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.

1 files changed, 13 insertions, 3 deletions

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 <numpy.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 <numpy.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: