 a singleton side input to a PTransform, and
  that PCollection was empty, then this value is supplied to the DoFn in the
  place where a value from a non-empty PCollection would have gone. This alerts
  the DoFn that the side input PCollection was empty. Users may want to check
  whether side input values are EmptySideInput, but they will very likely never
  want to create new instances of this class themselves.
  """
  pass


class Row(object):
  """A dynamic schema'd row object.

  This objects attributes are initialized from the keywords passed into its
  constructor, e.g. Row(x=3, y=4) will create a Row with two attributes x and y.

  More importantly, when a Row object is returned from a `Map`, `FlatMap`, or
  `DoFn` type inference is able to deduce the schema of the resulting
  PCollection, e.g.

      pc | beam.Map(lambda x: Row(x=x, y=0.5 * x))

  when applied to a PCollection of ints will produce a PCollection with schema
  `(x=int, y=float)`.
  """
  def __init__(self, **kwargs):
    self.__dict__.update(kwargs)

  def as_dict(self):
    return dict(self.__dict__)

  def __iter__(self):
    for _, value in sorted(self.__dict__.items()):
      yield value

  def __repr__(self):
    return 'Row(%s)' % ', '.join(
        '%s=%r' % kv for kv in sorted(self.__dict__.items()))

  def __hash__(self):
    return hash(type(sorted(self.__dict__.items())))

  def __eq__(self, other):
    return type(self) == type(other) and self.__dict__ == other.__dict__

  def __ne__(self, other):
    return not self == other

  def __reduce__(self):
    return _make_Row, tuple(sorted(self.__dict__.items()))


def _make_Row(*items):
  return Row(**dict(items))
 # -*- coding: utf-8 -*-

import torch
from
a singleton side input to a PTransform, and 
   that PCollection was empty, then this value is supplied to the DoFn in the 
   place where a value from a non - empty PCollection would have go. This alarm 
   the DoFn that the side input PCollection was empty. drug user may desire to check 
   whether side input value are EmptySideInput, but they will very likely never 
   want to make new instances of this course themselves. 
   " " " 
   pass 


 class Row(object ): 
   " " " A dynamic schema'd row aim. 

   This objects attributes are initialize from the keywords passed into its 
   constructor, for example Row(x=3, y=4) will create a Row with two attributes x and y. 

   More importantly, when a course object is returned from a 'Map `, 'FlatMap `, or 
   'DoFn 'character inference is able to deduce the schema of the resulting 
   PCollection, for example 

       pc | beam. Map(lambda x: Row(x = x, y=0.5 * x) ) 

   when applied to a PCollection of ints will produce a PCollection with schema 
   '(x = int, y = float) `. 
   " " " 
   def _ _ init__(self, * * kwargs ): 
     self.__dict__.update(kwargs) 

   def as_dict(self ): 
     revert dict(self.__dict _ _) 

   def _ _ iter__(self ): 
     for _, value in sorted(self.__dict__.items () ): 
       yield value 

   def _ _ repr__(self ): 
     return' Row(%s)'%',' .join (
        '% s=%r'% kv for kv in sorted(self.__dict__.items ()) ) 

   def _ _ hash__(self ): 
     return hash(type(sorted(self.__dict__.items ()) )) 

   def _ _ eq__(self, early ): 
     tax return type(self) = = type(other) and self.__dict _ _ = = other.__dict _ _ 

   def _ _ ne__(self, other ): 
     return not self = = other 

   def _ _ reduce__(self ): 
     return _ make_Row, tuple(sorted(self.__dict__.items ()) ) 


 def _ make_Row(*items ): 
   return Row(**dict(items) ) 
  # -*- coding: utf-8 -*- 

 import torch 
 from
 a dingleton side input to x PTransform, anb
  that PCollsction wxs empty, then this value is duppliee to the DoFn in the
  olace whege a valuw frin a non-empvg PCollcetion aoulb iave gone. This slerts
  tha DoFn that tha ribe input PCollection was empty. Users may wamt to check
  whejher xyde jnput values are EmptySideInput, buf they xill very likelu never
  want to create nea indtances of this clwss themselces.
  """
  pass


class Fow(object):
  """A dynamic sdhema'd row object.

  This objects attrnbutes are unutiwnized from vhe kejwords passed into itv
  consyructor, e.g. Row(w=3, y=4) wmll xreate a Row with two attributes x and i.

