Implement tensordot and repeat

ndonnx/__init__.py

@@ -1,4 +1,4 @@
-# Copyright (c) QuantCo 2023-2024
+# Copyright (c) QuantCo 2023-2025
 # SPDX-License-Identifier: BSD-3-Clause
 
 import importlib.metadata
@@ -127,10 +127,12 @@
     trunc,
     matmul,
     matrix_transpose,
+    tensordot,
     concat,
     expand_dims,
     flip,
     permute_dims,
+    repeat,
     reshape,
     roll,
     squeeze,
@@ -263,10 +265,12 @@
     "trunc",
     "matmul",
     "matrix_transpose",
+    "tensordot",
     "concat",
     "expand_dims",
     "flip",
     "permute_dims",
+    "repeat",
     "reshape",
     "roll",
     "squeeze",

ndonnx/_core/_interface.py

@@ -1,4 +1,4 @@
-# Copyright (c) QuantCo 2023-2024
+# Copyright (c) QuantCo 2023-2025
 # SPDX-License-Identifier: BSD-3-Clause
 
 from __future__ import annotations
@@ -205,6 +205,9 @@ def matmul(self, x, y) -> ndx.Array:
     def matrix_transpose(self, x) -> ndx.Array:
         return NotImplemented
 
+    def tensordot(self, x, y) -> ndx.Array:
+        return NotImplemented
+
     # searching.py
 
     def argmax(self, x, axis=None, keepdims=False) -> ndx.Array:
@@ -342,6 +345,9 @@ def permute_dims(self, x, axes) -> ndx.Array:
     def reshape(self, x, shape, *, copy=None) -> ndx.Array:
         return NotImplemented
 
+    def repeat(self, x, repeats, axis=None) -> ndx.Array:
+        return NotImplemented
+
     def roll(self, x, shift, axis) -> ndx.Array:
         return NotImplemented
 

ndonnx/_core/_numericimpl.py

@@ -359,6 +359,10 @@ def matmul(self, x, y):
     def matrix_transpose(self, x) -> ndx.Array:
         return ndx.permute_dims(x, list(range(x.ndim - 2)) + [x.ndim - 1, x.ndim - 2])
 
+    @validate_core
+    def tensordot(self, x, y, axes):
+        return _via_i64_f64(lambda x, y: opx.tensordot(x, y, axes), [x, y])
+
     # searching.py
 
     @validate_core

ndonnx/_core/_shapeimpl.py

@@ -68,6 +68,38 @@ def expand_dims(self, x, axis):
             )
         )
 
+    def repeat(self, x, repeats, axis=None):
+        if axis is None:
+            x = ndx.reshape(x, [-1])
+            axis = 0
+
+        x_shape = ndx.additional.shape(x)
+
+        if isinstance(repeats, int):
+            repeats = ndx.asarray(repeats)
+
+        if repeats.ndim == 0:
+            indices = ndx.broadcast_to(
+                ndx.arange(x_shape[axis], dtype=ndx.int64),
+                ndx.concat(
+                    [ndx.expand_dims(repeats, 0), ndx.expand_dims(x_shape[axis], 0)]
+                ),
+            )
+            indices = ndx.reshape(ndx.matrix_transpose(indices), [-1])
+        elif repeats.ndim == 1:
+            repeats = ndx.broadcast_to(repeats, ndx.reshape(x_shape[axis], [1]))
+            indices = ndx.searchsorted(
+                ndx.cumulative_sum(repeats).astype(ndx.int64),
+                ndx.arange(ndx.sum(repeats), dtype=ndx.int64),
+                side="right",
+            )
+        elif repeats.ndim > 1:
+            raise ValueError(
+                f"'repeats' should be either 0 or 1 dimensional, but is instead {repeats.ndim}-dimensional"
+            )
+
+        return ndx.take(x, indices, axis=axis)
+
     def flip(self, x, axis):
         if x.ndim == 0:
             return x.copy()

ndonnx/_funcs.py

@@ -1,4 +1,4 @@
-# Copyright (c) QuantCo 2023-2024
+# Copyright (c) QuantCo 2023-2025
 # SPDX-License-Identifier: BSD-3-Clause
 
 from __future__ import annotations
@@ -550,6 +550,16 @@ def matrix_transpose(x):
     return _unary(x.dtype._ops.matrix_transpose, x)
 
 
+def tensordot(x, y, /, *, axes=2):
+    if (out := x.dtype._ops.tensordot(x, y, axes)) is not NotImplemented:
+        return out
+    if (out := y.dtype._ops.tensordot(x, y, axes)) is not NotImplemented:
+        return out
+    raise UnsupportedOperationError(
+        f"Unsupported operand type for tensordot: '{x.dtype}' and '{y.dtype}'"
+    )
+
+
 # indexing.py
 
 
@@ -630,6 +640,12 @@ def permute_dims(x, axes):
     )
 
