✨ HasMatrixTranspose

Author: nstarman

src/array_api_typing/_array.py

@@ -4,7 +4,7 @@
 )
 
 from types import ModuleType
-from typing import Literal, Protocol
+from typing import Literal, Protocol, Self
 from typing_extensions import TypeVar
 
 NamespaceT_co = TypeVar("NamespaceT_co", covariant=True, default=ModuleType)
@@ -76,10 +76,32 @@ def device(self) -> object:  # TODO: more specific type
         ...
 
 
+class HasMatrixTranspose(Protocol):
+    """Protocol for array classes that have a matrix transpose attribute."""
+
+    @property
+    def mT(self) -> Self:  # noqa: N802
+        """Transpose of a matrix (or a stack of matrices).
+
+        If an array instance has fewer than two dimensions, an error should be
+        raised.
+
+        Returns:
+            Self: array whose last two dimensions (axes) are permuted in reverse
+                order relative to original array (i.e., for an array instance
+                having shape `(..., M, N)`, the returned array must have shape
+                `(..., N, M))`.  The returned array must have the same data type
+                as the original array.
+
+        """
+        ...
+
+
 class Array(
     # ------ Attributes -------
     HasDType[DTypeT_co],
     HasDevice,
+    HasMatrixTranspose,
     # ------- Methods ---------
     HasArrayNamespace[NamespaceT_co],
     # -------------------------

tests/integration/test_numpy1p0.pyi

@@ -59,3 +59,7 @@ _: dtype[Any] = x_i32.dtype
 # Check Attribute `.device`
 _: object = x_f32.device
 _: object = x_i32.device
+
+# Check Attribute `.mT`
+_: xpt.Array[dtype[Any]] = x_f32.mT
+_: xpt.Array[dtype[Any]] = x_i32.mT

tests/integration/test_numpy2p0.pyi

@@ -66,3 +66,8 @@ _: np.dtype[B] = x_b.dtype
 _: object = x_f32.device
 _: object = x_i32.device
 _: object = x_b.device
+
+# Check Attribute `.mT`
+_: xpt.Array[np.dtype[F32]] = x_f32.mT
+_: xpt.Array[np.dtype[I32]] = x_i32.mT
+_: xpt.Array[np.dtype[B]] = x_b.mT