Fix numpy vecdot to apply axis before broadcasting

This is changed in the 2023 version of the spec, and matches the new np.vecdot
gufunc.

array_api_compat/common/_aliases.py

@@ -489,20 +489,17 @@ def tensordot(x1: ndarray,
     return xp.tensordot(x1, x2, axes=axes, **kwargs)
 
 def vecdot(x1: ndarray, x2: ndarray, /, xp, *, axis: int = -1) -> ndarray:
-    ndim = max(x1.ndim, x2.ndim)
-    x1_shape = (1,)*(ndim - x1.ndim) + tuple(x1.shape)
-    x2_shape = (1,)*(ndim - x2.ndim) + tuple(x2.shape)
-    if x1_shape[axis] != x2_shape[axis]:
+    if x1.shape[axis] != x2.shape[axis]:
         raise ValueError("x1 and x2 must have the same size along the given axis")
 
     if hasattr(xp, 'broadcast_tensors'):
         _broadcast = xp.broadcast_tensors
     else:
         _broadcast = xp.broadcast_arrays
 
-    x1_, x2_ = _broadcast(x1, x2)
-    x1_ = xp.moveaxis(x1_, axis, -1)
-    x2_ = xp.moveaxis(x2_, axis, -1)
+    x1_ = xp.moveaxis(x1, axis, -1)
+    x2_ = xp.moveaxis(x2, axis, -1)
+    x1_, x2_ = _broadcast(x1_, x2_)
 
     res = x1_[..., None, :] @ x2_[..., None]
     return res[..., 0, 0]