OPUS-MT-train/lib/projects/memad.mk
2021-02-25 17:17:21 +02:00

484 lines
18 KiB
Makefile

MEMAD_LANGS = de en fi fr nl sv
MEMAD_LANGS3 = deu eng fin fra nld swe
#-------------------------------------------------------------------
# models for the MeMAD project based on Tatoeba MT challenge data
#-------------------------------------------------------------------
tatoeba-memad: tatoeba-memad-multi tatoeba-memad-bilingual
tatoeba-memad-multi: tatoeba-memad-m2m tatoeba-memad-m2e tatoeba-memad-e2m
tatoeba-memad-e2m:
${MAKE} TRGLANGS="${MEMAD_LANGS3}" SRCLANGS="eng" \
HPC_DISK=500 MODELTYPE=transformer-align tatoeba-job-1m
tatoeba-memad-m2e:
${MAKE} SRCLANGS="${MEMAD_LANGS3}" TRGLANGS="eng" \
HPC_DISK=500 MODELTYPE=transformer-align tatoeba-job-1m
tatoeba-memad-m2m:
${MAKE} SRCLANGS="${MEMAD_LANGS3}" TRGLANGS="${MEMAD_LANGS3}" \
SKIP_LANGPAIRS="deu-deu|eng-eng|fin-fin|fra-fra|nld-nld|swe-swe" \
HPC_DISK=500 MODELTYPE=transformer-align tatoeba-job-1m
tatoeba-memad-bilingual:
@for s in ${MEMAD_LANGS3}; do \
for t in ${MEMAD_LANGS3}; do \
if [ "$$s" != "$$t" ]; then \
${MAKE} HPC_DISK=500 SRCLANGS=$$s TRGLANGS=$$t \
MODELTYPE=transformer-align tatoeba-job; \
fi \
done \
done
tatoeba-memad-dist:
${MAKE} TRGLANGS="${MEMAD_LANGS3}" SRCLANGS="eng" \
MODELTYPE=transformer-align \
tatoeba-multilingual-eval-1m compare-tatoeba-1m eval-testsets-tatoeba-1m
${MAKE} TRGLANGS="${MEMAD_LANGS3}" SRCLANGS="eng" \
TATOEBA_RELEASEDIR=models-memad \
TATOEBA_MODELSHOME=models-memad \
MODELTYPE=transformer-align release-tatoeba-1m
${MAKE} SRCLANGS="${MEMAD_LANGS3}" TRGLANGS="eng" \
MODELTYPE=transformer-align \
tatoeba-multilingual-eval-1m compare-tatoeba-1m eval-testsets-tatoeba-1m
${MAKE} SRCLANGS="${MEMAD_LANGS3}" TRGLANGS="eng" \
TATOEBA_RELEASEDIR=models-memad \
TATOEBA_MODELSHOME=models-memad \
MODELTYPE=transformer-align release-tatoeba-1m
${MAKE} SRCLANGS="${MEMAD_LANGS3}" TRGLANGS="${MEMAD_LANGS3}" \
SKIP_LANGPAIRS="deu-deu|eng-eng|fin-fin|fra-fra|nld-nld|swe-swe" \
MODELTYPE=transformer-align \
tatoeba-multilingual-eval-1m compare-tatoeba-1m eval-testsets-tatoeba-1m
${MAKE} SRCLANGS="${MEMAD_LANGS3}" TRGLANGS="${MEMAD_LANGS3}" \
SKIP_LANGPAIRS="deu-deu|eng-eng|fin-fin|fra-fra|nld-nld|swe-swe" \
TATOEBA_RELEASEDIR=models-memad \
TATOEBA_MODELSHOME=models-memad \
