diff --git a/run.py b/run.py
new file mode 100644
index 0000000..3fd8894
--- /dev/null
+++ b/run.py
@@ -0,0 +1,55 @@
+import os
+import copy
+import time
+import random
+import sys
+import shutil
+import subprocess
+
+from subprocess import STDOUT
+
+def execute(command):    
+    popen = subprocess.Popen(command, stdout=subprocess.PIPE)
+    lines_iterator = iter(popen.stdout.readline, b"")
+    for line in lines_iterator:
+        print(line) # yield line
+		
+#parameter w.r.t. MPI
+work_dir = 'D:\\Your Directory'
+port = '5719'
+machinefile= 'host.txt'
+
+#parameter w.r.t. SG-Mixture Training
+size = 50
+train = 'Your Training File'
+read_vocab = 'Your Vocab File'
+sense_file = 'Your Sense File, see sense_file.txt as an example'
+binary = 2
+init_learning_rate = 0.025
+epoch = 1
+window = 5
+threads = 8
+mincount = 5
+EM_iteration = 1
+momentum = 0.05
+top_n = 0
+top_ratio = 0
+default_sense = 1
+sense_num_multi = 5
+binary_embedding_file = 'emb.bin'
+text_embedding_file = 'emb.txt'
+huff_tree_file = 'huff.txt'
+outputlayer_binary_file = 'emb_out.bin'
+outputlayer_text_file = 'emb_out.txt'
+preload_cnt = 5
+data_block_size = 50000
+pipline = '0'
+multinomial = '0'
+
+mpi_args = '-port {0} -wdir {1} -machinefile {2} '.format(port, work_dir, machinefile)
+sg_mixture_args  = ' -train_file {0} -binary_embedding_file {1} -text_embedding_file {2} -threads {3} -size {4} -binary {5} -epoch {6} -init_learning_rate {7} -min_count {8} -window {9} -momentum {12} -EM_iteration {13} -top_n {14} -top_ratio {14} -default_sense {16} -sense_num_multi {17} -huff_tree_file {18} -vocab_file {19} -outputlayer_binary_file {20} -outputlayer_text_file {21} -read_sense {22} -data_block_size {23} -is_pipline {24} -store_multinomial {25} -max_preload_size {26}'.format(train, binary_embedding_file, text_embedding_file, threads, size, binary, epoch, init_learning_rate, mincount, window, momentum, EM_iteration, top_n,  top_ratio, default_sense, sense_num_multi, huff_tree_file, read_vocab, outputlayer_binary_file, outputlayer_text_file, sense_file, data_block_size, pipline, multinomial, preload_cnt)
+
+print mpi_args
+print sg_mixture_args
+
+proc = execute("mpiexec " + mpi_args + 'distributed_skipgram_mixture ' + sg_mixture_args)
diff --git a/sense_file.txt b/sense_file.txt
new file mode 100644
index 0000000..b719164
--- /dev/null
+++ b/sense_file.txt
@@ -0,0 +1,1724 @@
+love
+sex
+tiger
+cat
+book
+paper
+computer
+keyboard
+internet
+plane
+car
+train
+telephone
+communication
+television
+radio
+media
+drug
+abuse
+bread
+butter
+cucumber
+potato
+doctor
+nurse
+professor
+student
+smart
+stupid
+company
+stock
+market
+phone
+jaguar
+egg
+fertility
+live
+life
+library
+bank
+money
+wood
+forest
+cash
+king
+cabbage
+queen
+rook
+bishop
+rabbi
+holy
+fuck
+football
+soccer
+basketball
+tennis
+racket
+peace
+terror
+law
+lawyer
+movie
+star
+popcorn
+critic
+theater
+physics
+proton
+chemistry
+space
+alcohol
+vodka
+gin
+brandy
+drink
+ear
+mouth
+eat
+baby
+mother
+automobile
+gem
+jewel
+journey
+voyage
+boy
+lad
+coast
+shore
+asylum
+madhouse
+magician
+wizard
+midday
+noon
+furnace
+stove
+food
+fruit
+bird
+cock
+crane
+tool
+implement
+brother
+monk
+oracle
+cemetery
+woodland
+rooster
+hill
+graveyard
+slave
+chord
+smile
+glass
+string
+dollar
+currency
+wealth
+property
+possession
+deposit
+withdrawal
+laundering
+operation
+feline
+carnivore
+mammal
+animal
+organism
+fauna
+zoo
+psychology
+psychiatry
+anxiety
+fear
+depression
+clinic
+mind
+health
+science
+discipline
+cognition
+planet
+constellation
+moon
+sun
+galaxy
+astronomer
+precedent
+example
+information
+collection
+group
+antecedent
+cup
+coffee
+tableware
+article
+artifact
+object
+entity
+substance
+liquid
+energy
+secretary
+senate
+laboratory
+weapon
+secret
+fingerprint
+investigation
+effort
+water
+scientist
+news
+report
+canyon
+landscape
+image
+surface
+discovery
+seepage
+sign
+recess
+mile
+kilometer
+territory
+atmosphere
+president
+medal
+war
+troops
+record
+number
+skin
+eye
+history
+volunteer
+motto
+prejudice
+recognition
+decoration
+valor
+century
+year
+nation
+delay
+racism
+minister
+party
+plan
+minority
+attempt
+government
+crisis
+deployment
+departure
+announcement
+stroke
+hospital
+disability
+death
+victim
+emergency
+treatment
+recovery
+journal
+association
+personnel
+liability
+insurance
+school
+center
+reason
+hypertension
+criterion
+hundred
+percent
+infrastructure
+row
+inmate
+evidence
+term
+word
+similarity
+board
+recommendation
+governor
+interview
+country
+travel
+activity
+competition
+price
+consumer
+confidence
+problem
+airport
+flight
+credit
+card
+hotel
+reservation
+grocery
+registration
+arrangement
+accommodation
+month
+type
+kind
+arrival
+bed
+closet
+clothes
+situation
+conclusion
+isolation
+impartiality
+interest
+direction
+combination
+street
+place
+avenue
+block
+children
+listing
+proximity
+category
+cell
+production
+hike
+benchmark
+index
+trading
+gain
+dividend
+payment
+calculation
+computation
+oil
+warning
+profit
+loss
+yen
+buck
+software
+network
+hardware
+equipment
+maker
+luxury
+five
+investor
+earning
+baseball
+season
+game
+victory
+team
+marathon
+sprint
+series
+defeat
+seven
+seafood
+sea
+lobster
+wine
+preparation
+video
+archive
+start
+match
+round
+boxing
+championship
+tournament
+fighting
+defeating
+line
+day
+summer
+drought
+nature
+dawn
+environment
+ecology
+man
+woman
+murder
+manslaughter
+soap
+opera
+performance
+lesson
+focus
+crew
+film
+lover
+quarrel
+viewer
+serial
+possibility
+girl
+population
+development
+morality
+importance
+marriage
+gender
+equality
+change
+attitude
+family
+planning
+industry
+sugar
+approach
+practice
+institution
+ministry
+culture
+challenge
+size
+prominence
+citizen
+people
+issue
+experience
+music
+project
+metal
+aluminum
+chance
+credibility
+exhibit
+memorabilia
+concert
+virtuoso
+rock
+jazz
+museum
+observation
+architecture
+world
+preservation
+admission
+ticket
+shower
+thunderstorm
+flood
+weather
+forecast
+disaster
+area
+office
+brazil
+nut
+triple
+cd
+aglow
+harvard
+yale
+cambridge
+israel
+east
+israeli
+japanese
+american
+jerusalem
+wall
+mexico
+puebla
+opec
+saudi
+palestinian
+arab
+wednesday
+weekday
+haven
+ability
+know-how
+persecution
+accepted
+acknowledged
+believe
+welcome
+accommodate
+adjust
+settlement
+acronym
+form
+inaction
+confession
+matriculation
+advance
+headway
+propose
+advised
+inform
+affect
+tense
+aged
+develop
+old
+worn
+young
+aim
+cause
+hold
+thing
+airfield
+sterol
+component
+ambush
+surprise
+herbivore
+statement
+answering
+counter
+react
+worry
+access
+converge
+arch
+curve
+building
+urban
+shoulder
+flower
+weight
+ash
+bone
+assignment
+document
+assimilation
+americanization
+realtor
+astrophysicist
+bedlam
+shelter
+stp
+crime
+attempted
+initiate
+give
+attended
+guard
+respect
+window
+treat
+back
+lumbar
+out
+second
+side
+riverbank
+base
+air
+build
+structure
+ball
+tip-off
+bat
+bats
+placental
+turn
+beam
+signal
+plant
+platform
+plot
+point
+bent
+double
+inclination
+bias
+experimenter
+bigger
+large
+meat
+bitter
+ale
+resentful
+taste
+close
+blow
+blowing
+exhale
+insufflate
+blown
+swat
+deal
+directorate
+open
+phrase
+picture
+booster
+advertiser
+advocate
+bootleg
+covering
+produce
+whiskey
+bore
+cut
+flow
+stuff
+bound
+boundary
+skirt
+vault
+bow
+knot
+bowling
+wheel
+yield
+hit
+angstrom
+branching
+bifurcation
+grow
+cover
+bring
+return
+bronze
+nickel
+sculpture
+freemason
+bill
+horse
+buffer
+zone
+bug
+defect
+insect
+burning
+important
+burnt
+treated
+bury
+hide
+lay
+steal
+cake
+dish
+tablet
+interpolation
+camp
+gathering
+camping
+pitch
+capital
+assets
+primary
+seed
+playing
+ration
+see
+limousine
+predator
+carrier
+traveler
+vehicle
+cast
+shoot
+catching
+catch
+perceive
+compartment
+membrane
+site
+central
+fiscal
+refer
+think
+tract
+integer
+litigate
+contest
+fortune
+ring
+relation
+channels
+transmission
+charcoal
+fuel
+checked
+examine
+offspring
+cholera
+infectious
+arpeggio
+play
+circulation
+dissemination
+citation
+act
+award
+national
+clean
+dry
+jerk
+remove
+clear
+innocence
+make
+session
+closed
+state
+up
+storage
+toilet
+closing
+finale
+motion
+snap
+glide
+slope
+penis
+populace
+collect
+due
+archives
+data
+prayer
+scrape
+take
+colored
+black
+grey
+colors
+emblem
+ensign
+pigment
+scheme
+commit
+vow
+abstraction
+communications
+compact
+case
+pack
+packed
+short
+write
+compound
+enhance
+recombine
+whole
+conversion
+procedure
+assumption
+judgment
+connect
+natural
+topology
+content
+disapproval
+limit
+convinced
+disarm
+cool
+air-conditioned
+coldness
+answer
+negative
+ally
+course
+stream
+workshop
+blanket
+cloak
+submerge
+crabs
+crab
+crack
+check
+cracking
+noise
+sound
+ovation
+condition
+measurement
+cross
+marking
+meet
+gherkin
+melon
+counterculture
+subculture
+shape
+curb
+bit
+smother
+exchange
+prevalence
+cutting
+nip
+damned
+lost
+raise
+begin
+hour
+morrow
+deaf
+organic
+deceased
+born
+dead
+service
+set
+disappointment
+defeated
+upset
+ending
+overrun
+veto
+defense
+biological
+protection
+hesitate
+moratorium
+deliver
+serve
+demand
+call
+claim
+request
+supply
+demonic
+evil
+variation
+redeployment
+geological
+derived
+reap
+mental
+deepening
+elaboration
+qibla
+anorgasmia
+disabled
+unfit
+adversity
+wave
+system
+breakthrough
+disclosure
+display
+light
+model
+stick
+ditch
+abandon
+drain
+waterway
+numerator
+diving
+one-half
+theologian
+dominican
+dot
+disk
+seashore
+multiple
+draw
+entertainer
+gully
+drawing
+drag
+frame
+twitch
+dress
+formal
+morning
+neckline
+wear
+drive
+impulse
+mechanism
+operate
+ride
+drop
+descend
+measure
+dropping
+sink
+teardrop
+time
+anesthetic
+dwelling
+exist
+education
+effects
+backdate
+happen
+repercussion
+liberation
+white
+eliminate
+temp
+emphasized
+stress
+endeavor
+worst
+force
+heat
+habitat
+equal
+differ
+inadequate
+sameness
+tie
+person
+rescue
+establishment
+collectivization
+even
+identification
+notarize
+specimen
+parade
+possess
+show
+inexperience
+suffer
+extension
+expansion
+look
+fail
+choke
+shipwreck
+fair
+join
+midway
+moderate
+child
+famine
+irish
+lack
+fast
+abstain
+hunger
+sudden
+avifauna
+fearlessness
+panic
+sterility
+fiction
+canard
+fantasy
+field
+handle
+brush
+resist
+filled
+medium
+fine
+precise
+firm
+corporation
+hard
+forward
+fleet
+aircraft
+sortie
+debacle
+fill
+flush
+age
+down
+good
+rich
+fly
+blur
+concentration
+distinctness
+follow
+evaluate
+predict
+prognosis
+biome
+growth
+abbreviation
+fort
+presidio
+bold
+player
+position
+transport
+found
+wage
+freeing
+parole
+freelance
+work
+bear
+product
+intercourse
+fire
+full
+further
+far
+promote
+fused
+gauge
+united
+account
+obtain
+gallery
+audience
+parlay
+playoff
+gas
+sewer
+art
+crystalline
+asexual
+gen
+gig
+harpoon
+seidel
+gone
+gore
+blood
+pierce
+control
+graduate
+confer
+high
+instrument
+receive
+scholar
+greater
+shelf
+vinyl
+fractious
+soft
+weaponry
+hay
+fodder
+healing
+better
+illness
+heel
+stack
+height
+degree
+increase
+tor
+recital
+topographical
+home
+away
+honest
+sincere
+honey
+hooks
+hand
+hot
+calorific
+violent
+cardiovascular
+ice
+appearance
+visualize
+use
+standing
+increased
+add
+enhanced
+maximize
+list
+mass
+safety
+enterprise
+confirmation
+datum
+initial
+first
+letter
+resident
+instability
+disorder
+vicariate
+instruction
+recipe
+contract
+benefit
+enthusiasm
+intermediate
+chemical
+introduction
+opening
+usher
+count
+fishing
+iron
+alpha
+robust
+alienation
+solitude
+edit
+edition
+overriding
+unblock
+neck
+writing
+ship
+keep
+continue
+stronghold
+holder
+typeset
+rival
+region
+exclude
+painting
+scenery
+language
+soliloquy
+last
+end
+past
+populate
+rank
+run
+senior
+machine
+wash
+joke
+mosaic
+barrister
+song
+learned
