native_neural_network_std 0.2.1

Ergonomic std wrapper for the `native_neural_network` crate (no_std) — std-friendly re-exports and utilities.
Documentation 
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#[derive(Clone, Copy, Debug, PartialEq, Eq)]
pub enum BatchStdError {
    ShapeMismatch,
    Empty,
}

impl From<native_neural_network::batching::BatchError> for BatchStdError {
    fn from(e: native_neural_network::batching::BatchError) -> Self {
        match e {
            native_neural_network::batching::BatchError::ShapeMismatch => {
                BatchStdError::ShapeMismatch
            }
            native_neural_network::batching::BatchError::Empty => BatchStdError::Empty,
        }
    }
}

pub fn pad_sequences_u32(
    sequences: &[&[u32]],
    pad_id: u32,
    out: &mut [u32],
    max_len: usize,
) -> Result<(), BatchStdError> {
    native_neural_network::batching::pad_sequences_u32(sequences, pad_id, out, max_len)
        .map_err(|e| e.into())
}

pub fn make_padding_mask(
    tokens: &[u32],
    pad_id: u32,
    out_mask: &mut [u8],
) -> Result<(), BatchStdError> {
    native_neural_network::batching::make_padding_mask(tokens, pad_id, out_mask)
        .map_err(|e| e.into())
}

pub fn for_each_token_row(tokens: &[u32], row_width: usize, f: impl FnMut(usize, &[u32])) -> bool {
    native_neural_network::batching::for_each_token_row(tokens, row_width, f)
}

pub fn count_non_pad(tokens: &[u32], pad_id: u32) -> usize {
    native_neural_network::batching::count_non_pad(tokens, pad_id)
}

pub fn max_sequence_len(sequences: &[&[u32]]) -> Option<usize> {
    native_neural_network::batching::max_sequence_len(sequences)
}

pub fn sequence_lengths(sequences: &[&[u32]], out: &mut [usize]) -> bool {
    native_neural_network::batching::sequence_lengths(sequences, out)
}