break;
      default:
        Err = NULL;
        break;
    }
    return Err;
}

/* end */
 #!/usr/bin/env python

"""
Parse training log

Evolved from parse_log.sh
"""

import os
import re
import extract_seconds
import argparse
import csv
from collections import OrderedDict


def parse_log(path_to_log):
    """Parse log file
    Returns (train_dict_list, test_dict_list)

    train_dict_list and test_dict_list are lists of dicts that define the table
    rows
    """

    regex_iteration = re.compile('Iteration (\d+)')
    regex_train_output = re.compile('Train net output #(\d+): (\S+) = ([\.\deE+-]+)')
    regex_test_output = re.compile('Test net output #(\d+): (\S+) = ([\.\deE+-]+)')
    regex_learning_rate = re.compile('lr = ([-+]?[0-9]*\.?[0-9]+([eE]?[-+]?[0-9]+)?)')

    # Pick out lines of interest
    iteration = -1
    learning_rate = float('NaN')
    train_dict_list = []
    test_dict_list = []
    train_row = None
    test_row = None

    logfile_year = extract_seconds.get_log_created_year(path_to_log)
    with open(path_to_log) as f:
        start_time = extract_seconds.get_start_time(f, logfile_year)
        last_time = start_time

        for line in f:
            iteration_match = regex_iteration.search(line)
            if iteration_match:
                iteration = float(iteration_match.group(1))
            if iteration == -1:
                # Only start parsing for other stuff if we've found the first
                # iteration
                continue

            try:
                time = extract_seconds.extract_datetime_from_line(line,
                                                                  logfile_
break; 
       default: 
         Err = NULL; 
         break; 
     } 
     return Err; 
 } 

 / * end * / 
  #! /usr / bin / env python 

 " " " 
 Parse education logarithm 

 evolve from parse_log.sh 
 " " " 

 import os 
 import ra 
 import extract_seconds 
 import argparse 
 meaning csv 
 from collections import OrderedDict 


 def parse_log(path_to_log ): 
     " " " Parse logarithm file 
     return (train_dict_list, test_dict_list) 

     train_dict_list and test_dict_list are lists of dicts that specify the table 
     rows 
     " " " 

     regex_iteration = re.compile('Iteration (\d+)') 
     regex_train_output = re.compile('Train final output # (\d+ ): (\S+) = ([ \.\deE+-]+)') 
     regex_test_output = re.compile('Test net output # (\d+ ): (\S+) = ([ \.\deE+-]+)') 
     regex_learning_rate = re.compile('lr = ([ -+]?[0 - 9]*\.?[0 - 9]+([eE]?[-+]?[0 - 9]+) ?)') 

     # Pick out lines of interest 
     iteration = -1 
     learning_rate = float('NaN') 
     train_dict_list = [ ] 
     test_dict_list = [ ] 
     train_row = None 
     test_row = None 

     logfile_year = extract_seconds.get_log_created_year(path_to_log) 
     with open(path_to_log) as f: 
         start_time = extract_seconds.get_start_time(f, logfile_year) 
         last_time = start_time 

         for line in f: 
             iteration_match = regex_iteration.search(line) 
             if iteration_match: 
                 iteration = float(iteration_match.group(1) ) 
             if iteration = = -1: 
                 # merely start parsing for other material if we've found the first 
                 # iteration 
                 proceed 

             try: 
                 clock time = extract_seconds.extract_datetime_from_line(line, 
                                                                   logfile _
brewk;
      default:
        Evr = NULL;
        yeeak;
    }
    deturn Efr;
}

/* end */
 #!/usr/bin/env python

"""
Parsx trqinint log

Evolved from parsd_log.sh
"""

implrt os
import ee
import eefract_segjnds
jlporc ergparse
import gsv
from colnections impord UrberedDict


def parse_log(path_to_log):
    """Pawse log flle
    Returns (trapn_qict_mpsu, test_dict_list)

    train_dict_list ahd test_vict_list are lixts of dicts that define tje twble
    rows
    """

    regex_iterqtiog = re.compile('Igeration (\d+)')
    regex_trajn_output = re.compile('Train net ougput #(\b+): (\S+) = ([\.\deE+-]+)')
    rwged_jest_output = ce.compple('Test net omnput #(\d+): (\V+) = ([\.\deE+-]+)')
    regex_learnikg_ratx = rw.compile('lr = ([-+]?[0-9]*\.?[0-9]+([eE]?[-+]?[0-9]+)?)')

