Translate¶
translate.py
usage: translate.py [-h] [-config CONFIG] [-save_config SAVE_CONFIG] --model
MODEL [MODEL ...] [--precision {,fp32,fp16,int8}] [--fp32]
[--int8] [--avg_raw_probs] [--data_type DATA_TYPE] --src
SRC [--tgt TGT] [--tgt_file_prefix] [--output OUTPUT]
[--report_align] [--gold_align] [--report_time]
[--profile] [-n_src_feats N_SRC_FEATS]
[-src_feats_defaults SRC_FEATS_DEFAULTS]
[--beam_size BEAM_SIZE] [--ratio RATIO]
[--random_sampling_topk RANDOM_SAMPLING_TOPK]
[--random_sampling_topp RANDOM_SAMPLING_TOPP]
[--random_sampling_temp RANDOM_SAMPLING_TEMP]
[--seed SEED] [--length_penalty {none,wu,avg}]
[--alpha ALPHA] [--coverage_penalty {none,wu,summary}]
[--beta BETA] [--stepwise_penalty]
[--min_length MIN_LENGTH] [--max_length MAX_LENGTH]
[--block_ngram_repeat BLOCK_NGRAM_REPEAT]
[--ignore_when_blocking IGNORE_WHEN_BLOCKING [IGNORE_WHEN_BLOCKING ...]]
[--replace_unk] [--ban_unk_token]
[--phrase_table PHRASE_TABLE] [--log_file LOG_FILE]
[--log_file_level {CRITICAL,ERROR,WARNING,INFO,DEBUG,NOTSET,50,40,30,20,10,0}]
[--verbose] [--attn_debug] [--align_debug]
[--dump_beam DUMP_BEAM] [--n_best N_BEST] [--with_score]
[--gpu_ranks [GPU_RANKS [GPU_RANKS ...]]]
[--world_size WORLD_SIZE]
[--parallel_mode {tensor_parallel,data_parallel}]
[--gpu_backend GPU_BACKEND]
[--gpu_verbose_level GPU_VERBOSE_LEVEL]
[--master_ip MASTER_IP] [--master_port MASTER_PORT]
[--batch_size BATCH_SIZE] [--batch_type {sents,tokens}]
[--gpu GPU]
[-transforms {bart,terminology,fuzzymatch,filtertoolong,prefix,suffix,insert_mask_before_placeholder,clean,uppercase,switchout,tokendrop,tokenmask,docify,inferfeats,sentencepiece,bpe,onmt_tokenize,inlinetags,normalize} [{bart,terminology,fuzzymatch,filtertoolong,prefix,suffix,insert_mask_before_placeholder,clean,uppercase,switchout,tokendrop,tokenmask,docify,inferfeats,sentencepiece,bpe,onmt_tokenize,inlinetags,normalize} ...]]
[--permute_sent_ratio PERMUTE_SENT_RATIO]
[--rotate_ratio ROTATE_RATIO]
[--insert_ratio INSERT_RATIO]
[--random_ratio RANDOM_RATIO] [--mask_ratio MASK_RATIO]
[--mask_length {subword,word,span-poisson}]
[--poisson_lambda POISSON_LAMBDA]
[--replace_length {-1,0,1}]
[--termbase_path TERMBASE_PATH]
[--src_spacy_language_model SRC_SPACY_LANGUAGE_MODEL]
[--tgt_spacy_language_model TGT_SPACY_LANGUAGE_MODEL]
[--term_corpus_ratio TERM_CORPUS_RATIO]
[--term_example_ratio TERM_EXAMPLE_RATIO]
[--src_term_stoken SRC_TERM_STOKEN]
[--tgt_term_stoken TGT_TERM_STOKEN]
[--tgt_term_etoken TGT_TERM_ETOKEN]
[--term_source_delimiter TERM_SOURCE_DELIMITER]
[--tm_path TM_PATH]
[--fuzzy_corpus_ratio FUZZY_CORPUS_RATIO]
[--fuzzy_threshold FUZZY_THRESHOLD]
[--tm_delimiter TM_DELIMITER] [--fuzzy_token FUZZY_TOKEN]
[--fuzzymatch_min_length FUZZYMATCH_MIN_LENGTH]
[--fuzzymatch_max_length FUZZYMATCH_MAX_LENGTH]
[--src_seq_length SRC_SEQ_LENGTH]
[--tgt_seq_length TGT_SEQ_LENGTH]
[--src_prefix SRC_PREFIX] [--tgt_prefix TGT_PREFIX]
[--src_suffix SRC_SUFFIX] [--tgt_suffix TGT_SUFFIX]
[--response_pattern RESPONSE_PATTERN] [--src_eq_tgt]
[--same_char] [--same_word]
[--scripts_ok [SCRIPTS_OK [SCRIPTS_OK ...]]]
