pub fn normalize_f32_vectors(inp: &ndarray::NdArray<f32>, out: &mut ndarray::NdArray<f32>) {
    out.reshape(inp.shape().clone());
    let collen = inp.shape().last() as usize;
    for (inp, out) in inp.iter_rows().zip(out.iter_rows_mut()) {
        let mut vec_len = 0.0;
        for i in inp.iter().take(collen) {
            vec_len += i * i;
        }
        let inv_vec_len = _fast_inv_sqrt_f32(vec_len);

        for i in 0..inp.len() {
            out[i] = inp[i] * inv_vec_len;
        }
    }
}
/// Normalize the inner column vectors using [fast_inv_sqrt](https://en.wikipedia.org/wiki/Fast_inverse_square_root) algorithm. Meaning slightly inaccurate
/// results. E.g. a vector might have a length slightly less than 1.
Normalize the inner column vectors using [fast_inv_sqrt] algorithm. Meaning slightly inaccurate
results.
Normalize the inner column vectors using [ fast_inv_sqrt ] algorithm . Meaning slightly inaccurate results .
pub fn normalize_f32_vectors(inp: &ndarray::NdArray<f32>, out: &mut ndarray::NdArray<f32>) {
    out.reshape(inp.shape().clone());
    let collen = inp.shape().last() as usize;
    for (inp, out) in inp.iter_rows().zip(out.iter_rows_mut()) {
        let mut vec_len = 0.0;
        for i in inp.iter().take(collen) {
            vec_len += i * i;
        }
        let inv_vec_len = _fast_inv_sqrt_f32(vec_len);
        for i in 0..inp.len() {
            out[i] = inp[i] * inv_vec_len;
        }
    }
}
pub fn normalize_f32_vectors ( inp : & ndarray :: NdArray < f32 > , out : & mut ndarray :: NdArray < f32 > ) { out . reshape ( inp . shape ( ) . clone ( ) ) ; let collen = inp . shape ( ) . last ( ) as usize ; for ( inp , out ) in inp . iter_rows ( ) . zip ( out . iter_rows_mut ( ) ) { let mut vec_len = 0.0 ; for i in inp . iter ( ) . take ( collen ) { vec_len += i * i ; } let inv_vec_len = _fast_inv_sqrt_f32 ( vec_len ) ; for i in 0 .. inp . len ( ) { out [ i ] = inp [ i ] * inv_vec_len ; } } }
Normalize the inner column vectors using [fast_inv_sqrt](https://en.wikipedia.org/wiki/Fast_inverse_square_root) algorithm.
Normalize the inner column vectors using [ fast_inv_sqrt ] ( https : // en . wikipedia . org / wiki / Fast_inverse_square_root ) algorithm .
inp
&ndarray::NdArray<f32>
out
&mut ndarray::NdArray<f32>