- -model  Path to model .pt file
- -data_type [text] Type of the source input. Options: [text|img].
- -src  Source sequence to decode (one line per sequence)
- -src_dir  Source directory for image or audio files
- -tgt  True target sequence (optional)
- -output [pred.txt] Path to output the predictions (each line will be the decoded sequence
- -dynamic_dict  Create dynamic dictionaries
- -share_vocab  Share source and target vocabulary
- -beam_size  Beam size
- -alpha  Google NMT length penalty parameter (higher = longer generation)
- -beta  Coverage penalty parameter
- -max_sent_length  Maximum sentence length.
- -replace_unk  Replace the generated UNK tokens with the source token that had highest attention weight. If phrase_table is provided, it will lookup 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
- -verbose  Print scores and predictions for each sentence
- -attn_debug  Print best attn for each word
- -dump_beam  File to dump beam information to.
- -n_best  If verbose is set, will output the n_best decoded sentences
- -batch_size  Batch size
- -gpu [-1] Device to run on
- -sample_rate  Sample rate.
- -window_size [0.02] Window size for spectrogram in seconds
- -window_stride [0.01] Window stride for spectrogram in seconds
- -window [hamming] Window type for spectrogram generation
- -report_bleu  Report bleu score after translation by calling tools/multi-bleu.perl on command line.
- -report_rouge  Report Report rouge 1/2/3/L/SU4 score after translation by calling tools/multi-bleu.perl on command line. Use pyrouge as backend. Scores may be slightly different with those by calling files2rouge.