diff options
Diffstat (limited to 'VNFs/DPPD-PROX/helper-scripts/rapid/rapid_test.py')
| -rw-r--r-- | VNFs/DPPD-PROX/helper-scripts/rapid/rapid_test.py | 441 |
1 files changed, 441 insertions, 0 deletions
diff --git a/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_test.py b/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_test.py new file mode 100644 index 00000000..deba695f --- /dev/null +++ b/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_test.py @@ -0,0 +1,441 @@ +#!/usr/bin/python + +## +## Copyright (c) 2020 Intel Corporation +## +## 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, software +## distributed under the License is distributed on an "AS IS" BASIS, +## WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +## See the License for the specific language governing permissions and +## limitations under the License. +## + +import yaml +import requests +import time +import os +import copy +from past.utils import old_div +from rapid_log import RapidLog +from rapid_log import bcolors +inf = float("inf") +from datetime import datetime as dt + +_CURR_DIR = os.path.dirname(os.path.realpath(__file__)) + +class RapidTest(object): + """ + Class to manage the testing + """ + def __init__(self, test_param, runtime, testname, environment_file ): + self.test = test_param + self.test['runtime'] = runtime + self.test['testname'] = testname + self.test['environment_file'] = environment_file + if 'maxr' not in self.test.keys(): + self.test['maxr'] = 1 + if 'maxz' not in self.test.keys(): + self.test['maxz'] = inf + with open(os.path.join(_CURR_DIR,'format.yaml')) as f: + self.data_format = yaml.load(f, Loader=yaml.FullLoader) + + @staticmethod + def get_percentageof10Gbps(pps_speed,size): + # speed is given in pps, returning % of 10Gb/s + # 12 bytes is the inter packet gap + # pre-amble is 7 bytes + # SFD (start of frame delimiter) is 1 byte + # Total of 20 bytes overhead per packet + return (pps_speed / 1000000.0 * 0.08 * (size+20)) + + @staticmethod + def get_pps(speed,size): + # speed is given in % of 10Gb/s, returning Mpps + # 12 bytes is the inter packet gap + # pre-amble is 7 bytes + # SFD (start of frame delimiter) is 1 byte + # Total of 20 bytes overhead per packet + return (speed * 100.0 / (8*(size+20))) + + @staticmethod + def get_speed(packet_speed,size): + # return speed in Gb/s + # 12 bytes is the inter packet gap + # pre-amble is 7 bytes + # SFD (start of frame delimiter) is 1 byte + # Total of 20 bytes overhead per packet + return (packet_speed / 1000.0 * (8*(size+20))) + + @staticmethod + def set_background_flows(background_machines, number_of_flows): + for machine in background_machines: + _ = machine.set_flows(number_of_flows) + + @staticmethod + def set_background_speed(background_machines, speed): + for machine in background_machines: + machine.set_generator_speed(speed) + + @staticmethod + def set_background_size(background_machines, imix): + # imixs is a list of packet sizes + for machine in background_machines: + machine.set_udp_packet_size(imix) + + @staticmethod + def start_background_traffic(background_machines): + for machine in background_machines: + machine.start() + + @staticmethod + def stop_background_traffic(background_machines): + for machine in background_machines: + machine.stop() + + @staticmethod + def parse_data_format_dict(data_format, variables): + for k, v in data_format.items(): + if type(v) is dict: + RapidTest.parse_data_format_dict(v, variables) + else: + if v in variables.keys(): + data_format[k] = variables[v] + + def post_data(self, variables): + test_type = type(self).