MODELTYPE=transformer-align release-tatoeba-1m
@for s in ${MEMAD_LANGS3}; do \
for t in ${MEMAD_LANGS3}; do \
if [ "$$s" != "$$t" ]; then \
${MAKE} SRCLANGS=$$s TRGLANGS=$$t \
MODELTYPE=transformer-align \
tatoeba-multilingual-eval compare-tatoeba eval-testsets-tatoeba; \
${MAKE} SRCLANGS=$$s TRGLANGS=$$t \
TATOEBA_RELEASEDIR=models-memad \
TATOEBA_MODELSHOME=models-memad \
MODELTYPE=transformer-align release-tatoeba; \
fi \
done \
done
#----------------------------------------------------------------
# fine-tuning on YLE subtitle data
#----------------------------------------------------------------
tatoeba-yletest-fisv:
${MAKE} TESTSET_HOME=${PWD}/memad-testsets \
MODELTYPE=transformer-align \
tatoeba-fin2swe-testsets
MEMAD_SUBTYPE = FIN-SWE
MEMAD_LANGPAIR = fin2swe
MEMAD_TUNETASK = tune
tatoeba-yletune-all: tatoeba-yletune-finswe-all tatoeba-yletune-swefin-all
tatoeba-yletune-finswe-all: tatoeba-yletune-finswe tatoeba-yletune-fihswe \
tatoeba-yletune-finswh tatoeba-yletune-fihswh tatoeba-yletune-fisw
tatoeba-yletune-swefin-all: tatoeba-yletune-swefin tatoeba-yletune-swefih \
tatoeba-yletune-swhfin tatoeba-yletune-swhfih tatoeba-yletune-swfi
tatoeba-yleeval-all:
${MAKE} MEMAD_TUNETASK=tuneeval tatoeba-yletune-all
tatoeba-yledist-all:
${MAKE} MEMAD_TUNETASK=tunedist \
TATOEBA_RELEASEDIR=models-memad-tuned \
TATOEBA_MODELSHOME=models-memad-tuned \
tatoeba-yletune-all
tatoeba-yletune-finswe:
${MAKE} MEMAD_SUBTYPE=FIN-SWE MEMAD_LANGPAIR=fin2swe tatoeba-yletune
tatoeba-yletune-fihswe:
${MAKE} MEMAD_SUBTYPE=FIH-SWE MEMAD_LANGPAIR=fin2swe tatoeba-yletune
tatoeba-yletune-finswh:
${MAKE} MEMAD_SUBTYPE=FIN-SWH MEMAD_LANGPAIR=fin2swe tatoeba-yletune
tatoeba-yletune-fihswh:
${MAKE} MEMAD_SUBTYPE=FIH-SWH MEMAD_LANGPAIR=fin2swe tatoeba-yletune
tatoeba-yletune-fisw:
${MAKE} MEMAD_SUBTYPE=FI-SW MEMAD_LANGPAIR=fin2swe tatoeba-yletune
tatoeba-yletune-swefin:
${MAKE} MEMAD_SUBTYPE=FIN-SWE MEMAD_LANGPAIR=swe2fin tatoeba-yletune
tatoeba-yletune-swefih:
${MAKE} MEMAD_SUBTYPE=FIH-SWE MEMAD_LANGPAIR=swe2fin tatoeba-yletune
tatoeba-yletune-swhfin:
${MAKE} MEMAD_SUBTYPE=FIN-SWH MEMAD_LANGPAIR=swe2fin tatoeba-yletune
tatoeba-yletune-swhfih:
${MAKE} MEMAD_SUBTYPE=FIH-SWH MEMAD_LANGPAIR=swe2fin tatoeba-yletune
tatoeba-yletune-swfi:
${MAKE} MEMAD_SUBTYPE=FI-SW MEMAD_LANGPAIR=swe2fin tatoeba-yletune
tatoeba-yletune:
${MAKE} TESTSET_HOME=${PWD}/memad-testsets \
MODELTYPE=transformer-align \
TUNE_TRAINSET=YLE-train.${MEMAD_SUBTYPE} \
TUNE_DEVSET=YLE-dev.${MEMAD_SUBTYPE} \
TUNE_TESTSET=YLE-test.${MEMAD_SUBTYPE} \
tatoeba-${MEMAD_LANGPAIR}-${MEMAD_TUNETASK}
## tuning with OpenSubtitles
## (does not seem to work well ...)
tatoeba-tune-fisv:
${MAKE} TESTSET_HOME=${PWD}/memad-testsets \
MODELTYPE=transformer-align \
tatoeba-fin2swe-domaintune
tatoeba-testtuned-fisv:
${MAKE} TESTSET_HOME=${PWD}/memad-testsets \
MODELTYPE=transformer-align \
tatoeba-fin2swe-evalall tatoeba-swe2fin-domaintuneeval
tatoeba-tune-svfi:
${MAKE} TESTSET_HOME=${PWD}/memad-testsets \
MODELTYPE=transformer-align \
tatoeba-swe2fin-domaintune
tatoeba-testtuned-svfi:
${MAKE} TESTSET_HOME=${PWD}/memad-testsets \
MODELTYPE=transformer-align \
tatoeba-swe2fin-evalall tatoeba-swe2fin-domaintuneeval
MEMAD_DATATYPE = train
MEMAD_LANGPAIR = fin-swe
MEMAD_LANG3 = FIN
MEMAD_LANG2 = fi
memad-yle-data:
for s in FIN-SWE FIN-SWH FIH-SWE FIH-SWH FI-SW; do \
for d in train dev test; do \
${MAKE} MEMAD_DATATYPE=$$d MEMAD_LANG3=fin MEMAD_LANGPAIR=fin-swe MEMAD_LANG2=fi \
work-tatoeba/data/simple/YLE-$$d.$$s.fin-swe.clean.fin.gz \
work-tatoeba/data/simple/YLE-$$d.$$s.fin-swe.clean.fin.labels; \
${MAKE} MEMAD_DATATYPE=$$d MEMAD_LANG3=swe MEMAD_LANGPAIR=fin-swe MEMAD_LANG2=sv \
work-tatoeba/data/simple/YLE-$$d.$$s.fin-swe.clean.swe.gz \
work-tatoeba/data/simple/YLE-$$d.$$s.fin-swe.clean.swe.labels; \
done \
done
work-tatoeba/data/simple/YLE-${MEMAD_DATATYPE}.%.${MEMAD_LANGPAIR}.clean.${MEMAD_LANG3}.gz: YLE/%.${MEMAD_DATATYPE}.${MEMAD_LANG2}
gzip -c < $< > $@
work-tatoeba/data/simple/YLE-${MEMAD_DATATYPE}.%.${MEMAD_LANGPAIR}.clean.${MEMAD_LANG3}.labels:
echo -n ${MEMAD_LANG3} > $@
#----------------------------------------------------------------
# other OPUS models
#----------------------------------------------------------------
# FIT_DATA_SIZE=2000000
memad-multi-subs:
${MAKE} SRCLANGS="${MEMAD_LANGS}" TRGLANGS="${MEMAD_LANGS}" \
SKIP_LANGPAIRS="de-de|en-en|fi-fi|fr-fr|nl-nl|sv-sv" \
DEVSET=OpenSubtitles TRAINSET= MODELTYPE=transformer data
${MAKE} SRCLANGS="${MEMAD_LANGS}" TRGLANGS="${MEMAD_LANGS}" \
SKIP_LANGPAIRS="de-de|en-en|fi-fi|fr-fr|nl-nl|sv-sv" \
DEVSET=OpenSubtitles TRAINSET= MODELTYPE=transformer \
WALLTIME=72 HPC_MEM=8g HPC_CORES=1 train.submit-multigpu
memad-multi-subs-dist:
${MAKE} SRCLANGS="${MEMAD_LANGS}" TRGLANGS="${MEMAD_LANGS}" \
SKIP_LANGPAIRS="de-de|en-en|fi-fi|fr-fr|nl-nl|sv-sv" \
DEVSET=OpenSubtitles TRAINSET= MODELTYPE=transformer \
WALLTIME=72 HPC_MEM=8g HPC_CORES=1 eval