+discover
+educated
+scholarly
+left
+dad
+admonition
+lever
+house
+being
+lift
+aid
+consequence
+lower
+move
+lighter
+heavy
+headlight
+lighten
+smoke
+limb
+branch
+crib
+lie
+matter
+organization
+post
+sick
+shopping
+looking
+search
+sightseeing
+sparkle
+reducing
+wastage
+sleep
+agape
+care
+like
+lowering
+decrease
+devalue
+movement
+reef
+escapologist
+magus
+manufacturer
+homicide
+manufacture
+commercial
+mark
+broad
+buoy
+class
+labor
+shop
+trade
+spouse
+married
+final
+matchstick
+mature
+distinguish
+telecommunication
+mention
+allusion
+comment
+photograph
+merit
+demerit
+worthiness
+silver
+tombac
+middle
+phase
+put
+milk
+nutriment
+recall
+mine
+strip
+sulfur
+clergyman
+foreign
+priesthood
+minor
+miss
+failure
+mock
+derision
+tease
+ptolemaic
+mole
+spy
+pile
+religious
+solar
+week
+inner
+virtue
+morocco
+levant
+moroccan
+motel
+motor
+mother-in-law
+yeast
+agent
+stepper
+catchphrase
+mourning
+sadness
+beak
+tongue
+ms
+gulf
+depository
+narrow
+determine
+limited
+strait
+spanish
+characteristic
+nerves
+psychological
+newspaper
+item
+publisher
+update
+nobility
+aristocrat
+majority
+practical
+business
+printing
+offset
+balance
+compensation
+rift
+musical
+action
+prophecy
+orchestrated
+score
+individual
+oxygen
+battalion
+panorama
+parent
+part
+interruption
+dance
+union
+pass
+accomplishment
+passing
+done
+leave
+patronage
+blessing
+pat
+touch
+repayment
+amity
+occupancy
+perfect
+polish
+unbroken
+magic
+department
+police
+delegate
+siphon
+plain
+knit
+llano
+obvious
+simple
+employee
+seaplane
+follower
+schedule
+plasma
+gamma
+curtain
+played
+die
+foul
+thousand
+poll
+homo
+straw
+vote
+pop
+father
+overpopulation
+criminal
+liabilities
+expectation
+vine
+pound
+formalism
+learn
+prairie
+grassland
+civil
+smell
+self-preservation
+pressing
+squeeze
+cost
+principle
+hellenism
+yin
+print
+contact
+difficulty
+poser
+growing
+academician
+advantage
+bulge
+projecting
+communicate
+moneymaker
+limelight
+promise
+betrothal
+declare
+pledge
+nucleon
+vicinity
+psychotherapy
+argue
+quiet
+louden
+order
+leader
+title
+anti-semitism
+profiling
+broadcasting
+raising
+bump
+rise
+upbringing
+reading
+interpretation
+read
+explanation
+generalize
+present
+rebel
+soldier
+designation
+advice
+puff
+improvement
+rally
+reduced
+abbreviate
+bated
+low
+reduce
+simplify
+slash
+reed
+body
+entrance
+relieve
+comfort
+free
+announce
+blue
+resistance
+resolution
+physical
+retirement
+status
+reverse
+gear
+opposition
+right
+proper
+chondrite
+limestone
+rod
+role
+hat
+rolling
+robbery
+romance
+intrigue
+quality
+chicken
+rose
+damask
+soar
+rough
+crushed
+golf
+ammunition
+dispute
+terrace
+rubber
+crepe
+running
+dash
+sacrifice
+kill
+sales
+divestiture
+income
+sample
+satellite
+outer
+scattered
+break
+disband
+incoherent
+alumnus
+virtuosity
+cosmographer
+south
+leap
+ordinal
+assistant
+password
+appreciate
+diocese
+seeing
+exudation
+sent
+ordered
+quarterly
+broadcast
+spot
+foreplay
+sheet
+expanse
+worksheet
+shifting
+shining
+shooting
+sucker
+arrive
+diamond
+shot
+colorful
+grapeshot
+plumbing
+token
+single
+common
+singles
+badminton
+singleton
+sit
+element
+classify
+coat
+magnitude
+slain
+worker
+slight
+dismiss
+insignificant
+silent
+slip
+freudian
+slow
+gradual
+smashing
+blast
+expression
+smoking
+emit
+inhale
+vaporization
+bribe
+saddle
+compatible
+sole
+solo
+perform
+sounding
+depth
+location
+spiral
+coiled
+helix
+splash
+spread
+discharge
+disparity
+dispersion
+distributed
+square
+angular
+lawful
+polygon
+stalls
+livery
+have
+path
+beginning
+starter
+get
+stated
+still
+silence
+merchandise
+stocks
+framework
+heater
+striking
+conspicuous
+crash
+impressive
+arrange
+fingerboard
+strike
+study
+examination
+learning
+review
+submarine
+sandwich
+subordinate
+dog
+insubordinate
+under
+succeeding
+suffering
+enjoy
+pain
+beet
+solstice
+sunburst
+bubble
+horizontal
+suspension
+lapse
+sway
+power
+cutlery
+color
+telling
+narration
+referent
+tenure
+africa
+box
+things
+expect
+storm
+tag
+means
+topping
+tops
+crown
+touched
+touching
+universe
+trace
+support
+traffic
+commerce
+gravitation
+tour
+walk
+dealing
+trench
+trick
+deceive
+shift
+daze
+hostile
+march
+trouble
+perturbation
+twist
+adult
+identify
+version
+uniform
+jump
+upgrade
+afflict
+agitation
+disturbance
+troubled
+application
+consume
+used
+functional
+usual
+familiar
+vanished
+vector
+radius
+videotape
+violate
+musician
+vision
+imagination
+screwdriver
+void
+invalid
+nonexistence
+validate
+waking
+sleeping
+walking
+accompany
+locomotion
+wade
+wandering
+about
+stray
+battle
+hostility
+strategic
+shampoo
+lake
+perspiration
+wet
+ways
+shipyard
+weak
+diluted
+weakening
+transformation
+flimsy
+abundance
+persuasion
+precipitation
+welsh
+brythonic
+wetness
+bleach
+light-skinned
+dark
+delaware
+withdraw
+retrograde
+female
+silva
+red
+workings
+excavation
+chow
+poor
+result
+wounded
+wrong
+false
+improper
+injury
+y2k
+yielding
+assent
+facility
+undertaking
+retail
+credence
+bundle
+overlook
+happening
+room
+relearn
+express
+anagram
+insane
+awake
+lamb
+mutiny
+enclose
+mute
+foundation
+nonprofessional
+grazed
+extort
+efferent
+brave
+hurl
+asian
+longing
+intolerable
+grieve
+hailstone
+considered
+wind
+kick
+formation
+scan
+protest
+desk
+indirect
+compel
+prepared
+ask
+stabilize
+conference
+impermanent
+backward
+solemnize
+liquidate
+damage
+likeness
+constitute
+patterned
+prepare
+english
+lip
+nearness
+nonexistent
+imperative
+mocha
+sauce
+living
+calmness
+male
+flap
+maradona
+arafat
diff --git a/src/multiverso_skipgram_mixture.cpp b/src/multiverso_skipgram_mixture.cpp
index f7890a2..87e9435 100755
--- a/src/multiverso_skipgram_mixture.cpp
+++ b/src/multiverso_skipgram_mixture.cpp
@@ -1,4 +1,4 @@
-#include "multiverso_skipgram_mixture.h"
+#include "MultiversoSkipGramMixture.h"
 #include <algorithm>
 
