mirror of
https://github.com/Helsinki-NLP/OPUS-MT-train.git
synced 2024-11-27 11:03:13 +03:00
894 lines
35 KiB
Makefile
894 lines
35 KiB
Makefile
# -*-makefile-*-
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#
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# create data files for taining, validation and testing
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#
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# - combine all bitexts in TRAINSET
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# - add backtranslation, pivoted data if necessary
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# - add language labels if necessary (multi-target models)
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# - over/under-sampling of training data if necessary (multilingual models)
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# - shuffle dev/test data and divide into to disjoint sets
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# - reverse data sets for the other translation direction (bilingual models only)
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# - run word alignment if necessary (models with guided alignment = transformer-align)
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#
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#
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# TODO: write data info to some model-specific file insetad of README.md
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# (applies for train/val/test!)
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## training data size (generates count if not in README.md)
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TRAINDATA_SIZE = ${shell \
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if [ -e ${WORKDIR}/train/README.md ]; then \
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if [ `grep 'total size (${DATASET}):' ${WORKDIR}/train/README.md | wc -l` -gt 0 ]; then \
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grep 'total size (${DATASET}):' ${WORKDIR}/train/README.md | cut -f2 -d':' ; \
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elif [ -e ${TRAIN_SRC}.clean.${PRE_SRC}.gz ]; then \
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echo -n '* total size (${DATASET}): ' >> ${WORKDIR}/train/README.md; \
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${GZIP} -cd < ${TRAIN_SRC}.clean.${PRE_SRC}.gz | wc -l >> ${WORKDIR}/train/README.md; \
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grep 'total size (${DATASET}):' ${WORKDIR}/train/README.md | cut -f2 -d':' ; \
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fi \
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elif [ -e ${TRAIN_SRC}.clean.${PRE_SRC}.gz ]; then \
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echo '\# ${DATASET}' >> ${WORKDIR}/train/README.md; \
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echo '' >> ${WORKDIR}/train/README.md; \
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echo -n '* total size (${DATASET}): ' >> ${WORKDIR}/train/README.md; \
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${GZIP} -cd < ${TRAIN_SRC}.clean.${PRE_SRC}.gz | wc -l >> ${WORKDIR}/train/README.md; \
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grep 'total size (${DATASET}):' ${WORKDIR}/train/README.md | cut -f2 -d':' ; \
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fi }
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## look for cleanup scripts and put them into a pipe
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## they should be executable and should basically read STDIN and print to STDOUT
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## no further arguments are supported
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ifneq (${wildcard ${REPOHOME}scripts/cleanup/${SRC}},)
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SRC_CLEANUP_SCRIPTS = | ${subst ${SPACE}, | ,${shell find ${REPOHOME}scripts/cleanup/${SRC} -executable -type f}}
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endif
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ifneq (${wildcard ${REPOHOME}scripts/cleanup/${TRG}},)
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TRG_CLEANUP_SCRIPTS = | ${subst ${SPACE}, | ,${shell find ${REPOHOME}scripts/cleanup/${TRG} -executable -type f}}
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endif
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##-------------------------------------------------------------
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## backtranslated data and pivot-based synthetic training data
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##-------------------------------------------------------------
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## back translation data
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## - use only the latest backtranslations
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## if such a subdir exists
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ifneq (${wildcard ${BACKTRANS_HOME}/${TRG}-${SRC}/latest},)
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BACKTRANS_DIR = ${BACKTRANS_HOME}/${TRG}-${SRC}/latest
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else
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BACKTRANS_DIR = ${BACKTRANS_HOME}/${TRG}-${SRC}
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endif
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## TODO: make it possible to select only parts of the BT data
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## ---> use TRAINDATA_SIZE to take max the same amount of all shuffled BT data
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# back-translation data (target-to-source)
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ifeq (${USE_BACKTRANS},1)
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BACKTRANS_SRC = ${sort ${wildcard ${BACKTRANS_DIR}/*.${SRCEXT}.gz}}
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BACKTRANS_TRG = ${patsubst %.${SRCEXT}.gz,%.${TRGEXT}.gz,${BACKTRANS_SRC}}
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endif
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# forward-translation data (source-to-target)
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ifeq (${USE_FORWARDTRANS},1)
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FORWARDTRANS_SRC = ${sort ${wildcard ${FORWARDTRANS_HOME}/${SRC}-${TRG}/latest/*.${SRCEXT}.gz}}
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FORWARDTRANS_TRG = ${patsubst %.${SRCEXT}.gz,%.${TRGEXT}.gz,${FORWARDTRANS_SRC}}
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endif
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# forward-translation data (source-to-target)
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# filtered by reconstruction scores (ce filter)
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ifneq (${USE_FORWARDTRANS_SELECTED},)
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FORWARDTRANS_SRC += ${sort ${wildcard ${FORWARDTRANS_HOME}/${SRC}-${TRG}/latest/*.${SRCEXT}.best${USE_FORWARDTRANS_SELECTED}.gz}}
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FORWARDTRANS_TRG += ${sort ${wildcard ${FORWARDTRANS_HOME}/${SRC}-${TRG}/latest/*.${TRGEXT}.best${USE_FORWARDTRANS_SELECTED}.gz}}
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endif
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## selected by "raw" (unnormalised) scores
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ifneq (${USE_FORWARDTRANS_SELECTED_RAW},)
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FORWARDTRANS_SRC += ${sort ${wildcard ${FORWARDTRANS_HOME}/${SRC}-${TRG}/latest/*.${SRCEXT}.rawbest${USE_FORWARDTRANS_SELECTED_RAW}.gz}}
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FORWARDTRANS_TRG += ${sort ${wildcard ${FORWARDTRANS_HOME}/${SRC}-${TRG}/latest/*.${TRGEXT}.rawbest${USE_FORWARDTRANS_SELECTED_RAW}.gz}}
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endif
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# forward-translation data of monolingual data (source-to-target)
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ifeq (${USE_FORWARDTRANSMONO},1)
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FORWARDTRANSMONO_SRC = ${sort ${wildcard ${BACKTRANS_HOME}/${SRC}-${TRG}/latest/*.${SRCEXT}.gz}}
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FORWARDTRANSMONO_TRG = ${patsubst %.${SRCEXT}.gz,%.${TRGEXT}.gz,${FORWARDTRANSMONO_SRC}}
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endif
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# forward translation using pivoting (target language is automatically created)
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ifeq (${USE_FORWARD_PIVOTING},1)
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PIVOTING_SRC = ${sort ${wildcard ${PIVOTTRANS_HOME}/${TRG}-${SRC}/latest/*.${SRCEXT}.gz}}
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PIVOTING_TRG = ${patsubst %.${SRCEXT}.gz,%.${TRGEXT}.gz,${PIVOTING_SRC}}
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endif
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# backward translation using pivoting (source language is automatically created)
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ifeq (${USE_BACKWARD_PIVOTING},1)
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PIVOTING_SRC += ${sort ${wildcard ${PIVOTTRANS_HOME}/${SRC}-${TRG}/latest/*.${SRCEXT}.gz}}
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PIVOTING_TRG = ${patsubst %.${SRCEXT}.gz,%.${TRGEXT}.gz,${PIVOTING_SRC}}
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endif
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# pivot-based data augmentation data (in both directions)
