Flask, Response, request, render_template, make_response,
redirect)
from flask_restful import Api, Resource, reqparse, abort
import json
import string
import random
# from functools import wraps
from datetime import datetime
# parse new archive post request
archives_parser = reqp... |
from os import environ
from copy import deepcopy
from pytest import fixture, raises
from time import sleep
from time import time
import docker
from .brain import r
from .brain.controller import plugins
CLIENT = docker.from_env()
HARNESS_ID = "111-AAA"
HARNESS_NAME = "Harness"
TEST_PLUGIN_DATA = {
"id": HARNESS_I... |
import logging
import sys
from collections import OrderedDict
import torch
import torchvision.models as models
from torch.utils import model_zoo
from torchvision.models.resnet import BasicBlock, model_urls, Bottleneck
import torch.nn.functional as F
import skeleton
import torch.nn as nn
import math
import pdb
from to... |
import torch
from torch import Tensor
from torch.nn import Linear, BatchNorm1d, Module, Sequential, ReLU
from torch_geometric.nn import MessagePassing, global_mean_pool
from torch_geometric.utils import dense_to_sparse, remove_self_loops
import torch_geometric.transforms as T
from torch_geometric.datasets import QM9
fr... |
import OpenGL.GL as GL
import pygame
import numpy
import math
vertex_shader = """
#version 330
in vec2 position;
in vec2 coord;
uniform mat4 model;
uniform mat4 view;
uniform mat4 projection;
out vec2 texcoord;
void main()
{
vec4 pos = vec4(position.xy, 1.0f, 1.0f);
gl_Position = projection * view * model ... |
from base import *
def analyse_performance_with_stimuli_tonefreq(analysis, estimator,
tonefreqkey='tonefreq',
fraction=1.0):
sn_level_range = analysis.moresettings['sn_level_range']
bins = analysis.moresettings['tonefre... |
# parser for Structure_Info.txt files
# author: <NAME>
#
# i'm calling sections and headers ('---...---' and '[...]') as contexts (ctx)
# every context is given a unique name (heading, unique id among headings)
# useful info is available in:
# 1. ctx_dict: a dict from context name to a dict of feature names and values
... |
import re
import os
import sys
import json
import shlex
import logging
import argparse
from evaluators import SomeEvaluator as Some
from evaluators import AllEvaluator as All
from comparers import *
logging.basicConfig()
class Queue:
def __init__(self, init=None):
self._items = init if init is not None ... |
#!/usr/bin/python3
# first pass assembles everything but does not resolve labels
# second pass just adds in the label vales
#
# must throw an error on all errors with a useful error message (file, lineno, line)
#
## currently used
# lab:
# var[n]:
# var[]: 1 2 3 4
# var[n]: 1 2 3 4
# :const
#
## required extensions
# ... |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
import numpy as np
import math, os, pdb, sys, glob
from os import path as osp
from pathlib import Path
lib_dir = (Path(__f... |
# From notion.collection
from typing import Callable, List
import re
from notion.block import CollectionViewBlock, TextBlock
TAB = 2
class PageBaseBlock:
def __init__(self, _id="unknown", _type="unknown", _children=[]):
self.id = _id
self.type = _type
self.children: List[PageBaseBlock] =... |
# -*- coding: utf-8 -*-
#
# This file is part of Karesansui.
#
# Copyright (C) 2009-2012 HDE, Inc.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without lim... |
import hmac
import base64
import re
import string
import json
import logging
from urllib.parse import urlparse
from time import sleep
from ulauncher.api.client.Extension import Extension
from ulauncher.api.client.EventListener import EventListener
from ulauncher.api.shared.action.CopyToClipboardAction import CopyToClip... |
import gym
import numpy as np
from vel.exceptions import VelException
def take_along_axis(large_array, indexes):
""" Take along axis """
# Reshape indexes into the right shape
if len(large_array.shape) > len(indexes.shape):
indexes = indexes.reshape(indexes.shape + tuple([1] * (len(large_array.sh... |
"""optimize over a network structure."""
import argparse
import logging
import os
import copy
import matplotlib.pyplot as plt
import numpy as np
import open3d as o3d
import pandas as pd
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from model import Neural_Prior
import config
from data i... |
from django.contrib.auth import get_user_model
from django.db.models import Prefetch, Q
from django.http import HttpResponseForbidden
from django.shortcuts import get_object_or_404
from django_filters.rest_framework import DjangoFilterBackend
from rest_framework import generics, viewsets
from rest_framework.decorators ... |
import sys
import pprint
import cProfile
import matplotlib.pyplot as plt
import numpy as np
import radical.utils as ru
import radical.pilot as rp
import radical.analytics as ra
from radical.utils.profile import *
from radical.pilot.states import *
# -----------------------------------------... |
from django.db.models.fields.related import ManyToManyField
from django.forms.models import ModelMultipleChoiceField
from _helpers.models import areas_ar_en, areas_en
from typing import Any, List, Optional, Sequence, Tuple
from django import forms
from django.contrib import admin
from django.contrib.admin.options impor... |
r'''
In practice, :class:`~pyop.linop.LinearOperator` instances composed of distinct
sub-blocks are common. In general, access to both the constituent operators and
larger operators is desired. The :mod:`~pyop.block` module provides several
functions to help build block instances of :class:`~pyop.linop.LinearOperator`... |
import yaml
import argparse
import os
from os import path as osp
import argparse
import joblib
from time import sleep
import numpy as np
import rlkit.torch.pytorch_util as ptu
from rlkit.launchers.launcher_util import setup_logger, set_seed
from rlkit.torch.sac.policies import PostCondMLPPolicyWrapper
from rlkit.dat... |
import unittest
from simulator.rate_player import SinglePlayerRating
from simulator.game_simulation import GameSimulation
from simulator.playoff_simulation import *
from simulator.rank_teams import rank_team_all, ranking_teams, sort_win_data
from simulator.season_simulation import run_simulation, initialize_playoff
... |
import os
import os.path as osp
import pickle
import json
import matplotlib.pyplot as plt
from scipy.ndimage import gaussian_filter1d
import copy
import numpy as np
from eval import voc_eval
sourcedir = '/grogu/user/jianrenw/data/OAK_LABEL_N'
annodir = '/grogu/user/jianrenw/data/OAK_TEST/Label'
config... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.