 MultiversoSkipGramMixture::MultiversoSkipGramMixture(Option *option, Dictionary *dictionary, HuffmanEncoder *huffman_encoder, Reader *reader)
@@ -35,7 +35,7 @@ void MultiversoSkipGramMixture::InitSenseCntInfo()
 		m_word_sense_info.word_sense_cnts_info[wordlist[i].first] = 1;
 
 	//Then, read words #sense info from the sense file
-	if (m_option->sense_file) 
+	if (m_option->sense_file)
 	{
 		FILE* fid = fopen(m_option->sense_file, "r");
 		char word[1000];
@@ -58,7 +58,7 @@ void MultiversoSkipGramMixture::InitSenseCntInfo()
 	int cnt = 0;
 	m_word_sense_info.multi_senses_words_cnt = 0;
 
-	for (int i = 0; i < m_dictionary->Size(); ++i) 
+	for (int i = 0; i < m_dictionary->Size(); ++i)
 	{
 		m_word_sense_info.p_input_embedding[i] = cnt;
 		if (m_word_sense_info.word_sense_cnts_info[i] > 1)
@@ -107,7 +107,7 @@ void MultiversoSkipGramMixture::Train(int argc, char *argv[])
 	multiverso::Log::ResetLogFile("log.txt");
 	m_process_id = multiverso::Multiverso::ProcessRank();
 	PrepareMultiversoParameterTables(m_option, m_dictionary);
-	
+
 	printf("Start to train ...\n");
 	TrainNeuralNetwork();
 	printf("Rank %d Finish training\n", m_process_id);
@@ -156,7 +156,7 @@ void MultiversoSkipGramMixture::PrepareMultiversoParameterTables(Option *opt, Di
 	{
 		for (int col = 0; col < opt->sense_num_multi; ++col)
 		{
-			multiverso::Multiverso::AddToServer<real>(kWordSensePriorTableId, row, col, 
+			multiverso::Multiverso::AddToServer<real>(kWordSensePriorTableId, row, col,
 				static_cast<real>(m_option->store_multinomial ? 1.0 / m_option->sense_num_multi : log(1.0 / m_option->sense_num_multi)));
 		}
 	}
@@ -198,7 +198,7 @@ void MultiversoSkipGramMixture::PushDataBlock(
 	{
 		std::chrono::milliseconds dura(200);
 		std::this_thread::sleep_for(dura);
-		
+
 		RemoveDoneDataBlock(datablock_queue);
 	}
 }
diff --git a/src/param_loader.cpp b/src/param_loader.cpp
index f1117d7..f2be012 100755
--- a/src/param_loader.cpp
+++ b/src/param_loader.cpp
@@ -1,4 +1,4 @@
-#include "param_loader.h"
+#include "ParamLoader.h"
 
 template<typename T>
 ParameterLoader<T>::ParameterLoader(Option *option, void** word2vector_neural_networks, WordSenseInfo* word_sense_info)
@@ -21,12 +21,12 @@ void ParameterLoader<T>::ParseAndRequest(multiverso::DataBlockBase *data_block)
 	fprintf(m_log_file, "%lf\n", (clock() - m_start_time) / (double)CLOCKS_PER_SEC);
 	multiverso::Log::Info("Rank %d ParameterLoader begin %d\n", multiverso::Multiverso::ProcessRank(), m_parse_and_request_count);
 	DataBlock *data = reinterpret_cast<DataBlock*>(data_block);
-	
+
 	SkipGramMixtureNeuralNetwork<T>* sg_mixture_neural_network = reinterpret_cast<SkipGramMixtureNeuralNetwork<T>*>(m_sgmixture_neural_networks[m_parse_and_request_count % 2]);
 	++m_parse_and_request_count;
 	data->UpdateNextRandom();
 	sg_mixture_neural_network->PrepareParmeter(data);
-	
+
 	std::vector<int>& input_layer_nodes = sg_mixture_neural_network->GetInputLayerNodes();
 	std::vector<int>& output_layer_nodes = sg_mixture_neural_network->GetOutputLayerNodes();
 	assert(sg_mixture_neural_network->status == 0);
@@ -62,4 +62,4 @@ void ParameterLoader<T>::ParseAndRequest(multiverso::DataBlockBase *data_block)
 }
 
