py3translationServer/py3translationServer.py.sh at main · gdiaz384/py3translationServer · GitHub

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#!/bin/bash
pushd $( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
# '#' means comment

# The NMT engine used to process the model. Can be fairseq or ctranslate2
mode=fairseq
#mode=ctranslate2

# The path to the model. No quotes.
# For fairseq, include the full path and model name.
# For ctranslate2, include only the path to model.bin but not the model name itself.
modelPath=./scratchpad/model/big.pretrain.pt
#modelPath=./scratchpad/ct2_model/

# Use two letter language codes: www.loc.gov/standards/iso639-2/php/code_list.php
sourceLanguage=ja
targetLanguage=en

# The path and file name for the source sentence piece model. No quotes.
sourceSentencePieceModel=./scratchpad/model/spm/spm.$sourceLanguage.nopretok.model

# The path and file name for the target sentence piece model. No quotes.
targetSentencePieceModel=./scratchpad/model/spm/spm.$targetLanguage.nopretok.model

# Valid values are: cpu, gpu, cuda, directml. gpu is aliased to cuda. directml requires fairseq.
device=cpu

# The path and file name for Python.
# To use with a portable version of Python, prepend a custom path to python.exe
pythonExe=python3

# Less common options. Append to core logic as needed.
# Specify the internet protocol address for the server. 0.0.0.0 means bind to all local addresses.
# --address 0.0.0.0
# Specify port to listen on. Associated with --address. Default=14366.
# --port 14366
# Disable performance metrics (time keeping).
# --disablePerfMetrics
# Preload the model for lower latency inferencing.
# --preloadModel
# Print more information.
# --verbose
# Print too much information.
# --debug

# To change internal fairseq or ctranslate2 variables, look at the defaults near the top of the .py file.


# Core logic. Invoke server with the options specified above.
"$pythonExe" py3translationServer.py $mode "$modelPath" -dev $device --sourceLanguage $sourceLanguage --targetLanguage $targetLanguage -sspm "$sourceSentencePieceModel" -tspm "$targetSentencePieceModel"
popd