Fast Neural Machine Translation in C++
Version: v1.7.0 67124f8 2018-11-28 13:04:30 +0000
Usage: ./marian/build/marian-decoder [OPTIONS]
-h,--help Print this help message and exit
--version Print the version number and exit
-c,--config VECTOR ... Configuration file(s). If multiple, later overrides earlier
-w,--workspace UINT=512 Preallocate arg MB of work space
--log TEXT Log training process information to file given by arg
--log-level TEXT=info Set verbosity level of logging: trace, debug, info, warn,
err(or), critical, off
--log-time-zone TEXT Set time zone for the date shown on logging
--quiet Suppress all logging to stderr. Logging to files still works
--quiet-translation Suppress logging for translation
--seed UINT Seed for all random number generators. 0 means initialize
randomly
--clip-gemm FLOAT If not 0 clip GEMM input values to +/- arg
--interpolate-env-vars allow the use of environment variables in paths, of the form
${VAR_NAME}
--relative-paths All paths are relative to the config file location
--dump-config TEXT Dump current (modified) configuration to stdout and exit.
Possible values: full, minimal
-i,--input VECTOR=stdin ... Paths to input file(s), stdin by default
-o,--output TEXT=stdout Paths to output file(s), stdout by default
-v,--vocabs VECTOR ... Paths to vocabulary files have to correspond to --input
-b,--beam-size UINT=12 Beam size used during search with validating translator
-n,--normalize FLOAT=0 Divide translation score by pow(translation length, arg)
--max-length-factor FLOAT=3 Maximum target length as source length times factor
--word-penalty FLOAT Subtract (arg * translation length) from translation score
--allow-unk Allow unknown words to appear in output
--n-best Generate n-best list
--alignment TEXT Return word alignment. Possible values: 0.0-1.0, hard, soft
-d,--devices VECTOR=0 ... Specifies GPU ID(s) to use for training. Defaults to
0..num-devices-1
--num-devices UINT Number of GPUs to use for this process. Defaults to
length(devices) or 1
--cpu-threads UINT=0 Use CPU-based computation with this many independent
threads, 0 means GPU-based computation
--max-length UINT=1000 Maximum length of a sentence in a training sentence pair
--max-length-crop Crop a sentence to max-length instead of ommitting it if
longer than max-length
--mini-batch INT=1 Size of mini-batch used during batched translation
--mini-batch-words INT Set mini-batch size based on words instead of sentences
--maxi-batch INT=1 Number of batches to preload for length-based sorting
--maxi-batch-sort TEXT=none Sorting strategy for maxi-batch: none, src, trg (not
available for decoder)
--shuffle-in-ram Keep shuffled corpus in RAM, do not write to temp file
--optimize Optimize speed aggressively sacrificing memory or precision
--skip-cost Ignore model cost during translation, not recommended for
beam-size > 1
--shortlist VECTOR ... Use softmax shortlist: path first best prune
--weights VECTOR ... Scorer weights
--output-sampling=false Noise output layer with gumbel noise
-p,--port UINT Port number for web socket server
--ulr=false Enable ULR (Universal Language Representation)
--ulr-query-vectors TEXT Path to file with universal sources embeddings from
projection into universal space
--ulr-keys-vectors TEXT Path to file with universal sources embeddings of traget
keys from projection into universal space
--ulr-trainable-transformation=false Make Query Transformation Matrix A trainable
--ulr-dim-emb INT ULR monolingual embeddings dimension
--ulr-dropout FLOAT=0 ULR dropout on embeddings attentions. Default is no dropout
--ulr-softmax-temperature FLOAT=1 ULR softmax temperature to control randomness of
predictions. Deafult is 1.0: no temperature