pub fn new<'p, P>(p: P, config: &Gpt2Config) -> OpenAiGptModel
    where
        P: Borrow<nn::Path<'p>>,
    {
        let p = p.borrow();

        let tokens_embed = embedding(
            p / "tokens_embed",
            config.vocab_size,
            config.n_embd,
            Default::default(),
        );
        let positions_embed = embedding(
            p / "positions_embed",
            config.n_positions,
            config.n_embd,
            Default::default(),
        );

        let embd_pdrop = match config.embd_pdrop {
            Some(value) => value,
            None => 0.1,
        };
        let drop = Dropout::new(embd_pdrop);
        let mut h: Vec<Block> = vec![];
        let h_path = p / "h";
        for layer_index in 0..config.n_layer {
            h.push(Block::new(&h_path / layer_index, config, true));
        }
        let output_attentions = match config.output_attentions {
            Some(value) => value,
            None => false,
        };
        let output_hidden_states = match config.output_hidden_states {
            Some(value) => value,
            None => false,
        };
        OpenAiGptModel {
            tokens_embed,
            positions_embed,
            drop,
            h,
            output_hidden_states,
            output_attentions,
        }
    }
/// Build a new `OpenAiGptModel`
///
/// # Arguments
///
/// * `p` - Variable store path for the root of the GPT model
/// * `config` - `Gpt2Config` object defining the model architecture
///
/// # Example
///
/// ```no_run
/// use rust_bert::gpt2::Gpt2Config;
/// use rust_bert::openai_gpt::OpenAiGptModel;
/// use rust_bert::Config;
/// use std::path::Path;
/// use tch::{nn, Device};
///
/// let config_path = Path::new("path/to/config.json");
/// let device = Device::Cpu;
/// let p = nn::VarStore::new(device);
/// let config = Gpt2Config::from_file(config_path);
/// let gpt2: OpenAiGptModel = OpenAiGptModel::new(&p.root() / "gpt", &config);
/// ```
Build a new `OpenAiGptModel`
Build a new ` OpenAiGptModel `
pub fn new<'p, P>(p: P, config: &Gpt2Config) -> OpenAiGptModel
    where
        P: Borrow<nn::Path<'p>>,
    {
        let p = p.borrow();
        let tokens_embed = embedding(
            p / "tokens_embed",
            config.vocab_size,
            config.n_embd,
            Default::default(),
        );
        let positions_embed = embedding(
            p / "positions_embed",
            config.n_positions,
            config.n_embd,
            Default::default(),
        );
        let embd_pdrop = match config.embd_pdrop {
            Some(value) => value,
            None => 0.1,
        };
        let drop = Dropout::new(embd_pdrop);
        let mut h: Vec<Block> = vec![];
        let h_path = p / "h";
        for layer_index in 0..config.n_layer {
            h.push(Block::new(&h_path / layer_index, config, true));
        }
        let output_attentions = match config.output_attentions {
            Some(value) => value,
            None => false,
        };
        let output_hidden_states = match config.output_hidden_states {
            Some(value) => value,
            None => false,
        };
        OpenAiGptModel {
            tokens_embed,
            positions_embed,
            drop,
            h,
            output_hidden_states,
            output_attentions,
        }
    }
pub fn new < ' p , P > ( p : P , config : & Gpt2Config ) -> OpenAiGptModel where P : Borrow < nn :: Path < ' p > > , { let p = p . borrow ( ) ; let tokens_embed = embedding ( p / " " , config . vocab_size , config . n_embd , Default :: default ( ) , ) ; let positions_embed = embedding ( p / " " , config . n_positions , config . n_embd , Default :: default ( ) , ) ; let embd_pdrop = match config . embd_pdrop { Some ( value ) => value , None => 0.1 , } ; let drop = Dropout :: new ( embd_pdrop ) ; let mut h : Vec < Block > = vec ! [ ] ; let h_path = p / " " ; for layer_index in 0 .. config . n_layer { h . push ( Block :: new ( & h_path / layer_index , config , true ) ) ; } let output_attentions = match config . output_attentions { Some ( value ) => value , None => false , } ; let output_hidden_states = match config . output_hidden_states { Some ( value ) => value , None => false , } ; OpenAiGptModel { tokens_embed , positions_embed , drop , h , output_hidden_states , output_attentions , } }
Build a new `OpenAiGptModel`
Build a new ` OpenAiGptModel `
p
P
config
&Gpt2Config
p
P
config
&Gpt2Config
example


let config_path = Path::new("path/to/config.json");
let device = Device::Cpu;
let p = nn::VarStore::new(device);
let config = Gpt2Config::from_file(config_path);
let gpt2: OpenAiGptModel = OpenAiGptModel::new(&p.root() / "gpt", &config);
```
let config_path = Path :: new ( " path / to / config . json " ) ; let device = Device :: Cpu ; let p = nn :: VarStore :: new ( device ) ; let config = Gpt2Config :: from_file ( config_path ) ; let gpt2 : OpenAiGptModel = OpenAiGptModel :: new ( &p . root () / " gpt " &config ) ; ` ` `