407 lines
14 KiB
Rust
407 lines
14 KiB
Rust
// Uses `nalgebra` crate to invoke `np_linalg` and `sp_linalg` functions
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// When converting between `nalgebra::Matrix` and `NDArray` following considerations are necessary
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//
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// * Both `nalgebra::Matrix` and `NDArray` require their content to be stored in row-major order
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// * `NDArray` data pointer can be directly read and converted to `nalgebra::Matrix` (row and column number must be known)
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// * `nalgebra::Matrix::as_slice` returns the content of matrix in column-major order and initial data needs to be transposed before storing it in `NDArray` data pointer
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use core::slice;
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use nalgebra::DMatrix;
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fn report_error(
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error_name: &str,
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fn_name: &str,
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file_name: &str,
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line_num: u32,
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col_num: u32,
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err_msg: &str,
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) -> ! {
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panic!(
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"Exception {} from {} in {}:{}:{}, message: {}",
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error_name, fn_name, file_name, line_num, col_num, err_msg
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);
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}
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pub struct InputMatrix {
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pub ndims: usize,
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pub dims: *const usize,
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pub data: *mut f64,
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}
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impl InputMatrix {
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fn get_dims(&mut self) -> Vec<usize> {
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let dims = unsafe { slice::from_raw_parts(self.dims, self.ndims) };
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dims.to_vec()
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}
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}
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/// # Safety
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///
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/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
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#[no_mangle]
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pub unsafe extern "C" fn np_linalg_cholesky(mat1: *mut InputMatrix, out: *mut InputMatrix) {
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let mat1 = mat1.as_mut().unwrap();
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let out = out.as_mut().unwrap();
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if mat1.ndims != 2 {
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let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
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report_error("ValueError", "np_linalg_cholesky", file!(), line!(), column!(), &err_msg);
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}
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let dim1 = (*mat1).get_dims();
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if dim1[0] != dim1[1] {
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let err_msg =
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format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]);
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report_error("LinAlgError", "np_linalg_cholesky", file!(), line!(), column!(), &err_msg);
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}
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let outdim = out.get_dims();
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let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
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let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
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let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
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let result = matrix1.cholesky();
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match result {
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Some(res) => {
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out_slice.copy_from_slice(res.unpack().transpose().as_slice());
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}
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None => {
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report_error(
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"LinAlgError",
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"np_linalg_cholesky",
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file!(),
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line!(),
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column!(),
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"Matrix is not positive definite",
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);
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}
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};
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}
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/// # Safety
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///
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/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
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#[no_mangle]
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pub unsafe extern "C" fn np_linalg_qr(
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mat1: *mut InputMatrix,
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out_q: *mut InputMatrix,
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out_r: *mut InputMatrix,
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) {
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let mat1 = mat1.as_mut().unwrap();
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let out_q = out_q.as_mut().unwrap();
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let out_r = out_r.as_mut().unwrap();
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if mat1.ndims != 2 {
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let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
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report_error("ValueError", "np_linalg_cholesky", file!(), line!(), column!(), &err_msg);
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}
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let dim1 = (*mat1).get_dims();
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let outq_dim = (*out_q).get_dims();
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let outr_dim = (*out_r).get_dims();
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let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
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let out_q_slice = unsafe { slice::from_raw_parts_mut(out_q.data, outq_dim[0] * outq_dim[1]) };
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let out_r_slice = unsafe { slice::from_raw_parts_mut(out_r.data, outr_dim[0] * outr_dim[1]) };
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// Refer to https://github.com/dimforge/nalgebra/issues/735
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let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
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let res = matrix1.qr();
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let (q, r) = res.unpack();
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// Uses different algo need to match numpy
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out_q_slice.copy_from_slice(q.transpose().as_slice());
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out_r_slice.copy_from_slice(r.transpose().as_slice());
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}
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/// # Safety
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///
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/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
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#[no_mangle]
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pub unsafe extern "C" fn np_linalg_svd(
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mat1: *mut InputMatrix,
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outu: *mut InputMatrix,
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outs: *mut InputMatrix,
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outvh: *mut InputMatrix,
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) {
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let mat1 = mat1.as_mut().unwrap();
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let outu = outu.as_mut().unwrap();
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let outs = outs.as_mut().unwrap();
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let outvh = outvh.as_mut().unwrap();
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if mat1.ndims != 2 {
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let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
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report_error("ValueError", "np_linalg_svd", file!(), line!(), column!(), &err_msg);
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}
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let dim1 = (*mat1).get_dims();
