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Diffstat (limited to 'numpy/array_api/_linear_algebra_functions.py')
-rw-r--r-- | numpy/array_api/_linear_algebra_functions.py | 58 |
1 files changed, 58 insertions, 0 deletions
diff --git a/numpy/array_api/_linear_algebra_functions.py b/numpy/array_api/_linear_algebra_functions.py new file mode 100644 index 000000000..f13f9c541 --- /dev/null +++ b/numpy/array_api/_linear_algebra_functions.py @@ -0,0 +1,58 @@ +from __future__ import annotations + +from ._array_object import Array +from ._dtypes import _numeric_dtypes, _result_type + +from typing import Optional, Sequence, Tuple, Union + +import numpy as np + +# einsum is not yet implemented in the array API spec. + +# def einsum(): +# """ +# Array API compatible wrapper for :py:func:`np.einsum <numpy.einsum>`. +# +# See its docstring for more information. +# """ +# return np.einsum() + +def matmul(x1: Array, x2: Array, /) -> Array: + """ + Array API compatible wrapper for :py:func:`np.matmul <numpy.matmul>`. + + See its docstring for more information. + """ + # Note: the restriction to numeric dtypes only is different from + # np.matmul. + if x1.dtype not in _numeric_dtypes or x2.dtype not in _numeric_dtypes: + raise TypeError('Only numeric dtypes are allowed in matmul') + # Call result type here just to raise on disallowed type combinations + _result_type(x1.dtype, x2.dtype) + + return Array._new(np.matmul(x1._array, x2._array)) + +# Note: axes must be a tuple, unlike np.tensordot where it can be an array or array-like. +def tensordot(x1: Array, x2: Array, /, *, axes: Union[int, Tuple[Sequence[int], Sequence[int]]] = 2) -> Array: + # Note: the restriction to numeric dtypes only is different from + # np.tensordot. + if x1.dtype not in _numeric_dtypes or x2.dtype not in _numeric_dtypes: + raise TypeError('Only numeric dtypes are allowed in tensordot') + # Call result type here just to raise on disallowed type combinations + _result_type(x1.dtype, x2.dtype) + + return Array._new(np.tensordot(x1._array, x2._array, axes=axes)) + +def transpose(x: Array, /, *, axes: Optional[Tuple[int, ...]] = None) -> Array: + """ + Array API compatible wrapper for :py:func:`np.transpose <numpy.transpose>`. + + See its docstring for more information. + """ + return Array._new(np.transpose(x._array, axes=axes)) + +# Note: vecdot is not in NumPy +def vecdot(x1: Array, x2: Array, /, *, axis: Optional[int] = None) -> Array: + if axis is None: + axis = -1 + return tensordot(x1, x2, axes=((axis,), (axis,))) |