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| ``mx.nd.linalg.det`` |
| ======================================== |
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| Description |
| ---------------------- |
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| Compute the determinant of a matrix. |
| Input is a tensor *A* of dimension *n >= 2*. |
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| If *n=2*, *A* is a square matrix. We compute: |
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| *out* = *det(A)* |
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| If *n>2*, *det* is performed separately on the trailing two dimensions |
| for all inputs (batch mode). |
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| .. 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. |
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| **Example**:: |
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| Single matrix determinant |
| A = [[1., 4.], [2., 3.]] |
| det(A) = [-5.] |
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| Batch matrix determinant |
| A = [[[1., 4.], [2., 3.]], |
| [[2., 3.], [1., 4.]]] |
| det(A) = [-5., 5.] |
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| Arguments |
| ------------------ |
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| +----------------------------------------+------------------------------------------------------------+ |
| | Argument | Description | |
| +========================================+============================================================+ |
| | ``A`` | NDArray-or-Symbol. | |
| | | | |
| | | Tensor of square matrix | |
| +----------------------------------------+------------------------------------------------------------+ |
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| Value |
| ---------- |
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| ``out`` The result mx.ndarray |
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| Link to Source Code: http://github.com/apache/incubator-mxnet/blob/1.6.0/src/operator/tensor/la_op.cc#L973 |
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