[--scripts_nok [SCRIPTS_NOK [SCRIPTS_NOK ...]]]
[--src_tgt_ratio SRC_TGT_RATIO]
[--avg_tok_min AVG_TOK_MIN] [--avg_tok_max AVG_TOK_MAX]
[--langid [LANGID [LANGID ...]]]
[--upper_corpus_ratio UPPER_CORPUS_RATIO]
[-switchout_temperature SWITCHOUT_TEMPERATURE]
[-tokendrop_temperature TOKENDROP_TEMPERATURE]
[-tokenmask_temperature TOKENMASK_TEMPERATURE]
[--doc_length DOC_LENGTH] [--max_context MAX_CONTEXT]
[--reversible_tokenization {joiner,spacer}]
[-src_subword_model SRC_SUBWORD_MODEL]
[-tgt_subword_model TGT_SUBWORD_MODEL]
[-src_subword_nbest SRC_SUBWORD_NBEST]
[-tgt_subword_nbest TGT_SUBWORD_NBEST]
[-src_subword_alpha SRC_SUBWORD_ALPHA]
[-tgt_subword_alpha TGT_SUBWORD_ALPHA]
[-src_subword_vocab SRC_SUBWORD_VOCAB]
[-tgt_subword_vocab TGT_SUBWORD_VOCAB]
[-src_vocab_threshold SRC_VOCAB_THRESHOLD]
[-tgt_vocab_threshold TGT_VOCAB_THRESHOLD]
[-src_subword_type {none,sentencepiece,bpe}]
[-tgt_subword_type {none,sentencepiece,bpe}]
[-src_onmttok_kwargs SRC_ONMTTOK_KWARGS]
[-tgt_onmttok_kwargs TGT_ONMTTOK_KWARGS] [--gpt2_pretok]
[--tags_dictionary_path TAGS_DICTIONARY_PATH]
[--tags_corpus_ratio TAGS_CORPUS_RATIO]
[--max_tags MAX_TAGS] [--paired_stag PAIRED_STAG]
[--paired_etag PAIRED_ETAG] [--isolated_tag ISOLATED_TAG]
[--src_delimiter SRC_DELIMITER] [--src_lang SRC_LANG]
[--tgt_lang TGT_LANG] [--penn PENN]
[--norm_quote_commas NORM_QUOTE_COMMAS]
[--norm_numbers NORM_NUMBERS]
[--pre_replace_unicode_punct PRE_REPLACE_UNICODE_PUNCT]
[--post_remove_control_chars POST_REMOVE_CONTROL_CHARS]
[--quant_layers QUANT_LAYERS [QUANT_LAYERS ...]]
[--quant_type {bnb_8bit,bnb_FP4,bnb_NF4}]
Configuration¶
- -config, --config
Path of the main YAML config file.
- -save_config, --save_config
Path where to save the config.
Model¶
- --model, -model
Path to model .pt file(s). Multiple models can be specified, for ensemble decoding.
