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https://github.com/Helsinki-NLP/OPUS-MT-train.git
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176 lines
7.2 KiB
Makefile
176 lines
7.2 KiB
Makefile
# -*-makefile-*-
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#------------------------------------------------------------------------
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# translate and evaluate all test sets in testsets/
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#------------------------------------------------------------------------
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## testset dir for all test sets in this language pair
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## and all trokenized test sets that can be found in that directory
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TESTSET_HOME = ${REPOHOME}testsets
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TESTSET_DIR = ${TESTSET_HOME}/${SRC}-${TRG}
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TESTSETS = $(sort $(patsubst ${TESTSET_DIR}/%.${SRCEXT}.gz,%,${wildcard ${TESTSET_DIR}/*.${SRCEXT}.gz}))
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TESTSETS_PRESRC = $(patsubst %,${TESTSET_DIR}/%.${SRCEXT}.${PRE}.gz,${TESTSETS})
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TESTSETS_PRETRG = $(patsubst %,${TESTSET_DIR}/%.${TRGEXT}.${PRE}.gz,${TESTSETS})
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## eval all available test sets
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eval-testsets:
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for s in ${SRCLANGS}; do \
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for t in ${TRGLANGS}; do \
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${MAKE} SRC=$$s TRG=$$t compare-testsets-langpair; \
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done \
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done
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%-testsets-langpair: ${TESTSETS_PRESRC} ${TESTSETS_PRETRG}
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@echo "testsets: ${TESTSET_DIR}/*.${SRCEXT}.gz"
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for t in ${TESTSETS}; do \
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${MAKE} TESTSET=$$t TESTSET_NAME=$$t-${SRC}${TRG} ${@:-testsets-langpair=}; \
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done
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#------------------------------------------------------------------------
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# translate with an ensemble of several models
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#------------------------------------------------------------------------
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ENSEMBLE = ${wildcard ${WORKDIR}/${MODEL}.${MODELTYPE}.model*.npz.best-perplexity.npz}
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${WORKDIR}/${TESTSET_NAME}.${MODEL}${NR}.${MODELTYPE}.ensemble.${SRC}.${TRG}: ${TEST_SRC}.${PRE_SRC} ${ENSEMBLE}
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mkdir -p ${dir $@}
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grep . $< > $@.input
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${LOAD_ENV} && ${MARIAN_DECODER} -i $@.input \
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--models ${ENSEMBLE} \
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--vocabs ${MODEL_SRCVOCAB} ${MODEL_TRGVOCAB} \
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${MARIAN_DECODER_FLAGS} > $@.output
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ifneq ($(findstring spm,${PRE_TRG}),)
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sed 's/ //g;s/▁/ /g' < $@.output | sed 's/^ *//;s/ *$$//' > $@
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else
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sed 's/\@\@ //g;s/ \@\@//g;s/ \@\-\@ /-/g' < $@.output |\
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$(TOKENIZER)/detokenizer.perl -l ${TRG} > $@
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endif
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rm -f $@.input $@.output
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#------------------------------------------------------------------------
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# translate, evaluate and generate a file
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# for comparing system to reference translations
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#------------------------------------------------------------------------
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${WORKDIR}/${TESTSET_NAME}.${MODEL}${NR}.${MODELTYPE}.${SRC}.${TRG}: ${TEST_SRC}.${PRE_SRC} ${MODEL_FINAL}
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mkdir -p ${dir $@}
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grep . $< > $@.input
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${LOAD_ENV} && ${MARIAN_DECODER} -i $@.input \
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-c ${word 2,$^}.decoder.yml \
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${MARIAN_DECODER_FLAGS} > $@.output
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ifneq ($(findstring spm,${PRE_TRG}),)
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sed 's/ //g;s/▁/ /g' < $@.output | sed 's/^ *//;s/ *$$//' > $@
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else
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sed 's/\@\@ //g;s/ \@\@//g;s/ \@\-\@ /-/g' < $@.output |\
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$(TOKENIZER)/detokenizer.perl -l ${TRG} > $@
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endif
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rm -f $@.input $@.output
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## adjust tokenisation to non-space-separated languages
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## TODO: is it correct to simply use 'zh' or should we use 'intl'?
