def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) #print ('app_data', app_data) if app_data['mode'] == 'tune+': for g_size in [3, 5, 7, 10, 15]: create_lib(build_nlmeans, app, app_data, g_size) for t in range(0, 5): print("Running for iteration #", t) nlmeans(app_data) elif app_data['mode'] == 'tune': auto_tune(pipe_data, app_data) pass else: create_lib(build_nlmeans, app, app_data) for i in range(0, 5): nlmeans(app_data) return
def main(): print_header() print("[main]: initializing...") print("") app_data = {} app_data['app'] = app app_data['app_name'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune+': for g_size in [3, 5, 7]: for t1 in [8, 16, 32, 64, 128, 256]: for t2 in [8, 16, 32, 64, 128, 256]: create_lib(build_unsharp, app, app_data, g_size, [1, t1, t2]) for t in range(0, 0): print("Running for iteration #", t) elif app_data['mode'] == 'tune': print("Tuning") auto_tune(app_data) else: create_lib(build_unsharp, app, app_data) min_avg = 100000 for i in range(0, 10000000): min_avg = min(min_avg, unsharp_mask(app_data)) print("minimum average ", min_avg) return
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune+': for g_size in [3, 5, 7]: for t1 in [8, 16, 32, 64, 128, 256]: for t2 in [8, 16, 32, 64, 128, 256]: create_lib(build_pyramid, app, app_data, g_size, [t1, t2]) for t in range (0, 0): print ("Running for iteration #", t) pyramid_blending(app_data) elif app_data['mode'] == 'tune' or app_data['mode'] == 'tune_execute': auto_tune(app_data) pass else: create_lib(build_pyramid, app, app_data) min_avg = 100000 for r in range (0,5): min_avg = min (min_avg, pyramid_blending(app_data)) print ("Minimum Average Time ", min_avg) return
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune+': for g_size in [3, 5, 7]: for t1 in [8, 16, 32, 64, 128, 256]: for t2 in [8, 16, 32, 64, 128, 256]: create_lib(build_harris, app, app_data, g_size, [t1, t2]) for t in range(0, 0): print("Running for iteration #", t) harrispipe(app_data) elif app_data['mode'] == 'tune': print("Tuning") auto_tune(app_data) else: create_lib(build_harris, app, app_data) _m = 10000000 nsamples = 5 for i in range(0, nsamples): _m = min(_m, harrispipe(app_data)) print("[main] Minimum of averaged times across ", nsamples, "samples: ", _m, " ms") return
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune+': for g_size in [3, 5, 7, 9, 11, 200]: for t1 in [8, 16, 32, 64, 128, 256]: for t2 in [8, 16, 32, 64, 128, 256]: create_lib(build_interpolate, app, app_data, g_size, [1, t1, t2]) for t in range(0, 0): print("Running for iteration #", t) interpolate(app_data) elif app_data['mode'] == 'tune': pass else: create_lib(build_interpolate, app, app_data) _min_time = 10000 for t in range(0, 5): _min_time = min(_min_time, interpolate(app_data)) print("Minimum Time = ", _min_time) return
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune+': for g_size in [3, 5, 7]: for t1 in [8, 16, 32, 64, 128, 256]: for t2 in [8, 16, 32, 64, 128, 256]: create_lib(build_harris, app, app_data, g_size, [t1, t2]) for t in range (0, 0): print ("Running for iteration #", t) harrispipe(app_data) elif app_data['mode'] == 'tune': pass else: create_lib(build_harris, app, app_data) _m = 10000000 for i in range (0,5): _m = min (_m, harrispipe(app_data)) print ("min time is ", _m) return
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune+': for g_size in [3, 5, 7]: for t1 in [8, 16, 32, 64, 128, 256]: for t2 in [8, 16, 32, 64, 128, 256]: create_lib(build_campipe, app, app_data, g_size, [t1, t2]) for t in range (0, 0): print ("Running for iteration #", t) campipe(app_data) elif app_data['mode'] == 'tune': auto_tune(app_data) else: # create shared lib create_lib(build_campipe, app, app_data) min_avg = 100000 for t in range (0, 5): # execute the compiled pipeline min_avg = min (min_avg, campipe(app_data)) print ("Minimum Average ", min_avg) return
def main(): print_header() app_data = {} app_data['ROOT'] = ROOT # init all the required data init_all(app_data) print_config(app_data) app_name = "nas_mg_class_"+app_data['prob_class'] app_data['app'] = app_name if app_data['mode'] == 'tune': #app_tune(app_data) pass else: #------------------------------------------------------------------- # setting up residual norm computation create_lib(None, "norm", app_data) # setting up multigrid v-cycle computation create_lib(build_mg3p, app_name, app_data) # setting up standalone version of residual computation create_lib(build_resid, "resid", app_data) #------------------------------------------------------------------- init_norm(app_data) multigrid(app_data) verify_norm(app_data) #------------------------------------------------------------------- return
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune+': for g_size in [3, 5, 7, 9, 11, 200]: for t1 in [8, 16, 32, 64, 128, 256]: for t2 in [8, 16, 32, 64, 128, 256]: create_lib(build_interpolate, app, app_data, g_size, [1, t1, t2]) for t in range(0, 0): print("Running for iteration #", t) interpolate(app_data) elif app_data['mode'] == 'tune': print("Tuning") auto_tune(app_data) else: create_lib(build_interpolate, app, app_data) min_avg = 10000 nsamples = 5 print("[main] Benchmarking (%d samples)" % nsamples) for t in range(0, nsamples): min_avg = min(min_avg, interpolate(app_data)) print("[main] Minimum of averaged times across ", nsamples, "runs: ", min_avg, " ms") return
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune+': for g_size in [3, 5, 7]: for t1 in [8, 16, 32, 64, 128, 256]: for t2 in [8, 16, 32, 64, 128, 256]: create_lib(build_campipe, app, app_data, g_size, [t1, t2]) for t in range(0, 0): print("Running for iteration #", t) campipe(app_data) elif app_data['mode'] == 'tune': auto_tune(app_data) else: # create shared lib create_lib(build_campipe, app, app_data) min_avg = 100000 nsamples = 5 print("[main] Benchmarking (%d samples)" % nsamples) for t in range(0, nsamples): # execute the compiled pipeline min_avg = min(min_avg, campipe(app_data)) print("[main] Minimum of averaged times across ", nsamples, "samples: ", min_avg, " ms") return
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune+': for g_size in [3, 5, 7]: for t1 in [8, 16, 32, 64, 128, 256]: for t2 in [8, 16, 32, 64, 128, 256]: create_lib(build_bilateral, app, app_data, g_size, [1, t1, t2]) for t in range(0, 0): print("Running for iteration #", t) bilateralgrid(app_data) elif app_data['mode'] == 'tune': print("Tuning") auto_tune(app_data) else: create_lib(build_bilateral, app, app_data) min_avg = 10000 # input ("wait to run amplxe " + str(os.getpid())) # input ("wwww") nsamples = 5 print("[main] Benchmarking (%d samples)" % nsamples) for t in range(0, nsamples): min_avg = min(min_avg, bilateralgrid(app_data)) print("[main] Minimum of averaged times across ", nsamples, "samples: ", min_avg, " ms") return
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune+': for g_size in [3, 5, 7]: for t1 in [8, 16, 32, 64, 128, 256]: for t2 in [8, 16, 32, 64, 128, 256]: create_lib(build_bilateral, app, app_data, g_size, [1, t1, t2]) for t in range (0, 0): print ("Running for iteration #", t) bilateralgrid(app_data) elif app_data['mode'] == 'tune': pass else: create_lib(build_bilateral, app, app_data) _min_time = 10000 input ("wait to run amplxe " + str(os.getpid())) input ("wwww") for t in range(0, 5): _min_time = min (_min_time, bilateralgrid(app_data)) print ("Minimum Time = ", _min_time) return
def create_app(): app = make_json_app(__name__) # setup cross domain setup_cross_domain(app) # app basic configuration app.config.from_object('config.base') # init application init.init_all(app) # apply router router_index.apply(app) return app
def create_app(): app = make_json_app(__name__) # setup cross domain setup_cross_domain(app) # app basic configuration app.config.from_object("config.base") # init application init.init_all(app) # apply router router_index.apply(app) return app
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune' or app_data['mode'] == 'tune_execute': auto_tune(app_data) pass else: create_lib(build_pyramid, app, app_data) pyramid_blending(app_data) return
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune': auto_tune(app_data) else: create_lib(build_harris, app, app_data) harrispipe(app_data) return
def main(): try: try: intent = sys.argv[1] except: print("Please provide correct no of arguments") init.init_all() if intent=='scrap': scraper.scrap_gags() else: try: object_count = int(sys.argv[2]) Gag.get_gags(sys.argv[1], object_count) except: print("Count of object should be integer") except: print("An error has occured")
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune': #auto_tune(pipe_data,app_data) pass else: create_lib(build_bilateral, app, app_data) bilateralgrid(app_data) return
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune': #auto_tune(pipe_data,app_data) pass else: create_lib(build_maxfilter, app, app_data) maxfilter(app_data) return
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune': print("Tuning...") #auto_tune(app_data) else: create_lib(build_laplacian, app, app_data) for i in range(0, 5): laplacian(app_data) return
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune': auto_tune(app_data) else: # create shared lib create_lib(build_campipe, app, app_data) # execute the compiled pipeline campipe(app_data) return