__name__ + var = copy.deepcopy(self.data_format) + self.parse_data_format_dict(var, variables) + if var.keys() >= {'URL', test_type, 'Format'}: + URL='' + for value in var['URL'].values(): + URL = URL + value + HEADERS = {'X-Requested-With': 'Python requests', 'Content-type': 'application/rapid'} + if var['Format'] == 'PushGateway': + data = "\n".join("{} {}".format(k, v) for k, v in var[test_type].items()) + "\n" + response = requests.post(url=URL, data=data,headers=HEADERS) + elif var['Format'] == 'Xtesting': + data = var[test_type] + response = requests.post(url=URL, json=data) + if (response.status_code >= 300): + RapidLog.info('Cannot send metrics to {}'.format(URL)) + RapidLog.info(data) + return (var[test_type]) + + @staticmethod + def report_result(flow_number, size, data, prefix): + if flow_number < 0: + flow_number_str = '| ({:>4}) |'.format(abs(flow_number)) + else: + flow_number_str = '|{:>7} |'.format(flow_number) + if data['pps_req_tx'] is None: + pps_req_tx_str = '{0: >14}'.format(' NA |') + else: + pps_req_tx_str = '{:>7.3f} Mpps |'.format(data['pps_req_tx']) + if data['pps_tx'] is None: + pps_tx_str = '{0: >14}'.format(' NA |') + else: + pps_tx_str = '{:>7.3f} Mpps |'.format(data['pps_tx']) + if data['pps_sut_tx'] is None: + pps_sut_tx_str = '{0: >14}'.format(' NA |') + else: + pps_sut_tx_str = '{:>7.3f} Mpps |'.format(data['pps_sut_tx']) + if data['pps_rx'] is None: + pps_rx_str = '{0: >25}'.format('NA |') + else: + pps_rx_str = bcolors.OKBLUE + '{:>4.1f} Gb/s |{:7.3f} Mpps {}|'.format( + RapidTest.get_speed(data['pps_rx'],size),data['pps_rx'],bcolors.ENDC) + if data['abs_dropped'] is None: + tot_drop_str = ' | NA | ' + else: + tot_drop_str = ' | {:>9.0f} | '.format(data['abs_dropped']) + if data['lat_perc'] is None: + lat_perc_str = '|{:^10.10}|'.format('NA') + elif data['lat_perc_max'] == True: + lat_perc_str = '|>{}{:>5.0f} us{} |'.format(prefix['lat_perc'], + float(data['lat_perc']), bcolors.ENDC) + else: + lat_perc_str = '| {}{:>5.0f} us{} |'.format(prefix['lat_perc'], + float(data['lat_perc']), bcolors.ENDC) + if data['actual_duration'] is None: + elapsed_time_str = ' NA |' + else: + elapsed_time_str = '{:>3.0f} |'.format(data['actual_duration']) + if data['mis_ordered'] is None: + mis_ordered_str = ' NA ' + else: + mis_ordered_str = '{:>9.0f} '.format(data['mis_ordered']) + return(flow_number_str + '{:>5.1f}'.format(data['speed']) + '% ' + prefix['speed'] + + '{:>6.3f}'.format(RapidTest.get_pps(data['speed'],size)) + ' Mpps|' + + pps_req_tx_str + pps_tx_str + bcolors.ENDC + pps_sut_tx_str + + pps_rx_str + prefix['lat_avg'] + ' {:>6.0f}'.format(data['lat_avg']) + + ' us' + lat_perc_str +prefix['lat_max']+'{:>6.0f}'.format(data['lat_max']) + + ' us | ' + '{:>9.0f}'.format(data['abs_tx']) + ' | {:>9.0f}'.format(data['abs_rx']) + + ' | '+ prefix['abs_drop_rate']+ '{:>9.0f}'.format(data['abs_tx']-data['abs_rx']) + + tot_drop_str + prefix['drop_rate'] + + '{:>5.2f}'.format(100*old_div(float(data['abs_tx']-data['abs_rx']),data['abs_tx'])) + ' |' + + prefix['mis_ordered'] + mis_ordered_str + bcolors.ENDC + + ' |' + elapsed_time_str) + + def run_iteration(self, requested_duration, flow_number, size, speed): + BUCKET_SIZE_EXP = self.gen_machine.bucket_size_exp + sleep_time = self.test['sleep_time'] + LAT_PERCENTILE = self.test['lat_percentile'] + iteration_data= {} + time_loop_data= {} + iteration_data['r'] = 