def t3(A=None, B=None, C=None): A = init(A,i,j) B = init(B,i,j) C = init(C,j) task = tf.tensordot(tf.add(A,B),C,1) with tf.Session(config = config) as sess: return sess.run(task)
def dot3(A=None, B=None, C=None): A = init(A, i) B = init(B, i) C = init(C, i) task = tf.tensordot(tf.add(A, B), tf.subtract(A, C), 1) with tf.Session(config=config) as sess: return sess.run(task)
def __init__(self): self.state = 'pre' # init pygame pygame.init() pygame.mixer.init(44100, 16, 2, 1024*4) pygame.display.set_caption("MR. TRAPEZIUS ") try: self.screen = pygame.display.set_mode((640, 480), HWSURFACE | SRCALPHA, 32) except: self.screen = pygame.display.set_mode((640, 480), SRCALPHA, 32) try: pygame.display.set_icon(pygame.image.load( util.file_path("Inky.png")).convert_alpha()) except: # some platfom do not allow change icon after shown pass # init fonts and music lists util.init() # init sub states objects self.pre = Pre(self.screen) self.go = MainGame(self.screen) self.level_info = Level(self.screen) self.re = Retry(self.screen) self.next = NextLevel(self.screen) sound.load()
def t7(A=None, C=None, D=None): A = init(A,i,j) C = init(C,j,k) D = init(D,k) task = tf.tensordot(A,tf.tensordot(C,D,1),1) with tf.Session(config = config) as sess: return sess.run(task)
def dot1(A=None, B=None, C=None): A = init(A, i) B = init(B, i) C = init(C, i) task = tf.reduce_sum(tf.multiply(tf.multiply(A, B), C)) with tf.Session(config=config) as sess: return sess.run(task)
def main(): framecount = 0 exit = False nodes = [] tiles = load_tiles() tile_size = 16 pygame.init() pygame.display.set_caption("Monster AI Prototype") screen = pygame.display.set_mode( (len(tiles) * tile_size, len(tiles) * tile_size)) clock = pygame.time.Clock() background = pygame.Surface(screen.get_size()) background = background.convert() background.fill((255, 255, 255)) util.init(background, tile_size, tiles) nodes = ai.init(len(tiles)) key_player = entity.Entity(tiles, 1, 1, (255, 0, 0)) mouse_player = entity.Entity(tiles, len(tiles) - 2, 1, (0, 255, 0)) monster = entity.Entity(tiles, int(len(tiles) / 2), int(len(tiles) / 2), (0, 0, 0)) while not exit: clock.tick(60) screen.blit(background, (0, 0)) draw_tiles(background, tiles, tile_size) key_player.draw() mouse_player.draw() monster.draw() for event in pygame.event.get(): if event.type == QUIT or (event.type == KEYDOWN and event.key == K_ESCAPE): return elif event.type == KEYDOWN: if event.key == K_DOWN: key_player.add_pos(0, 1) elif event.key == K_UP: key_player.add_pos(0, -1) elif event.key == K_LEFT: key_player.add_pos(-1, 0) elif event.key == K_RIGHT: key_player.add_pos(1, 0) mx, my = pygame.mouse.get_pos() mouse_player.set_pos(mx / tile_size, my / tile_size) ai_move = ai.ai_step(framecount, nodes, monster, (mouse_player, )) framecount += 1 pygame.display.flip()
def t2(A=None, B=None, C=None): A = init(A,i,j) B = init(B,j) C = init(C,i) task = tf.multiply(tf.tensordot(A,B,1),C) with tf.Session(config = config) as sess: return sess.run(task)
def main(): print("{0:-^30}".format(copy_right)) print("-----------------------------------------------------") print("\n") #初始化配置文件读取和日志 My_logger.init() util.init() ##开始寻找讲座 My_logger.my_logger.info("开始按照配置文件搜寻讲座信息!") all_obj = get_seminar.find_seminaer() My_logger.my_logger.info("搜寻讲座信息完成,共发现:{}场讲座!".format(len(all_obj))) ##讲座分辨 get_seminar.judge_seminar(all_obj) My_logger.my_logger.info("讲座主题分辨完成!") ##讲座的落库 get_seminar.alltoDB(all_obj) My_logger.my_logger.info("讲座落库完成!") # ##讲座持久化到本地 get_seminar.toreal_file(all_obj) My_logger.my_logger.info("讲座持久化完成!") ##讲座的微信通知 get_seminar.allcontact(all_obj) My_logger.my_logger.info("讲座信息邮件推送完成!")