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let outu_dim = (*outu).get_dims();
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let outs_dim = (*outs).get_dims();
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let outvh_dim = (*outvh).get_dims();
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let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
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let out_u_slice = unsafe { slice::from_raw_parts_mut(outu.data, outu_dim[0] * outu_dim[1]) };
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let out_s_slice = unsafe { slice::from_raw_parts_mut(outs.data, outs_dim[0]) };
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let out_vh_slice =
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unsafe { slice::from_raw_parts_mut(outvh.data, outvh_dim[0] * outvh_dim[1]) };
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let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
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let result = matrix.svd(true, true);
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out_u_slice.copy_from_slice(result.u.unwrap().transpose().as_slice());
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out_s_slice.copy_from_slice(result.singular_values.as_slice());
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out_vh_slice.copy_from_slice(result.v_t.unwrap().transpose().as_slice());
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}
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/// # Safety
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///
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/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
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#[no_mangle]
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pub unsafe extern "C" fn np_linalg_inv(mat1: *mut InputMatrix, out: *mut InputMatrix) {
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let mat1 = mat1.as_mut().unwrap();
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let out = out.as_mut().unwrap();
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if mat1.ndims != 2 {
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let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
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report_error("ValueError", "np_linalg_inv", file!(), line!(), column!(), &err_msg);
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}
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let dim1 = (*mat1).get_dims();
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if dim1[0] != dim1[1] {
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let err_msg =
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format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]);
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report_error("LinAlgError", "np_linalg_inv", file!(), line!(), column!(), &err_msg);
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}
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let outdim = out.get_dims();
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let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
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let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
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let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
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if !matrix.is_invertible() {
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report_error(
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"LinAlgError",
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"np_linalg_inv",
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file!(),
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line!(),
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column!(),
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"no inverse for Singular Matrix",
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);
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}
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let inv = matrix.try_inverse().unwrap();
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out_slice.copy_from_slice(inv.transpose().as_slice());
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}
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/// # Safety
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///
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/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
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#[no_mangle]
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pub unsafe extern "C" fn np_linalg_pinv(mat1: *mut InputMatrix, out: *mut InputMatrix) {
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let mat1 = mat1.as_mut().unwrap();
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let out = out.as_mut().unwrap();
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if mat1.ndims != 2 {
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let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
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report_error("ValueError", "np_linalg_pinv", file!(), line!(), column!(), &err_msg);
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}
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let dim1 = (*mat1).get_dims();
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let outdim = out.get_dims();
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let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
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let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
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let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
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let svd = matrix.svd(true, true);
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let inv = svd.pseudo_inverse(1e-15);
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match inv {
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Ok(m) => {
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out_slice.copy_from_slice(m.transpose().as_slice());
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}
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Err(err_msg) => {
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report_error("LinAlgError", "np_linalg_pinv", file!(), line!(), column!(), err_msg);
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}
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}
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}
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/// # Safety
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///
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/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
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#[no_mangle]
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pub unsafe extern "C" fn np_linalg_matrix_power(
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mat1: *mut InputMatrix,
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mat2: *mut InputMatrix,
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out: *mut InputMatrix,
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) {
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let mat1 = mat1.as_mut().unwrap();
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let mat2 = mat2.as_mut().unwrap();
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let out = out.as_mut().unwrap();
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if mat1.ndims != 2 {
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let err_msg = format!("expected 2D Vector Input, but received {}D", mat1.ndims);
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report_error("ValueError", "np_linalg_matrix_power", file!(), line!(), column!(), &err_msg);
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}
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let dim1 = (*mat1).get_dims();
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let power = unsafe { slice::from_raw_parts_mut(mat2.data, 1) };
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let power = power[0];
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let outdim = out.get_dims();
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let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
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let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
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let abs_pow = power.abs();
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let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
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let mut result = matrix1.pow(abs_pow as u32);
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if power < 0.0 {
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if !result.is_invertible() {
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report_error(
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"LinAlgError",
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"np_linalg_inv",
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file!(),
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line!(),
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column!(),
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"no inverse for Singular Matrix",
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);
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}
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result = result.try_inverse().unwrap();
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}
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out_slice.copy_from_slice(result.transpose().as_slice());
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}
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/// # Safety
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///
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/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
