haojin2 commented on a change in pull request #17851: [WIP] [Numpy]
np.linalg.qr forward implementation
URL: https://github.com/apache/incubator-mxnet/pull/17851#discussion_r393969808
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File path: python/mxnet/numpy/linalg.py
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@@ -291,6 +291,78 @@ def cholesky(a):
return _mx_nd_np.linalg.cholesky(a)
+def qr(a, mode='reduced'):
+ r"""
+ Compute the qr factorization of a matrix a.
+ Factor the matrix a as qr, where q is orthonormal and r is
upper-triangular.
+
+ Parameters
+ ----------
+ a : (..., M, N) ndarray
+ Matrix or stack of matrices to be qr factored.
+ mode: {‘reduced’, ‘complete’, ‘r’, ‘raw’, ‘full’, ‘economic’}, optional
+ Only default mode, 'reduced', is implemented. If K = min(M, N), then
+ * 'reduced’ : returns q, r with dimensions (M, K), (K, N) (default)
+
+ Returns
+ -------
+ q : (..., M, K) ndarray
+ A matrix or stack of matrices with K orthonormal columns, with K =
min(M, N).
+ r : (..., K, N) ndarray
+ A matrix or stack of upper triangular matrices.
+
+ Raises
+ ------
+ MXNetError
+ If factoring fails.
+
+ Examples
+ --------
+ >>> from mxnet import np
+ >>> a = np.random.uniform(-10, 10, (3, 3))
+ >>> a
+ array([[ 0.9762707 , 1.8568916 , 4.303787 ],
+ [ 6.885315 , 2.0552673 , 7.1589127 ],
Review comment:
would you please fix the alignment of the examples here?
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