From 8f7d00ed447174d9398af3365709222b529c1cad Mon Sep 17 00:00:00 2001 From: Aaron Meurer Date: Fri, 6 Aug 2021 18:22:00 -0600 Subject: Run (selective) black on the array_api submodule I've omitted a few changes from black that messed up the readability of some complicated if statements that were organized logically line-by-line, and some changes that use unnecessary operator spacing. --- numpy/array_api/_linear_algebra_functions.py | 16 +++++++++++++--- 1 file changed, 13 insertions(+), 3 deletions(-) (limited to 'numpy/array_api/_linear_algebra_functions.py') diff --git a/numpy/array_api/_linear_algebra_functions.py b/numpy/array_api/_linear_algebra_functions.py index f13f9c541..089081725 100644 --- a/numpy/array_api/_linear_algebra_functions.py +++ b/numpy/array_api/_linear_algebra_functions.py @@ -17,6 +17,7 @@ import numpy as np # """ # return np.einsum() + def matmul(x1: Array, x2: Array, /) -> Array: """ Array API compatible wrapper for :py:func:`np.matmul `. @@ -26,23 +27,31 @@ def matmul(x1: Array, x2: Array, /) -> Array: # 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') + 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: +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') + 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 `. @@ -51,6 +60,7 @@ def transpose(x: Array, /, *, axes: Optional[Tuple[int, ...]] = None) -> Array: """ 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: -- cgit v1.2.1