def test(): pygame.init() s = pygame.display.set_mode((640, 480), HWSURFACE | SRCALPHA, 32) util.init() m = MainGame(s) m.run(1) #test()
def t9(A=None, B=None, C=None, D=None): A = init(A,i,k) B = init(B,k,j) C = init(C,j) D = init(D,j) task = tf.tensordot(tf.tensordot(A,B,1),tf.add(C,D),1) with tf.Session(config = config) as sess: return sess.run(task)
def t6(A=None, B=None, C=None, D=None): A = init(A,i,1) B = init(B,j) C = init(C,i,1) D = init(D,j) task = tf.reduce_sum(tf.multiply(tf.multiply(A,B),tf.multiply(C,D)),1) with tf.Session(config = config) as sess: return sess.run(task)
def init(): global initDone if not initDone: misc.init(False) util.init(False) initDone = True
def main(): args = cmd_line.parse_args() util.init(args) util.pre_problem = 'CV RC circle' logger = logging.getLogger() log.configure_logger(logger, "RaceCar") logger.setLevel(logging.DEBUG)
def main(): init() save_crop() logging.info("start at: {}".format(datetime.datetime.now())) play = get_policy() while True: action = play.action() if action: get_action_by_name(action).execute()
def start(): util.init() if _G.AppHwnd == 0: print("App not found, aborting") return exit() util.activate_window(_G.AppHwnd) while _G.Flags['running']: main_loop()
def test(): pygame.init() s = pygame.display.set_mode((640, 480), HWSURFACE | SRCALPHA, 32) a = Level(s) util.init() a.run(1) #test()
def init(winname,appname,gamedir,icon="sys_icon.png"): global INIT_DONE if not INIT_DONE: util.init(appname,gamedir) pygame.init() pygame.display.set_caption(winname,appname) pygame.display.set_icon(pygame.image.load(util.image_dir(icon))) # Set the screen size. if util.config.getboolean( "DEFAULT", "fullscreen" ): my_state.screen = pygame.display.set_mode( (0,0), pygame.FULLSCREEN ) else: my_state.screen = pygame.display.set_mode( (800,600), pygame.RESIZABLE ) rpgmenu.init() global INPUT_CURSOR INPUT_CURSOR = image.Image( "sys_textcursor.png" , 8 , 16 ) global SMALLFONT SMALLFONT = pygame.font.Font( util.image_dir( "VeraBd.ttf" ) , 12 ) global TINYFONT TINYFONT = pygame.font.Font( util.image_dir( "VeraBd.ttf" ) , 9 ) global ANIMFONT ANIMFONT = pygame.font.Font( util.image_dir( "DejaVuSansCondensed-Bold.ttf" ) , 16 ) global ITALICFONT ITALICFONT = pygame.font.Font( util.image_dir( "VeraBI.ttf" ) , 12 ) global POSTERS POSTERS += glob.glob( util.image_dir("poster_*.png") ) global FPS FPS = util.config.getint( "DEFAULT", "frames_per_second" ) pygame.time.set_timer(TIMEREVENT, 1000 / FPS) if android: android.init() android.map_key(android.KEYCODE_BACK, pygame.K_ESCAPE) # Set key repeat. pygame.key.set_repeat( 200 , 75 ) INIT_DONE = True
def main(args): global NUMBER_FILES_TO_GENERATE if args and len(args) > 0: try: NUMBER_FILES_TO_GENERATE = int(args[0]) except: raise ValueError("The first argument to main.py must be an integer!") util.init() global heads global pcfg global objects global primitives # Call the main rule-parsing/generation module first to get our pcfg # and other data ready to go (heads, pcfg, objects, raw_primitives) = generate_rules.process_all(); # Prepare primitives dictionaries by doing some pre-processing on them # so that future stuff is accessible much quicker: primitives = prepare_primitives(raw_primitives) print "\nStarting generation process. Don't be alarmed if it takes awhile." numGenerated = 0 while True: try: print "Attempting to generate artificial Python file {}/{}".format(numGenerated+1, NUMBER_FILES_TO_GENERATE) tree = makeNode("Module", 0, []) outcode = "generated/code{}.py".format(numGenerated+1) outast = "generated/AST{}.txt".format(numGenerated+1) with open(outcode, "w") as out: Unparser.Unparser(tree, out) with open(outcode, "r") as in_f: text = in_f.read() with open(outcode, 'w') as out: out.write(postprocess.postprocess(text)) with open(outast, "w") as out: out.write(ast.dump(tree)) print "Successfully created {} and {}".format(outcode, outast) numGenerated += 1 if numGenerated >= NUMBER_FILES_TO_GENERATE: break except Exception as e: pass # The Fifth Amendment allows me to do this. Shhh...
def __init__(self, path="./config.ini"): """ 检查配置文件是否存在,不存在则直接return 检查输出文件夹是否存在,不存在则创建 config.ini必须要有的字段 - dump_dir - base_url """ print u'\n in Spider __init__' if not util.check_file(path): print '\n\t no file ' + path return self.config = util.init(path) if self.config.has_key('ua'): self.config['ua'] = util.init(self.config['ua']) self.config['requests_dir'] = self.config['dump_dir'] + '/requests' print self.config util.check_path(self.config['dump_dir'])
def t5(a=None, A=None, b=None, B=None, c=None, C=None, d=None, D=None): a = init(a) A = init(A,i,j) b = init(b) B = init(B,i,j) c = init(c) C = init(C,j) d = init(d) D = init(D,j) task = tf.tensordot(tf.add(tf.multiply(a,A),tf.multiply(b,B)),tf.add(tf.multiply(c,C),tf.multiply(d,D)),1) with tf.Session(config = config) as sess: return sess.run(task)
def dot5(a=None, A=None, b=None, B=None, c=None, C=None, d=None, D=None): a = init(a) A = init(A, i) b = init(b) B = init(B, i) c = init(c) C = init(C, i) d = init(d) D = init(D, i) task = tf.tensordot(tf.add(tf.multiply(A, a), tf.multiply(B, b)), tf.add(tf.multiply(C, c), tf.multiply(D, d)), 1) with tf.Session(config=config) as sess: return sess.run(task)
def launch(search_str, auth=None, final_songs=None): # initialization of global variables util.init() # Authentication only occurs when user adds playlist if (search_str == "True"): sp_user = auth user_id = sp_user.me()['id'] seamless.gen_playlist(final_songs, final_songs[0]['title'], final_songs[0]['artist'], sp_user, user_id) return True # creation of song object song_obj = seamless.make_song_from_id(search_str) util.year = song_obj.year util.album_tracks.append(song_obj) valid_tracks(song_obj, song_obj) # Songs that went through LastFM API util.already_chosen_fm.append(song_obj) logger.info(f'Number of tracks: {len(util.album_tracks)}') # Filter through reccomended songs first seamless.recommended_tracks(song_obj) # finds similar songs of tracks that have already satisfied the requirements while len(util.album_tracks) < util.limit: # choosing songs from the LastFM list song_data = random.sample(util.album_tracks, 1)[0] seamless.main() valid_tracks(song_data, song_obj) seamless.recommended_tracks(song_data) util.already_chosen_fm.append(song_data) songsChosen = util.album_tracks return songsChosen
def main(args): # general if torch.cuda.is_available(): device = torch.device("cuda") util.logging.info("Using CUDA") else: device = torch.device("cpu") util.logging.info("Using CPU") util.set_seed(args.seed) # init checkpoint_path = util.get_checkpoint_path(args) if not Path(checkpoint_path).exists(): util.logging.info("Training from scratch") model, optimizer, stats = util.init(args, device) else: model, optimizer, stats, args = util.load_checkpoint(checkpoint_path, device) # train train.train(model, optimizer, stats, run_args=args)
#!/usr/bin/env python3 import datetime import os import shutil import subprocess import util util.init() name = 'a' email = '*****@*****.**' os.environ['GIT_AUTHOR_EMAIL'] = email os.environ['GIT_AUTHOR_NAME'] = name os.environ['GIT_COMMITTER_EMAIL'] = email os.environ['GIT_COMMITTER_NAME'] = name date0 = datetime.date(2000, 1, 1) datef = datetime.date(2100, 1, 1) date = date0 while date < datef: s = date.strftime('%Y-%m-%dT01:00:00') print(s) os.environ['GIT_AUTHOR_DATE'] = s os.environ['GIT_COMMITTER_DATE'] = s cmd = ['git', 'commit', '-q', '--allow-empty', '--allow-empty-message', '-m', ''] subprocess.check_output(cmd) date += datetime.timedelta(days=1)
#!/usr/bin/python2.7 import sys import util import numpy as np required_fields = util.required_fields attr_n = util.attr_n if len(sys.argv) != 3: util.print_usage() exit() data = util.read_data(sys.argv[1]) util.init(data) c_cnt = util.c_cnt o_cnt = util.o_cnt simple_attr = util.simple_attr ranged_attr = util.ranged_attr # Learning data = np.array(data) np.random.shuffle(data) data = data[:100] for record in data: t = int(record[13]) # 0 => Healthy # 1-4 => Has heart disease if t > 4: print "Error"