0; + + while (iteration_data['r'] < self.test['maxr']): + self.gen_machine.start_latency_cores() + time.sleep(sleep_time) + # Sleep_time is needed to be able to do accurate measurements to check for packet loss. We need to make this time large enough so that we do not take the first measurement while some packets from the previous tests migth still be in flight + t1_rx, t1_non_dp_rx, t1_tx, t1_non_dp_tx, t1_drop, t1_tx_fail, t1_tsc, abs_tsc_hz = self.gen_machine.core_stats() + t1_dp_rx = t1_rx - t1_non_dp_rx + t1_dp_tx = t1_tx - t1_non_dp_tx + self.gen_machine.set_generator_speed(0) + self.gen_machine.start_gen_cores() + self.set_background_speed(self.background_machines, 0) + self.start_background_traffic(self.background_machines) + if 'ramp_step' in self.test.keys(): + ramp_speed = self.test['ramp_step'] + else: + ramp_speed = speed + while ramp_speed < speed: + self.gen_machine.set_generator_speed(ramp_speed) + self.set_background_speed(self.background_machines, ramp_speed) + time.sleep(2) + ramp_speed = ramp_speed + self.test['ramp_step'] + self.gen_machine.set_generator_speed(speed) + self.set_background_speed(self.background_machines, speed) + iteration_data['speed'] = speed + time_loop_data['speed'] = speed + time.sleep(2) ## Needs to be 2 seconds since this 1 sec is the time that PROX uses to refresh the stats. Note that this can be changed in PROX!! Don't do it. + start_bg_gen_stats = [] + for bg_gen_machine in self.background_machines: + bg_rx, bg_non_dp_rx, bg_tx, bg_non_dp_tx, _, _, bg_tsc, _ = bg_gen_machine.core_stats() + bg_gen_stat = { + "bg_dp_rx" : bg_rx - bg_non_dp_rx, + "bg_dp_tx" : bg_tx - bg_non_dp_tx, + "bg_tsc" : bg_tsc + } + start_bg_gen_stats.append(dict(bg_gen_stat)) + if self.sut_machine!= None: + t2_sut_rx, t2_sut_non_dp_rx, t2_sut_tx, t2_sut_non_dp_tx, t2_sut_drop, t2_sut_tx_fail, t2_sut_tsc, sut_tsc_hz = self.sut_machine.core_stats() + t2_rx, t2_non_dp_rx, t2_tx, t2_non_dp_tx, t2_drop, t2_tx_fail, t2_tsc, tsc_hz = self.gen_machine.core_stats() + tx = t2_tx - t1_tx + iteration_data['abs_tx'] = tx - (t2_non_dp_tx - t1_non_dp_tx ) + iteration_data['abs_rx'] = t2_rx - t1_rx - (t2_non_dp_rx - t1_non_dp_rx) + iteration_data['abs_dropped'] = iteration_data['abs_tx'] - iteration_data['abs_rx'] + if tx == 0: + RapidLog.critical("TX = 0. Test interrupted since no packet has been sent.") + if iteration_data['abs_tx'] == 0: + RapidLog.critical("Only non-dataplane packets (e.g. ARP) sent. Test interrupted since no packet has been sent.") + # Ask PROX to calibrate the bucket size once we have a PROX function to do this. + # Measure latency statistics per second + iteration_data.update(self.gen_machine.lat_stats()) + t2_lat_tsc = iteration_data['lat_tsc'] + sample_count = 0 + for sample_percentile, bucket in enumerate(iteration_data['buckets'],start=1): + sample_count += bucket + if sample_count > sum(iteration_data['buckets']) * LAT_PERCENTILE: + break + iteration_data['lat_perc_max'] = (sample_percentile == len(iteration_data['buckets'])) + iteration_data['bucket_size'] = float(2 ** BUCKET_SIZE_EXP) / (old_div(float(iteration_data['lat_hz']),float(10**6))) + time_loop_data['bucket_size'] = iteration_data['bucket_size'] + iteration_data['lat_perc'] = sample_percentile * iteration_data['bucket_size'] + if self.test['test'] == 'fixed_rate': + iteration_data['pps_req_tx'] = None + iteration_data['pps_tx'] = None + iteration_data['pps_sut_tx'] = None + iteration_data['pps_rx'] = None + iteration_data['lat_perc'] = None + iteration_data['actual_duration'] = None + iteration_prefix = {'speed' : '', + 'lat_avg' : '', + 'lat_perc' : '', + 'lat_max' : '', + 'abs_drop_rate' : '', + 'mis_ordered' : '', + 'drop_rate' : ''} + RapidLog.info(self.report_result(flow_number, size, + iteration_data, iteration_prefix )) + tot_rx = tot_non_dp_rx = tot_tx = tot_non_dp_tx = tot_drop = 0 + iteration_data['lat_avg'] = iteration_data['lat_used'] = 0 + tot_lat_measurement_duration = float(0) + iteration_data['actual_duration'] = float(0) + tot_sut_core_measurement_duration = float(0) + tot_sut_rx = tot_sut_non_dp_rx = tot_sut_tx = tot_sut_non_dp_tx = tot_sut_drop = tot_sut_tx_fail = tot_sut_tsc = 0 + lat_avail = core_avail = sut_avail = False + while (iteration_data['actual_duration'] - float(requested_duration) <= 0.1) or (tot_lat_measurement_duration - float(requested_duration) <= 0.1): + time.sleep(0.5) + time_loop_data.update(self.gen_machine.lat_stats()) + # Get statistics after some execution time + if time_loop_data['lat_tsc'] != t2_lat_tsc: + single_lat_measurement_duration = (time_loop_data['lat_tsc'] - t2_lat_tsc) * 1.0 / time_loop_data['lat_hz'] # time difference between the 2 measurements, expressed in seconds. + # A second has passed in between to lat_stats requests. Hence we need to process the results + tot_lat_measurement_duration = tot_lat_measurement_duration + single_lat_measurement_duration + if iteration_data['lat_min'] > time_loop_data['lat_min']: + iteration_data['lat_min'] = time_loop_data['lat_min'] + if iteration_data['lat_max'] < time_loop_data['lat_max']: + iteration_data['lat_max'] = time_loop_data['lat_max'] + iteration_data['lat_avg'] = iteration_data['lat_avg'] + time_loop_data['lat_avg'] * single_lat_measurement_duration # Sometimes, There is more than 1 second between 2 lat_stats. Hence we will take the latest measurement + iteration_data['lat_used'] = iteration_data['lat_used'] + time_loop_data['lat_used'] * single_lat_measurement_duration # and give it more weigth. + sample_count = 0 + for sample_percentile, bucket in enumerate(time_loop_data['buckets'],start=1): + sample_count += bucket + if sample_count > sum(time_loop_data['buckets']) * LAT_PERCENTILE: + break + time_loop_data['lat_perc_max'] = (sample_percentile == len(time_loop_data['buckets'])) + time_loop_data['lat_perc'] = sample_percentile * iteration_data['bucket_size'] + iteration_data['buckets'] = [iteration_data['buckets'][i] + time_loop_data['buckets'][i] for i in range(len(iteration_data['buckets']))] + t2_lat_tsc = time_loop_data['lat_tsc'] + lat_avail = True + t3_rx, t3_non_dp_rx, t3_tx, t3_non_dp_tx, t3_drop, t3_tx_fail, t3_tsc, tsc_hz = self.gen_machine.core_stats() + if t3_tsc != t2_tsc: + time_loop_data['actual_duration'] = (t3_tsc - t2_tsc) * 1.0 / tsc_hz # time difference between the 2 measurements, expressed in seconds. + iteration_data['actual_duration'] = iteration_data['actual_duration'] + time_loop_data['actual_duration'] + delta_rx = t3_rx - t2_rx + tot_rx += delta_rx + delta_non_dp_rx = t3_non_dp_rx - t2_non_dp_rx + tot_non_dp_rx += delta_non_dp_rx + delta_tx = t3_tx - t2_tx + tot_tx += delta_tx + delta_non_dp_tx = t3_non_dp_tx - t2_non_dp_tx + tot_non_dp_tx += delta_non_dp_tx + delta_dp_tx = delta_tx -delta_non_dp_tx + delta_dp_rx = delta_rx -delta_non_dp_rx + time_loop_data['abs_dropped'] = delta_dp_tx - delta_dp_rx + iteration_data['abs_dropped'] += time_loop_data['abs_dropped'] + delta_drop = t3_drop - t2_drop + tot_drop += delta_drop + t2_rx, t2_non_dp_rx, t2_tx, t2_non_dp_tx, t2_drop, t2_tx_fail, t2_tsc = t3_rx, t3_non_dp_rx, t3_tx, t3_non_dp_tx, t3_drop, t3_tx_fail, t3_tsc + core_avail = True + if self.sut_machine!