Module marian

Marian

Implementation of the Marian language model (Marian: Fast Neural Machine Translation in {C++} Junczys-Dowmunt, Grundkiewicz, Dwojak, Hoang, Heafield, Neckermann, Seide, Germann, Fikri Aji, Bogoychev, Martins, Birch, 2018). The base model is implemented in the bart_model::BartModel struct. This model includes a language model head: marian_model::MarianForConditionalGeneration implementing the common generation_utils::LanguageGenerator trait shared between the models used for generation (see pipelines for more information).

Model set-up and pre-trained weights loading

A full working example is provided in examples/translation_marian, run with cargo run --example translation_marian. All models expect the following resources:

• Configuration file expected to have a structure following the Transformers library
• Model weights are expected to have a structure and parameter names following the Transformers library. A conversion using the Python utility scripts is required to convert the .bin weights to the .ot format.
• MarianTokenizer using a vocab.json vocabulary and spiece.model sentence piece model

Pretrained models for a number of language pairs are available and can be downloaded using RemoteResources. These are shared under Creative Commons Attribution 4.0 International License license by the Opus-MT team from Language Technology at the University of Helsinki at https://github.com/Helsinki-NLP/Opus-MT.

use tch::{nn, Device};
use rust_bert::bart::{BartConfig, BartModel};
use rust_bert::marian::MarianForConditionalGeneration;
use rust_bert::resources::{LocalResource, ResourceProvider};
use rust_bert::Config;
use rust_tokenizers::tokenizer::MarianTokenizer;

let config_resource = LocalResource {
    local_path: PathBuf::from("path/to/config.json"),
};
let vocab_resource = LocalResource {
    local_path: PathBuf::from("path/to/vocab.json"),
};
let sentence_piece_resource = LocalResource {
    local_path: PathBuf::from("path/to/spiece.model"),
};
let weights_resource = LocalResource {
    local_path: PathBuf::from("path/to/model.ot"),
};
let config_path = config_resource.get_local_path()?;
let vocab_path = vocab_resource.get_local_path()?;
let spiece_path = sentence_piece_resource.get_local_path()?;
let weights_path = weights_resource.get_local_path()?;

let device = Device::cuda_if_available();
let mut vs = nn::VarStore::new(device);
let tokenizer = MarianTokenizer::from_files(
    vocab_path.to_str().unwrap(),
    spiece_path.to_str().unwrap(),
    true,
);
let config = BartConfig::from_file(config_path);
let marian_model = MarianForConditionalGeneration::new(&vs.root(), &config);
vs.load(weights_path)?;

Structs

MarianConfigResources

Marian Pretrained model config files

MarianForConditionalGeneration

Marian Model for conditional generation

MarianGenerator

Language generation model based on the Marian architecture for machine translation

MarianModelPreset

Marian translation model pre-sets

MarianModelResources

Marian Pretrained model weight files

MarianSourceLanguages

Marian source languages pre-sets

MarianSpmResources

Marian Pretrained sentence piece model files

MarianTargetLanguages

Marian target languages pre-sets

MarianVocabResources

Marian Pretrained model vocab files

Type Aliases

MarianConfig

Marian model configuration