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ifeq (${USE_PIVOTING},1)
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PIVOTING_SRC = ${sort ${wildcard ${PIVOTTRANS_HOME}/${SRC}-${TRG}/latest/*.${SRCEXT}.gz} \
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${wildcard ${PIVOTTRANS_HOME}/${TRG}-${SRC}/latest/*.${SRCEXT}.gz}}
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PIVOTING_TRG = ${patsubst %.${SRCEXT}.gz,%.${TRGEXT}.gz,${PIVOTING_SRC}}
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endif
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print-datasets:
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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 print-datasets-current-langpair; \
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done \
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done
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print-datasets-current-langpair:
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@echo ${TATOEBA_TRAINSET}
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@echo ${TRAINSET}
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@echo "all data:"
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@echo ${CLEAN_TRAIN_SRC}
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@echo ${CLEAN_TRAIN_TRG}
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@echo "back-translation data:"
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@echo ${BACKTRANS_SRC}
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@echo ${BACKTRANS_TRG}
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@echo "forward translation data:"
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@echo ${FORWARDTRANS_SRC}
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@echo ${FORWARDTRANS_TRG}
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@echo "monolingual forward translation data:"
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@echo ${FORWARDTRANSMONO_SRC}
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@echo ${FORWARDTRANSMONO_TRG}
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@echo "pivot-based translation data:"
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@echo ${PIVOTING_SRC}
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@echo ${PIVOTING_TRG}
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##-------------------------------------------------------------
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## data sets (train/dev/test)
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##-------------------------------------------------------------
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## data sets to be included in the train/dev/test sets
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## with some basic pre-processing (see lib/preprocess.mk)
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CLEAN_TRAIN_SRC = ${patsubst %,${DATADIR}/${PRE}/%.${LANGPAIR}.${CLEAN_TRAINDATA_TYPE}.${SRCEXT}.gz,${TRAINSET}} \
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${BACKTRANS_SRC} ${FORWARDTRANS_SRC} ${FORWARDTRANSMONO_SRC} ${PIVOTING_SRC}
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CLEAN_TRAIN_TRG = ${patsubst %,${DATADIR}/${PRE}/%.${LANGPAIR}.${CLEAN_TRAINDATA_TYPE}.${TRGEXT}.gz,${TRAINSET}} \
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${BACKTRANS_TRG} ${FORWARDTRANS_TRG} ${FORWARDTRANSMONO_TRG} ${PIVOTING_TRG}
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CLEAN_DEV_SRC = ${patsubst %,${DATADIR}/${PRE}/%.${LANGPAIR}.${CLEAN_DEVDATA_TYPE}.${SRCEXT}.gz,${DEVSET}}
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CLEAN_DEV_TRG = ${patsubst %.${SRCEXT}.gz,%.${TRGEXT}.gz,${CLEAN_DEV_SRC}}
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CLEAN_TEST_SRC = ${patsubst %,${DATADIR}/${PRE}/%.${LANGPAIR}.${CLEAN_TESTDATA_TYPE}.${SRCEXT}.gz,${TESTSET}}
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CLEAN_TEST_TRG = ${patsubst %.${SRCEXT}.gz,%.${TRGEXT}.gz,${CLEAN_TEST_SRC}}
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CLEAN_TEST_SRC_STATS = ${CLEAN_TEST_SRC:.gz=.stats}
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CLEAN_TEST_TRG_STATS = ${CLEAN_TEST_TRG:.gz=.stats}
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DATA_SRC := ${sort ${CLEAN_TRAIN_SRC} ${CLEAN_DEV_SRC} ${CLEAN_TEST_SRC}}
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DATA_TRG := ${sort ${CLEAN_TRAIN_TRG} ${CLEAN_DEV_TRG} ${CLEAN_TEST_TRG}}
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##-------------------------------------------------------------
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## make data in reverse direction without re-doing word alignment etc ...
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## ---> this is dangerous when things run in parallel
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## ---> only works for bilingual models
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##-------------------------------------------------------------
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REV_LANGSTR = ${subst ${SPACE},+,$(TRGLANGS)}-${subst ${SPACE},+,$(SRCLANGS)}
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REV_WORKDIR = ${WORKHOME}/${REV_LANGSTR}
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.PHONY: reverse-data
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reverse-data:
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ifeq (${PRE_SRC},${PRE_TRG})
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ifeq (${words ${SRCLANGS}},1)
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ifeq (${words ${TRGLANGS}},1)
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mkdir -p ${REV_WORKDIR}/train
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-if [ -e ${TRAIN_SRC}.clean.${PRE_SRC}.gz ]; then \
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ln -s ${TRAIN_SRC}.clean.${PRE_SRC}.gz ${REV_WORKDIR}/train/${notdir ${TRAIN_TRG}.clean.${PRE_TRG}.gz}; \
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ln -s ${TRAIN_TRG}.clean.${PRE_TRG}.gz ${REV_WORKDIR}/train/${notdir ${TRAIN_SRC}.clean.${PRE_SRC}.gz}; \
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cp ${WORKDIR}/train/README.md ${REV_WORKDIR}/train/README.md; \
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fi
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-if [ -e ${SUBWORD_SRC_MODEL} ]; then \
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ln -s ${SUBWORD_SRC_MODEL} ${REV_WORKDIR}/train/${notdir ${SUBWORD_TRG_MODEL}}; \
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fi
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-if [ -e ${SUBWORD_TRG_MODEL} ]; then \
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ln -s ${SUBWORD_TRG_MODEL} ${REV_WORKDIR}/train/${notdir ${SUBWORD_SRC_MODEL}}; \
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fi
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-if [ -e ${SUBWORD_SRC_MODEL}.vocab ]; then \
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ln -s ${SUBWORD_SRC_MODEL}.vocab ${REV_WORKDIR}/train/${notdir ${SUBWORD_TRG_MODEL}}.vocab; \
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fi
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-if [ -e ${SUBWORD_TRG_MODEL}.vocab ]; then \
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ln -s ${SUBWORD_TRG_MODEL}.vocab ${REV_WORKDIR}/train/${notdir ${SUBWORD_SRC_MODEL}}.vocab; \
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fi
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-if [ -e ${TRAIN_ALG} ]; then \
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if [ ! -e ${REV_WORKDIR}/train/${notdir ${TRAIN_ALG}} ]; then \
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${GZIP} -cd < ${TRAIN_ALG} | ${MOSESSCRIPTS}/generic/reverse-alignment.perl |\
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${GZIP} -c > ${REV_WORKDIR}/train/${notdir ${TRAIN_ALG}}; \
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fi \
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fi
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-if [ -e ${DEV_SRC}.${PRE_SRC} ]; then \
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mkdir -p ${REV_WORKDIR}/val; \
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ln -s ${DEV_SRC}.${PRE_SRC} ${REV_WORKDIR}/val/${notdir ${DEV_TRG}.${PRE_TRG}}; \
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ln -s ${DEV_TRG}.${PRE_TRG} ${REV_WORKDIR}/val/${notdir ${DEV_SRC}.${PRE_SRC}}; \
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ln -s ${DEV_SRC} ${REV_WORKDIR}/val/${notdir ${DEV_TRG}}; \
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ln -s ${DEV_TRG} ${REV_WORKDIR}/val/${notdir ${DEV_SRC}}; \
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ln -s ${DEV_SRC}.shuffled.gz ${REV_WORKDIR}/val/${notdir ${DEV_SRC}.shuffled.gz}; \
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ln -s ${DEV_SRC}.notused.gz ${REV_WORKDIR}/val/${notdir ${DEV_TRG}.notused.gz}; \
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ln -s ${DEV_TRG}.notused.gz ${REV_WORKDIR}/val/${notdir ${DEV_SRC}.notused.gz}; \
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cp ${WORKDIR}/val/README.md ${REV_WORKDIR}/val/README.md; \
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fi
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-if [ -e ${TEST_SRC} ]; then \
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mkdir -p ${REV_WORKDIR}/test; \
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ln -s ${TEST_SRC} ${REV_WORKDIR}/test/${notdir ${TEST_TRG}}; \
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ln -s ${TEST_TRG} ${REV_WORKDIR}/test/${notdir ${TEST_SRC}}; \