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#[no_mangle]
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pub unsafe extern "C" fn np_linalg_det(mat1: *mut InputMatrix, out: *mut InputMatrix) {
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let mat1 = mat1.as_mut().unwrap();
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let out = out.as_mut().unwrap();
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if mat1.ndims != 2 {
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let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
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report_error("ValueError", "np_linalg_det", file!(), line!(), column!(), &err_msg);
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}
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let dim1 = (*mat1).get_dims();
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let out_slice = unsafe { slice::from_raw_parts_mut(out.data, 1) };
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let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
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let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
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if !matrix.is_square() {
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let err_msg =
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format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]);
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report_error("LinAlgError", "np_linalg_inv", file!(), line!(), column!(), &err_msg);
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}
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out_slice[0] = matrix.determinant();
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}
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/// # Safety
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///
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/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
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#[no_mangle]
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pub unsafe extern "C" fn sp_linalg_lu(
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mat1: *mut InputMatrix,
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out_l: *mut InputMatrix,
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out_u: *mut InputMatrix,
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) {
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let mat1 = mat1.as_mut().unwrap();
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let out_l = out_l.as_mut().unwrap();
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let out_u = out_u.as_mut().unwrap();
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if mat1.ndims != 2 {
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let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
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report_error("ValueError", "sp_linalg_lu", file!(), line!(), column!(), &err_msg);
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}
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let dim1 = (*mat1).get_dims();
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let outl_dim = (*out_l).get_dims();
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let outu_dim = (*out_u).get_dims();
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let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
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let out_l_slice = unsafe { slice::from_raw_parts_mut(out_l.data, outl_dim[0] * outl_dim[1]) };
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let out_u_slice = unsafe { slice::from_raw_parts_mut(out_u.data, outu_dim[0] * outu_dim[1]) };
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let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
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let (_, l, u) = matrix.lu().unpack();
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out_l_slice.copy_from_slice(l.transpose().as_slice());
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out_u_slice.copy_from_slice(u.transpose().as_slice());
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}
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/// # Safety
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///
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/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
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#[no_mangle]
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pub unsafe extern "C" fn sp_linalg_schur(
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mat1: *mut InputMatrix,
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out_t: *mut InputMatrix,
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out_z: *mut InputMatrix,
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) {
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let mat1 = mat1.as_mut().unwrap();
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let out_t = out_t.as_mut().unwrap();
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let out_z = out_z.as_mut().unwrap();
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if mat1.ndims != 2 {
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let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
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report_error("ValueError", "sp_linalg_schur", file!(), line!(), column!(), &err_msg);
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}
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let dim1 = (*mat1).get_dims();
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if dim1[0] != dim1[1] {
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let err_msg =
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format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]);
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report_error("LinAlgError", "np_linalg_schur", file!(), line!(), column!(), &err_msg);
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}
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let out_t_dim = (*out_t).get_dims();
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let out_z_dim = (*out_z).get_dims();
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let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
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let out_t_slice = unsafe { slice::from_raw_parts_mut(out_t.data, out_t_dim[0] * out_t_dim[1]) };
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let out_z_slice = unsafe { slice::from_raw_parts_mut(out_z.data, out_z_dim[0] * out_z_dim[1]) };
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let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
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let (z, t) = matrix.schur().unpack();
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out_t_slice.copy_from_slice(t.transpose().as_slice());
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out_z_slice.copy_from_slice(z.transpose().as_slice());
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}
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/// # Safety
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///
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/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
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#[no_mangle]
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pub unsafe extern "C" fn sp_linalg_hessenberg(
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mat1: *mut InputMatrix,
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out_h: *mut InputMatrix,
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out_q: *mut InputMatrix,
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) {
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let mat1 = mat1.as_mut().unwrap();
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let out_h = out_h.as_mut().unwrap();
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let out_q = out_q.as_mut().unwrap();
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if mat1.ndims != 2 {
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let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
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report_error("ValueError", "sp_linalg_hessenberg", file!(), line!(), column!(), &err_msg);
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}
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let dim1 = (*mat1).get_dims();
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if dim1[0] != dim1[1] {
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let err_msg =
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format!("last 2 dimensions of the array must be square: {} != {}", dim1[0], dim1[1]);
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report_error("LinAlgError", "sp_linalg_hessenberg", file!(), line!(), column!(), &err_msg);
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}
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let out_h_dim = (*out_h).get_dims();
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let out_q_dim = (*out_q).get_dims();
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let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
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let out_h_slice = unsafe { slice::from_raw_parts_mut(out_h.data, out_h_dim[0] * out_h_dim[1]) };
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let out_q_slice = unsafe { slice::from_raw_parts_mut(out_q.data, out_q_dim[0] * out_q_dim[1]) };
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let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
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let (q, h) = matrix.hessenberg().unpack();
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out_h_slice.copy_from_slice(h.transpose().as_slice());
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out_q_slice.copy_from_slice(q.transpose().as_slice());
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}
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