[−][src]Struct rust_bert::openai_gpt::OpenAiGptModel
GPT Base model
Base architecture for GPT model. Usually complemented with a task-specific head, such as a language model head. As opposed to GPT2, GPT does not give the possibility to re-use past activations as an input. It is made of the following blocks:
tokens_embed
:token
embeddingspositions_embed
:position
embeddingsh
: Encoder (transformer) made of a vector of layers. Each layer is made of a multi-head attention layer, layer-normalization layers and a MLP made of linear layers.output_hidden_states
: flag indicating if the model should return all hidden states (as opposed to only the last layer)output_attentions
: flag indicating if the model should return activation weights
Methods
impl OpenAiGptModel
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pub fn new(p: &Path, config: &Gpt2Config) -> OpenAiGptModel
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Build a new OpenAiGptModel
Arguments
p
- Variable store path for the root of the GPT modelconfig
-Gpt2Config
object defining the model architecture
Example
use tch::{nn, Device}; use rust_bert::Config; use std::path::Path; use rust_bert::gpt2::Gpt2Config; use rust_bert::openai_gpt::OpenAiGptModel; 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);
pub fn forward_t(
&self,
input_ids: &Option<Tensor>,
attention_mask: &Option<Tensor>,
token_type_ids: &Option<Tensor>,
position_ids: &Option<Tensor>,
input_embeds: &Option<Tensor>,
train: bool
) -> Result<(Tensor, Option<Vec<Tensor>>, Option<Vec<Tensor>>), &'static str>
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&self,
input_ids: &Option<Tensor>,
attention_mask: &Option<Tensor>,
token_type_ids: &Option<Tensor>,
position_ids: &Option<Tensor>,
input_embeds: &Option<Tensor>,
train: bool
) -> Result<(Tensor, Option<Vec<Tensor>>, Option<Vec<Tensor>>), &'static str>
Forward pass through the model
Arguments
input_ids
- Optional input tensor of shape (batch size, sequence_length). If None, pre-computed embeddings must be provided (seeinput_embeds
)attention_mask
- Optional mask of shape (batch size, sequence_length). Masked position have value 0, non-masked value 1. If None set to 1input_embeds
- Optional pre-computed input embeddings of shape (batch size, sequence_length, hidden_size). If None, input ids must be provided (seeinput_ids
)token_type_ids
- Optional token type ids used to indicate the portion of the input the token belongs to. If not None, token type embeddings will be added to the token and position embeddings.position_ids
- Optional position ids of shape (batch size, sequence_length). If None, will be incremented starting from the length of the past input.train
- boolean flag to turn on/off the dropout layers in the model. Should be set to false for inference.
Returns
output
-Tensor
of shape (batch size, sequence_length, hidden_size) representing the activations of the last hidden statehidden_states
-Option<Vec<Tensor>>
of length num_hidden_layers with shape (batch size, sequence_length, hidden_size)attentions
-Option<Vec<Tensor>>
of length num_hidden_layers with shape (batch size, sequence_length, hidden_size)
Example
use rust_bert::gpt2::Gpt2Config; use rust_bert::openai_gpt::OpenAiGptModel; let (batch_size, sequence_length, past_sequence_length) = (64, 128, 56); let input_tensor = Tensor::rand(&[batch_size, sequence_length], (Int64, device)); let attention_mask = Tensor::zeros(&[batch_size, sequence_length], (Int64, device)); let token_type_ids = Tensor::ones(&[batch_size, sequence_length], (Int64, device)); let position_ids = Tensor::arange(sequence_length, (Int64, device)).expand(&[batch_size, sequence_length], true); let (output, hidden_states, attentions) = no_grad(|| { gpt_model .forward_t(&Some(input_tensor), &Some(attention_mask), &Some(token_type_ids), &Some(position_ids), &None, false).unwrap() });
Auto Trait Implementations
impl !RefUnwindSafe for OpenAiGptModel
impl !Send for OpenAiGptModel
impl !Sync for OpenAiGptModel
impl Unpin for OpenAiGptModel
impl !UnwindSafe for OpenAiGptModel
Blanket Implementations
impl<T> Any for T where
T: 'static + ?Sized,
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T: 'static + ?Sized,
impl<T> Borrow<T> for T where
T: ?Sized,
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T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
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T: ?Sized,
fn borrow_mut(&mut self) -> &mut T
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impl<T> From<T> for T
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impl<T, U> Into<U> for T where
U: From<T>,
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U: From<T>,
impl<T, U> TryFrom<U> for T where
U: Into<T>,
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U: Into<T>,
type Error = Infallible
The type returned in the event of a conversion error.
fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>
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impl<T, U> TryInto<U> for T where
U: TryFrom<T>,
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U: TryFrom<T>,