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cp ${WORKDIR}/test/README.md ${REV_WORKDIR}/test/README.md; \
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fi
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-if [ -e ${MODEL_SRCVOCAB} ]; then \
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ln -s ${MODEL_SRCVOCAB} ${REV_WORKDIR}/${notdir ${MODEL_TRGVOCAB}}; \
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fi
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-if [ -e ${MODEL_TRGVOCAB} ]; then \
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ln -s ${MODEL_TRGVOCAB} ${REV_WORKDIR}/${notdir ${MODEL_SRCVOCAB}}; \
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fi
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-if [ -e ${MODEL_VOCAB} ]; then \
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ln -s ${MODEL_VOCAB} ${REV_WORKDIR}/${notdir ${MODEL_VOCAB}}; \
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fi
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##
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## this is a bit dangerous with some trick to
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## swap parameters between SRC and TRG
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##
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-if [ -e ${WORKDIR}/${MODELCONFIG} ]; then \
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if [ ! -e ${REV_WORKDIR}/${MODELCONFIG} ]; then \
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cat ${WORKDIR}/${MODELCONFIG} |\
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sed -e 's/SRC/TTT/g;s/TRG/SRC/g;s/TTT/TRG/' |\
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grep -v LANGPAIRSTR > ${REV_WORKDIR}/$(notdir ${MODELCONFIG}); \
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fi \
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fi
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endif
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endif
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endif
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.PHONY: clean-data rawdata
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clean-data rawdata:
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@for s in ${SRCLANGS}; do \
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for t in ${TRGLANGS}; do \
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echo "..... create raw data for $$s-$$t"; \
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${MAKE} SRC=$$s TRG=$$t clean-data-source; \
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done \
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done
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.PHONY: clean-data-source
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clean-data-source:
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@${MAKE} ${CLEAN_TEST_SRC} ${CLEAN_TEST_TRG}
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@${MAKE} ${CLEAN_TEST_SRC_STATS} ${CLEAN_TEST_TRG_STATS}
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@${MAKE} ${DATA_SRC} ${DATA_TRG}
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## shuffle training data (if one wants to do that after they have been created already)
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.PHONY: shuffle-training-data
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shuffle-training-data:
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ifneq (${wildcard ${TRAIN_ALG}},)
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paste <(gzip -cd ${TRAIN_SRC}.clean.${PRE_SRC}.gz) \
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<(gzip -cd ${TRAIN_TRG}.clean.${PRE_TRG}.gz) \
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<(gzip -cd ${TRAIN_ALG}) |\
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${SHUFFLE} |\
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tee >(cut -f1 | gzip -c >${TRAIN_SRC}.clean.${PRE_SRC}.new.gz) \
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>(cut -f2 | gzip -c >${TRAIN_TRG}.clean.${PRE_TRG}.new.gz) | \
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cut -f3 | gzip -c > ${TRAIN_ALG}.new.gz
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mv -f ${TRAIN_SRC}.clean.${PRE_SRC}.new.gz ${TRAIN_SRC}.clean.${PRE_SRC}.gz
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mv -f ${TRAIN_TRG}.clean.${PRE_TRG}.new.gz ${TRAIN_TRG}.clean.${PRE_TRG}.gz
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mv ${TRAIN_ALG}.new.gz ${TRAIN_ALG}
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else
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paste <(gzip -cd ${TRAIN_SRC}.clean.${PRE_SRC}.gz) \
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<(gzip -cd ${TRAIN_TRG}.clean.${PRE_TRG}.gz) |\
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${SHUFFLE} |\
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tee >(cut -f1 | gzip -c >${TRAIN_SRC}.clean.${PRE_SRC}.new.gz) \
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>(cut -f2 | gzip -c >${TRAIN_TRG}.clean.${PRE_TRG}.new.gz)
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mv -f ${TRAIN_SRC}.clean.${PRE_SRC}.new.gz ${TRAIN_SRC}.clean.${PRE_SRC}.gz
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mv -f ${TRAIN_TRG}.clean.${PRE_TRG}.new.gz ${TRAIN_TRG}.clean.${PRE_TRG}.gz
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endif
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## monolingual data sets (for sentence piece models)
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.INTERMEDIATE: ${LOCAL_MONO_DATA}.${PRE} ${LOCAL_MONO_DATA}.raw
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.PHONY: mono-data
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mono-data: ${LOCAL_MONO_DATA}.${PRE}
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## word alignment used for guided alignment
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## (always remove intermediate files)
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.INTERMEDIATE: ${LOCAL_TRAIN_SRC}.algtmp ${LOCAL_TRAIN_TRG}.algtmp
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${LOCAL_TRAIN_SRC}.algtmp: ${TRAIN_SRC}.clean.${PRE_SRC}${TRAINSIZE}.gz
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mkdir -p ${dir $@}
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${GZIP} -cd < $< > $@
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${LOCAL_TRAIN_TRG}.algtmp: ${TRAIN_TRG}.clean.${PRE_TRG}${TRAINSIZE}.gz
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mkdir -p ${dir $@}
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${GZIP} -cd < $< > $@
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## max number of lines in a corpus for running word alignment
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## (split into chunks of max that size before aligning)
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MAX_WORDALIGN_SIZE = 5000000
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# MAX_WORDALIGN_SIZE = 10000000
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# MAX_WORDALIGN_SIZE = 25000000
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## nr of simultaneous word alignment jobs
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## (assuming that each of them occupies up to 6 cores
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NR_ALIGN_JOBS ?= $$(( ${CPU_CORES} / 6 + 1 ))
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## job forcing doesn't work within recipes
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# ${MAKE} -j ${NR_ALIGN_JOBS} $$a
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${TRAIN_ALG}: ${TRAIN_SRC}.clean.${PRE_SRC}${TRAINSIZE}.gz \
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${TRAIN_TRG}.clean.${PRE_TRG}${TRAINSIZE}.gz
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${MAKE} ${LOCAL_TRAIN_SRC}.algtmp ${LOCAL_TRAIN_TRG}.algtmp
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if [ `head $(LOCAL_TRAIN_SRC).algtmp | wc -l` -gt 0 ]; then \
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mkdir -p $(LOCAL_TRAIN_SRC).algtmp.d; \
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mkdir -p $(LOCAL_TRAIN_TRG).algtmp.d; \
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split -l ${MAX_WORDALIGN_SIZE} $(LOCAL_TRAIN_SRC).algtmp $(LOCAL_TRAIN_SRC).algtmp.d/; \
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split -l ${MAX_WORDALIGN_SIZE} $(LOCAL_TRAIN_TRG).algtmp $(LOCAL_TRAIN_TRG).algtmp.d/; \
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a=`ls $(LOCAL_TRAIN_SRC).algtmp.d/* | sed 's#$$#.alg#' | xargs`; \
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if [ "$$a" != "" ]; then \
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${MAKE} $$a; \
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cat $(LOCAL_TRAIN_SRC).algtmp.d/*.alg | ${GZIP} -c > $@; \
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rm -f ${LOCAL_TRAIN_SRC}.algtmp.d/*; \
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rm -f ${LOCAL_TRAIN_TRG}.algtmp.d/*; \
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fi; \
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rmdir ${LOCAL_TRAIN_SRC}.algtmp.d; \
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rmdir ${LOCAL_TRAIN_TRG}.algtmp.d; \
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fi
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rm -f ${LOCAL_TRAIN_SRC}.algtmp ${LOCAL_TRAIN_TRG}.algtmp
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## old: do this sequenctially
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## new: do this in parallel via make (see above)
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## disadvantage: may require more memory!