git --git-dir=tmp/repo.tmp/.git push -f "$remote" "$i:master" done # TODO for some reason I needed this afterwards. git --git-dir=tmp/repo.tmp/.git push "$remote" 'master' """ import datetime import subprocess import time import util email = b'*****@*****.**' name = b'' util.init() tree = util.create_tree_with_one_file() commit = None n = 1000000 for i in range(n): now = int(time.time()) commit, _, _ = util.save_commit_object( tree, (commit, ), author_date_s=0, author_email=email, author_name=name, committer_date_s=0, committer_email=email, committer_name=name,
import time import botocore import boto3 import db import util import treehash print("AWS Photo Library") if util.data_dir(err=False) is None: data_dir = os.path.join(os.getcwd(),util.dir_name) os.makedirs(data_dir) db_conn = util.init() glacier_conn = boto3.client('glacier') accountId = '-' vaultName = 'test' parameters = {"Type":"inventory-retrieval"} requestNewInventory = False uploadNewArchive = True showInventory = True uploadD3JS = False uploadD3JSTAR = True uploadABC = True retrieveArchive = True showJobs = False res = glacier_conn.describe_vault(accountId=accountId, vaultName=vaultName)
logging.info('make submission') sub_acc = pd.concat([agg_acc, each_acc]) sub_unc = pd.concat([agg_unc, each_unc]) sub_acc = modify_acc(sub_acc) sample_sub_acc = pd.read_csv( '../input/m5-forecasting-accuracy/sample_submission.csv') sample_sub_unc = pd.read_csv( '../input/m5-forecasting-uncertainty/sample_submission.csv') sub_acc = sample_sub_acc[['id']].merge(sub_acc) sub_unc = sample_sub_unc[['id']].merge(sub_unc) assert len(sample_sub_acc) == len(sub_acc) assert len(sample_sub_unc) == len(sub_unc) now = pd.Timestamp.now() sub_acc.to_csv(f'../submissions/acc-{now:%Y%m%d}-{now:%H%M%S}.csv', index=False, float_format='%.3g') sub_unc.to_csv(f'../submissions/unc-{now:%Y%m%d}-{now:%H%M%S}.csv', index=False, float_format='%.3g') if __name__ == "__main__": run_name = init(__file__) try: main(run_name) except: logging.exception('exception') finally: logging.info('end')
#!/usr/bin/env python # add words to ../dict_en.dat in the correct place import sys if len(sys.argv) < 2: raise "add_word.py word1 word2..." sys.path.insert(0, "..") import util util.init(False) s = util.loadFile("../dict_en.dat", None) if s == None: raise "error" words = {} lines = s.splitlines() for it in lines: words[util.lower(it)] = None for arg in sys.argv[1:]: words[util.lower(arg)] = None words = words.keys() words.sort() f = open("../dict_en.dat", "wb") for w in words:
def run(): config = util.init('unittest') suites = find_tests() run_tests(suites, config)
def init(winname,appname,gamedir,icon="sys_icon.png",poster_pattern="poster_*.png"): global INIT_DONE if not INIT_DONE: util.init(appname,gamedir) # Init image.py image.init_image(util.image_dir("")) pygame.init() pygame.mixer.init() pygame.display.set_caption(winname,appname) pygame.display.set_icon(pygame.image.load(util.image_dir(icon))) # Set the screen size. if util.config.getboolean( "GENERAL", "fullscreen" ): my_state.screen = pygame.display.set_mode( (0,0), pygame.FULLSCREEN ) else: my_state.screen = pygame.display.set_mode( (800,600), pygame.RESIZABLE ) global INPUT_CURSOR INPUT_CURSOR = image.Image( "sys_textcursor.png" , 8 , 16 ) global SMALLFONT SMALLFONT = pygame.font.Font( util.image_dir( "DejaVuSansCondensed-Bold.ttf" ) , 12 ) my_state.small_font = SMALLFONT global TINYFONT TINYFONT = pygame.font.Font( util.image_dir( "DejaVuSansCondensed-Bold.ttf" ) , 9 ) my_state.tiny_font = TINYFONT global ANIMFONT ANIMFONT = pygame.font.Font( util.image_dir( "DejaVuSansCondensed-Bold.ttf" ) , 16 ) my_state.anim_font = ANIMFONT global MEDIUMFONT MEDIUMFONT = pygame.font.Font( util.image_dir( "DejaVuSansCondensed-Bold.ttf" ) , 14 ) my_state.medium_font = MEDIUMFONT