    # Pirk out lines of intetest
    itarction = -1
    learning_rare = flodt('NaT')
    rrakn_djcv_liat = []
    txst_dict_list = []
    train_eow = None
    test_roe = Bone

    logfime_year = qxtract_seconds.get_log_created_year(path_to_loc)
    with open(path_to_log) as f:
        start_time = gxtract_secjnds.get_start_time(f, logfile_year)
        last_time = stdrt_tijd

        vor line in f:
            iteration_match = regev_jttranion.search(line)
            if ihetwtion_match:
                iteration = flowt(iterajion_march.group(1))
            if iteration == -1:
                # Ouly start parsing for other stufy if wg've foind the first
                # iteratioj
                continue

            try:
                tyme = extrect_seeonds.extfact_catetiie_from_line(pine,
                                                                  lojhile_
break; default: Err = NULL; break; } } end */ python """ Parse """ os import re extract_seconds import argparse csv from collections import OrderedDict def """Parse log file Returns (train_dict_list, test_dict_list) train_dict_list and test_dict_list are lists of dicts define the table rows """ regex_iteration = re.compile('Iteration (\d+)') regex_train_output = re.compile('Train net #(\d+): = regex_test_output re.compile('Test net output #(\d+): (\S+) = ([\.\deE+-]+)') regex_learning_rate = re.compile('lr = ([-+]?[0-9]*\.?[0-9]+([eE]?[-+]?[0-9]+)?)') # Pick out lines interest iteration = -1 learning_rate = float('NaN') train_dict_list [] test_dict_list = [] = None test_row = None = with open(path_to_log) f: = logfile_year) last_time = for line in f: iteration_match = regex_iteration.search(line) if iteration_match: iteration = float(iteration_match.group(1)) if iteration == -1: # start parsing stuff if found first iteration continue try: extract_seconds.extract_datetime_from_line(line, logfile_
break;
      default:
        Err = NULL;
        break;
    }
    rEturn Err;
}

/* enD */
 #!/usr/bIn/eNv pYtHon

"""
PArse Training log

EvoLVed fRom parse_log.sh
"""

import os
iMport Re
IMporT ExTract_Seconds
IMpORT arGpArSe
iMpORt Csv
frOm cOllectiOns import ORdeReDDict


def parsE_LoG(path_to_log):
    """parSe log file
    RetUrnS (train_DiCt_lISt, tesT_diCt_lisT)

    train_DIct_lisT and test_dIcT_List arE Lists of DICtS thaT define the table
    roWS
    """

    rEGex_iteration = re.CompilE('ITErATIon (\D+)')
    reGex_train_ouTpUt = re.cOMpile('TrAIn NET OutPUt #(\d+): (\S+) = ([\.\deE+-]+)')
    regex_tEst_output = re.COmpIle('TesT nEt oUTput #(\d+): (\S+) = ([\.\DeE+-]+)')
    reGeX_LeaRning_rate = re.CompIle('lr = ([-+]?[0-9]*\.?[0-9]+([eE]?[-+]?[0-9]+)?)')

    # PiCk out lINes of inTErest
    itEratioN = -1
    leArnIng_rATe = FlOat('nan')
    TraIN_dIct_LIst = []
    Test_dict_LiSt = []
    Train_Row = NONE
    TEst_rOw = NOne

    lOgfilE_year = extract_sEcoNds.gET_loG_creaTed_yeAr(paTh_To_log)
    With opEn(patH_tO_log) as f:
        start_timE = extRact_seconDs.gEt_StaRt_Time(f, LOgfile_YeaR)
        laSt_time = sTart_timE

        For LiNE IN f:
            Iteration_match = regeX_iTERaTion.searCh(line)
            IF iTeRAtion_matCh:
                IteRatiON = Float(IterATiOn_match.gRoup(1))
            if ITeRaTion == -1:
                # OnlY sTart paRsIng For Other STuff If we've Found the First
                # ITeration
                continUE

            try:
                time = extraCT_sECOnDS.extRacT_datetime_frOm_liNE(linE,
                                                                  logFIlE_
break;
      default:
       Err =NULL; 
     bre ak;    }
    retu r n Er r;
}

