ensembling_tutorial.md

This document describes the usage of the sample_ensemble script.

If we launch the script with the --help flag, the different options are shown:

 python sample_ensemble.py --help
 usage: Apply several translation models for making predictions
       -ds DATASET  [-h] [--n-best] [-t TEXT] [-d DEST]  [-w [WEIGHTS [WEIGHTS ...]]] 
       [-v] [-c CONFIG] --models MODELS [MODELS ...]

  optional arguments:
    -h, --help            show this help message and exit
    -ds DATASET, --dataset DATASET
                          Dataset instance with data
    -t TEXT, --text TEXT  Text file with source sentences
    -d DEST, --dest DEST  File to save translations in
    -v, --verbose         Be verbose
    -c CONFIG, --config CONFIG
                          Config pkl for loading the model configuration. If not
                          specified, hyperparameters are read from config.py
    -w [WEIGHTS [WEIGHTS ...]], --weights [WEIGHTS [WEIGHTS ...]]
                        Weight given to each model in the ensemble. You should
                        provide the same number of weights than models.By
                        default, it applies the same weight to each model
                        (1/N).                       
    --n-best              Write n-best list (n = beam size)                       
    --models MODELS [MODELS ...]

The main arguments are the following:

• --dataset DATASET: Path to the dataset instance used for training the model. REQUIRED since it establishes several hyperparameters, index2word mappings, etc.
• --text TEXT: Path to a text file with source sentences. If this is specified, the model will translate only the sources sentences from this file.
• --n-best: Write the list N-best list (N = beam size)
• --weights [WEIGHTS] : Weight given to each model in the ensemble. You should provide the same number of weights than models. If unspecified, it applies the same weight to each model (1/N).
• --dest DEST: Path to a file to save translations in. If not specified, the translations won't be stored.
• --config CONFIG: Config pkl for loading the model configuration. If not specified, hyperparameters are read from config.py
• --models MODELS [MODELS ...]: List of models to load. REQUIRED. Here, we only need to specify the prefix of each model. For instance, if we want to sample from the models from epochs 1, 2 and 3 from models stored in the trained_models folder, this option should be: --models trained_models/epoch_1 trained_models/epoch_2 trained_models/epoch_3.