ckt624 commented on a change in pull request #15861: Numpy det and slogdet 
operator
URL: https://github.com/apache/incubator-mxnet/pull/15861#discussion_r313730410
 
 

 ##########
 File path: python/mxnet/_numpy_op_doc.py
 ##########
 @@ -20,6 +20,129 @@
 """Doc placeholder for numpy ops with prefix _np."""
 
 
+def _np_linalg_det(a):
+    """
+    det(a)
+
+    Compute the determinant of an array.
+
+    Parameters
+    ----------
+    a : (..., M, M) ndarray
+        Input array to compute determinants for.
+
+    Returns
+    -------
+    det : (...) ndarray
+        Determinant of `a`.
+
+    See Also
+    --------
+    slogdet : Another way to represent the determinant, more suitable
+    for large matrices where underflow/overflow may occur.
+
+    Notes
+    -----
+
+    Broadcasting rules apply, see the `numpy.linalg` documentation for
+    details.
+
+    The determinant is computed via LU factorization using the LAPACK
+    routine z/dgetrf.
+
+    Examples
+    --------
+    The determinant of a 2-D array [[a, b], [c, d]] is ad - bc:
+
+    >>> a = np.array([[1, 2], [3, 4]])
+    >>> np.linalg.det(a)
+    -2.0
+
+    Computing determinants for a stack of matrices:
+
+    >>> a = np.array([ [[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]] ])
+    >>> a.shape
+    (3, 2, 2)
+    >>> np.linalg.det(a)
+    array([-2., -3., -8.])
+    """
+    pass
+
+
+def _np_linalg_slogdet(a):
+    """
+    slogdet(a)
+
+    Compute the sign and (natural) logarithm of the determinant of an array.
+
+    If an array has a very small or very large determinant, then a call to
+    `det` may overflow or underflow. This routine is more robust against such
+    issues, because it computes the logarithm of the determinant rather than
+    the determinant itself.
+
+    Parameters
+    ----------
+    a : (..., M, M) ndarray
+        Input array, has to be a square 2-D array.
+
+    Returns
+    -------
+    sign : (...) ndarray
+        A number representing the sign of the determinant. For a real matrix,
+        this is 1, 0, or -1. For a complex matrix, this is a complex number
 
 Review comment:
   fixed. Thx.

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