Clarify axes keyword in tensordot function

CHANGELOG.md

@@ -44,6 +44,7 @@ Also, that release drops support for Python 3.9, making Python 3.10 the minimum
 * Compile indexing extension with `-fno-sycl-id-queries-fit-in-int` to support huge arrays [#2721](https://github.com/IntelPython/dpnp/pull/2721)
 * Updated `dpnp.fix` to reuse `dpnp.trunc` internally [#2722](https://github.com/IntelPython/dpnp/pull/2722)
 * Changed the build scripts and documentation due to `python setup.py develop` deprecation notice [#2716](https://github.com/IntelPython/dpnp/pull/2716)
+* Clarified behavior on repeated `axes` in `dpnp.tensordot` and `dpnp.linalg.tensordot` functions [#2733](https://github.com/IntelPython/dpnp/pull/2733)
 
 ### Deprecated
 

dpnp/dpnp_iface_linearalgebra.py

@@ -1121,7 +1121,7 @@ def outer(a, b, out=None):
     return result
 
 
-def tensordot(a, b, axes=2):
+def tensordot(a, b, /, *, axes=2):
     r"""
     Compute tensor dot product along specified axes.
 
@@ -1148,7 +1148,10 @@ def tensordot(a, b, axes=2):
           axes must match.
         * (2,) array_like: A list of axes to be summed over, first sequence
           applying to `a`, second to `b`. Both elements array_like must be of
-          the same length.
+          the same length. Each axis may appear at most once; repeated axes are
+          not allowed.
+
+        Default: ``2``.
 
     Returns
     -------
@@ -1178,6 +1181,13 @@ def tensordot(a, b, axes=2):
     two sequences of the same length, with the first axis to sum over given
     first in both sequences, the second axis second, and so forth.
 
+    For example, if ``a.shape == (2, 3, 4)`` and ``b.shape == (3, 4, 5)``, then
+    ``axes=([1, 2], [0, 1])`` sums over the ``(3, 4)`` dimensions of both
+    arrays and produces an output of shape ``(2, 5)``.
+
+    Each summation axis corresponds to a distinct contraction index; repeating
+    an axis (for example ``axes=([1, 1], [0, 0])``) is invalid.
+
     The shape of the result consists of the non-contracted axes of the
     first tensor, followed by the non-contracted axes of the second.
 

dpnp/linalg/dpnp_iface_linalg.py

@@ -1975,9 +1975,10 @@ def tensordot(a, b, /, *, axes=2):
           axes must match.
         * (2,) array_like: A list of axes to be summed over, first sequence
           applying to `a`, second to `b`. Both elements array_like must be of
-          the same length.
+          the same length. Each axis may appear at most once; repeated axes are
+          not allowed.
 
-          Default: ``2``.
+        Default: ``2``.
 
     Returns
     -------
@@ -2007,6 +2008,13 @@ def tensordot(a, b, /, *, axes=2):
     two sequences of the same length, with the first axis to sum over given
     first in both sequences, the second axis second, and so forth.
 
+    For example, if ``a.shape == (2, 3, 4)`` and ``b.shape == (3, 4, 5)``, then
+    ``axes=([1, 2], [0, 1])`` sums over the ``(3, 4)`` dimensions of both
+    arrays and produces an output of shape ``(2, 5)``.
+
+    Each summation axis corresponds to a distinct contraction index; repeating
+    an axis (for example ``axes=([1, 1], [0, 0])``) is invalid.
+
     The shape of the result consists of the non-contracted axes of the
     first tensor, followed by the non-contracted axes of the second.
 

dpnp/tests/test_product.py

@@ -1842,6 +1842,13 @@ def test_error(self):
         with pytest.raises(ValueError):
             dpnp.tensordot(dpnp.arange(4), dpnp.array(5), axes=-1)
 
+    @pytest.mark.parametrize("xp", [numpy, dpnp])
+    def test_repeated_axes(self, xp):
+        a = xp.ones((2, 3, 3))
+        b = xp.ones((3, 3, 4))
+        with pytest.raises(ValueError):
+            xp.tensordot(a, b, axes=([1, 1], [0, 0]))
+
 
 class TestVdot:
     @pytest.mark.parametrize("dtype", get_all_dtypes(no_none=True))