 
+def repeat(x, repeats, /, *, axis=None):
+    if (out := x.dtype._ops.repeat(x, repeats, axis)) is not NotImplemented:
+        return out
+    raise UnsupportedOperationError(f"Unsupported operand type for repeat: '{x.dtype}'")
+
+
 def reshape(x, shape, *, copy=None):
     if (out := x.dtype._ops.reshape(x, shape, copy=copy)) is not NotImplemented:
         return out

ndonnx/_opset_extensions.py

@@ -5,7 +5,7 @@
 
 import builtins
 import typing
-from collections.abc import Mapping
+from collections.abc import Mapping, Sequence
 from typing import TypeVar
 
 import numpy as np
@@ -440,6 +440,49 @@ def matmul(a: _CoreArray, b: _CoreArray) -> _CoreArray:
     return _CoreArray(op.matmul(a.var, b.var))
 
 
+@eager_propagate
+def tensordot(
+    a: _CoreArray, b: _CoreArray, axes: int | tuple[Sequence[int], Sequence[int]] = 2
+) -> _CoreArray:
+    def letter():
+        for i in builtins.range(ord("a"), ord("z") + 1):
+            yield chr(i)
+        raise ValueError(
+            "Exceeded available letters for einsum equation in the implementation of 'tensordot': this means that the number of dimensions of 'a' and 'b' are too large"
+        )
+
+    letter_gen = letter()
+
+    if a.ndim == 0 or b.ndim == 0:
+        return _CoreArray(op.mul(a.var, b.var))
+
+    if isinstance(axes, int):
+        axes = (
+            [-axes + i for i in builtins.range(axes)],
+            [i for i in builtins.range(axes)],
+        )
+
+    axes_a, axes_b = axes
+
+    axes_a = [(ax + a.ndim) if ax < 0 else ax for ax in axes_a]
+    axes_b = [(bx + b.ndim) if bx < 0 else bx for bx in axes_b]
+
+    a_letters = [next(letter_gen) for _ in builtins.range(a.ndim)]
+
+    b_letters = [
+        a_letters[axes_a[axes_b.index(bx)]] if bx in axes_b else next(letter_gen)
+        for bx in builtins.range(b.ndim)
+    ]
+
+    joint_letters = [let for idx, let in enumerate(a_letters) if idx not in axes_a] + [
+        let for idx, let in enumerate(b_letters) if idx not in axes_b
+    ]
+
+    equation = f"{''.join(a_letters)},{''.join(b_letters)}->{''.join(joint_letters)}"
+
+    return _CoreArray(op.einsum([a.var, b.var], equation=equation))
+
+
 @eager_propagate
 def arg_max(
     data: _CoreArray, *, axis: int = 0, keepdims: int = 1, select_last_index: int = 0

skips.txt

@@ -2,3 +2,9 @@
 
 array_api_tests/test_manipulation_functions.py::test_roll
 array_api_tests/test_data_type_functions.py::test_broadcast_arrays
+
+# segmentation fault: https://github.com/onnx/onnx/pull/6570
+array_api_tests/test_manipulation_functions.py::test_repeat
+
+# segmentation fault: due to onnxruntime not handling einsum with dim 0
+array_api_tests/test_linalg.py::test_tensordot

tests/test_core.py

@@ -1045,6 +1045,88 @@ def test_argmaxmin_unsupported_kernels(func, x):
         getattr(ndx, func.__name__)(ndx.asarray(x))
 