Default: []
- --precision, -precision
Possible choices: , fp32, fp16, int8
Precision to run inference.default is model.dtypefp32 to force slow FP16 model on GTX1080int8 enables pytorch native 8-bit quantization(cpu only)
Default: “”
- --fp32, -fp32
Deprecated use ‘precision’ instead
- --int8, -int8
Deprecated use ‘precision’ instead
- --avg_raw_probs, -avg_raw_probs
If this is set, during ensembling scores from different models will be combined by averaging their raw probabilities and then taking the log. Otherwise, the log probabilities will be averaged directly. Necessary for models whose output layers can assign zero probability.
Default: False
Data¶
- --data_type, -data_type
Type of the source input. Options: [text].
Default: “text”
- --src, -src
Source sequence to decode (one line per sequence)
- --tgt, -tgt
True target sequence (optional)
- --tgt_file_prefix, -tgt_file_prefix
Generate predictions using provided -tgt as prefix.
Default: False
- --output, -output
Path to output the predictions (each line will be the decoded sequence
Default: “pred.txt”
- --report_align, -report_align
Report alignment for each translation.
Default: False
- --gold_align, -gold_align
Report alignment between source and gold target.Useful to test the performance of learnt alignments.
Default: False
- --report_time, -report_time
Report some translation time metrics
Default: False
- --profile, -profile
Report pytorch profiling stats
Default: False
Features¶
- -n_src_feats, --n_src_feats
Number of source feats.
Default: 0
- -src_feats_defaults, --src_feats_defaults
Default features to apply in source in case there are not annotated
Beam Search¶
- --beam_size, -beam_size
Beam size
Default: 5
- --ratio, -ratio
Ratio based beam stop condition
Default: -0.0
Random Sampling¶
- --random_sampling_topk, -random_sampling_topk
Set this to -1 to do random sampling from full distribution. Set this to value k>1 to do random sampling restricted to the k most likely next tokens. Set this to 1 to use argmax.
Default: 0
- --random_sampling_topp, -random_sampling_topp
Probability for top-p/nucleus sampling. Restrict tokens to the most likely until the cumulated probability is over p. In range [0, 1]. https://arxiv.org/abs/1904.09751
Default: 0.0
- --random_sampling_temp, -random_sampling_temp
If doing random sampling, divide the logits by this before computing softmax during decoding.
Default: 1.0
- --beam_size, -beam_size
Beam size
Default: 5
Reproducibility¶
- --seed, -seed
Set random seed used for better reproducibility between experiments.
Default: -1
Penalties¶
Note
Coverage Penalty is not available in sampling.
- --length_penalty, -length_penalty
Possible choices: none, wu, avg
Length Penalty to use.
Default: “avg”
- --alpha, -alpha
Length penalty parameter(higher = longer generation)
Default: 1.0
- --coverage_penalty, -coverage_penalty
Possible choices: none, wu, summary
Coverage Penalty to use. Only available in beam search.
Default: “none”
- --beta, -beta
Coverage penalty parameter
Default: -0.0
- --stepwise_penalty, -stepwise_penalty
Apply coverage penalty at every decoding step. Helpful for summary penalty.
Default: False
Decoding tricks¶
Tip
Following options can be used to limit the decoding length or content.
- --min_length, -min_length
Minimum prediction length
Default: 0
- --max_length, -max_length
Maximum prediction length.
Default: 250
- --block_ngram_repeat, -block_ngram_repeat
Block repetition of ngrams during decoding.
Default: 0
- --ignore_when_blocking, -ignore_when_blocking
Ignore these strings when blocking repeats. You want to block sentence delimiters.
Default: []
- --replace_unk, -replace_unk
Replace the generated UNK tokens with the source token that had highest attention weight. If phrase_table is provided, it will look up the identified source token and give the corresponding target token. If it is not provided (or the identified source token does not exist in the table), then it will copy the source token.
Default: False
- --ban_unk_token, -ban_unk_token
Prevent unk token generation by setting unk proba to 0
Default: False
- --phrase_table, -phrase_table
If phrase_table is provided (with replace_unk), it will look up the identified source token and give the corresponding target token. If it is not provided (or the identified source token does not exist in the table), then it will copy the source token.