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# for s in `ls $(LOCAL_TRAIN_SRC).algtmp.d`; do \
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# echo "align part $$s"; \
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# ${WORDALIGN} --overwrite \
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# -s $(LOCAL_TRAIN_SRC).algtmp.d/$$s \
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# -t $(LOCAL_TRAIN_TRG).algtmp.d/$$s \
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# -f $(LOCAL_TRAIN_SRC).algtmp.d/$$s.fwd \
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# -r $(LOCAL_TRAIN_TRG).algtmp.d/$$s.rev; \
|
|
# done;
|
|
|
|
|
|
$(LOCAL_TRAIN_SRC).algtmp.d/%.alg: $(LOCAL_TRAIN_SRC).algtmp.d/% $(LOCAL_TRAIN_TRG).algtmp.d/%
|
|
echo "align part ${notdir $<}"
|
|
${WORDALIGN} --overwrite \
|
|
-s $(word 1,$^) \
|
|
-t $(word 2,$^) \
|
|
-f $(word 1,$^).fwd \
|
|
-r $(word 2,$^).rev
|
|
echo "merge and symmetrize part ${notdir $<}"
|
|
${ATOOLS} -c grow-diag-final -i $(word 1,$^).fwd -j $(word 2,$^).rev > $@
|
|
rm -f $(word 1,$^).fwd $(word 2,$^).rev
|
|
|
|
|
|
|
|
|
|
## fetch OPUS data, try in this order
|
|
##
|
|
## (1) check first whether they exist on the local file system
|
|
## (2) check that Moses files can be downloaded
|
|
## (3) read with opus_read from local file system
|
|
## (4) fetch and read with opus_read
|
|
##
|
|
## TODO:
|
|
## - should we do langid filtering and link prob filtering here?
|
|
## (could set OPUSREAD_ARGS for that)
|
|
##
|
|
|
|
%.${SRCEXT}.raw:
|
|
mkdir -p ${dir $@}
|
|
-( c=${patsubst %.${LANGPAIR}.${SRCEXT}.raw,%,${notdir $@}}; \
|
|
if [ -e ${OPUSHOME}/$$c/latest/moses/${LANGPAIR}.txt.zip ]; then \
|
|
unzip -d ${dir $@} -n ${OPUSHOME}/$$c/latest/moses/${LANGPAIR}.txt.zip; \
|
|
mv ${dir $@}$$c*.${LANGPAIR}.${SRCEXT} $@; \
|
|
mv ${dir $@}$$c*.${LANGPAIR}.${TRGEXT} ${@:.${SRCEXT}.raw=.${TRGEXT}.raw}; \
|
|
rm -f ${@:.${SRCEXT}.raw=.xml} ${@:.${SRCEXT}.raw=.ids} ${dir $@}/README ${dir $@}/LICENSE; \
|
|
elif [ "${call url-exists,${call resource-url,${SRCEXT},${TRGEXT},${patsubst %.${LANGPAIR}.${SRCEXT}.raw,%,${notdir $@}}}}" == "1" ]; then \
|
|
l="${call resource-url,${SRCEXT},${TRGEXT},${patsubst %.${LANGPAIR}.${SRCEXT}.raw,%,${notdir $@}}}"; \
|
|
echo "============================================"; \
|
|
echo "fetch moses data from $$l"; \
|
|
echo "============================================"; \
|
|
${WGET} -qq -O $@-$$c-${LANGPAIR}.zip $$l; \
|
|
unzip -d ${dir $@} -n $@-$$c-${LANGPAIR}.zip; \
|
|
mv ${dir $@}$$c*.${LANGPAIR}.${SRCEXT} $@; \
|
|
mv ${dir $@}$$c*.${LANGPAIR}.${TRGEXT} ${@:.${SRCEXT}.raw=.${TRGEXT}.raw}; \
|
|
rm -f ${@:.${SRCEXT}.raw=.xml} ${@:.${SRCEXT}.raw=.ids} ${dir $@}/README ${dir $@}/LICENSE; \
|
|
rm -f $@-$$c-${LANGPAIR}.zip; \
|
|
elif [ -e ${OPUSHOME}/$$c/latest/xml/${LANGPAIR}.xml.gz ]; then \
|
|
echo "============================================"; \
|
|
echo "extract $$c (${LANGPAIR}) from XML in local OPUS copy"; \
|
|
echo "============================================"; \
|
|
opus_read ${OPUSREAD_ARGS} -ln -rd ${OPUSHOME} -d $$c -s ${SRC} -t ${TRG} \
|
|
-wm moses -p raw -w $@ ${@:.${SRCEXT}.raw=.${TRGEXT}.raw}; \
|
|
else \
|
|
echo "============================================"; \
|
|
echo "fetch $$c (${LANGPAIR}) from OPUS"; \
|
|
echo "============================================"; \
|
|
opus_read ${OPUSREAD_ARGS} -ln -q -dl ${TMPWORKDIR} -d $$c -s ${SRC} -t ${TRG} \
|
|
-wm moses -p raw -w $@ ${@:.${SRCEXT}.raw=.${TRGEXT}.raw}; \
|
|
fi )
|
|
|
|
# echo "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!"; \
|
|
# echo "!! skip $@"; \
|
|
# echo "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!"; \
|
|
|
|
|
|
%.${TRGEXT}.raw: %.${SRCEXT}.raw
|
|
@echo "done!"