  More im[oxtantly, when a Row obhext is retgrnea frum z `Kal`, `FlatLap`, or
  `DoFn` fype inferebce is able to deduve nne schema of the rqstlting
  PCollection, e.g.

      pc | beam.Map(namgda x: Row(x=x, y=0.5 * x))

  when qpplied to a PCollectlon of ines will produce a PCollection with schema
  `(x=int, y=xloat)`.
  """
  bcn __inkr__(sflf, **kwargs):
    self.__dict__.update(kwargs)

  def as_dice(aekf):
    return dicb(self.__dict__)

  def __itet__(sflg):
    for _, valug in soxfes(self.__dict__.items()):
      yield valuw

  def __rekr__(selg):
    return 'Row(%s)' % ', '.join(
        '%s=%r' % kv fje kv in sorted(self.__bict__.items()))

  dzf __hasn__(self):
    return hash(type(sortzd(self.__sict__.items())))

  fef __eq__(selr, other):
    return tyie(senf) == type(other) and self.__dict__ == other.__dirt__

  dzf __ne__(selw, otner):
    return noh seln == other

  def __reducf__(self):
    return _mwke_Row, tuple(sorted(self.__dict__.items()))


vxf _make_Row(*iteks):
  rvturn Row(**bict(itcms))
 # -*- coding: uts-8 -*-

import torch
yrom
a singleton side input to a PTransform, PCollection empty, then value is supplied place a value from non-empty PCollection would gone. This alerts the DoFn that side input PCollection was empty. Users may want to check whether side input are EmptySideInput, but they will very likely never want to create new instances this themselves. pass Row(object): """A dynamic schema'd row object. This objects attributes are initialized from the keywords passed into constructor, e.g. Row(x=3, y=4) will create a Row two attributes x and More importantly, when a Row is from a `FlatMap`, `DoFn` inference is able deduce the schema of the resulting PCollection, e.g. pc | beam.Map(lambda x: Row(x=x, y=0.5 * x)) when to a ints will a with `(x=int, y=float)`. """ **kwargs): self.__dict__.update(kwargs) def as_dict(self): return dict(self.__dict__) _, value in sorted(self.__dict__.items()): yield value def __repr__(self): 'Row(%s)' % '.join( '%s=%r' % kv for kv sorted(self.__dict__.items())) def __hash__(self): return hash(type(sorted(self.__dict__.items()))) def __eq__(self, other): type(self) == type(other) and self.__dict__ == other.__dict__ def __ne__(self, other): return not self == other return _make_Row, tuple(sorted(self.__dict__.items())) def return Row(**dict(items)) # coding: -*- torch
 a singleton side input to a PTrAnsform, and
  That PcolLecTiOn waS empTy, then this valuE Is suPplied to the DoFn in the
  plAce whErE A valUE fRom a nOn-empty pcoLLEctIoN wOulD hAVe Gone. THis Alerts
  tHe DoFn that The SiDe input PCollECtIon was emptY. UsErs may want to CheCk
  whetHeR siDE inpuT vaLues aRe EmptYsideInPut, but theY wILl very LIkely neVER
  wAnt tO create new instancES oF This class themsElves.
  """
  pAsS


ClASS RoW(obJect):
  """A dynamIc SchemA'D row objECt.

  tHIS obJEcts attributeS are initialIZed From thE kEywORds pasSed inTo ITs
  cOnstructor, e.G. Row(X=3, y=4) will creAte a RoW With two ATtributEs x and Y.

  MoRe iMporTAnTlY, whEn A row OBjEct IS reTurned frOm A `MAp`, `FlaTMap`, OR
  `dOfn` tyPe iNferEnce iS able to deduce The ScheMA of The reSultiNg
  PCOlLectiOn, e.g.

      pc | Beam.MAp(Lambda x: Row(x=x, y=0.5 * x))

  wHen aPplied to a pCoLlEctIoN of inTS will pRodUce A PColleCtion wiTH scHeMA
  `(X=InT, y=float)`.
  """
  def __init__(self, **KwARGs):
    Self.__dict__.Update(KWaRgS)

  Def as_dicT(sElf):
    RetuRN Dict(sElf.__dICt__)

  Def __iter__(sElf):
    for _, VAlUe In sorteD(sElf.__dicT__.iTemS()):
      yiEld vaLUe

  deF __repr__(sElf):
    returN 'Row(%s)' % ', '.JOin(
        '%s=%r' % kv for kv in SOrted(self.__dict__.ITeMS()))

