mirror of
https://github.com/guillaume-be/rust-bert.git
synced 2024-09-11 12:55:34 +03:00
99 lines
3.5 KiB
Rust
99 lines
3.5 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 failure;
|
|
|
|
use rust_bert::gpt2::Gpt2Config;
|
|
use rust_bert::openai_gpt::{
|
|
OpenAIGPTLMHeadModel, OpenAiGptConfigResources, OpenAiGptMergesResources,
|
|
OpenAiGptModelResources, OpenAiGptVocabResources,
|
|
};
|
|
use rust_bert::pipelines::generation::{Cache, LMHeadModel};
|
|
use rust_bert::resources::{download_resource, RemoteResource, Resource};
|
|
use rust_bert::Config;
|
|
use rust_tokenizers::{OpenAiGptTokenizer, Tokenizer, TruncationStrategy};
|
|
use tch::{nn, Device, Tensor};
|
|
|
|
fn main() -> failure::Fallible<()> {
|
|
// Resources paths
|
|
let config_resource = Resource::Remote(RemoteResource::from_pretrained(
|
|
OpenAiGptConfigResources::GPT,
|
|
));
|
|
let vocab_resource = Resource::Remote(RemoteResource::from_pretrained(
|
|
OpenAiGptVocabResources::GPT,
|
|
));
|
|
let merges_resource = Resource::Remote(RemoteResource::from_pretrained(
|
|
OpenAiGptMergesResources::GPT,
|
|
));
|
|
let weights_resource = Resource::Remote(RemoteResource::from_pretrained(
|
|
OpenAiGptModelResources::GPT,
|
|
));
|
|
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)?;
|
|
|
|
// Set-up masked LM model
|
|
let device = Device::Cpu;
|
|
let mut vs = nn::VarStore::new(device);
|
|
let tokenizer = OpenAiGptTokenizer::from_file(
|
|
vocab_path.to_str().unwrap(),
|
|
merges_path.to_str().unwrap(),
|
|
true,
|
|
);
|
|
let config = Gpt2Config::from_file(config_path);
|
|
let openai_gpt = OpenAIGPTLMHeadModel::new(&vs.root(), &config);
|
|
vs.load(weights_path)?;
|
|
|
|
// Define input
|
|
let input = ["Wondering what the next word will"];
|
|
let tokenized_input =
|
|
tokenizer.encode_list(input.to_vec(), 128, &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 (output, _, _, _, _) = openai_gpt
|
|
.forward_t(
|
|
&Some(input_tensor),
|
|
Cache::None,
|
|
&None,
|
|
&None,
|
|
&None,
|
|
&None,
|
|
None,
|
|
&None,
|
|
false,
|
|
)
|
|
.unwrap();
|
|
|
|
let next_word_id = output.get(0).get(-1).argmax(-1, true).int64_value(&[0]);
|
|
let next_word = tokenizer.decode(vec![next_word_id], true, true);
|
|
println!("Provided input: {}", input[0]);
|
|
println!("Next word: {}", next_word);
|
|
|
|
Ok(())
|
|
}
|