mx.symbol.linalg_det
¶
Description¶
Compute the determinant of a matrix. Input is a tensor A of dimension n >= 2.
If n=2, A is a square matrix. We compute:
out = det(A)
If n>2, det is performed separately on the trailing two dimensions for all inputs (batch mode).
Note
The operator supports float32 and float64 data types only.
Note
There is no gradient backwarded when A is non-invertible (which is equivalent to det(A) = 0) because zero is rarely hit upon in float point computation and the Jacobi’s formula on determinant gradient is not computationally efficient when A is non-invertible.
Example:
Single matrix determinant
A = [[1., 4.], [2., 3.]]
det(A) = [-5.]
Batch matrix determinant
A = [[[1., 4.], [2., 3.]],
[[2., 3.], [1., 4.]]]
det(A) = [-5., 5.]
Usage¶
mx.symbol.linalg_det(...)
Arguments¶
Argument |
Description |
---|---|
|
NDArray-or-Symbol. Tensor of square matrix |
|
string, optional. Name of the resulting symbol. |
Value¶
out
The result mx.symbol
Link to Source Code: http://github.com/apache/incubator-mxnet/blob/1.6.0/src/operator/tensor/la_op.cc#L973