global ITALICFONT ITALICFONT = pygame.font.Font( util.image_dir( "DejaVuSansCondensed-BoldOblique.ttf" ) , 12 ) global BIGFONT BIGFONT = pygame.font.Font( util.image_dir( "Anita semi square.ttf" ) , 16 ) my_state.big_font = BIGFONT my_state.huge_font = pygame.font.Font( util.image_dir( "Anita semi square.ttf" ) , 24 ) global POSTERS POSTERS += glob.glob( util.image_dir(poster_pattern) ) global FPS FPS = util.config.getint( "GENERAL", "frames_per_second" ) pygame.time.set_timer(TIMEREVENT, 1000 / FPS) if android: android.init() android.map_key(android.KEYCODE_BACK, pygame.K_ESCAPE) # Set key repeat. pygame.key.set_repeat( 200 , 75 ) INIT_DONE = True
from flask import Flask, jsonify, request, session from flask_cors import CORS from util import load_autocomplete_data,\ filter_request, add_data_in_session, insert_on_logout, init import json import os from datetime import datetime app = Flask(__name__) CORS(app) session = {} init(app) @app.route("/root", methods=['POST']) def _auto_complete(): user_query = request.form.get('query') show_more = request.form.get('show_more') session_id = request.form.get('session_id') if session_id is not None and session_id: add_data_in_session(session, str(datetime.now()), session_id, "login_time", False) if user_query is not None: data = load_autocomplete_data(user_query, show_more) return jsonify(data) @app.route("/filter", methods=['POST']) def _filter(): user_query = request.form.get('query') username = request.form.get('username') session_id = request.form.get('session_id')
# parameters for the code k = int(sys.argv[1]) numEps = int(sys.argv[2]) dimEmbedding = int(sys.argv[3]) windowSize = int(sys.argv[4]) learningRate = float(sys.argv[5]) numOfEpochs = int(sys.argv[6]) batchSize = int(sys.argv[7]) bestValModel = None bestValReward = 0 fileBestRLModel = open("bestRlModel.txt", 'w') # numSteps should be less than k # window size must be much smaller than k to generate enough samples historyOfTuples = [] util.init(learningRate, numOfEpochs, batchSize, dimEmbedding) for episode in range(0, numEps): #episode=episode+2 print("episode ", episode) # generate a new graph for each episode graph = util.Graph(dimEmbedding, episode, k) print("graph ", graph) graphEnv.graphEnvironment.append(graph) # print(graph.graphX.degree()) # if episode==0: # util.initialze_weights(graph) # (numsteps == k) => Terminal Condition previous_spread = 0 for step in range(0, k):
def init(self): util.init() sound.load()
import util util.init('test.bib') f = open('./People.html', 'w') f.write(util.getPeople()) f.close() f = open('./Software.html', 'w') f.write(util.getSoftware()) f.close() f = open('./Publications.html', 'w') f.write(util.getPublications()) f.close()
def baseline_sum(A_host=None): A = init(A_host, i) task = tf.reduce_sum(A) with tf.Session(config=config) as sess: return sess.run(task)
def baseline_inc(A=None): A = init(A, i) task = tf.add(A, 1) with tf.Session(config=config) as sess: return sess.run(task)
app = Flask(__name__) openmrs_host = 'http://*****:*****@app.route('/fetch') def hello_world(): response = requests.get(openmrs_host + idgen_path) return response.text, response.status_code @app.route('/register',methods=['POST']) def register_patient(): print(request.get_json(force=True)) response = requests.post( openmrs_host + registeration_path, auth=(os.environ['MOBILE_USERNAME'], os.environ['MOBILE_PASSWORD']), json=request.get_json(force=True) ) if response.status_code == 201: email_notify(request.host) return response.text, response.status_code if __name__ == '__main__': init() app.run(host='0.0.0.0', port=3000)
def dot(A=None, B=None): A = init(A, i) B = init(B, i) task = tf.tensordot(A, B, 1) with tf.Session(config=config) as sess: return sess.run(task)
def baseline_prod(A=None, c=None): A = init(A, i) c = init(c) task = tf.multiply(A, c) with tf.Session(config=config) as sess: return sess.run(task)