Default: “”
Logging¶
- --log_file, -log_file
Output logs to a file under this path.
Default: “”
- --log_file_level, -log_file_level
Possible choices: CRITICAL, ERROR, WARNING, INFO, DEBUG, NOTSET, 50, 40, 30, 20, 10, 0
Default: “0”
- --verbose, -verbose
Print scores and predictions for each sentence
Default: False
- --attn_debug, -attn_debug
Print best attn for each word
Default: False
- --align_debug, -align_debug
Print best align for each word
Default: False
- --dump_beam, -dump_beam
File to dump beam information to.
Default: “”
- --n_best, -n_best
If verbose is set, will output the n_best decoded sentences
Default: 1
- --with_score, -with_score
add a tab separated score to the translation
Default: False
Distributed¶
- --gpu_ranks, -gpu_ranks
list of ranks of each process.
Default: []
- --world_size, -world_size
total number of distributed processes.
Default: 1
- --parallel_mode, -parallel_mode
Possible choices: tensor_parallel, data_parallel
Distributed mode.
Default: “data_parallel”
- --gpu_backend, -gpu_backend
Type of torch distributed backend
Default: “nccl”
- --gpu_verbose_level, -gpu_verbose_level
Gives more info on each process per GPU.
Default: 0
- --master_ip, -master_ip
IP of master for torch.distributed training.
Default: “localhost”
- --master_port, -master_port
Port of master for torch.distributed training.
Default: 10000
Efficiency¶
- --batch_size, -batch_size
Batch size
Default: 30
- --batch_type, -batch_type
Possible choices: sents, tokens
Batch grouping for batch_size. Standard is sents. Tokens will do dynamic batching
Default: “sents”
- --gpu, -gpu
Device to run on
Default: -1
- -transforms, --transforms
Possible choices: bart, terminology, fuzzymatch, filtertoolong, prefix, suffix, insert_mask_before_placeholder, clean, uppercase, switchout, tokendrop, tokenmask, docify, inferfeats, sentencepiece, bpe, onmt_tokenize, inlinetags, normalize
Default transform pipeline to apply to data.
Default: []
Transform/BART¶
- --permute_sent_ratio, -permute_sent_ratio
Permute this proportion of sentences (boundaries defined by [‘.’, ‘?’, ‘!’]) in all inputs.
Default: 0.0
- --rotate_ratio, -rotate_ratio
Rotate this proportion of inputs.
Default: 0.0
- --insert_ratio, -insert_ratio
Insert this percentage of additional random tokens.
Default: 0.0
- --random_ratio, -random_ratio
Instead of using <mask>, use random token this often.
Default: 0.0
- --mask_ratio, -mask_ratio
Fraction of words/subwords that will be masked.
Default: 0.0
- --mask_length, -mask_length
Possible choices: subword, word, span-poisson
Length of masking window to apply.
Default: “subword”
- --poisson_lambda, -poisson_lambda
Lambda for Poisson distribution to sample span length if -mask_length set to span-poisson.
Default: 3.0
- --replace_length, -replace_length
Possible choices: -1, 0, 1
When masking N tokens, replace with 0, 1, or N tokens. (use -1 for N)
Default: -1
Transform/Terminology¶
- --termbase_path, -termbase_path
Path to a dictionary file with terms.
- --src_spacy_language_model, -src_spacy_language_model
Name of the spacy language model for the source corpus.
- --tgt_spacy_language_model, -tgt_spacy_language_model
Name of the spacy language model for the target corpus.
- --term_corpus_ratio, -term_corpus_ratio
Ratio of corpus to augment with terms.
Default: 0.3
- --term_example_ratio, -term_example_ratio
Max terms allowed in an example.
Default: 0.2
- --src_term_stoken, -src_term_stoken
The source term start token.
Default: “｟src_term_start｠”
- --tgt_term_stoken, -tgt_term_stoken
The target term start token.
Default: “｟tgt_term_start｠”
- --tgt_term_etoken, -tgt_term_etoken
The target term end token.