${MAKE} SRCLANGS="${MEMAD_LANGS}" TRGLANGS="${MEMAD_LANGS}" \
SKIP_LANGPAIRS="de-de|en-en|fi-fi|fr-fr|nl-nl|sv-sv" \
DEVSET=OpenSubtitles TRAINSET= MODELTYPE=transformer \
WALLTIME=72 HPC_MEM=8g HPC_CORES=1 eval-testsets
${MAKE} SRCLANGS="${MEMAD_LANGS}" TRGLANGS="${MEMAD_LANGS}" \
SKIP_LANGPAIRS="de-de|en-en|fi-fi|fr-fr|nl-nl|sv-sv" \
DEVSET=OpenSubtitles TRAINSET= MODELTYPE=transformer \
WALLTIME=72 HPC_MEM=8g HPC_CORES=1 release
memad-multi-subs-release:
${MAKE} SRCLANGS="${MEMAD_LANGS}" TRGLANGS="${MEMAD_LANGS}" \
SKIP_LANGPAIRS="de-de|en-en|fi-fi|fr-fr|nl-nl|sv-sv" \
DEVSET=OpenSubtitles TRAINSET= MODELTYPE=transformer \
WALLTIME=72 HPC_MEM=8g HPC_CORES=1 release
memad-multi-train:
${MAKE} SRCLANGS="${MEMAD_LANGS}" TRGLANGS="${MEMAD_LANGS}" MODELTYPE=transformer data
${MAKE} SRCLANGS="${MEMAD_LANGS}" TRGLANGS="${MEMAD_LANGS}" MODELTYPE=transformer \
WALLTIME=72 HPC_MEM=8g HPC_CORES=1 HPC_DISK=1500 train.submit-multigpu
%-memad-multi:
${MAKE} SRCLANGS="${MEMAD_LANGS}" TRGLANGS="${MEMAD_LANGS}" MODELTYPE=transformer data
${MAKE} SRCLANGS="${MEMAD_LANGS}" TRGLANGS="${MEMAD_LANGS}" MODELTYPE=transformer \
${@:-memad-multi=}
memad-multiparallel: memad-multiparallel-basic \
memad-multiparallel-all \
memad-multiparallel-intra \
memad-multiparallel-intra-all
memad-multiparallel-basic:
mkdir $@
cd $@ && opus2multi /projappl/nlpl/data/OPUS/OpenSubtitles/latest/xml en de fi fr nl sv
memad-multiparallel-all:
mkdir $@
cd $@ && opus2multi /projappl/nlpl/data/OPUS/OpenSubtitles/latest/all en de fi fr nl sv
memad-multiparallel-intra:
mkdir $@
cd $@ && opus2multi -i /projappl/nlpl/data/OPUS/OpenSubtitles/latest/xml/en-en.xml.gz\
/projappl/nlpl/data/OPUS/OpenSubtitles/latest/xml en de fi fr nl sv
memad-multiparallel-intra-all:
mkdir $@
cd $@ && opus2multi -i /projappl/nlpl/data/OPUS/OpenSubtitles/latest/xml/en-en.xml.gz\
/projappl/nlpl/data/OPUS/OpenSubtitles/latest/all en de fi fr nl sv
memad2en:
${MAKE} LANGS="${MEMAD_LANGS}" PIVOT=en all2pivot
memad-fiensv:
${MAKE} SRCLANGS=sv TRGLANGS=fi traindata-spm
${MAKE} SRCLANGS=sv TRGLANGS=fi devdata-spm
${MAKE} SRCLANGS=sv TRGLANGS=fi wordalign-spm
${MAKE} SRCLANGS=sv TRGLANGS=fi WALLTIME=72 HPC_MEM=4g HPC_CORES=1 train-spm.submit-multigpu
${MAKE} SRCLANGS=sv TRGLANGS=fi reverse-data-spm
${MAKE} SRCLANGS=fi TRGLANGS=sv WALLTIME=72 HPC_MEM=4g HPC_CORES=1 train-spm.submit-multigpu
${MAKE} SRCLANGS=en TRGLANGS=fi traindata-spm
${MAKE} SRCLANGS=en TRGLANGS=fi devdata-spm
${MAKE} SRCLANGS=en TRGLANGS=fi wordalign-spm
${MAKE} SRCLANGS=en TRGLANGS=fi WALLTIME=72 HPC_MEM=4g HPC_CORES=1 train-spm.submit-multigpu
