text
stringlengths
1
93.6k
elif macpdutype == 1:
subidx = 2
macpdusubtype = int(bitstream[subidx:subidx + 1], 2)
if macpdusubtype == 0:
return Fragtype.MAC_INNER
elif macpdusubtype == 1:
return Fragtype.MAC_END
def getStartFbi(in_pdu):
bitstream = hex_to_binary(in_pdu)
return int(bitstream[2:3], 2)
def getFrEndFbi(in_pdu):
bitstream = hex_to_binary(in_pdu)
return int(bitstream[3:4], 2)
def stripFillingBin(in_bitstream):
bitstream = in_bitstream
for x in xrange(0, len(bitstream)):
streamidx = len(bitstream) - 1 - x
if int(bitstream[streamidx:streamidx + 1], 2) == 1:
return bitstream[:len(bitstream) - x - 1]
def stripFillingHex(in_pdu):
bitstream = hex_to_binary(in_pdu)
for x in xrange(0, len(bitstream)):
streamidx = len(bitstream) - 1 - x
if int(bitstream[streamidx:streamidx + 1], 2) == 1:
return bitstream[:len(bitstream) - x - 1]
def getFragTmsdu(in_bitstream):
if len(in_bitstream) == 272:
return in_bitstream[4:-4]
return in_bitstream[4:]
def getEndTmsdu(in_bitstream):
offset = 11
mac_end_li = int(in_bitstream[5:5 + 6], 2)
if int(in_bitstream[offset:offset + 1], 2) == 1:
offset = offset + 1 + 8
else:
offset += 1
if int(in_bitstream[offset:offset + 1], 2) == 1:
offset = offset + 1 + 22
if int(in_bitstream[offset:offset + 1], 2) == 1:
offset = offset + 1 + 10
else:
offset += 1
else:
offset += 1
# if int(in_bitstream[offset:offset+2],2) == 0:
# offset = offset + 4
# else:
# offset = offset + 2
outtmsdu = in_bitstream[offset:offset + (mac_end_li * 8)]
# print "END_MAC_LEN: " + str(mac_end_li*8)
# print "END_MAC_LEN_STRIPED: " + str(len(outtmsdu))
return outtmsdu
# <FILESEP>
#!/usr/bin/env python3
"""
major actions here: fine-tune the features and evaluate different settings
"""
import os
import torch
import warnings
import numpy as np
import random
import time
from time import sleep
from random import randint
import src.utils.logging as logging
from src.configs.config import get_cfg
from src.data import loader as data_loader
from src.engine.evaluator import Evaluator
from src.engine.trainer import Trainer
from src.models.build_model import build_model
from src.utils.file_io import PathManager
from launch import default_argument_parser, logging_train_setup
warnings.filterwarnings("ignore")