@@ -914,9 +914,11 @@ def lu_factor(a, overwrite_a=False, check_finite=True):
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where `P` is a permutation matrix, `L` is lower triangular with unit
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diagonal elements, and `U` is upper triangular.
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+ For full documentation refer to :obj:`scipy.linalg.lu_factor`.
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+
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Parameters
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----------
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- a : (M, N) {dpnp.ndarray, usm_ndarray}
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+ a : (..., M, N) {dpnp.ndarray, usm_ndarray}
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Input array to decompose.
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overwrite_a : {None, bool}, optional
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Whether to overwrite data in `a` (may increase performance).
@@ -931,13 +933,14 @@ def lu_factor(a, overwrite_a=False, check_finite=True):
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Returns
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-------
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- lu : (M, N) dpnp.ndarray
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- Matrix containing U in its upper triangle, and L in its lower triangle.
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- The unit diagonal elements of L are not stored.
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- piv : (K, ) dpnp.ndarray
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- Pivot indices representing the permutation matrix P:
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+ lu : (..., M, N) dpnp.ndarray
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+ Matrix containing `U` in its upper triangle,
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+ and `L` in its lower triangle.
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+ The unit diagonal elements of `L` are not stored.
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+ piv : (..., K) dpnp.ndarray
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+ Pivot indices representing the permutation matrix `P`:
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row i of matrix was interchanged with row piv[i].
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- ``K = min(M, N)``.
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+ Where ``K = min(M, N)``.
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Warning
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-------
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