${MAKE} SRCLANGS=en TRGLANGS=fi reverse-data-spm
${MAKE} SRCLANGS=fi TRGLANGS=en WALLTIME=72 HPC_MEM=4g HPC_CORES=1 train-spm.submit-multigpu
memad250-fiensv:
${MAKE} CONTEXT_SIZE=250 memad-fiensv_doc
memad-fiensv_doc:
${MAKE} SRCLANGS=sv TRGLANGS=fi traindata-doc
${MAKE} SRCLANGS=sv TRGLANGS=fi devdata-doc
${MAKE} SRCLANGS=sv TRGLANGS=fi WALLTIME=72 HPC_MEM=8g MARIAN_WORKSPACE=20000 HPC_CORES=1 train-doc.submit-multigpu
${MAKE} SRCLANGS=sv TRGLANGS=fi reverse-data-doc
${MAKE} SRCLANGS=fi TRGLANGS=sv WALLTIME=72 HPC_MEM=8g MARIAN_WORKSPACE=20000 HPC_CORES=1 train-doc.submit-multigpu
${MAKE} SRCLANGS=en TRGLANGS=fi traindata-doc
${MAKE} SRCLANGS=en TRGLANGS=fi devdata-doc
${MAKE} SRCLANGS=en TRGLANGS=fi WALLTIME=72 HPC_MEM=4g HPC_CORES=1 train-doc.submit-multigpu
${MAKE} SRCLANGS=en TRGLANGS=fi reverse-data-doc
${MAKE} SRCLANGS=fi TRGLANGS=en WALLTIME=72 HPC_MEM=4g HPC_CORES=1 train-doc.submit-multigpu
memad-fiensv_more:
${MAKE} SRCLANGS=sv TRGLANGS=fi traindata-doc
${MAKE} SRCLANGS=sv TRGLANGS=fi devdata-doc
${MAKE} SRCLANGS=sv TRGLANGS=fi WALLTIME=72 HPC_MEM=8g MARIAN_WORKSPACE=20000 HPC_CORES=1 train-doc.submit-multigpu
${MAKE} SRCLANGS=sv TRGLANGS=fi reverse-data-doc
${MAKE} SRCLANGS=fi TRGLANGS=sv WALLTIME=72 HPC_MEM=8g MARIAN_WORKSPACE=20000 HPC_CORES=1 train-doc.submit-multigpu
${MAKE} CONTEXT_SIZE=500 memad-fiensv_doc
memad:
for s in fi en sv de fr nl; do \
for t in en fi sv de fr nl; do \
if [ "$$s" != "$$t" ]; then \
if ! grep -q 'stalled ${MARIAN_EARLY_STOPPING} times' ${WORKHOME}/$$s-$$t/${DATASET}.*.valid${NR.log}; then\
${MAKE} SRCLANGS=$$s TRGLANGS=$$t bilingual-dynamic; \
fi \
fi \
done \
done
# ${MAKE} SRCLANGS=$$s TRGLANGS=$$t data; \
# ${MAKE} SRCLANGS=$$s TRGLANGS=$$t HPC_CORES=1 HPC_MEM=4g train.submit-multigpu; \
fiensv_bpe:
${MAKE} SRCLANGS=fi TRGLANGS=sv traindata-bpe
${MAKE} SRCLANGS=fi TRGLANGS=sv devdata-bpe
${MAKE} SRCLANGS=fi TRGLANGS=sv wordalign-bpe
${MAKE} SRCLANGS=fi TRGLANGS=sv WALLTIME=72 HPC_MEM=4g HPC_CORES=1 train-bpe.submit-multigpu
${MAKE} SRCLANGS=fi TRGLANGS=en traindata-bpe
${MAKE} SRCLANGS=fi TRGLANGS=en devdata-bpe
${MAKE} SRCLANGS=fi TRGLANGS=en wordalign-bpe
${MAKE} SRCLANGS=fi TRGLANGS=en WALLTIME=72 HPC_MEM=4g HPC_CORES=1 train-bpe.submit-multigpu
fiensv_spm:
${MAKE} SRCLANGS=fi TRGLANGS=sv traindata-spm
${MAKE} SRCLANGS=fi TRGLANGS=sv devdata-spm
${MAKE} SRCLANGS=fi TRGLANGS=sv wordalign-spm
${MAKE} SRCLANGS=fi TRGLANGS=sv WALLTIME=72 HPC_MEM=4g HPC_CORES=1 train-spm.submit-multigpu
${MAKE} SRCLANGS=fi TRGLANGS=en traindata-spm