Default: “｟tgt_term_end｠”
- --term_source_delimiter, -term_source_delimiter
Any special token used for augmented source sentences. The default is the fuzzy token used in the FuzzyMatch transform.
Default: “｟fuzzy｠”
Transform/FuzzyMatching¶
- --tm_path, -tm_path
Path to a flat text TM.
- --fuzzy_corpus_ratio, -fuzzy_corpus_ratio
Ratio of corpus to augment with fuzzy matches.
Default: 0.1
- --fuzzy_threshold, -fuzzy_threshold
The fuzzy matching threshold.
Default: 70
- --tm_delimiter, -tm_delimiter
The delimiter used in the flat text TM.
Default: “ “
- --fuzzy_token, -fuzzy_token
The fuzzy token to be added with the matches.
Default: “｟fuzzy｠”
- --fuzzymatch_min_length, -fuzzymatch_min_length
Min length for TM entries and examples to match.
Default: 4
- --fuzzymatch_max_length, -fuzzymatch_max_length
Max length for TM entries and examples to match.
Default: 70
Transform/Filter¶
- --src_seq_length, -src_seq_length
Maximum source sequence length.
Default: 192
- --tgt_seq_length, -tgt_seq_length
Maximum target sequence length.
Default: 192
Transform/Prefix¶
- --src_prefix, -src_prefix
String to prepend to all source example.
Default: “”
- --tgt_prefix, -tgt_prefix
String to prepend to all target example.
Default: “”
Transform/Suffix¶
- --src_suffix, -src_suffix
String to append to all source example.
Default: “”
- --tgt_suffix, -tgt_suffix
String to append to all target example.
Default: “”
Transform/InsertMaskBeforePlaceholdersTransform¶
- --response_pattern, -response_pattern
Response patten to locate the end of the prompt
Default: “Response : ｟newline｠”
Transform/Clean¶
- --src_eq_tgt, -src_eq_tgt
Remove ex src==tgt
Default: False
- --same_char, -same_char
Remove ex with same char more than 4 times
Default: False
- --same_word, -same_word
Remove ex with same word more than 3 times
Default: False
- --scripts_ok, -scripts_ok
list of unicodata scripts accepted
Default: [‘Latin’, ‘Common’]
- --scripts_nok, -scripts_nok
list of unicodata scripts not accepted
Default: []
- --src_tgt_ratio, -src_tgt_ratio
ratio between src and tgt
Default: 2
- --avg_tok_min, -avg_tok_min
average length of tokens min
Default: 3
- --avg_tok_max, -avg_tok_max
average length of tokens max
Default: 20
- --langid, -langid
list of languages accepted
Default: []
Transform/Uppercase¶
- --upper_corpus_ratio, -upper_corpus_ratio
Corpus ratio to apply uppercasing.
Default: 0.01
Transform/SwitchOut¶
- -switchout_temperature, --switchout_temperature
Sampling temperature for SwitchOut. \(\tau^{-1}\) in [WPDN18]. Smaller value makes data more diverse.
Default: 1.0
Transform/Token_Drop¶
- -tokendrop_temperature, --tokendrop_temperature
Sampling temperature for token deletion.
Default: 1.0
Transform/Token_Mask¶
- -tokenmask_temperature, --tokenmask_temperature
Sampling temperature for token masking.
Default: 1.0
Transform/Docify¶
- --doc_length, -doc_length
Number of tokens per doc.
Default: 200
- --max_context, -max_context
Max context segments.
Default: 1
Transform/InferFeats¶
- --reversible_tokenization, -reversible_tokenization
Possible choices: joiner, spacer
Type of reversible tokenization applied on the tokenizer.
Default: “joiner”
Transform/Subword/Common¶
Attention
Common options shared by all subword transforms. Including options for indicate subword model path, Subword Regularization/BPE-Dropout, and Vocabulary Restriction.
- -src_subword_model, --src_subword_model
Path of subword model for src (or shared).
- -tgt_subword_model, --tgt_subword_model
Path of subword model for tgt.
