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translate.py
# Options: translate.py:
translate.py

### **Model**:
* **-model []** 
Path to model .pt file

### **Data**:
* **-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**:
* **-beam_size [5]** 
Beam size

* **-alpha []** 
Google NMT length penalty parameter (higher = longer generation)

* **-beta []** 
Coverage penalty parameter

* **-max_sent_length [100]** 
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

### **Logging**:
* **-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 [1]** 
If verbose is set, will output the n_best decoded sentences

### **Efficiency**:
* **-batch_size [30]** 
Batch size

* **-gpu [-1]** 
Device to run on

### **Speech**:
* **-sample_rate [16000]** 
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

### **Score**:
* **-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.