${MAKE} SRCLANGS=fi TRGLANGS=en devdata-spm
${MAKE} SRCLANGS=fi TRGLANGS=en wordalign-spm
${MAKE} SRCLANGS=fi TRGLANGS=en WALLTIME=72 HPC_MEM=4g HPC_CORES=1 train-spm.submit-multigpu
fifr_spm:
${MAKE} SRCLANGS=fr TRGLANGS=fi traindata-spm
${MAKE} SRCLANGS=fr TRGLANGS=fi devdata-spm
${MAKE} SRCLANGS=fr TRGLANGS=fi wordalign-spm
${MAKE} SRCLANGS=fr TRGLANGS=fi WALLTIME=72 HPC_MEM=4g HPC_CORES=1 train-spm.submit-multigpu
${MAKE} SRCLANGS=fr TRGLANGS=fi reverse-data-spm
${MAKE} SRCLANGS=fi TRGLANGS=fr WALLTIME=72 HPC_MEM=4g HPC_CORES=1 train-spm.submit-multigpu
fifr_doc:
${MAKE} SRCLANGS=fr TRGLANGS=fi traindata-doc
${MAKE} SRCLANGS=fr TRGLANGS=fi devdata-doc
${MAKE} SRCLANGS=fr TRGLANGS=fi WALLTIME=72 HPC_MEM=8g MARIAN_WORKSPACE=20000 HPC_CORES=1 train-doc.submit-multigpu
${MAKE} SRCLANGS=fr TRGLANGS=fi reverse-data-doc
${MAKE} SRCLANGS=fi TRGLANGS=fr WALLTIME=72 HPC_MEM=8g MARIAN_WORKSPACE=20000 HPC_CORES=1 train-doc.submit-multigpu
fide_spm:
${MAKE} SRCLANGS=de TRGLANGS=fi traindata-spm
${MAKE} SRCLANGS=de TRGLANGS=fi devdata-spm
${MAKE} SRCLANGS=de TRGLANGS=fi wordalign-spm
${MAKE} SRCLANGS=de TRGLANGS=fi WALLTIME=72 HPC_MEM=4g HPC_CORES=1 train-spm.submit-multigpu
${MAKE} SRCLANGS=de TRGLANGS=fi reverse-data-spm
${MAKE} SRCLANGS=fi TRGLANGS=de WALLTIME=72 HPC_MEM=4g HPC_CORES=1 train-spm.submit-multigpu
memad_spm:
for s in fi en sv de fr nl; do \
for t in en fi sv de fr nl; do \
if [ "$$s" != "$$t" ]; then \
if ! grep -q 'stalled ${MARIAN_EARLY_STOPPING} times' ${WORKHOME}/$$s-$$t/*.valid${NR.log}; then\
${MAKE} SRCLANGS=$$s TRGLANGS=$$t traindata-spm; \
${MAKE} SRCLANGS=$$s TRGLANGS=$$t devdata-spm; \
${MAKE} SRCLANGS=$$s TRGLANGS=$$t wordalign-spm; \
${MAKE} SRCLANGS=$$s TRGLANGS=$$t HPC_CORES=1 HPC_MEM=4g train-spm.submit-multigpu; \
fi \
fi \
done \
done
memad_doc:
for s in fi en sv; do \
for t in en fi sv; do \
if [ "$$s" != "$$t" ]; then \
if ! grep -q 'stalled ${MARIAN_EARLY_STOPPING} times' ${WORKHOME}/$$s-$$t/*.valid${NR.log}; then\
${MAKE} SRCLANGS=$$s TRGLANGS=$$t traindata-doc; \
${MAKE} SRCLANGS=$$s TRGLANGS=$$t devdata-doc; \
${MAKE} SRCLANGS=$$s TRGLANGS=$$t HPC_CORES=1 HPC_MEM=4g MODELTYPE=transformer train-doc.submit-multigpu; \
fi \
fi \
done \
done
memad_docalign:
for s in fi en sv; do \
for t in en fi sv; do \
if [ "$$s" != "$$t" ]; then \
if ! grep -q 'stalled ${MARIAN_EARLY_STOPPING} times' ${WORKHOME}/$$s-$$t/*.valid${NR.log}; then\
${MAKE} SRCLANGS=$$s TRGLANGS=$$t traindata-doc; \
${MAKE} SRCLANGS=$$s TRGLANGS=$$t devdata-doc; \
${MAKE} SRCLANGS=$$s TRGLANGS=$$t HPC_CORES=1 HPC_MEM=4g train-doc.submit-multigpu; \