def main(): print_header() print("[main]: initializing...") print("") app_data = {} app_data['app'] = app app_data['app_name'] = app app_data['ROOT'] = ROOT init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune': print("Tuning") auto_tune(app_data) else: create_lib(build_unsharp, app, app_data) unsharp_mask(app_data) return
def main(): print_header() print("[main]: initializing...") print("") app_data = {} app_data['app'] = app app_data['app_name'] = app app_data['ROOT'] = ROOT g_sizes = [3, 5, 7] tile_sizes = [8, 16, 32, 64] #, 128, 256] init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune+': for g_size in g_sizes: for t1 in tile_sizes: for t2 in tile_sizes: create_lib(build_mfd, app, app_data, g_size, [1, t1, t2]) for t in range(0, 0): print("Running for iteration #", t) elif app_data['mode'] == 'tune': print("Tuning") auto_tune(app_data) else: create_lib(build_mfd, app, app_data) min_avg = 100000 nsamples = 5 for i in range(0, nsamples): min_avg = min(min_avg, minifluxdiv(app_data)) print("[main] Minimum of averaged times across ", nsamples, "samples: ", min_avg, " ms") return
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT # init all the required data init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune': auto_tune(app_data) else: #------------------------------------------------------------------- create_lib(None, "norm", app_data) create_lib(build_mg_cycle, app_data['cycle_name'], app_data) #------------------------------------------------------------------- init_norm(app_data) multigrid(app_data) #------------------------------------------------------------------- return
def main(): print_header() app_data = {} app_data['app'] = app app_data['ROOT'] = ROOT # init all the required data init_all(app_data) print_config(app_data) if app_data['mode'] == 'tune': print("Tuning...") auto_tune(app_data) else: #------------------------------------------------------------------- create_lib(None, "norm", app_data) create_lib(build_jacobi, app, app_data) #------------------------------------------------------------------- init_norm(app_data) exec_jacobi(app_data) #------------------------------------------------------------------- return
from flask import Flask, session, request, render_template, redirect import time import order_def import holding_def import init import math import func_def myWeb = Flask(__name__) trade_board_length = 60 # 交易面板容纳的最大订单数量 price_queue_length = 4 # 价格队列的长度 order_limit = 6 # 单个用户订单上限 # 运行中 admin_pwd, user_pwd, buy_order, sell_order, user_holding, price_order, market_price, order_cnt = init.init_all( ) # 主页 @myWeb.route("/") def root(): return render_template("index.html", MSG="请登录") # 用户登陆,成功则返回main_page.html,否则返回index.html @myWeb.route("/login", methods=["post", "get"]) def login(): # print(request.method, type(request.method)) if request.method == "GET": return render_template("index.html", MSG="请登录") username = request.form['username']
@app.route('/qrcode.jpg') def qr_jpg(): key = get_qr_key() f = BytesIO() img = qrcode.make(request.url_root + 'control/?key=' + key) img = img.convert('RGB').resize((240, 240)) img.save(f, format='jpeg') f.seek(0) return send_file(f, mimetype='image/jpeg') if __name__ == '__main__': print('Starting...') plant = session.query(Plant).first() if not plant: init_all(session) plant = session.query(Plant).first() sched = Scheduler() sched.start() sched.add_cron_job(fetch_and_save_data, minute="*/{}".format(FETCH_DATA_INTERVAL), args=[session, plant]) sched.add_cron_job(fetch_and_save_image, minute="*/{}".format(FETCH_IMAGE_INTERVAL), args=[session, plant]) if MODE != 'demo': sched.add_cron_job(trigger_led, minute="*/{}".format(TRIGGER_INTERVAL), args=[plant]) sched.add_cron_job(trigger_pump, minute="*/{}".format(TRIGGER_INTERVAL),
port2 = "4725" case_common.setappiumimput(deviceid1) case_common.setappiumimput(deviceid2) case_common.clearAppdata(deviceid1) case_common.clearAppdata(deviceid2) driver1 = startDemo(deviceid1, device_list[1], port1) driver2 = startDemo(deviceid2, device_list[3], port2) test_login(driver1, username="******", password="******") test_login(driver2, username="******", password="******") case_common.change_appkeyandserver(driver1, appkey, resturl, imserver, test_env, test_type) case_common.change_appkeyandserver(driver2, appkey, resturl, imserver, test_env, test_type) init.init_all() driver1 = startDemo(deviceid1, device_list[1], port1) driver2 = startDemo(deviceid2, device_list[3], port2) testset_account(driver1) test_login(driver1, username=accountA, password="******") test_login(driver2, username=accountB, password="******") del_conversation(driver1) del_conversation(driver2) testset_call(driver1, driver2, userA=accountA, userB=accountB) testset_single_chat(driver1, driver2,