 template class ParameterLoader<float>;
-template class ParameterLoader<double>;
+template class ParameterLoader<double>;
\ No newline at end of file
diff --git a/src/skipgram_mixture_neural_network.cpp b/src/skipgram_mixture_neural_network.cpp
index 2c3370c..9eab9bf 100755
--- a/src/skipgram_mixture_neural_network.cpp
+++ b/src/skipgram_mixture_neural_network.cpp
@@ -1,7 +1,7 @@
-#include "skipgram_mixture_neural_network.h"
+#include "SkipGramMixtureNeuralNetwork.h"
 
 template<typename T>
-SkipGramMixtureNeuralNetwork<T>::SkipGramMixtureNeuralNetwork(Option* option, HuffmanEncoder* huffmanEncoder, WordSenseInfo* word_sense_info,  Dictionary* dic, int dicSize)
+SkipGramMixtureNeuralNetwork<T>::SkipGramMixtureNeuralNetwork(Option* option, HuffmanEncoder* huffmanEncoder, WordSenseInfo* word_sense_info, Dictionary* dic, int dicSize)
 {
 	status = 0;
 	m_option = option;
@@ -37,18 +37,18 @@ SkipGramMixtureNeuralNetwork<T>::~SkipGramMixtureNeuralNetwork()
 }
 
 template<typename T>
-void SkipGramMixtureNeuralNetwork<T>::Train(int* sentence, int sentence_length, T* gamma, T* fTable, T* input_backup)
+void SkipGramMixtureNeuralNetwork<T>::Train(int* sentence, int sentence_length, T* gamma, T* f_table, T* input_backup)
 {
-	ParseSentence(sentence, sentence_length, gamma, fTable, input_backup, &SkipGramMixtureNeuralNetwork<T>::TrainSample);
+	ParseSentence(sentence, sentence_length, gamma, f_table, input_backup, &SkipGramMixtureNeuralNetwork<T>::TrainSample);
 }
 
 template<typename T>
 //The E - step, estimate the posterior multinomial probabilities
-T SkipGramMixtureNeuralNetwork<T>::Estimate_Gamma_m(int word_input, std::vector<std::pair<int, int> >& output_nodes, T* posterior_ll, T* estimation, T* sense_prior, T* f_m)
+T SkipGramMixtureNeuralNetwork<T>::EstimateGamma(int word_input, std::vector<std::pair<int, int> >& output_nodes, T* posterior_ll, T* estimation, T* sense_prior, T* f_m)
 {
-	T* inputEmbedding = m_input_embedding_weights_ptr[word_input];
+	T* input_embedding = m_input_embedding_weights_ptr[word_input];
 	T f, log_likelihood = 0;
-	for (int sense_idx = 0; sense_idx < m_word_sense_info->word_sense_cnts_info[word_input]; ++sense_idx, inputEmbedding += m_option->embeding_size)
+	for (int sense_idx = 0; sense_idx < m_word_sense_info->word_sense_cnts_info[word_input]; ++sense_idx, input_embedding += m_option->embeding_size)
 	{
 		posterior_ll[sense_idx] = sense_prior[sense_idx] < eps ? MIN_LOG : log(sense_prior[sense_idx]); //posterior likelihood for each sense
 
@@ -56,7 +56,7 @@ T SkipGramMixtureNeuralNetwork<T>::Estimate_Gamma_m(int word_input, std::vector<
 
 		for (int d = 0; d < output_nodes.size(); ++d, fidx++)
 		{
-			f = Util::InnerProduct(inputEmbedding, m_output_embedding_weights_ptr[output_nodes[d].first], m_option->embeding_size);
+			f = Util::InnerProduct(input_embedding, m_output_embedding_weights_ptr[output_nodes[d].first], m_option->embeding_size);
 			f = Util::Sigmoid(f);
 			f_m[fidx] = f;
 			if (output_nodes[d].second) //huffman code, 0 or 1
@@ -78,7 +78,7 @@ T SkipGramMixtureNeuralNetwork<T>::Estimate_Gamma_m(int word_input, std::vector<
 
 template<typename T>
 //The M Step: update the sense prior probabilities to maximize the Q function
-void SkipGramMixtureNeuralNetwork<T>::Maximize_Pi(int word_input, T* log_likelihood)
+void SkipGramMixtureNeuralNetwork<T>::MaximizeSensePriors(int word_input, T* log_likelihood)
 {
 	if (m_word_sense_info->word_sense_cnts_info[word_input] == 1)
 	{
@@ -101,11 +101,11 @@ void SkipGramMixtureNeuralNetwork<T>::UpdateEmbeddings(int word_input, std::vect
 {
 	T g;
 	T* output_embedding;
-	T* inputEmbedding;
+	T* input_embedding;
 	if (direction == UpdateDirection::UPDATE_INPUT)
-		inputEmbedding = m_input_embedding_weights_ptr[word_input];
-	else inputEmbedding = input_backup;
-	for (int sense_idx = 0; sense_idx < m_word_sense_info->word_sense_cnts_info[word_input]; ++sense_idx, inputEmbedding += m_option->embeding_size)
+		input_embedding = m_input_embedding_weights_ptr[word_input];
+	else input_embedding = input_backup;
+	for (int sense_idx = 0; sense_idx < m_word_sense_info->word_sense_cnts_info[word_input]; ++sense_idx, input_embedding += m_option->embeding_size)
 	{
 		int64_t fidx = sense_idx * MAX_CODE_LENGTH;
 		for (int d = 0; d < output_nodes.size(); ++d, ++fidx)
@@ -115,12 +115,12 @@ void SkipGramMixtureNeuralNetwork<T>::UpdateEmbeddings(int word_input, std::vect
 			if (direction == UpdateDirection::UPDATE_INPUT) //Update Input
 			{
 				for (int j = 0; j < m_option->embeding_size; ++j)
-					inputEmbedding[j] += g * output_embedding[j];
+					input_embedding[j] += g * output_embedding[j];
 			}
 			else  // Update Output
 			{
 				for (int j = 0; j < m_option->embeding_size; ++j)
-					output_embedding[j] += g * inputEmbedding[j];
+					output_embedding[j] += g * input_embedding[j];
 			}
 		}
 	}
@@ -132,7 +132,7 @@ template<typename T>
 void SkipGramMixtureNeuralNetwork<T>::TrainSample(int input_node, std::vector<std::pair<int, int> >& output_nodes, void* v_gamma, void* v_fTable, void* v_input_backup)
 {
 	T* gamma = (T*)v_gamma; //stores the posterior probabilities
-	T* fTable = (T*)v_fTable; //stores the inner product values of input and output embeddings
+	T* f_table = (T*)v_fTable; //stores the inner product values of input and output embeddings
 	T* input_backup = (T*)v_input_backup;
 
