mirror of
https://github.com/guillaume-be/rust-bert.git
synced 2024-09-11 12:55:34 +03:00
88 lines
3.4 KiB
Rust
88 lines
3.4 KiB
Rust
// Copyright 2019-present, the HuggingFace Inc. team, The Google AI Language Team and Facebook, Inc.
|
|
// Copyright 2019 Guillaume Becquin
|
|
// Licensed under the Apache License, Version 2.0 (the "License");
|
|
// you may not use this file except in compliance with the License.
|
|
// You may obtain a copy of the License at
|
|
// http://www.apache.org/licenses/LICENSE-2.0
|
|
// Unless required by applicable law or agreed to in writing, software
|
|
// distributed under the License is distributed on an "AS IS" BASIS,
|
|
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
// See the License for the specific language governing permissions and
|
|
// limitations under the License.
|
|
|
|
extern crate anyhow;
|
|
|
|
use rust_bert::bart::{
|
|
BartConfig, BartConfigResources, BartMergesResources, BartModel, BartModelResources,
|
|
BartVocabResources,
|
|
};
|
|
use rust_bert::resources::{RemoteResource, Resource};
|
|
use rust_bert::Config;
|
|
use rust_tokenizers::{RobertaTokenizer, Tokenizer, TruncationStrategy};
|
|
use tch::{nn, no_grad, Device, Tensor};
|
|
|
|
fn main() -> anyhow::Result<()> {
|
|
// Resources paths
|
|
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 = config_resource.get_local_path()?;
|
|
let vocab_path = vocab_resource.get_local_path()?;
|
|
let merges_path = merges_resource.get_local_path()?;
|
|
let weights_path = weights_resource.get_local_path()?;
|
|
|
|
// Set-up masked LM model
|
|
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,
|
|
false,
|
|
)?;
|
|
let config = BartConfig::from_file(config_path);
|
|
let bart_model = BartModel::new(&vs.root(), &config, false);
|
|
vs.load(weights_path)?;
|
|
|
|
// Define input
|
|
let input = ["One two three four"];
|
|
|
|
// Credits: WikiNews, CC BY 2.5 license (https://en.wikinews.org/wiki/Astronomers_find_water_vapour_in_atmosphere_of_exoplanet_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);
|
|
|
|
// Forward pass
|
|
let model_output =
|
|
no_grad(|| bart_model.forward_t(Some(&input_tensor), None, None, None, None, None, false));
|
|
|
|
// Print masked tokens
|
|
println!("{:?}", model_output.encoder_hidden_state);
|
|
println!("{:?}", model_output.decoder_hidden_state);
|
|
println!(
|
|
"{:?}",
|
|
model_output.decoder_hidden_state.double_value(&[0, 0, 0])
|
|
);
|
|
Ok(())
|
|
}
|