|
|
|
|
|
|
## TODO: does this causes make to frequently redo the same data?
|
|
## --> could be a problem with large models!
|
|
.INTERMEDIATE: ${LOCAL_TRAIN_SRC} ${LOCAL_TRAIN_TRG}
|
|
|
|
## define dependency on DEVDATA if they need to be added to the train data
|
|
ifeq (${USE_REST_DEVDATA},1)
|
|
LOCAL_TRAINDATA_DEPENDENCIES = ${DEV_SRC} ${DEV_TRG}
|
|
endif
|
|
|
|
|
|
## for multilingual systems:
|
|
## shuffle the complete training data set
|
|
## if the option is set to 1
|
|
ifeq (${SHUFFLE_MULTILINGUAL_DATA},1)
|
|
ifneq ($(words ${SRCLANGS} ${TRGLANGS}),2)
|
|
SHUFFLE_TRAINING_DATA = 1
|
|
endif
|
|
endif
|
|
|
|
|
|
## add training data for each language combination
|
|
## and put it together in local space
|
|
${LOCAL_TRAIN_SRC}: ${LOCAL_TRAINDATA_DEPENDENCIES}
|
|
@mkdir -p ${dir $@}
|
|
@echo "" > ${dir $@}README.md
|
|
@echo "# ${notdir ${TRAIN_BASE}}" >> ${dir $@}README.md
|
|
@echo "" >> ${dir $@}README.md
|
|
@rm -f ${LOCAL_TRAIN_SRC} ${LOCAL_TRAIN_TRG}
|
|
-@for s in ${SRCLANGS}; do \
|
|
for t in ${TRGLANGS}; do \
|
|
if [ ! `echo "$$s-$$t $$t-$$s" | egrep '${SKIP_LANGPAIRS}' | wc -l` -gt 0 ]; then \
|
|
if [ "${SKIP_SAME_LANG}" == "1" ] && [ "$$s" == "$$t" ]; then \
|
|
echo "!!!!!!!!!!! skip language pair $$s-$$t !!!!!!!!!!!!!!!!"; \
|
|
else \
|
|
echo "..... add data for $$s-$$t"; \
|
|
${MAKE} DATASET=${DATASET} SRC:=$$s TRG:=$$t add-to-local-train-data; \
|
|
fi \
|
|
else \
|
|
echo "!!!!!!!!!!! skip language pair $$s-$$t !!!!!!!!!!!!!!!!"; \
|
|
fi \
|
|
done \
|
|
done
|
|
ifeq (${USE_REST_DEVDATA},1)
|
|
@if [ -e ${DEV_SRC}.notused.gz ]; then \
|
|
echo "..... add unused devdata to training data"; \
|
|
echo "* unused dev/test data is added to training data" >> ${dir $@}README.md; \
|
|
${GZIP} -cd < ${DEV_SRC}.notused.gz >> ${LOCAL_TRAIN_SRC}; \
|
|
${GZIP} -cd < ${DEV_TRG}.notused.gz >> ${LOCAL_TRAIN_TRG}; \
|
|
fi
|
|
endif
|
|
######################################
|
|
# run another round of cleaning if
|
|
# CLEAN_CORPUS_TRAINING_DATA is set
|
|
# --> could be useful if there is
|
|
# noisy data in back-translations etc
|
|
######################################
|
|
ifeq (${CLEAN_CORPUS_TRAINING_DATA},1)
|
|
@echo ".... another cleanup of local training data"
|
|
@ln -s ${LOCAL_TRAIN_SRC} ${LOCAL_TRAIN_SRC}.${SRCEXT}
|
|
@ln -s ${LOCAL_TRAIN_TRG} ${LOCAL_TRAIN_SRC}.${TRGEXT}
|
|
@$(MOSESSCRIPTS)/training/clean-corpus-n.perl \
|
|
-ratio ${NR_TOKEN_RATIO} \
|
|
-max-word-length ${MAX_TOKEN_LENGTH} \
|
|
${LOCAL_TRAIN_SRC} $(SRCEXT) $(TRGEXT) \
|
|
${LOCAL_TRAIN_SRC}.clean \
|
|
${MIN_NR_TOKENS} ${MAX_NR_TOKENS}
|
|
@mv -f ${LOCAL_TRAIN_SRC}.clean.${SRCEXT} ${LOCAL_TRAIN_SRC}
|
|
@mv -f ${LOCAL_TRAIN_SRC}.clean.${TRGEXT} ${LOCAL_TRAIN_TRG}
|
|
@rm -f ${LOCAL_TRAIN_SRC}.${SRCEXT} ${LOCAL_TRAIN_SRC}.${TRGEXT}
|
|
endif
|
|
ifeq (${SHUFFLE_TRAINING_DATA},1)
|
|
@echo ".... shuffle complete training data"
|
|
@paste ${LOCAL_TRAIN_SRC} ${LOCAL_TRAIN_TRG} | ${SHUFFLE} > ${LOCAL_TRAIN_SRC}.shuffled
|
|
@cut -f1 ${LOCAL_TRAIN_SRC}.shuffled > ${LOCAL_TRAIN_SRC}
|
|
@cut -f2 ${LOCAL_TRAIN_SRC}.shuffled > ${LOCAL_TRAIN_TRG}
|
|
@rm -f ${LOCAL_TRAIN_SRC}.shuffled
|
|
endif
|
|
|
|
|
|
|
|
## everything is done in the target above
|
|
${LOCAL_TRAIN_TRG}: ${LOCAL_TRAIN_SRC}
|
|
@echo "done!"
|
|
|
|
|
|
|
|
|
|
|
|
## cut the data sets immediately if we don't have
|
|
## to shuffle first! This saves a lot of time!
|
|
|
|
ifneq (${SHUFFLE_DATA},1)
|
|
ifdef FIT_DATA_SIZE
|
|
CUT_DATA_SETS = | head -${FIT_DATA_SIZE}
|
|
endif
|
|
endif
|
|
|
|
|
|
## add language labels to the source language
|
|
## if we have multiple target languages
|
|
|
|
ifeq (${USE_TARGET_LABELS},1)
|
|
LABEL_SOURCE_DATA = | sed "s/^/>>${TRG}<< /"
|
|
endif
|
|
|
|
|
|
## add to the training data
|
|
|
|
.PHONY: add-to-local-train-data
|
|
add-to-local-train-data: ${CLEAN_TRAIN_SRC} ${CLEAN_TRAIN_TRG}
|
|
ifdef CHECK_TRAINDATA_SIZE
|
|
@if [ `${GZCAT} ${wildcard ${CLEAN_TRAIN_SRC}} | wc -l` != `${GZCAT} ${wildcard ${CLEAN_TRAIN_TRG}} | wc -l` ]; then \
|
|
echo "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!"; \
|
|
echo "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!"; \
|
|
echo "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!"; \
|
|
echo "source and target are not of same length!"; \
|
|
echo "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!"; \
|
|
echo "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!"; \
|
|
echo "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!"; \
|
|
echo ${CLEAN_TRAIN_SRC}; \
|
|
echo ${CLEAN_TRAIN_TRG}; \
|
|
fi
|
|
endif
|
|
@echo "..... add info about training data"
|
|
@mkdir -p ${dir ${LOCAL_TRAIN_SRC}} ${dir ${LOCAL_TRAIN_TRG}}
|
|
@echo -n "* ${SRC}-${TRG}: " >> ${dir ${LOCAL_TRAIN_SRC}}README.md
|
|
@for d in ${wildcard ${CLEAN_TRAIN_SRC}}; do \
|
|
l=`${GZIP} -cd < $$d ${CUT_DATA_SETS} 2>/dev/null | wc -l`; \
|
|
if [ $$l -gt 0 ]; then \
|
|
echo "$$d" | xargs basename | \
|
|
sed -e 's#.${SRC}.gz$$##' \
|
|
-e 's#.clean$$##'\
|
|
-e 's#.${LANGPAIR}$$##' | tr "\n" ' ' >> ${dir ${LOCAL_TRAIN_SRC}}README.md; \
|
|
echo -n "($$l) " >> ${dir ${LOCAL_TRAIN_SRC}}README.md; \
|
|
fi \
|
|
done
|
|
@echo "" >> ${dir ${LOCAL_TRAIN_SRC}}README.md
|
|
######################################
|
|
# create local data files (add label if necessary)
|
|
######################################
|
|
@echo "..... create training data in local scratch space"
