Bring vecdot implementation in line with the one in array-api-compat (#…

…402)

cubed/array_api/linear_algebra_functions.py

@@ -3,7 +3,11 @@
 
 from cubed.array_api.data_type_functions import result_type
 from cubed.array_api.dtypes import _numeric_dtypes
-from cubed.array_api.manipulation_functions import expand_dims
+from cubed.array_api.manipulation_functions import (
+    broadcast_arrays,
+    expand_dims,
+    moveaxis,
+)
 from cubed.backend_array_api import namespace as nxp
 from cubed.core import blockwise, reduction, squeeze
 
@@ -158,12 +162,21 @@ def _tensordot(a, b, axes):
 
 
 def vecdot(x1, x2, /, *, axis=-1, use_new_impl=True, split_every=None):
+    # based on the implementation in array-api-compat
     if x1.dtype not in _numeric_dtypes or x2.dtype not in _numeric_dtypes:
         raise TypeError("Only numeric dtypes are allowed in vecdot")
-    return tensordot(
-        x1,
-        x2,
-        axes=((axis,), (axis,)),
+
+    if x1.shape[axis] != x2.shape[axis]:
+        raise ValueError("x1 and x2 must have the same size along the given axis")
+
+    x1_ = moveaxis(x1, axis, -1)
+    x2_ = moveaxis(x2, axis, -1)
+    x1_, x2_ = broadcast_arrays(x1_, x2_)
+
+    res = matmul(
+        x1_[..., None, :],
+        x2_[..., None],
         use_new_impl=use_new_impl,
         split_every=split_every,
     )
+    return res[..., 0, 0]