 	T posterior_ll[MAX_SENSE_CNT]; //stores the posterior log likelihood
@@ -149,16 +149,16 @@ void SkipGramMixtureNeuralNetwork<T>::TrainSample(int input_node, std::vector<st
 		log_likelihood = 0;
 
 		// E-Step
-		log_likelihood += Estimate_Gamma_m(input_node, output_nodes, posterior_ll, gamma, sense_prior, fTable);
+		log_likelihood += EstimateGamma(input_node, output_nodes, posterior_ll, gamma, sense_prior, f_table);
 
 		// M-Step
 		if (m_option->store_multinomial)
-			Maximize_Pi(input_node, gamma);
+			MaximizeSensePriors(input_node, gamma);
 		else
-			Maximize_Pi(input_node, posterior_ll);
+			MaximizeSensePriors(input_node, posterior_ll);
 
-		UpdateEmbeddings(input_node, output_nodes, gamma, fTable, input_backup, UpdateDirection::UPDATE_INPUT);
-		UpdateEmbeddings(input_node, output_nodes, gamma, fTable, input_backup, UpdateDirection::UPDATE_OUTPUT);
+		UpdateEmbeddings(input_node, output_nodes, gamma, f_table, input_backup, UpdateDirection::UPDATE_INPUT);
+		UpdateEmbeddings(input_node, output_nodes, gamma, f_table, input_backup, UpdateDirection::UPDATE_OUTPUT);
 
 	}
 }
@@ -205,10 +205,10 @@ void SkipGramMixtureNeuralNetwork<T>::DealPrepareParameter(int input_node, std::
 
 template<typename T>
 /*
-  Parse a sentence and deepen into two branchs:
-  one for TrainNN, the other one is for Parameter_parse&request
+Parse a sentence and deepen into two branchs:
+one for TrainNN, the other one is for Parameter_parse&request
 */
-void SkipGramMixtureNeuralNetwork<T>::ParseSentence(int* sentence, int sentence_length, T* gamma, T* fTable, T* input_backup, FunctionType function)
+void SkipGramMixtureNeuralNetwork<T>::ParseSentence(int* sentence, int sentence_length, T* gamma, T* f_table, T* input_backup, FunctionType function)
 {
 	if (sentence_length == 0)
 		return;
@@ -220,7 +220,7 @@ void SkipGramMixtureNeuralNetwork<T>::ParseSentence(int* sentence, int sentence_
 	{
 		if (sentence[sentence_position] == -1) continue;
 		int feat_size = 0;
-		
+
 		for (int i = 0; i < m_option->window_size * 2 + 1; ++i)
 			if (i != m_option->window_size)
 			{
@@ -233,7 +233,7 @@ void SkipGramMixtureNeuralNetwork<T>::ParseSentence(int* sentence, int sentence_
 					input_node = feat[feat_size - 1];
 					output_nodes.clear();
 					Parse(input_node, sentence[sentence_position], output_nodes);
-					(this->*function)(input_node, output_nodes, gamma, fTable, input_backup);
+					(this->*function)(input_node, output_nodes, gamma, f_table, input_backup);
 				}
 			}
 	}
@@ -282,7 +282,7 @@ std::vector<int>& SkipGramMixtureNeuralNetwork<T>::GetOutputLayerNodes()
 }
 
 template<typename T>
-void SkipGramMixtureNeuralNetwork<T>::SetInputEmbeddingWeights(int input_node_id, T* ptr)
+void SkipGramMixtureNeuralNetwork<T>::SetinputEmbeddingWeights(int input_node_id, T* ptr)
 {
 	m_input_embedding_weights_ptr[input_node_id] = ptr;
 }
@@ -306,7 +306,7 @@ void SkipGramMixtureNeuralNetwork<T>::SetSensePriorParaWeights(int input_node_id
 }
 
