extern crate failure;
use rust_bert::bart::{
BartConfig, BartConfigResources, BartMergesResources, BartModel, BartModelResources,
BartVocabResources,
};
use rust_bert::resources::{download_resource, RemoteResource, Resource};
use rust_bert::Config;
use rust_tokenizers::{RobertaTokenizer, Tokenizer, TruncationStrategy};
use tch::{nn, no_grad, Device, Tensor};
fn main() -> failure::Fallible<()> {
let config_resource =
Resource::Remote(RemoteResource::from_pretrained(BartConfigResources::BART));
let vocab_resource =
Resource::Remote(RemoteResource::from_pretrained(BartVocabResources::BART));
let merges_resource =
Resource::Remote(RemoteResource::from_pretrained(BartMergesResources::BART));
let weights_resource =
Resource::Remote(RemoteResource::from_pretrained(BartModelResources::BART));
let config_path = download_resource(&config_resource)?;
let vocab_path = download_resource(&vocab_resource)?;
let merges_path = download_resource(&merges_resource)?;
let weights_path = download_resource(&weights_resource)?;
let device = Device::cuda_if_available();
let mut vs = nn::VarStore::new(device);
let tokenizer = RobertaTokenizer::from_file(
vocab_path.to_str().unwrap(),
merges_path.to_str().unwrap(),
false,
);
let config = BartConfig::from_file(config_path);
let bart_model = BartModel::new(&vs.root(), &config, false);
vs.load(weights_path)?;
let input = ["In findings published Tuesday in Cornell University's arXiv by a team of scientists \
from the University of Montreal and a separate report published Wednesday in Nature Astronomy by a team \
from University College London (UCL), the presence of water vapour was confirmed in the atmosphere of K2-18b, \
a planet circling a star in the constellation Leo. This is the first such discovery in a planet in its star's \
habitable zone — not too hot and not too cold for liquid water to exist. The Montreal team, led by Björn Benneke, \
used data from the NASA's Hubble telescope to assess changes in the light coming from K2-18b's star as the planet \
passed between it and Earth. They found that certain wavelengths of light, which are usually absorbed by water, \
weakened when the planet was in the way, indicating not only does K2-18b have an atmosphere, but the atmosphere \
contains water in vapour form. The team from UCL then analyzed the Montreal team's data using their own software \
and confirmed their conclusion. This was not the first time scientists have found signs of water on an exoplanet, \
but previous discoveries were made on planets with high temperatures or other pronounced differences from Earth. \
\"This is the first potentially habitable planet where the temperature is right and where we now know there is water,\" \
said UCL astronomer Angelos Tsiaras. \"It's the best candidate for habitability right now.\" \"It's a good sign\", \
said Ryan Cloutier of the Harvard–Smithsonian Center for Astrophysics, who was not one of either study's authors. \
\"Overall,\" he continued, \"the presence of water in its atmosphere certainly improves the prospect of K2-18b being \
a potentially habitable planet, but further observations will be required to say for sure. \"
K2-18b was first identified in 2015 by the Kepler space telescope. It is about 110 light-years from Earth and larger \
but less dense. Its star, a red dwarf, is cooler than the Sun, but the planet's orbit is much closer, such that a year \
on K2-18b lasts 33 Earth days. According to The Guardian, astronomers were optimistic that NASA's James Webb space \
telescope — scheduled for launch in 2021 — and the European Space Agency's 2028 ARIEL program, could reveal more \
about exoplanets like K2-18b."];
let tokenized_input =
tokenizer.encode_list(input.to_vec(), 1024, &TruncationStrategy::LongestFirst, 0);
let max_len = tokenized_input
.iter()
.map(|input| input.token_ids.len())
.max()
.unwrap();
let tokenized_input = tokenized_input
.iter()
.map(|input| input.token_ids.clone())
.map(|mut input| {
input.extend(vec![0; max_len - input.len()]);
input
})
.map(|input| Tensor::of_slice(&(input)))
.collect::<Vec<_>>();
let input_tensor = Tensor::stack(tokenized_input.as_slice(), 0).to(device);
let (decoder_output, encoder_output, _, _, _, _, _) =
no_grad(|| bart_model.forward_t(Some(&input_tensor), None, None, None, None, None, false));
println!("{:?}", encoder_output);
println!("{:?}", decoder_output);
Ok(())
}