fi \
fi \
done \
done
enfisv:
${MAKE} SRCLANGS="en fi sv" TRGLANGS="en fi sv" traindata devdata wordalign
${MAKE} SRCLANGS="en fi sv" TRGLANGS="en fi sv" HPC_MEM=4g WALLTIME=72 HPC_CORES=1 train.submit-multigpu
en-fiet:
${MAKE} SRCLANGS="en" TRGLANGS="et fi" traindata devdata
${MAKE} SRCLANGS="en" TRGLANGS="et fi" HPC_MEM=4g HPC_CORES=1 train.submit-multigpu
${MAKE} TRGLANGS="en" SRCLANGS="et fi" traindata devdata
${MAKE} TRGLANGS="en" SRCLANGS="et fi" HPC_MEM=4g HPC_CORES=1 train.submit-multigpu
memad-multi1:
for s in "${SCANDINAVIAN}" "en fr" "et hu fi" "${WESTGERMANIC}" "ca es fr ga it la oc pt_br pt"; do \
${MAKE} SRCLANGS="$$s" TRGLANGS="$$s" traindata devdata; \
${MAKE} SRCLANGS="$$s" TRGLANGS="$$s" HPC_MEM=4g HPC_CORES=1 train.submit-multigpu; \
done
for s in "${SCANDINAVIAN}" "en fr" "et hu fi" "${WESTGERMANIC}" "ca es fr ga it la oc pt_br pt"; do \
for t in "${SCANDINAVIAN}" "en fr" "et hu fi" "${WESTGERMANIC}" "ca es fr ga it la oc pt_br pt"; do \
if [ "$$s" != "$$t" ]; then \
${MAKE} SRCLANGS="$$s" TRGLANGS="$$t" traindata devdata; \
${MAKE} SRCLANGS="$$s" TRGLANGS="$$t" HPC_MEM=4g HPC_CORES=1 train.submit-multigpu; \
fi \
done \
done
memad-multi2:
for s in "en fr" "et hu fi" "${WESTGERMANIC}" "ca es fr ga it la oc pt_br pt"; do \
for t in "${SCANDINAVIAN}" "en fr" "et hu fi" "${WESTGERMANIC}" "ca es fr ga it la oc pt_br pt"; do \
if [ "$$s" != "$$t" ]; then \
${MAKE} SRCLANGS="$$s" TRGLANGS="$$t" traindata devdata; \
${MAKE} SRCLANGS="$$s" TRGLANGS="$$t" HPC_MEM=4g HPC_CORES=1 train.submit-multigpu; \
fi \
done \
done
memad-multi3:
for s in "${SCANDINAVIAN}" "${WESTGERMANIC}" "ca es fr ga it la oc pt_br pt"; do \
${MAKE} SRCLANGS="$$s" TRGLANGS="en" traindata devdata; \
${MAKE} SRCLANGS="$$s" TRGLANGS="en" HPC_MEM=4g HPC_CORES=1 train.submit-multigpu; \
${MAKE} SRCLANGS="en" TRGLANGS="$$s" traindata devdata; \
${MAKE} SRCLANGS="en" TRGLANGS="$$s" HPC_MEM=4g HPC_CORES=1 train.submit-multigpu; \
done
${MAKE} SRCLANGS="en" TRGLANGS="fr" traindata devdata
${MAKE} SRCLANGS="en" TRGLANGS="fr" HPC_MEM=4g HPC_CORES=1 train.submit-multigpu
${MAKE} SRCLANGS="fr" TRGLANGS="en" traindata devdata
${MAKE} SRCLANGS="fr" TRGLANGS="en" HPC_MEM=4g HPC_CORES=1 train.submit-multigpu
memad-fi:
for l in en sv de fr; do \
${MAKE} SRCLANGS=$$l TRGLANGS=fi traindata devdata; \
${MAKE} SRCLANGS=$$l TRGLANGS=fi HPC_MEM=4g HPC_CORES=1 train.submit-multigpu; \
${MAKE} TRGLANGS=$$l SRCLANGS=fi traindata devdata; \
${MAKE} TRGLANGS=$$l SRCLANGS=fi HPC_MEM=4g HPC_CORES=1 train.submit-multigpu; \
done