 template<typename T>
-T* SkipGramMixtureNeuralNetwork<T>::GetInputEmbeddingWeights(int input_node_id)
+T* SkipGramMixtureNeuralNetwork<T>::GetinputEmbeddingWeights(int input_node_id)
 {
 	return m_input_embedding_weights_ptr[input_node_id];
 }
diff --git a/src/skipgram_mixture_neural_network.h b/src/skipgram_mixture_neural_network.h
index 2471fc2..7b98d30 100755
--- a/src/skipgram_mixture_neural_network.h
+++ b/src/skipgram_mixture_neural_network.h
@@ -17,6 +17,146 @@ enum class UpdateDirection
 template<typename T>
 class SkipGramMixtureNeuralNetwork
 {
+#pragma once
+
+#include <vector>
+
+#include "Util.h"
+#include <multiverso.h>
+#include "HuffmanEncoder.h"
+#include "MultiversoSkipGramMixture.h"
+#include "cstring"
+
+	enum class UpdateDirection
+	{
+		UPDATE_INPUT,
+		UPDATE_OUTPUT
+	};
+
+	template<typename T>
+	class SkipGramMixtureNeuralNetwork
+	{
+	public:
+		T learning_rate;
+		T sense_prior_momentum;
+
+		int status;
+		SkipGramMixtureNeuralNetwork(Option* option, HuffmanEncoder* huffmanEncoder, WordSenseInfo* word_sense_info, Dictionary* dic, int dicSize);
+		~SkipGramMixtureNeuralNetwork();
+
+		void Train(int* sentence, int sentence_length, T* gamma, T* fTable, T* input_backup);
+
+		/*!
+		* \brief Collect all the input words and output nodes in the data block
+		*/
+		void PrepareParmeter(DataBlock *data_block);
+
+		std::vector<int>& GetInputLayerNodes();
+		std::vector<int>& GetOutputLayerNodes();
+
+		/*!
+		* \brief Set the pointers to those local parameters
+		*/
+		void SetInputEmbeddingWeights(int input_node_id, T* ptr);
+		void SetOutputEmbeddingWeights(int output_node_id, T* ptr);
+		void SetSensePriorWeights(int input_node_id, T*ptr);
+		void SetSensePriorParaWeights(int input_node_id, T* ptr);
+
+		/*!
+		* \brief Get the pointers to those locally updated parameters
+		*/
+		T* GetInputEmbeddingWeights(int input_node_id);
+		T* GetEmbeddingOutputWeights(int output_node_id);
+		T* GetSensePriorWeights(int input_node_id);
+		T* GetSensePriorParaWeights(int input_node_id);
+
+	private:
+		Option *m_option;
+		Dictionary *m_dictionary;
+		HuffmanEncoder *m_huffman_encoder;
+		int m_dictionary_size;
+
+		WordSenseInfo* m_word_sense_info;
+
+		T** m_input_embedding_weights_ptr; //Points to every word's input embedding vector
+		bool *m_seleted_input_embedding_weights;
+		T** m_output_embedding_weights_ptr;  //Points to every huffman node's embedding vector
+		bool *m_selected_output_embedding_weights;
+
+		T** m_sense_priors_ptr; //Points to the multinomial parameters, if store_multinomial is set to zero.
+		T** m_sense_priors_paras_ptr;//Points to sense prior parameters. If store_multinomial is zero, then it points to the log of multinomial, otherwise points to the multinomial parameters
+
+		std::vector<int> m_input_layer_nodes;
+		std::vector<int> m_output_layer_nodes;
+
+		typedef void(SkipGramMixtureNeuralNetwork<T>::*FunctionType)(int input_node, std::vector<std::pair<int, int> >& output_nodes, void* v_gamma, void* v_fTable, void* v_input_backup);
+
+		/*!
+		* \brief Parse the needed parameter in a window
+		*/
+		void Parse(int feat, int word_idx, std::vector<std::pair<int, int> >& output_nodes);
+
+		/*!
+		* \brief Parse a sentence and deepen into two branchs
+		* \one for TrainNN,the other one is for Parameter_parse&request
+		*/
+		void ParseSentence(int* sentence, int sentence_length, T* gamma, T* fTable, T* input_backup, FunctionType function);
+
+		/*!
+		* \brief Copy the input_nodes&output_nodes to WordEmbedding private set
+		*/
+		void DealPrepareParameter(int input_nodes, std::vector<std::pair<int, int> >& output_nodes, void* v_gamma, void* v_fTable, void* v_input_backup);
+
+		/*!
+		* \brief Train a window sample and update the
+		* \input-embedding&output-embedding vectors
+		* \param word_input represent the input words
+		* \param output_nodes represent the ouput nodes on huffman tree, including the node index and path label
+		* \param v_gamma is the temp memory to store the posterior probabilities of each sense
+		* \param v_fTable is the temp memory to store the sigmoid value of inner product of input and output embeddings
+		* \param v_input_backup stores the input embedding vectors as backup
+		*/
+		void TrainSample(int word_input, std::vector<std::pair<int, int> >& output_nodes, void* v_gamma, void* v_fTable, void* v_input_backup);
+
+		/*!
+		* \brief The E-step, estimate the posterior multinomial probabilities
+		* \param word_input represent the input words
+		* \param output_nodes represent the ouput nodes on huffman tree, including the node index and path label
+		* \param posterior represents the calculated posterior log likelihood
+		* \param estimation represents the calculated gammas (see the paper), that is, the softmax terms of posterior
+		* \param sense_prior represents the parameters of sense prior probablities for each polysemous words
+		* \param f_m is the temp memory to store the sigmoid value of inner products of input and output embeddings
+		*/
+		T EstimateGamma(int word_input, std::vector<std::pair<int, int> >& output_nodes, T* posterior, T* estimation, T* sense_prior, T* f_m);
+
+		/*!
+		* \brief The M step: update the embedding vectors to maximize the Q function
+		* \param word_input represent the input words
+		* \param output_nodes represent the ouput nodes on huffman tree, including the node index and path label
+		* \param estimation represents the calculated gammas (see the paper), that is, the softmax terms of posterior
+		* \param f_m is the temp memory to store the sigmoid value of inner products of input and output embeddings
+		* \param input_backup stores the input embedding vectors as backup
+		* \param direction: update input vectors or output vectors
+		*/
+		void UpdateEmbeddings(int word_input, std::vector<std::pair<int, int> >& output_nodes, T* estimation, T* f_m, T* input_backup, UpdateDirection direction);
+
+		/*!
+		* \brief The M Step: update the sense prior probabilities to maximize the Q function
+		* \param word_input represent the input words
+		* \param curr_priors are the closed form values of the sense priors in this iteration
+		*/
+		void MaximizeSensePriors(int word_input, T* curr_priors);
+
+		/*
+		* \brief Record the input word so that parameter loader can be performed
+		*/
+		void AddInputLayerNode(int node_id);
+
+		/*
+		* \brief Record the huffman tree node so that parameter loader can be performed
+		*/
+		void AddOutputLayerNode(int node_id);
+	};
 public:
 	T learning_rate;
 	T sense_prior_momentum;
diff --git a/src/trainer.cpp b/src/trainer.cpp
index d99047d..657dca3 100755
--- a/src/trainer.cpp
+++ b/src/trainer.cpp
@@ -1,4 +1,4 @@
-#include "trainer.h"
+#include "Trainer.h"
 
 template<typename T>
 Trainer<T>::Trainer(int trainer_id, Option *option, void** word2vector_neural_networks, multiverso::Barrier *barrier, Dictionary* dictionary, WordSenseInfo* word_sense_info, HuffmanEncoder* huff_encoder)
@@ -12,8 +12,8 @@ Trainer<T>::Trainer(int trainer_id, Option *option, void** word2vector_neural_ne
 	m_word_sense_info = word_sense_info;
 	m_huffman_encoder = huff_encoder;
 
-	gamma = (T*)calloc(m_option-> window_size * MAX_SENSE_CNT, sizeof(T));
-	fTable = (T*)calloc(m_option-> window_size * MAX_CODE_LENGTH * MAX_SENSE_CNT, sizeof(T));
+	gamma = (T*)calloc(m_option->window_size * MAX_SENSE_CNT, sizeof(T));
+	fTable = (T*)calloc(m_option->window_size * MAX_CODE_LENGTH * MAX_SENSE_CNT, sizeof(T));
 	input_backup = (T*)calloc(m_option->embeding_size * MAX_SENSE_CNT, sizeof(T));
 
 	m_start_time = 0;
@@ -62,7 +62,7 @@ void Trainer<T>::TrainIteration(multiverso::DataBlockBase *data_block)
 	{
 		local_output_layer_nodes.push_back(output_layer_nodes[i]);
 	}
-	
+
 	CopyParameterFromMultiverso(local_input_layer_nodes, local_output_layer_nodes, word2vector_neural_network);
 
 	multiverso::Row<int64_t>& word_count_actual_row = GetRow<int64_t>(kWordCountActualTableId, 0);
@@ -72,11 +72,11 @@ void Trainer<T>::TrainIteration(multiverso::DataBlockBase *data_block)
 	word2vector_neural_network->learning_rate = learning_rate;
 