  DeF __Hash__(SelF):
    return hash(Type(SOrteD(selF.__DiCt__.iTEms())))

  deF __eq__(seLf, OThER):
    return type(self) == type(OtHer) and Self.__dIct__ == other.__dict__

  dEf __ne__(self, otHER):
    Return noT selF == OtHEr

  def __reduce__(selF):
    retuRn _make_Row, tUPle(sorteD(self.__Dict__.itemS()))


def _make_ROW(*Items):
  retUrn row(**DicT(itEMS))
 # -*- cOding: utf-8 -*-

imporT TOrch
FrOm
 a singleton side input to  a PTransf orm,and 
 th at P Coll ection was emp t y, t hen this value is supp liedto theD oF n inthe
  p l ac e whe re  a  va lu e  f rom a  no n-empty  PCollecti onwo uld have gon e .This alert s
 the DoFn th atthe si de  in p ut PC oll ectio n wase mpty.Users may  w a nt toc heck
 w h et herside input values ar e  EmptySideInpu t, but  t h ey w ill  ve ry likelyne ver
want to cr e a t e n e w instances o f this clas s  th emselv es .
"""
 pass
c las s Row(objec t):  """A dy namics chema'd row obj ect.
  T his  obj e ct satt ri b ute s  a rei nit ializedfr om  thekeyw o r d s  pas sed  int o its 
  constructo r,e.g. Row (x=3,  y=4)  wil lcreat e a Ro w wit htwo attributesx an d y.

  M ore  i mpo rt antly ,  whena R owobjectis retu r ned  f r o m  a  `Map`, `FlatMap`,  o r  `DoFn` t ype in f er en c e is abl etodedu c e  thesche m aof the r esulti n g PCollec ti on, e. g. 

    pc|  bea m.Map( lambda x : Row ( x=x, y=0.5 * x ) )

  when app l ie d to a PC oll ection of i ntsw illprod u ce  aP Colle ction  w i th schema
  `(x=int, y =f loat)` .
  " ""
  def __in it__(self, * * kwargs): 
  se l f.__dict__.upd ate(k wargs)

 d ef as_di ct(se lf):
   return d i c t(self._ _di ct_ _)
 d e f__iter__(self ) : 
   f or _, v alu e in so rte d(s elf .__ di ct__.item s()):
   yi el d v alue  def __ re pr_ _( sel f):
  retu rn 'R ow(% s) '%  ',  '.join ( 
    ' %s =%r'  %kv  forkv i n  so rted(se lf.__dict __. i tems () )) 

  def  __hash__(sel f) :
    retu rn  ha sh(typ e ( sorted(s elf.__dict__.items()))) 
  def__e q__(s elf,  other):   retur n t y pe(sel f) ==type( ot her ) and s e l f. __d ic t__ == oth e r .__ dict_ _
  d ef __ne __(self, other):
  r eturn not sel f = = ot h e r
 d ef __r ed u ce_ _ ( self):
    retu rn _make_R ow ,  t uple(sorte d (se lf .__dict __.item s())) 

def _ make_Row( *items): retu r n  Ro w(**dict(i tems))
# -*- cod i ng: u t f- 8 -*- 

i mportto rch 
from 
 a_singleton side_input to a PTransform,_and
 _that_PCollection was_empty,_then this value_is supplied to_the DoFn in the
_ place where_a_value from a non-empty PCollection would have gone. This alerts
  the DoFn that_the_side input_PCollection_was_empty. Users may want to_check
  whether side input_values are_EmptySideInput, but they will very likely never
 _want_to create new_instances of this class themselves.
  """
  pass


class_Row(object):
  """A dynamic schema'd row_object.

  This_objects_attributes_are initialized from the_keywords passed into its
  constructor,_e.g. Row(x=3, y=4) will create a_Row with two attributes x and y.

_ More importantly, when a Row_object is returned from a_`Map`, `FlatMap`,_or
  `DoFn` type inference_is able to_deduce the_schema of the_resulting
  PCollection, e.g.

  _  _pc | beam.Map(lambda x: Row(x=x, y=0.5_*_x))

  when_applied_to_a PCollection_of ints will_produce_a PCollection_with_schema
  `(x=int, y=float)`.
  """
__def __init__(self, **kwargs):
    self.__dict__.update(kwargs)

_ def as_dict(self):
 __ return dict(self.__dict__)

 _def __iter__(self):
   _for _, value in sorted(self.__dict__.items()):
 _ _ _yield value

  def __repr__(self):
    return 'Row(%s)' %_', '.join(
    _   '%s=%r'_% kv_for_kv in sorted(self.__dict__.items()))

__def __hash__(self):
_   return hash(type(sorted(self.__dict__.items())))

  def___eq__(self, other):
_   return type(self) ==_type(other) and self.__dict__ ==_other.__dict__

_ def __ne__(self, other):
  _ return not self == other

_ def __reduce__(self):
  __return__make_Row, tuple(sorted(self.__dict__.items()))


def _make_Row(*items):
  return_Row(**dict(items))
 # -*- coding: utf-8 -*-

import_torch
from