Translate¶

translate.py

usage: translate.py [-h] [-config CONFIG] [-save_config SAVE_CONFIG] --model
                    MODEL [MODEL ...] [--fp32] [--int8] [--avg_raw_probs]
                    [--data_type DATA_TYPE] --src SRC [-src_feats SRC_FEATS]
                    [--tgt TGT] [--tgt_file_prefix] [--output OUTPUT]
                    [--report_align] [--report_time] [--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]
                    [--batch_size BATCH_SIZE] [--batch_type {sents,tokens}]
                    [--gpu GPU]
                    [-transforms {sentencepiece,bpe,onmt_tokenize,filtertoolong,prefix,bart,filterfeats,inferfeats,switchout,tokendrop,tokenmask} [{sentencepiece,bpe,onmt_tokenize,filtertoolong,prefix,bart,filterfeats,inferfeats,switchout,tokendrop,tokenmask} ...]]
                    [-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]
                    [--src_seq_length SRC_SEQ_LENGTH]
                    [--tgt_seq_length TGT_SEQ_LENGTH]
                    [--src_prefix SRC_PREFIX] [--tgt_prefix TGT_PREFIX]
                    [--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}]
                    [--reversible_tokenization {joiner,spacer}]
                    [--prior_tokenization]
                    [-switchout_temperature SWITCHOUT_TEMPERATURE]
                    [-tokendrop_temperature TOKENDROP_TEMPERATURE]
                    [-tokenmask_temperature TOKENMASK_TEMPERATURE]

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: []

--fp32, -fp32

Force the model to be in FP32 because FP16 is very slow on GTX1080(ti).

Default: False

--int8, -int8

Enable dynamic 8-bit quantization (CPU only).

Default: False

--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)

-src_feats, --src_feats

Source sequence features (dict format). Ex: {‘feat_0’: ‘../data.txt.feats0’, ‘feat_1’: ‘../data.txt.feats1’}

--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

--report_time, -report_time

Report some translation time metrics

Default: False

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

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: sentencepiece, bpe, onmt_tokenize, filtertoolong, prefix, bart, filterfeats, inferfeats, switchout, tokendrop, tokenmask

Default transform pipeline to apply to data.

Default: []

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’}”

Transform/Filter¶

--src_seq_length, -src_seq_length

Maximum source sequence length.

Default: 200

--tgt_seq_length, -tgt_seq_length

Maximum target sequence length.

Default: 200

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/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/InferFeats¶

--reversible_tokenization, -reversible_tokenization

Possible choices: joiner, spacer

Type of reversible tokenization applied on the tokenizer.

Default: “joiner”

--prior_tokenization, -prior_tokenization

Whether the input has already been tokenized.

Default: False

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