code: def _use_qr(u, m, n, params):
      """QDWH iteration using QR decomposition.
  
      Args:
      u: a matrix, with static (padded) shape M x N.
      m, n: the dynamic shape of the matrix, where m <= M and n <= N.
      params: the QDWH parameters.
      """
      a, b, c = params
      M, N = u.shape
  
      y = _dynamic_concat(
          jnp.sqrt(c) * u, jnp.eye(N, dtype=jnp.dtype(u)), m
      )
      q, _ = lax_linalg.qr(y, full_matrices=False)
      # q1 = q[:m, :]
      q1 = _mask(lax.slice(q, (0, 0), (M, N)), (m, n))
      # q2 = (q[m:, :]).T.conj()
      q2 = lax.dynamic_slice_in_dim(q, m, N, axis=0)
      q2 = _mask(q2, (n, n)).T.conj()
      e = b / c
      u = e * u + (a - e) / jnp.sqrt(c) * jnp.einsum(
          "ij,jk->ik", q1, q2
      )
      return u
  
file_path: jax/jax/_src/lax/qdwh.py
imports: from __future__ import annotations
  import functools
  import jax
  import jax.numpy
  from jax import lax
  from jax._src import core
  from jax._src.lax import linalg
label_desc: Use image node_id 4 for calling a global function with example usage: _use_qr(u, m, n, params) and returns: u