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Remove axis kwarg support from matrix_norm (#321)
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spec/extensions/linear_algebra_functions.md

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@@ -261,23 +261,19 @@ Returns the multiplicative inverse of a square matrix (or a stack of square matr
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Alias for {ref}`function-matmul`.
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(function-linalg-matrix-norm)=
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### linalg.matrix_norm(x, /, *, axis=(-2, -1), keepdims=False, ord='fro')
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### linalg.matrix_norm(x, /, *, keepdims=False, ord='fro')
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Computes the matrix norm of a matrix (or a stack of matrices) `x`.
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#### Parameters
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- **x**: _<array>_
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- input array. Must have at least `2` dimensions. Should have a floating-point data type.
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- **axis**: _Tuple\[ int, int ]_
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- a 2-tuple which specifies the axes (dimensions) defining two-dimensional matrices for which to compute matrix norms. Negative indices must be supported. Default: `(-2, -1)` (i.e., the last two-dimensions).
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- input array having shape `(..., M, N)` and whose innermost two dimensions form `MxN` matrices. Should have a floating-point data type.
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- **keepdims**: _bool_
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- If `True`, the axes (dimensions) specified by `axis` must be included in the result as singleton dimensions, and, accordingly, the result must be compatible with the input array (see {ref}`broadcasting`). Otherwise, if `False`, the axes (dimensions) specified by `axis` must not be included in the result. Default: `False`.
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- If `True`, the last two axes (dimensions) must be included in the result as singleton dimensions, and, accordingly, the result must be compatible with the input array (see {ref}`broadcasting`). Otherwise, if `False`, the last two axes (dimensions) must not be included in the result. Default: `False`.
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- **ord**: _Optional\[ Union\[ int, float, Literal\[ inf, -inf, 'fro', 'nuc' ] ] ]_
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@@ -309,7 +305,7 @@ Computes the matrix norm of a matrix (or a stack of matrices) `x`.
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- **out**: _<array>_
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- an array containing the norms. If `keepdims` is `False`, the returned array must have a rank which is two less than the rank of `x`. The returned array must have a floating-point data type determined by {ref}`type-promotion`.
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- an array containing the norms for each `MxN` matrix. If `keepdims` is `False`, the returned array must have a rank which is two less than the rank of `x`. The returned array must have a floating-point data type determined by {ref}`type-promotion`.
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(function-linalg-matrix_power)=
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### linalg.matrix_power(x, n, /)

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