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ifneq ($(filter zh zho jp jpn cmn,${TRGLANGS}),)
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SACREBLEU_PARAMS = --tokenize zh
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endif
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## simple hack that makes chrF scores compatible with previous version
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## of sacrebleu (now: score in percentages)
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## --> this breaks easily if the score < 10 or = 100
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%.eval: % ${TEST_TRG}
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paste ${TEST_SRC}.${PRE_SRC} ${TEST_TRG} | grep $$'.\t' | cut -f2 > $@.ref
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cat $< | sacrebleu -f text ${SACREBLEU_PARAMS} $@.ref > $@
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cat $< | sacrebleu -f text ${SACREBLEU_PARAMS} --metrics=chrf --width=3 $@.ref |\
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sed 's/\([0-9][0-9]\)\.\([0-9]*\)$$/0.\1\2/' >> $@
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rm -f $@.ref
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%.compare: %.eval
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grep . ${TEST_SRC} > $@.1
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grep . ${TEST_TRG} > $@.2
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grep . ${<:.eval=} > $@.3
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paste -d "\n" $@.1 $@.2 $@.3 |\
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sed -e "s/'/'/g" \
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-e 's/"/"/g' \
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-e 's/</</g' \
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-e 's/>/>/g' \
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-e 's/&/&/g' |\
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sed 'n;n;G;' > $@
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rm -f $@.1 $@.2 $@.3
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##--------------------------------------------------------------------------------------------
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## some tools for reporting current scores in the work directory
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##
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## make print-bleu-scores ......... print all bleu scores for all tested benchmarks and models
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## make compare-bleu-scores ....... compare scores with best BLEU scores in leaderboard
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## make print-improved-models ..... print model scores that are better than best reported score
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## make print-decreased-models .... print model scores that are worse than best reported score
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##--------------------------------------------------------------------------------------------
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print-bleu-score-table:
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@grep BLEU ${WORKHOME}/*/*.eval |\
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perl -pe 's#^${WORKHOME}/([^/]*)/([^\.]+)\.(.*?-.*?\.)?([^\.]+\.[^\.]+\.[^\.]+)\.([^\.]+)\.([^\.]+)\.eval:.*? = ([0-9\.]+) .*$$#$$5-$$6\t$$7\t$$2\t$$1\t$$4#' |\
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perl -pe '@a=split(/\t/);if($$a[0]=~/multi/){$$a[0]=$$a[3];};$$_=join("\t",@a);' |\
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sort -k3,3 -k1,1 -k2,2nr
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print-bleu-scores:
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@make -s print-bleu-score-table |\
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perl -e 'while (<>){@a=split(/\t/);printf "%15s %5.2f %-25s %-15s %s",@a;}'
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LEADERBOARD_DIR = ${REPOHOME}scores
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## manipulating test set names is really messy
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## - need to remove language ID pairs
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## - could be different variants (2-lettter codes, 3-letter codes)
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## - newstest sometimes has additional langpair-IDs in their names
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compare-bleu-score-table:
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@grep BLEU ${WORKHOME}/*/*.eval |\
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perl -pe 's#^${WORKHOME}/([^/]*)/([^\.]+)\.(.*?-.*?\.)?([^\.]+\.[^\.]+\.[^\.]+)\.([^\.]+)\.([^\.]+)\.eval:.*? = ([0-9\.]+) .*$$#$$5-$$6\t$$7\t$$2\t$$1\t$$4#' |\
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perl -pe '@a=split(/\t/);if($$a[0]=~/multi/){$$a[0]=$$a[3];};$$_=join("\t",@a);' |\
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perl -pe '@a=split(/\t/);$$a[2]=lc($$a[2]);$$a[2]=~s/^(.*)\-[a-z]{4}$$/$$1/;$$a[2]=~s/^(.*)\-[a-z]{6}$$/$$1/;$$a[2]=~s/^(news.*)\-[a-z]{4}/$$1/;if (-e "${LEADERBOARD_DIR}/$$a[0]/$$a[2]/bleu-scores.txt"){$$b=`head -1 ${LEADERBOARD_DIR}/$$a[0]/$$a[2]/bleu-scores.txt | cut -f1`;$$b+=0;}else{$$b=0;}$$d=$$a[1]-$$b;splice(@a,2,0,$$b,$$d);$$_=join("\t",@a);' |\
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sort -k5,5 -k1,1 -k2,2nr
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compare-bleu-scores:
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@make -s compare-bleu-score-table |\
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perl -e 'printf "%15s %5s %5s %6s %-25s %-15s %s","langpair","BLEU","best","diff","testset","dir","model\n";while (<>){@a=split(/\t/);printf "%15s %5.2f %5.2f %6.2f %-25s %-15s %s",@a;}'
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print-improved-models:
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@make -s compare-bleu-scores |\
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grep -v ' 0.00' | grep -v ' -[0-9]'
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print-decreased-models:
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@make -s compare-bleu-scores |\
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grep ' -[0-9]'
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## compare BLEU scores for the current model
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compare-model-bleu-score-table:
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@grep BLEU ${WORKDIR}/*.eval |\
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perl -pe 's#^${WORKHOME}/([^/]*)/([^\.]+)\.(.*?-.*?\.)?([^\.]+\.[^\.]+\.[^\.]+)\.([^\.]+)\.([^\.]+)\.eval:.*? = ([0-9\.]+) .*$$#$$5-$$6\t$$7\t$$2\t$$1\t$$4#' |\
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perl -pe '@a=split(/\t/);if($$a[0]=~/multi/){$$a[0]=$$a[3];};$$_=join("\t",@a);' |\
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perl -pe '@a=split(/\t/);$$a[2]=lc($$a[2]);$$a[2]=~s/^(.*)\-[a-z]{4}$$/$$1/;$$a[2]=~s/^(.*)\-[a-z]{6}$$/$$1/;$$a[2]=~s/^(news.*)\-[a-z]{4}$$/$$1/;if (-e "${LEADERBOARD_DIR}/$$a[0]/$$a[2]/bleu-scores.txt"){$$b=`head -1 ${LEADERBOARD_DIR}/$$a[0]/$$a[2]/bleu-scores.txt | cut -f1`;$$b+=0;}else{$$b=0;}$$d=$$a[1]-$$b;splice(@a,2,0,$$b,$$d);$$_=join("\t",@a);' |\
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sort -k5,5 -k1,1 -k2,2nr
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compare-model-bleu-scores:
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make -s compare-model-bleu-score-table |\
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perl -e 'printf "%15s %5s %5s %6s %-25s %-15s %s","langpair","BLEU","best","diff","testset","dir","model\n";while (<>){@a=split(/\t/);printf "%15s %5.2f %5.2f %6.2f %-25s %-15s %s",@a;}'
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print-improved-bleu:
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@make -s compare-model-bleu-scores |\
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grep -v ' 0.00' | grep -v ' -[0-9]'
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print-decreased-bleu:
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@make -s compare-model-bleu-scores |\
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grep ' -[0-9]'
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