use crate::error::Result;
use ndarray::Array2;
use ort::Session;
pub fn predict(
session: &Session,
token_ids: Vec<i64>,
attention_masks: Vec<i64>,
) -> Result<Array2<f32>> {
let outputs = session.run(
ort::inputs! {
"input_ids" => Array2::from_shape_vec((1, token_ids.len()), token_ids).unwrap(),
"attention_mask" => Array2::from_shape_vec((1, attention_masks.len()), attention_masks).unwrap(),
}?
)?;
let output = outputs.get("output").unwrap();
let content = output.try_extract_tensor::<f32>()?.to_owned();
let (data, _) = content.clone().into_raw_vec_and_offset();
Ok(Array2::from_shape_vec((content.shape()[0], content.shape()[1]), data).unwrap())
}