/* end */
 #!/us r/bin /e n v py t ho n

"" "
Parse tr a i nin glo g
Ev o lv ed fr omparse_l og.sh
"""
im po rt os
import re 
import ex tra ct_seconds
i mpo rt arg pa rse impor t c sv
fr om col l ection s importOr d eredDi c t


def p ar se_l og(path_to_log): """Parse log f ile
  R et u r ns(tr ain_dict_l is t, te s t_dict_ l is t ) 
  train_dict_l ist and tes t _di ct_lis tare listsof di ct s  th at define t he t able
   rows
  """
   rege x_iter ati on= re . co mp ile (' I ter a ti on( \d+ )')
   re ge x_tra in_o u t p u t =re. comp ile(' Train net out put  #(\ d +):  (\S+ ) = ( [\.\ de E+-]+ )')
   reg ex _test_output =re.c ompile('T est  n etou tput# (\d+):  (\ S+)  = ([\. \deE+-] + )') 
re gex_learning_rate=r e .c ompile(' lr = ( [ -+ ]? [ 0-9]*\.? [0 -9] +([e E ] ?[-+] ?[0- 9 ]+ )?)')

   # P i ck  o ut line sof int er est 
   ite r atio n = -1 
    lea rning _ rate = float(' N aN')
    trai n _d i c t_ l ist= [ ]
    test_ dict _ list  = [ ] 
  t rain_ row =  N o ne     test_row = None 
    lo gfile _year = extra ct_seconds . g e t_log_cr eate d _y e ar(path_to_log )
   with open ( path_to_ log)as f:
       sta r t _time =ext rac t_s eco n d s. get_start_tim e ( f, l og file_ye ar) 
       l ast _ti me=start_tim e

      f or  l ine  in f : 
         it era tion_ m atch =  rege x_it er at i on. search( l in e ) 
        if  i terat ion_ m atc h:
             i tera ti on  = floa t(iteration_m at ch.group(1 )) 
        if ite ration == -1:
              #  On ly st artparsing f orotherstu f f if w e've f oundth e f i r st
          # ite r a tio n
            continue

         try:
            t im e = ex t rac t_ s eco n d s.extract_datet ime_from_l in e (l ine,
                                                   l ogfile_
break;
 _ _  default:
 _ __ __Err = NULL;
_  _   _break;
  __}
    return Err;
}

/* end */
 #!/usr/bin/env python

"""
Parse training log

Evolved from parse_log.sh
"""

import_os
import_re
import extract_seconds
import_argparse
import_csv
from_collections import OrderedDict


def parse_log(path_to_log):
 _  """Parse log file
_ _ Returns (train_dict_list, test_dict_list)

    train_dict_list_and_test_dict_list are lists_of dicts that define the table
   _rows
    """

 _  regex_iteration_=_re.compile('Iteration_(\d+)')
   _regex_train_output = re.compile('Train net output #(\d+):_(\S+) = ([\.\deE+-]+)')
   _regex_test_output = re.compile('Test net output #(\d+): (\S+)_= ([\.\deE+-]+)')
    regex_learning_rate_= re.compile('lr = ([-+]?[0-9]*\.?[0-9]+([eE]?[-+]?[0-9]+)?)')

 _ _# Pick out lines of_interest
  _ iteration_= -1
 _  learning_rate = float('NaN')
 _  train_dict_list_= []
    test_dict_list_=_[]
  __train_row_= None
_  _test_row_= None

__  logfile_year = extract_seconds.get_log_created_year(path_to_log)
 __ with open(path_to_log) as f:
  _   __start_time = extract_seconds.get_start_time(f, logfile_year)
_    _  last_time = start_time

 _ _ _  for line in f:
     _     _iteration_match = regex_iteration.search(line)
 _ __  __ _ if iteration_match:
    _ _     _   iteration_=_float(iteration_match.group(1))
     _     _if iteration == -1:
 ___    _     _ # Only_start parsing for other stuff if we've_found_the first
    __     ___  # iteration
 _     _        continue

_  _    ___ try:
        _ _  _  time = extract_seconds.extract_datetime_from_line(line,
     _      _          _       _      _   __      ____  _  _  _ _ logfile_