=None: + t3_sut_rx, t3_sut_non_dp_rx, t3_sut_tx, t3_sut_non_dp_tx, t3_sut_drop, t3_sut_tx_fail, t3_sut_tsc, sut_tsc_hz = self.sut_machine.core_stats() + if t3_sut_tsc != t2_sut_tsc: + single_sut_core_measurement_duration = (t3_sut_tsc - t2_sut_tsc) * 1.0 / sut_tsc_hz # time difference between the 2 measurements, expressed in seconds. + tot_sut_core_measurement_duration = tot_sut_core_measurement_duration + single_sut_core_measurement_duration + tot_sut_rx += t3_sut_rx - t2_sut_rx + tot_sut_non_dp_rx += t3_sut_non_dp_rx - t2_sut_non_dp_rx + delta_sut_tx = t3_sut_tx - t2_sut_tx + tot_sut_tx += delta_sut_tx + delta_sut_non_dp_tx = t3_sut_non_dp_tx - t2_sut_non_dp_tx + tot_sut_non_dp_tx += delta_sut_non_dp_tx + t2_sut_rx, t2_sut_non_dp_rx, t2_sut_tx, t2_sut_non_dp_tx, t2_sut_drop, t2_sut_tx_fail, t2_sut_tsc = t3_sut_rx, t3_sut_non_dp_rx, t3_sut_tx, t3_sut_non_dp_tx, t3_sut_drop, t3_sut_tx_fail, t3_sut_tsc + sut_avail = True + if self.test['test'] == 'fixed_rate': + if lat_avail == core_avail == True: + lat_avail = core_avail = False + time_loop_data['pps_req_tx'] = (delta_tx + delta_drop - delta_rx)/time_loop_data['actual_duration']/1000000 + time_loop_data['pps_tx'] = delta_tx/time_loop_data['actual_duration']/1000000 + if self.sut_machine != None and sut_avail: + time_loop_data['pps_sut_tx'] = delta_sut_tx/single_sut_core_measurement_duration/1000000 + sut_avail = False + else: + time_loop_data['pps_sut_tx'] = None + time_loop_data['pps_rx'] = delta_rx/time_loop_data['actual_duration']/1000000 + time_loop_data['abs_tx'] = delta_dp_tx + time_loop_data['abs_rx'] = delta_dp_rx + time_loop_prefix = {'speed' : '', + 'lat_avg' : '', + 'lat_perc' : '', + 'lat_max' : '', + 'abs_drop_rate' : '', + 'mis_ordered' : '', + 'drop_rate' : ''} + RapidLog.info(self.report_result(flow_number, size, time_loop_data, + time_loop_prefix)) + time_loop_data['test'] = self.test['testname'] + time_loop_data['environment_file'] = self.test['environment_file'] + time_loop_data['Flows'] = flow_number + time_loop_data['Size'] = size + time_loop_data['RequestedSpeed'] = RapidTest.get_pps(speed, size) + _ = self.post_data(time_loop_data) + end_bg_gen_stats = [] + for bg_gen_machine in self.background_machines: + bg_rx, bg_non_dp_rx, bg_tx, bg_non_dp_tx, _, _, bg_tsc, bg_hz = bg_gen_machine.core_stats() + bg_gen_stat = {"bg_dp_rx" : bg_rx - bg_non_dp_rx, + "bg_dp_tx" : bg_tx - bg_non_dp_tx, + "bg_tsc" : bg_tsc, + "bg_hz" : bg_hz + } + end_bg_gen_stats.append(dict(bg_gen_stat)) + self.stop_background_traffic(self.background_machines) + i = 0 + bg_rates =[] + while i < len(end_bg_gen_stats): + bg_rates.append(0.000001*(end_bg_gen_stats[i]['bg_dp_rx'] - + start_bg_gen_stats[i]['bg_dp_rx']) / ((end_bg_gen_stats[i]['bg_tsc'] - + start_bg_gen_stats[i]['bg_tsc']) * 1.0 / end_bg_gen_stats[i]['bg_hz'])) + i += 1 + if len(bg_rates): + iteration_data['avg_bg_rate'] = sum(bg_rates) / len(bg_rates) + RapidLog.debug('Average Background traffic rate: {:>7.3f} Mpps'.format(iteration_data['avg_bg_rate'])) + else: + iteration_data['avg_bg_rate'] = None + #Stop generating + self.gen_machine.stop_gen_cores() + time.sleep(3.5) + self.gen_machine.stop_latency_cores() + iteration_data['r'] += 1 + iteration_data['lat_avg'] = old_div(iteration_data['lat_avg'], float(tot_lat_measurement_duration)) + iteration_data['lat_used'] = old_div(iteration_data['lat_used'], float(tot_lat_measurement_duration)) + t4_tsc = t2_tsc + while t4_tsc == t2_tsc: + t4_rx, t4_non_dp_rx, t4_tx, t4_non_dp_tx, t4_drop, t4_tx_fail, t4_tsc, abs_tsc_hz = self.gen_machine.core_stats() + if self.test['test'] == 'fixed_rate': + iteration_data['lat_tsc'] = t2_lat_tsc + while iteration_data['lat_tsc'] == t2_lat_tsc: + iteration_data.update(self.gen_machine.lat_stats()) + sample_count = 0 + for percentile, bucket in enumerate(iteration_data['buckets'],start=1): + sample_count += bucket + if sample_count > sum(iteration_data['buckets']) * LAT_PERCENTILE: + break + iteration_data['lat_perc_max'] = (percentile == len(iteration_data['buckets'])) + iteration_data['lat_perc'] = percentile * iteration_data['bucket_size'] + delta_rx = t4_rx - t2_rx + delta_non_dp_rx = t4_non_dp_rx - t2_non_dp_rx + delta_tx = t4_tx - t2_tx + delta_non_dp_tx = t4_non_dp_tx - t2_non_dp_tx + delta_dp_tx = delta_tx -delta_non_dp_tx + delta_dp_rx = delta_rx -delta_non_dp_rx + iteration_data['abs_tx'] = delta_dp_tx + iteration_data['abs_rx'] = delta_dp_rx + iteration_data['abs_dropped'] += delta_dp_tx - delta_dp_rx + iteration_data['pps_req_tx'] = None + iteration_data['pps_tx'] = None + iteration_data['pps_sut_tx'] = None + iteration_data['drop_rate'] = 100.0*(iteration_data['abs_tx']-iteration_data['abs_rx'])/iteration_data['abs_tx'] + iteration_data['actual_duration'] = None + break ## Not really needed since the while loop will stop when evaluating the value of r + else: + sample_count = 0 + for percentile, bucket in enumerate(iteration_data['buckets'],start=1): + sample_count += bucket + if sample_count > sum(iteration_data['buckets']) * LAT_PERCENTILE: + break + iteration_data['lat_perc_max'] = (percentile == len(iteration_data['buckets'])) + iteration_data['lat_perc'] = percentile * iteration_data['bucket_size'] + iteration_data['pps_req_tx'] = (tot_tx + tot_drop - tot_rx)/iteration_data['actual_duration']/1000000.0 # tot_drop is all packets dropped by all tasks. This includes packets dropped at the generator task + packets dropped by the nop task. In steady state, this equals to the number of packets received by this VM + iteration_data['pps_tx'] = tot_tx/iteration_data['actual_duration']/1000000.0 # tot_tx is all generated packets actually accepted by the interface + iteration_data['pps_rx'] = tot_rx/iteration_data['actual_duration']/1000000.0 # tot_rx is all packets received by the nop task = all packets received in the gen VM + if self.sut_machine != None and sut_avail: + iteration_data['pps_sut_tx'] = tot_sut_tx / tot_sut_core_measurement_duration / 1000000.0 + else: + iteration_data['pps_sut_tx'] = None + iteration_data['abs_tx'] = (t4_tx - t1_tx) - (t4_non_dp_tx - t1_non_dp_tx) + iteration_data['abs_rx'] = (t4_rx - t1_rx) - (t4_non_dp_rx - t1_non_dp_rx) + iteration_data['abs_dropped'] = iteration_data['abs_tx'] - iteration_data['abs_rx'] + iteration_data['drop_rate'] = 100.0*iteration_data['abs_dropped']/iteration_data['abs_tx'] + if ((iteration_data['drop_rate'] < self.test['drop_rate_threshold']) or (iteration_data['abs_dropped'] == self.test['drop_rate_threshold'] ==0) or (iteration_data['abs_dropped'] > self.test['maxz'])): + break + self.gen_machine.stop_latency_cores() + iteration_data['abs_tx_fail'] = t4_tx_fail - t1_tx_fail + return (iteration_data) |