How can I convert a Vector to Tensor?

[zemelLeong]

impl<B: Backend> PositionalEncoder<B> {
    pub fn new(
        d_model: usize,
        max_seq_len: Option<usize>,
        dropout: Option<f64>,
        device: &B::Device,
    ) -> Self {
        let max_seq_len = max_seq_len.unwrap_or(900);
        // let mut pe = Tensor::zeros([max_seq_len, d_model], device);
        let mut pe = vec![vec![0.0; d_model]; max_seq_len];

        for pos in 0..max_seq_len {
            for i in (0..d_model).step_by(2) {
                let sin_coef = (10000.0_f64).powf((2 * i) as f64 / d_model as f64);
                let cos_coef = (10000.0_f64).powf((2 * (i + 1)) as f64 / d_model as f64);
                pe[pos][i] = (pos as f64 / sin_coef).sin();
                pe[pos][i + 1] = (pos as f64 / cos_coef).cos();
            }
        }
        let pe = Tensor::<B, 2>::from_data(Data::from(pe), device);
        let pe = pe.unsqueeze();
        let dropout = DropoutConfig::new(dropout.unwrap_or(0.1)).init();
        Self {
            d_model,
            dropout,
            pe,
        }
    }
}

error[E0277]: the trait bound `Data<_, _>: From<Vec<Vec<f64>>>` is not satisfied
   --> src\lore_processor.rs:101:44
    |
101 |         let pe = Tensor::<B, 2>::from_data(Data::from(pe), device);
    |                                            ^^^^ the trait `From<Vec<Vec<f64>>>` is not implemented for `Data<_, _>`
    |
    = help: the following other types implement trait `From<T>`:
              <Data<E, D> as From<DataSerialize<E>>>
              <Data<E, 1> as From<[E; A]>>
              <Data<E, 2> as From<[[E; B]; A]>>
              <Data<E, 3> as From<[[[E; C]; B]; A]>>
              <Data<E, 4> as From<[[[[E; D]; C]; B]; A]>>
              <Data<E, D> as From<&DataSerialize<E>>>
              <Data<E, 1> as From<&[E]>>

[laggui]

It was already answered on discord but will provide an example here for future reference. You can use Data::new with Shape to create a new tensor.

For example, you can convert an image vector to tensor:

// Here img_vec is a Vec<u8> for an image with shape 224x224x3
Tensor::<B, 3>::from_data(Data::new(img_vec, Shape::new(224, 224, 3)).convert(), device)

[canxin121]

Could you provide the discord url of the answer?

[laggui]

Sure, there is not much additional info but here is the original answer on discord: https://discord.com/channels/1038839012602941528/1038839013735399547/1210560858522910800