|
|
@${GZCAT} ${wildcard ${CLEAN_TRAIN_SRC}} ${CUT_DATA_SETS} 2>/dev/null \
|
|
${LABEL_SOURCE_DATA} > ${LOCAL_TRAIN_SRC}.${LANGPAIR}.src
|
|
@${GZCAT} ${wildcard ${CLEAN_TRAIN_TRG}} ${CUT_DATA_SETS} 2>/dev/null \
|
|
> ${LOCAL_TRAIN_TRG}.${LANGPAIR}.trg
|
|
######################################
|
|
# SHUFFLE_DATA is set?
|
|
# --> shuffle data for each langpair
|
|
# --> do this when FIT_DATA_SIZE is set!
|
|
######################################
|
|
ifeq (${SHUFFLE_DATA},1)
|
|
@if [ -s ${LOCAL_TRAIN_SRC}.${LANGPAIR}.src ]; then \
|
|
echo "..... shuffle training data"; \
|
|
paste ${LOCAL_TRAIN_SRC}.${LANGPAIR}.src ${LOCAL_TRAIN_TRG}.${LANGPAIR}.trg |\
|
|
${SHUFFLE} > ${LOCAL_TRAIN_SRC}.shuffled; \
|
|
cut -f1 ${LOCAL_TRAIN_SRC}.shuffled > ${LOCAL_TRAIN_SRC}.${LANGPAIR}.src; \
|
|
cut -f2 ${LOCAL_TRAIN_SRC}.shuffled > ${LOCAL_TRAIN_TRG}.${LANGPAIR}.trg; \
|
|
rm -f ${LOCAL_TRAIN_SRC}.shuffled; \
|
|
else \
|
|
echo "..... empty training data: ${LOCAL_TRAIN_SRC}.${LANGPAIR}.src"; \
|
|
fi
|
|
endif
|
|
######################################
|
|
# FIT_DATA_SIZE is set?
|
|
# --> fit data to specific size
|
|
# --> under/over sampling!
|
|
######################################
|
|
@echo -n "* ${SRC}-${TRG}: total size = " >> ${dir ${LOCAL_TRAIN_SRC}}README.md
|
|
ifdef FIT_DATA_SIZE
|
|
@echo "sample data to fit size = ${FIT_DATA_SIZE}"
|
|
@${REPOHOME}scripts/fit-data-size.pl -m ${MAX_OVER_SAMPLING} ${FIT_DATA_SIZE} \
|
|
${LOCAL_TRAIN_SRC}.${LANGPAIR}.src | wc -l >> ${dir ${LOCAL_TRAIN_SRC}}README.md
|
|
@${REPOHOME}scripts/fit-data-size.pl -m ${MAX_OVER_SAMPLING} ${FIT_DATA_SIZE} \
|
|
${LOCAL_TRAIN_SRC}.${LANGPAIR}.src >> ${LOCAL_TRAIN_SRC}
|
|
@${REPOHOME}scripts/fit-data-size.pl -m ${MAX_OVER_SAMPLING} ${FIT_DATA_SIZE} \
|
|
${LOCAL_TRAIN_TRG}.${LANGPAIR}.trg >> ${LOCAL_TRAIN_TRG}
|
|
else
|
|
@cat ${LOCAL_TRAIN_SRC}.${LANGPAIR}.src | wc -l >> ${dir ${LOCAL_TRAIN_SRC}}README.md
|
|
@cat ${LOCAL_TRAIN_SRC}.${LANGPAIR}.src >> ${LOCAL_TRAIN_SRC}
|
|
@cat ${LOCAL_TRAIN_TRG}.${LANGPAIR}.trg >> ${LOCAL_TRAIN_TRG}
|
|
endif
|
|
@rm -f ${LOCAL_TRAIN_SRC}.${LANGPAIR}.src ${LOCAL_TRAIN_TRG}.${LANGPAIR}.trg
|
|
|
|
|
|
|
|
|
|
####################
|
|
# development data
|
|
####################
|
|
|
|
.PHONY: show-devdata
|
|
show-devdata:
|
|
@echo "${CLEAN_DEV_SRC}"
|
|
@echo "${CLEAN_DEV_TRG}"
|
|
@echo ${SUBWORD_SRC_MODEL}
|
|
@echo ${SUBWORD_TRG_MODEL}
|
|
@echo "${DEV_SRC}.${PRE_SRC}"
|
|
@echo "${DEV_TRG}.${PRE_TRG}"
|
|
|
|
.PHONY: raw-devdata
|
|
raw-devdata: ${DEV_SRC} ${DEV_TRG}
|
|
|
|
|
|
## TODO: should we have some kind of balanced shuffling
|
|
## to avoid bias towards bigger language pairs?
|
|
## maybe introduce over/undersampling of dev data like we have for train data?
|
|
|
|
${DEV_SRC}.shuffled.gz:
|
|
mkdir -p ${sort ${dir $@} ${dir ${DEV_SRC}} ${dir ${DEV_TRG}}}
|
|
rm -f ${DEV_SRC} ${DEV_TRG}
|
|
echo "# Validation data" > ${dir ${DEV_SRC}}README.md
|
|
echo "" >> ${dir ${DEV_SRC}}README.md
|
|
-for s in ${SRCLANGS}; do \
|
|
for t in ${TRGLANGS}; do \
|
|
if [ ! `echo "$$s-$$t $$t-$$s" | egrep '${SKIP_LANGPAIRS}' | wc -l` -gt 0 ]; then \
|
|
if [ "${SKIP_SAME_LANG}" == "1" ] && [ "$$s" == "$$t" ]; then \
|
|
echo "!!!!!!!!!!! skip language pair $$s-$$t !!!!!!!!!!!!!!!!"; \
|
|
else \
|
|
${MAKE} SRC=$$s TRG=$$t add-to-dev-data; \
|
|
fi \
|
|
else \
|
|
echo "!!!!!!!!!!! skip language pair $$s-$$t !!!!!!!!!!!!!!!!"; \
|
|
fi \
|
|
done \
|
|
done
|
|
ifeq (${SHUFFLE_DEVDATA},0)