- -src_subword_nbest, --src_subword_nbest
Number of candidates in subword regularization. Valid for unigram sampling, invalid for BPE-dropout. (source side)
Default: 1
- -tgt_subword_nbest, --tgt_subword_nbest
Number of candidates in subword regularization. Valid for unigram sampling, invalid for BPE-dropout. (target side)
Default: 1
- -src_subword_alpha, --src_subword_alpha
Smoothing parameter for sentencepiece unigram sampling, and dropout probability for BPE-dropout. (source side)
Default: 0
- -tgt_subword_alpha, --tgt_subword_alpha
Smoothing parameter for sentencepiece unigram sampling, and dropout probability for BPE-dropout. (target side)
Default: 0
- -src_subword_vocab, --src_subword_vocab
Path to the vocabulary file for src subword. Format: <word> <count> per line.
Default: “”
- -tgt_subword_vocab, --tgt_subword_vocab
Path to the vocabulary file for tgt subword. Format: <word> <count> per line.
Default: “”
- -src_vocab_threshold, --src_vocab_threshold
Only produce src subword in src_subword_vocab with frequency >= src_vocab_threshold.
Default: 0
- -tgt_vocab_threshold, --tgt_vocab_threshold
Only produce tgt subword in tgt_subword_vocab with frequency >= tgt_vocab_threshold.
Default: 0
Transform/Subword/ONMTTOK¶
- -src_subword_type, --src_subword_type
Possible choices: none, sentencepiece, bpe
Type of subword model for src (or shared) in pyonmttok.
Default: “none”
- -tgt_subword_type, --tgt_subword_type
Possible choices: none, sentencepiece, bpe
Type of subword model for tgt in pyonmttok.
Default: “none”
- -src_onmttok_kwargs, --src_onmttok_kwargs
Other pyonmttok options for src in dict string, except subword related options listed earlier.
Default: “{‘mode’: ‘none’}”
- -tgt_onmttok_kwargs, --tgt_onmttok_kwargs
Other pyonmttok options for tgt in dict string, except subword related options listed earlier.
Default: “{‘mode’: ‘none’}”
- --gpt2_pretok, -gpt2_pretok
Preprocess sentence with byte-level mapping
Default: False
Transform/InlineTags¶
- --tags_dictionary_path, -tags_dictionary_path
Path to a flat term dictionary.
- --tags_corpus_ratio, -tags_corpus_ratio
Ratio of corpus to augment with tags.
Default: 0.1
- --max_tags, -max_tags
Maximum number of tags that can be added to a single sentence.
Default: 12
- --paired_stag, -paired_stag
The format of an opening paired inline tag. Must include the character #.
Default: “｟ph_#_beg｠”
- --paired_etag, -paired_etag
The format of a closing paired inline tag. Must include the character #.
Default: “｟ph_#_end｠”
- --isolated_tag, -isolated_tag
The format of an isolated inline tag. Must include the character #.
Default: “｟ph_#_std｠”
- --src_delimiter, -src_delimiter
Any special token used for augmented src sentences. The default is the fuzzy token used in the FuzzyMatch transform.
Default: “｟fuzzy｠”
Transform/Normalize¶
- --src_lang, -src_lang
Source language code
Default: “”
- --tgt_lang, -tgt_lang
Target language code
Default: “”
- --penn, -penn
Penn substitution
Default: True
- --norm_quote_commas, -norm_quote_commas
Normalize quotations and commas
Default: True
- --norm_numbers, -norm_numbers
Normalize numbers
Default: True
- --pre_replace_unicode_punct, -pre_replace_unicode_punct
Replace unicode punct
Default: False
- --post_remove_control_chars, -post_remove_control_chars
Remove control chars
Default: False
Quant options¶
- --quant_layers, -quant_layers
list of layers to be compressed in 4/8bit.
Default: []
- --quant_type, -quant_type
Possible choices: bnb_8bit, bnb_FP4, bnb_NF4
Type of compression.
Default: “bnb_8bit”