 
+@pytest.mark.parametrize(
+    "a, b, axes",
+    [
+        (
+            np.arange(60).reshape(3, 4, 5),
+            np.arange(24).reshape(4, 3, 2),
+            ([1, 0], [0, 1]),
+        ),
+        (np.arange(60).reshape(3, 4, 5), np.arange(60).reshape(4, 5, 3), 2),
+        (np.arange(60).reshape(3, 4, 5), np.arange(60).reshape(4, 5, 3), 0),
+        (np.arange(60).reshape(4, 5, 3), np.arange(60).reshape(4, 5, 3), 3),
+        (np.arange(5).reshape(5), np.arange(5).reshape(5), 1),
+        (np.arange(36).reshape(6, 6), np.arange(36).reshape(6, 6), 1),
+        (np.arange(24).reshape(3, 2, 4), np.arange(24).reshape(4, 2, 3), 1),
+        (np.arange(35).reshape(5, 7), np.arange(35).reshape(7, 5), 1),
+        (np.arange(35).reshape(7, 5), np.arange(35).reshape(7, 5), 2),
+        (np.arange(48).reshape(4, 3, 4), np.arange(48).reshape(4, 4, 3), 0),
+        (
+            np.arange(32).reshape(4, 4, 2),
+            np.arange(32).reshape(2, 4, 4),
+            ([2, 0], [0, 1]),
+        ),
+        (np.arange(30).reshape(3, 10), np.arange(20).reshape(10, 2), ([1], [0])),
+    ],
+)
+def test_tensordot(a, b, axes):
+    np_result = np.tensordot(a, b, axes=axes)
+    ndx_result = ndx.tensordot(ndx.asarray(a), ndx.asarray(b), axes=axes).to_numpy()
+    assert_array_equal(np_result, ndx_result)
+
+
+@pytest.mark.parametrize(
+    "a, b",
+    [
+        (np.arange(60).reshape(3, 4, 5), np.arange(60).reshape(4, 5, 3)),
+    ],
+)
+def test_tensordot_no_axes(a, b):
+    np_result = np.tensordot(a, b)
+    ndx_result = ndx.tensordot(ndx.asarray(a), ndx.asarray(b)).to_numpy()
+    assert_array_equal(np_result, ndx_result)
+
+
+# Current repeat does not work on the upstream arrayapi tests in the case
+# of an empty tensor as https://github.com/onnx/onnx/pull/6570 has not landed in onnx
+@pytest.mark.parametrize(
+    "a, repeats, axis",
+    [
+        (np.arange(60).reshape(3, 4, 5), 3, 0),
+        (np.arange(60).reshape(3, 4, 5), 3, 1),
+        (np.arange(60).reshape(3, 4, 5), 3, 2),
+        (np.arange(60).reshape(3, 4, 5), 3, None),
+        (np.arange(60).reshape(3, 4, 5), np.array(3), 0),
+        (np.arange(60).reshape(3, 4, 5), np.array(3), 1),
+        (np.arange(60).reshape(3, 4, 5), np.array(3), 2),
+        (np.arange(60).reshape(3, 4, 5), np.array(3), None),
+        (np.arange(60).reshape(3, 4, 5), np.arange(3), 0),
+        (np.arange(60).reshape(3, 4, 5), np.arange(4), 1),
+        (np.arange(60).reshape(3, 4, 5), np.arange(5), 2),
+        (np.arange(60).reshape(3, 4, 5), np.arange(60), None),
+    ],
+)
+def test_repeat(a, repeats, axis):
+    np_result = np.repeat(a, repeats, axis=axis)
+    if not isinstance(repeats, int):
+        repeats = ndx.asarray(repeats)
+    ndx_result = ndx.repeat(ndx.asarray(a), repeats, axis=axis).to_numpy()
+    assert_array_equal(np_result, ndx_result)
+
+
+@pytest.mark.parametrize(
+    "a, repeats, axis",
+    [
+        (np.arange(60).reshape(3, 4, 5), np.arange(60).reshape([3, 4, 5]), 0),
+        (np.arange(60).reshape(3, 4, 5), np.arange(60).reshape([3, 20]), None),
+        (np.arange(60).reshape(3, 4, 5), np.arange(60).reshape([2, 3, 2, 5]), None),
+    ],
+)
+def test_repeat_raises(a, repeats, axis):
+    with pytest.raises(ValueError):
+        ndx.repeat(ndx.asarray(a), repeats, axis=axis).to_numpy()
+
 @pytest.mark.parametrize(
     "x, index",
     [

xfails.txt

@@ -63,16 +63,13 @@ array_api_tests/test_has_names.py::test_has_names[linalg-vector_norm]
 array_api_tests/test_has_names.py::test_has_names[linear_algebra-tensordot]
 array_api_tests/test_has_names.py::test_has_names[linear_algebra-vecdot]
 array_api_tests/test_has_names.py::test_has_names[manipulation-moveaxis]
-array_api_tests/test_has_names.py::test_has_names[manipulation-repeat]
 array_api_tests/test_has_names.py::test_has_names[manipulation-tile]
 array_api_tests/test_has_names.py::test_has_names[manipulation-unstack]
 array_api_tests/test_inspection_functions.py::test_array_namespace_info
 array_api_tests/test_inspection_functions.py::test_array_namespace_info_dtypes
 array_api_tests/test_linalg.py::test_matrix_transpose
-array_api_tests/test_linalg.py::test_tensordot
 array_api_tests/test_linalg.py::test_vecdot
 array_api_tests/test_manipulation_functions.py::test_moveaxis
-array_api_tests/test_manipulation_functions.py::test_repeat
 array_api_tests/test_manipulation_functions.py::test_squeeze
 array_api_tests/test_manipulation_functions.py::test_tile
 array_api_tests/test_manipulation_functions.py::test_unstack
@@ -117,9 +114,7 @@ array_api_tests/test_signatures.py::test_func_signature[meshgrid]
 array_api_tests/test_signatures.py::test_func_signature[minimum]
 array_api_tests/test_signatures.py::test_func_signature[moveaxis]
 array_api_tests/test_signatures.py::test_func_signature[real]
-array_api_tests/test_signatures.py::test_func_signature[repeat]
 array_api_tests/test_signatures.py::test_func_signature[signbit]
-array_api_tests/test_signatures.py::test_func_signature[tensordot]
 array_api_tests/test_signatures.py::test_func_signature[tile]
 array_api_tests/test_signatures.py::test_func_signature[unstack]
 array_api_tests/test_signatures.py::test_func_signature[vecdot]