|
|
paste ${DEV_SRC} ${DEV_TRG} | ${GZIP} -c > $@
|
|
else
|
|
paste ${DEV_SRC} ${DEV_TRG} | ${UNIQ} | ${SHUFFLE} | ${GZIP} -c > $@
|
|
endif
|
|
echo -n "* total-size-shuffled: " >> ${dir ${DEV_SRC}}README.md
|
|
${GZIP} -cd < $@ | wc -l >> ${dir ${DEV_SRC}}README.md
|
|
|
|
## OLD: don't uniq the dev-data ...
|
|
##
|
|
# paste ${DEV_SRC} ${DEV_TRG} | ${SHUFFLE} | ${GZIP} -c > $@
|
|
# echo -n "* total size of shuffled dev data: " >> ${dir ${DEV_SRC}}README.md
|
|
|
|
|
|
## if we have less than twice the amount of DEVMINSIZE in the data set
|
|
## --> extract some data from the training data to be used as devdata
|
|
|
|
${DEV_SRC}: %: %.shuffled.gz
|
|
## if we extract test and dev data from the same data set
|
|
## ---> make sure that we do not have any overlap between the two data sets
|
|
## ---> reserve at least DEVMINSIZE data for dev data and keep the rest for testing
|
|
ifeq (${DEVSET},${TESTSET})
|
|
@if (( `${GZIP} -cd < $< | wc -l` < $$((${DEVSIZE} + ${TESTSIZE})) )); then \
|
|
if (( `${GZIP} -cd < $< | wc -l` < $$((${DEVSMALLSIZE} + ${DEVMINSIZE})) )); then \
|
|
echo "extract ${DEVMINSIZE} examples from ${DEVSET} for dev and test"; \
|
|
${GZIP} -cd < $< | cut -f1 | head -${DEVMINSIZE} > ${DEV_SRC}; \
|
|
${GZIP} -cd < $< | cut -f2 | head -${DEVMINSIZE} > ${DEV_TRG}; \
|
|
mkdir -p ${dir ${TEST_SRC}}; \
|
|
${GZIP} -cd < $< | cut -f1 | tail -n +$$((${DEVMINSIZE} + 1)) > ${TEST_SRC}; \
|
|
${GZIP} -cd < $< | cut -f2 | tail -n +$$((${DEVMINSIZE} + 1)) > ${TEST_TRG}; \
|
|
else \
|
|
echo "extract ${DEVSMALLSIZE} examples from ${DEVSET} for dev and test"; \
|
|
${GZIP} -cd < $< | cut -f1 | head -${DEVSMALLSIZE} > ${DEV_SRC}; \
|
|
${GZIP} -cd < $< | cut -f2 | head -${DEVSMALLSIZE} > ${DEV_TRG}; \
|
|
mkdir -p ${dir ${TEST_SRC}}; \
|
|
${GZIP} -cd < $< | cut -f1 | tail -n +$$((${DEVSMALLSIZE} + 1)) > ${TEST_SRC}; \
|
|
${GZIP} -cd < $< | cut -f2 | tail -n +$$((${DEVSMALLSIZE} + 1)) > ${TEST_TRG}; \
|
|
fi; \
|
|
else \
|
|
echo "extract ${DEVSIZE} examples from ${DEVSET} for dev"; \
|
|
echo "extract ${TESTSIZE} examples from ${DEVSET} for test"; \
|
|
${GZIP} -cd < $< | cut -f1 | head -${DEVSIZE} > ${DEV_SRC}; \
|
|
${GZIP} -cd < $< | cut -f2 | head -${DEVSIZE} > ${DEV_TRG}; \
|
|
mkdir -p ${dir ${TEST_SRC}}; \
|
|
${GZIP} -cd < $< | cut -f1 | head -$$((${DEVSIZE} + ${TESTSIZE})) | tail -${TESTSIZE} > ${TEST_SRC}; \
|
|
${GZIP} -cd < $< | cut -f2 | head -$$((${DEVSIZE} + ${TESTSIZE})) | tail -${TESTSIZE} > ${TEST_TRG}; \
|
|
${GZIP} -cd < $< | cut -f1 | tail -n +$$((${DEVSIZE} + ${TESTSIZE} + 1)) | ${GZIP} -c > ${DEV_SRC}.notused.gz; \
|
|
${GZIP} -cd < $< | cut -f2 | tail -n +$$((${DEVSIZE} + ${TESTSIZE} + 1)) | ${GZIP} -c > ${DEV_TRG}.notused.gz; \
|
|
fi
|
|
else
|
|
@echo "extract ${DEVSIZE} examples from ${DEVSET} for dev"
|
|
@${GZIP} -cd < $< | cut -f1 | head -${DEVSIZE} > ${DEV_SRC}
|
|
@${GZIP} -cd < $< | cut -f2 | head -${DEVSIZE} > ${DEV_TRG}
|
|
@${GZIP} -cd < $< | cut -f1 | tail -n +$$((${DEVSIZE} + 1)) | ${GZIP} -c > ${DEV_SRC}.notused.gz
|
|
@${GZIP} -cd < $< | cut -f2 | tail -n +$$((${DEVSIZE} + 1)) | ${GZIP} -c > ${DEV_TRG}.notused.gz
|
|
endif
|
|
@echo "" >> ${dir ${DEV_SRC}}/README.md
|
|
@echo -n "* devset-selected: top " >> ${dir ${DEV_SRC}}/README.md
|
|
@wc -l < ${DEV_SRC} | tr "\n" ' ' >> ${dir ${DEV_SRC}}/README.md
|
|
@echo " lines of ${notdir $@}.shuffled" >> ${dir ${DEV_SRC}}/README.md
|
|
ifeq (${DEVSET},${TESTSET})
|
|
@echo -n "* testset-selected: next " >> ${dir ${DEV_SRC}}/README.md
|
|
@wc -l < ${TEST_SRC} | tr "\n" ' ' >> ${dir ${DEV_SRC}}/README.md
|
|
@echo " lines of ${notdir $@}.shuffled " >> ${dir ${DEV_SRC}}/README.md
|
|
@echo "* devset-unused: added to traindata" >> ${dir ${DEV_SRC}}/README.md
|
|
@echo "# Test data" > ${dir ${TEST_SRC}}/README.md
|
|
@echo "" >> ${dir ${TEST_SRC}}/README.md
|
|
@echo -n "testset-selected: next " >> ${dir ${TEST_SRC}}/README.md
|
|
@wc -l < ${TEST_SRC} | tr "\n" ' ' >> ${dir ${TEST_SRC}}/README.md
|
|
@echo " lines of ../val/${notdir $@}.shuffled" >> ${dir ${TEST_SRC}}/README.md
|
|
endif
|
|
|
|
|
|
${DEV_TRG}: ${DEV_SRC}
|
|
@echo "done!"
|
|
|
|
.PHONY: add-to-dev-data
|
|
add-to-dev-data: ${CLEAN_DEV_SRC} ${CLEAN_DEV_TRG}
|
|
@echo "add to devset: ${CLEAN_DEV_SRC}"
|
|
@mkdir -p ${dir ${DEV_SRC}}
|
|
@echo -n "* ${LANGPAIR}: ${DEVSET}, " >> ${dir ${DEV_SRC}}README.md
|
|
@${GZCAT} ${CLEAN_DEV_SRC} 2>/dev/null | wc -l >> ${dir ${DEV_SRC}}README.md
|
|
#-----------------------------------------------------------------
|
|
# sample devdata to balance size between different language pairs
|
|
# (only if FIT_DEVDATA_SIZE is set)
|
|
#-----------------------------------------------------------------
|
|
ifdef FIT_DEVDATA_SIZE
|
|
@echo "sample dev data to fit size = ${FIT_DEVDATA_SIZE}"
|
|
@${REPOHOME}scripts/fit-data-size.pl -m ${MAX_OVER_SAMPLING} ${FIT_DEVDATA_SIZE} \
|
|
${CLEAN_DEV_SRC} 2>/dev/null ${LABEL_SOURCE_DATA} >> ${DEV_SRC}
|
|