 	//Linearly increase the momentum from init_sense_prior_momentum to 1
-	word2vector_neural_network->sense_prior_momentum = m_option->init_sense_prior_momentum + 
+	word2vector_neural_network->sense_prior_momentum = m_option->init_sense_prior_momentum +
 		(1 - m_option->init_sense_prior_momentum) * word_count_actual_row.At(0) / (T)(m_option->total_words * m_option->epoch + 1);
-	
+
 	m_barrier->Wait();
-	
+
 	for (int i = m_trainer_id; i < data->Size(); i += m_option->thread_cnt)  //i iterates over all sentences
 	{
 		int sentence_length;
@@ -86,7 +86,7 @@ void Trainer<T>::TrainIteration(multiverso::DataBlockBase *data_block)
 		data->Get(i, sentence, sentence_length, word_count_deta, next_random);
 
 		word2vector_neural_network->Train(sentence, sentence_length, gamma, fTable, input_backup);
-		
+
 		m_word_count += word_count_deta;
 		if (m_word_count - m_last_word_count > 10000)
 		{
@@ -94,7 +94,7 @@ void Trainer<T>::TrainIteration(multiverso::DataBlockBase *data_block)
 			Add<int64_t>(kWordCountActualTableId, 0, 0, m_word_count - m_last_word_count);
 			m_last_word_count = m_word_count;
 			m_now_time = clock();
-			
+
 			if (m_trainer_id % 3 == 0)
 			{
 				multiverso::Log::Info("Rank %d Trainer %d lr: %.5f Mom: %.4f Progress: %.2f%% Words/thread/sec(total): %.2fk  W/t/sec(executive): %.2fk\n",
@@ -115,12 +115,12 @@ void Trainer<T>::TrainIteration(multiverso::DataBlockBase *data_block)
 			word2vector_neural_network->sense_prior_momentum = m_option->init_sense_prior_momentum + (1 - m_option->init_sense_prior_momentum) * word_count_actual_row.At(0) / (T)(m_option->total_words * m_option->epoch + 1);
 		}
 	}
-	
+
 	m_barrier->Wait();
 	AddParameterToMultiverso(local_input_layer_nodes, local_output_layer_nodes, word2vector_neural_network);
-	
+
 	m_executive_time += clock() - train_interation_start;
-	
+
 	multiverso::Log::Info("Rank %d Train %d end at %lfs, cost %lfs, total cost %lfs\n",
 		m_process_id,
 		m_trainer_id, clock() / (double)CLOCKS_PER_SEC,
@@ -159,7 +159,7 @@ template<typename T>
 int Trainer<T>::CopyParameterFromMultiverso(std::vector<int>& input_layer_nodes, std::vector<int>& output_layer_nodes, void* local_word2vector_neural_network)
 {
 	SkipGramMixtureNeuralNetwork<T>* word2vector_neural_network = (SkipGramMixtureNeuralNetwork<T>*)local_word2vector_neural_network;
-	
+
 	//Copy input embedding
 	for (int i = 0; i < input_layer_nodes.size(); ++i)
 	{
@@ -169,7 +169,7 @@ int Trainer<T>::CopyParameterFromMultiverso(std::vector<int>& input_layer_nodes,
 			CopyMemory(ptr + j * m_option->embeding_size, GetRow<T>(kInputEmbeddingTableId, row_id), m_option->embeding_size);
 		word2vector_neural_network->SetInputEmbeddingWeights(input_layer_nodes[i], ptr);
 	}
-	
+
 	//Copy output embedding
 	for (int i = 0; i < output_layer_nodes.size(); ++i)
 	{
@@ -184,7 +184,7 @@ int Trainer<T>::CopyParameterFromMultiverso(std::vector<int>& input_layer_nodes,
 			}
 		word2vector_neural_network->SetOutputEmbeddingWeights(output_layer_nodes[i], ptr);
 	}
-	
+
 	//Copy sense prior
 	for (int i = 0; i < input_layer_nodes.size(); ++i)
 	{
@@ -285,7 +285,7 @@ void Trainer<T>::SaveMultiInputEmbedding(const int epoch_id)
 
 		fid = fopen(outfile, "wb");
 
-	    fprintf(fid, "%d %d %d\n", m_dictionary->Size(), m_word_sense_info->total_senses_cnt, m_option->embeding_size);
+		fprintf(fid, "%d %d %d\n", m_dictionary->Size(), m_word_sense_info->total_senses_cnt, m_option->embeding_size);
 		for (int i = 0; i < m_dictionary->Size(); ++i)
 		{
 			fprintf(fid, "%s %d ", m_dictionary->GetWordInfo(i)->word.c_str(), m_word_sense_info->word_sense_cnts_info[i]);
@@ -297,7 +297,7 @@ void Trainer<T>::SaveMultiInputEmbedding(const int epoch_id)
 				CopyMemory(sense_priors_ptr, GetRow<T>(kWordSensePriorTableId, m_word_sense_info->p_wordidx2sense_idx[i]), m_option->sense_num_multi);
 				if (!m_option->store_multinomial)
 					Util::SoftMax(sense_priors_ptr, sense_priors_ptr, m_option->sense_num_multi);
-				
+
 				for (int j = 0; j < m_option->sense_num_multi; ++j)
 				{
 					fwrite(sense_priors_ptr + j, sizeof(real), 1, fid);
@@ -317,7 +317,7 @@ void Trainer<T>::SaveMultiInputEmbedding(const int epoch_id)
 				fwrite(&prob, sizeof(real), 1, fid);
 				emb_row_id = m_word_sense_info->p_input_embedding[i];
 				multiverso::Row<real>& embedding = GetRow<real>(kInputEmbeddingTableId, emb_row_id);
-				
+
 				for (int k = 0; k < m_option->embeding_size; ++k)
 				{
 					emb_tmp = embedding.At(k);
@@ -442,4 +442,4 @@ void Trainer<T>::SaveHuffEncoder()
 }
 
 template class Trainer<float>;
-template class Trainer<double>;
+template class Trainer<double>;
\ No newline at end of file