@${REPOHOME}scripts/fit-data-size.pl -m ${MAX_OVER_SAMPLING} ${FIT_DEVDATA_SIZE} \
|
|
${CLEAN_DEV_TRG} 2>/dev/null >> ${DEV_TRG}
|
|
else
|
|
@${GZCAT} ${CLEAN_DEV_SRC} 2>/dev/null ${LABEL_SOURCE_DATA} >> ${DEV_SRC}
|
|
@${GZCAT} ${CLEAN_DEV_TRG} 2>/dev/null >> ${DEV_TRG}
|
|
endif
|
|
|
|
|
|
####################
|
|
# test data
|
|
####################
|
|
##
|
|
## if devset and testset are from the same source:
|
|
## --> use part of the shuffled devset
|
|
## otherwise: create the testset
|
|
## exception: TESTSET exists in TESTSET_DIR
|
|
## --> just use that one
|
|
|
|
${TEST_SRC}: ${DEV_SRC}
|
|
ifneq (${TESTSET},${DEVSET})
|
|
mkdir -p ${dir $@}
|
|
rm -f ${TEST_SRC} ${TEST_TRG}
|
|
echo "# Test data" > ${dir ${TEST_SRC}}/README.md
|
|
echo "" >> ${dir ${TEST_SRC}}/README.md
|
|
if [ -e ${TESTSET_DIR}/${TESTSET}.${SRCEXT}.${PRE}.gz ]; then \
|
|
${MAKE} CLEAN_TEST_SRC=${TESTSET_DIR}/${TESTSET}.${SRCEXT}.${PRE}.gz \
|
|
CLEAN_TEST_TRG=${TESTSET_DIR}/${TESTSET}.${TRGEXT}.${PRE}.gz \
|
|
add-to-test-data; \
|
|
elif [ ! -e $@ ]; then \
|
|
for s in ${SRCLANGS}; do \
|
|
for t in ${TRGLANGS}; do \
|
|
if [ ! `echo "$$s-$$t $$t-$$s" | egrep '${SKIP_LANGPAIRS}' | wc -l` -gt 0 ]; then \
|
|
if [ "${SKIP_SAME_LANG}" == "1" ] && [ "$$s" == "$$t" ]; then \
|
|
echo "!!!!!!!!!!! skip language pair $$s-$$t !!!!!!!!!!!!!!!!"; \
|
|
else \
|
|
${MAKE} SRC=$$s TRG=$$t add-to-test-data; \
|
|
fi \
|
|
else \
|
|
echo "!!!!!!!!!!! skip language pair $$s-$$t !!!!!!!!!!!!!!!!"; \
|
|
fi \
|
|
done \
|
|
done; \
|
|
if [ ${TESTSIZE} -lt `cat $@ | wc -l` ]; then \
|
|
paste ${TEST_SRC} ${TEST_TRG} | ${SHUFFLE} | ${GZIP} -c > $@.shuffled.gz; \
|
|
${GZIP} -cd < $@.shuffled.gz | cut -f1 | tail -${TESTSIZE} > ${TEST_SRC}; \
|
|
${GZIP} -cd < $@.shuffled.gz | cut -f2 | tail -${TESTSIZE} > ${TEST_TRG}; \
|
|
echo "" >> ${dir $@}/README.md; \
|
|
echo "testset-selected: top ${TESTSIZE} lines of $@.shuffled!" >> ${dir $@}/README.md; \
|
|
fi \
|
|
else \
|
|
echo "test set $@ exists already! Don't overwrite!"; \
|
|
echo "TODO: should we touch it?"; \
|
|
fi
|
|
else
|
|
mkdir -p ${dir $@}
|
|
if [ -e ${TESTSET_DIR}/${TESTSET}.${SRCEXT}.${PRE}.gz ]; then \
|
|
${MAKE} CLEAN_TEST_SRC=${TESTSET_DIR}/${TESTSET}.${SRCEXT}.${PRE}.gz \
|
|
CLEAN_TEST_TRG=${TESTSET_DIR}/${TESTSET}.${TRGEXT}.${PRE}.gz \
|
|
add-to-test-data; \
|
|
elif (( `${GZIP} -cd < $<.shuffled.gz | wc -l` < $$((${DEVSIZE} + ${TESTSIZE})) )); then \
|
|
${GZIP} -cd < $<.shuffled.gz | cut -f1 | tail -n +$$((${DEVMINSIZE} + 1)) > ${TEST_SRC}; \
|
|
${GZIP} -cd < $<.shuffled.gz | cut -f2 | tail -n +$$((${DEVMINSIZE} + 1)) > ${TEST_TRG}; \
|
|
else \
|
|
${GZIP} -cd < $<.shuffled.gz | cut -f1 | tail -${TESTSIZE} > ${TEST_SRC}; \
|
|
${GZIP} -cd < $<.shuffled.gz | cut -f2 | tail -${TESTSIZE} > ${TEST_TRG}; \
|
|
fi
|
|
endif
|
|
|
|
${TEST_TRG}: ${TEST_SRC}
|
|
@echo "done!"
|
|
|
|
.PHONY: add-to-test-data
|
|
add-to-test-data: ${CLEAN_TEST_SRC}
|
|
@echo "add to testset: ${CLEAN_TEST_SRC}"
|
|
@echo "* ${LANGPAIR}: ${TESTSET}" >> ${dir ${TEST_SRC}}README.md
|
|
@${GZCAT} ${CLEAN_TEST_SRC} 2>/dev/null ${LABEL_SOURCE_DATA} >> ${TEST_SRC}
|
|
@${GZCAT} ${CLEAN_TEST_TRG} 2>/dev/null >> ${TEST_TRG}
|
|
|
|
|
|
|
|
## reduce training data size if necessary
|
|
ifdef TRAINSIZE
|
|
${TRAIN_SRC}.clean.${PRE_SRC}${TRAINSIZE}.gz: ${TRAIN_SRC}.clean.${PRE_SRC}.gz
|
|
${GZIP} -cd < $< | head -${TRAINSIZE} | ${GZIP} -c > $@
|
|
|
|
${TRAIN_TRG}.clean.${PRE_TRG}${TRAINSIZE}.gz: ${TRAIN_TRG}.clean.${PRE_TRG}.gz
|
|
${GZIP} -cd < $< | head -${TRAINSIZE} | ${GZIP} -c > $@
|
|
endif
|
|
|
|
|
|
|
|
## monolingual data: for language-specific sentence piece models
|
|
## that are independent of bitexts
|
|
## TODO: do we use this?
|
|
|
|
${LOCAL_MONO_DATA}.raw:
|
|
mkdir -p ${dir $@}
|
|
rm -f $@
|
|
-for l in ${LANGS}; do \
|
|
${MAKE} DATASET=${DATASET} LANGID:=$$l \
|
|
add-to-local-mono-data; \
|
|
done
|
|
|
|
## TODO: if it does not exist in local file system then use opus-tools to fetch!
|
|
.PHONY: add-to-local-mono-data
|
|
add-to-local-mono-data:
|
|
for c in ${MONOSET}; do \
|
|
if [ -e ${OPUSHOME}/$$c/latest/mono/${LANGID}.txt.gz ]; then \
|
|
${GZIP} -cd < ${OPUSHOME}/$$c/latest/mono/${LANGID}.txt.gz |\
|
|
${REPOHOME}scripts/filter/mono-match-lang.py -l ${LANGID} >> ${LOCAL_MONO_DATA}.raw; \
|
|
fi \
|
|
done
|
|
|
|
|
|
|
|
##----------------------------------------------
|
|
## get data from local space and compress ...
|
|
##----------------------------------------------
|
|
|
|
${WORKDIR}/%.${PRE_SRC}.gz: ${TMPWORKDIR}/${LANGPAIRSTR}/%.${PRE_SRC}
|
|
mkdir -p ${dir $@}
|
|
${GZIP} -c < $< > $@
|
|
-cat ${dir $<}README.md >> ${dir $@}README.md
|
|
|
|
ifneq (${PRE_SRC},${PRE_TRG})
|
|
${WORKDIR}/%.${PRE_TRG}.gz: ${TMPWORKDIR}/${LANGPAIRSTR}/%.${PRE_TRG}
|
|
mkdir -p ${dir $@}
|
|
${GZIP} -c < $< > $@
|
|
endif
|
|
|
|
|
|
|
|
|
|
|
|
|
|
include ${REPOHOME}lib/preprocess.mk
|
|
include ${REPOHOME}lib/bpe.mk
|
|
include ${REPOHOME}lib/sentencepiece.mk
|
|
|
|
|