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Implements ArrayAPI#17

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Merged
sdpython merged 27 commits intomainfromaapi2
Jun 10, 2023
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945749c
rename ArrayApi into BaseArrayApi
xadupreJun 5, 2023
38c3c0e
Implements ArrayAPI
xadupreJun 5, 2023
178185f
Merge branch 'main' of https://github.com/sdpython/onnx-array-api int…
xadupreJun 5, 2023
f0d4eba
documentation
xadupreJun 5, 2023
0ffa4b4
ci
xadupreJun 5, 2023
293c570
fix ci
xadupreJun 5, 2023
caf2324
xi
xadupreJun 5, 2023
768eb85
ci
xadupreJun 5, 2023
692774e
ci
xadupreJun 5, 2023
5c7dae1
ci
xadupreJun 5, 2023
1a1cd35
ci
xadupreJun 5, 2023
da3a7c8
many changes to follow the Array API
xadupreJun 5, 2023
c600890
more changes
xadupreJun 5, 2023
535cc4a
fix unit test
xadupreJun 5, 2023
5a07911
fix ci
xadupreJun 5, 2023
3481d27
ci
xadupreJun 5, 2023
1990fe8
api
xadupreJun 5, 2023
e0ca8c4
ci
xadupreJun 5, 2023
1e218b5
improvments
xadupreJun 5, 2023
e344011
refactorign
xadupreJun 6, 2023
178e3e9
fix asarray
xadupreJun 6, 2023
550d0dc
new udpates
sdpythonJun 8, 2023
0169b85
fix two bugs
xadupreJun 8, 2023
cb11e55
Add one unit test for empty input
xadupreJun 9, 2023
caa99a7
fix all when shape is empty and has one dimension
xadupreJun 10, 2023
8945d16
fix missing return
xadupreJun 10, 2023
7a979a2
remove the full tests
xadupreJun 10, 2023
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3 changes: 2 additions & 1 deletionCHANGELOGS.rst
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Expand Up@@ -4,4 +4,5 @@ Change Logs
0.2.0
+++++

* :pr:`3`: fixes Array API with onnxruntime
* :pr:`17`: implements ArrayAPI
* :pr:`3`: fixes Array API with onnxruntime and scikit-learn
7 changes: 7 additions & 0 deletions_doc/api/array_api.rst
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@@ -0,0 +1,7 @@
onnx_array_api.array_api
========================

.. toctree::

array_api_onnx_numpy
array_api_onnx_ort
5 changes: 5 additions & 0 deletions_doc/api/array_api_numpy.rst
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onnx_array_api.array_api.onnx_numpy
=============================================

.. automodule:: onnx_array_api.array_api.onnx_numpy
:members:
5 changes: 5 additions & 0 deletions_doc/api/array_api_ort.rst
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onnx_array_api.array_api.onnx_ort
=================================

.. automodule:: onnx_array_api.array_api.onnx_ort
:members:
1 change: 1 addition & 0 deletions_doc/api/index.rst
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Expand Up@@ -6,6 +6,7 @@ API
.. toctree::
:maxdepth: 1

array_api
npx_functions
npx_var
npx_jit
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29 changes: 27 additions & 2 deletions_doc/api/npx_annot.rst
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@@ -1,29 +1,54 @@
=============
npx.npx_types
=============

DType
=====

.. autoclass:: onnx_array_api.npx.npx_types.DType
:members:

Annotations
+++++++++++
===========

ElemType
++++++++

.. autoclass:: onnx_array_api.npx.npx_types.ElemType
:members:

ParType
+++++++

.. autoclass:: onnx_array_api.npx.npx_types.ParType
:members:

OptParType
++++++++++

.. autoclass:: onnx_array_api.npx.npx_types.OptParType
:members:

TensorType
++++++++++

.. autoclass:: onnx_array_api.npx.npx_types.TensorType
:members:

SequenceType
++++++++++++

.. autoclass:: onnx_array_api.npx.npx_types.SequenceType
:members:

TupleType
+++++++++

.. autoclass:: onnx_array_api.npx.npx_types.TupleType
:members:

Shortcuts
+++++++++
=========

.. autoclass:: onnx_array_api.npx.npx_types.Bool

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2 changes: 2 additions & 0 deletions_unittests/test_array_api.sh
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@@ -0,0 +1,2 @@
export ARRAY_API_TESTS_MODULE=onnx_array_api.array_api.onnx_numpy
pytest ../array-api-tests/array_api_tests/test_creation_functions.py::test_zeros
20 changes: 20 additions & 0 deletions_unittests/ut_array_api/test_onnx_numpy.py
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import unittest
import numpy as np
from onnx_array_api.ext_test_case import ExtTestCase
from onnx_array_api.array_api import onnx_numpy as xp
from onnx_array_api.npx.npx_numpy_tensors import EagerNumpyTensor


class TestOnnxNumpy(ExtTestCase):
def test_abs(self):
c = EagerNumpyTensor(np.array([4, 5], dtype=np.int64))
mat = xp.zeros(c, dtype=xp.int64)
matnp = mat.numpy()
self.assertEqual(matnp.shape, (4, 5))
self.assertNotEmpty(matnp[0, 0])
a = xp.absolute(mat)
self.assertEqualArray(np.absolute(mat.numpy()), a.numpy())


if __name__ == "__main__":
unittest.main(verbosity=2)
93 changes: 88 additions & 5 deletions_unittests/ut_npx/test_npx.py
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Expand Up@@ -29,6 +29,7 @@
npxapi_inline,
)
from onnx_array_api.npx.npx_functions import absolute as absolute_inline
from onnx_array_api.npx.npx_functions import all as all_inline
from onnx_array_api.npx.npx_functions import arange as arange_inline
from onnx_array_api.npx.npx_functions import arccos as arccos_inline
from onnx_array_api.npx.npx_functions import arccosh as arccosh_inline
Expand All@@ -50,6 +51,7 @@
from onnx_array_api.npx.npx_functions import det as det_inline
from onnx_array_api.npx.npx_functions import dot as dot_inline
from onnx_array_api.npx.npx_functions import einsum as einsum_inline
from onnx_array_api.npx.npx_functions import equal as equal_inline
from onnx_array_api.npx.npx_functions import erf as erf_inline
from onnx_array_api.npx.npx_functions import exp as exp_inline
from onnx_array_api.npx.npx_functions import expand_dims as expand_dims_inline
Expand DownExpand Up@@ -95,6 +97,7 @@
from onnx_array_api.npx.npx_numpy_tensors import EagerNumpyTensor
from onnx_array_api.npx.npx_types import (
Bool,
DType,
Float32,
Float64,
Int64,
Expand DownExpand Up@@ -127,18 +130,25 @@ def test_tensor(self):
self.assertEqual(dt.dtypes[0].dtype, ElemType.float32)
self.assertEmpty(dt.shape)
self.assertEqual(dt.type_name(), "TensorType['float32']")

dt = TensorType["float32"]
self.assertEqual(len(dt.dtypes), 1)
self.assertEqual(dt.dtypes[0].dtype, ElemType.float32)
self.assertEqual(dt.type_name(), "TensorType['float32']")

dt = TensorType[np.float32]
self.assertEqual(len(dt.dtypes), 1)
self.assertEqual(dt.dtypes[0].dtype, ElemType.float32)
self.assertEqual(dt.type_name(), "TensorType['float32']")
self.assertEmpty(dt.shape)

dt = TensorType[np.str_]
self.assertEqual(len(dt.dtypes), 1)
self.assertEqual(dt.dtypes[0].dtype, ElemType.str_)
self.assertEqual(dt.type_name(), "TensorType[strings]")
self.assertEmpty(dt.shape)

self.assertRaise(lambda: TensorType[None], TypeError)
self.assertRaise(lambda: TensorType[np.str_], TypeError)
self.assertRaise(lambda: TensorType[{np.float32, np.str_}], TypeError)

def test_superset(self):
Expand DownExpand Up@@ -1155,6 +1165,16 @@ def test_astype(self):
got = ref.run(None, {"A": x})
self.assertEqualArray(z, got[0])

def test_astype_dtype(self):
f = absolute_inline(copy_inline(Input("A")).astype(DType(7)))
self.assertIsInstance(f, Var)
onx = f.to_onnx(constraints={"A": Float64[None]})
x = np.array([[-5.4, 6.6]], dtype=np.float64)
z = np.abs(x.astype(np.int64))
ref = ReferenceEvaluator(onx)
got = ref.run(None, {"A": x})
self.assertEqualArray(z, got[0])

def test_astype_int(self):
f = absolute_inline(copy_inline(Input("A")).astype(1))
self.assertIsInstance(f, Var)
Expand DownExpand Up@@ -1413,6 +1433,9 @@ def test_einsum(self):
lambda x, y: np.einsum(equation, x, y),
)

def test_equal(self):
self.common_test_inline_bin(equal_inline, np.equal)

@unittest.skipIf(scipy is None, reason="scipy is not installed.")
def test_erf(self):
self.common_test_inline(erf_inline, scipy.special.erf)
Expand DownExpand Up@@ -1460,7 +1483,17 @@ def test_hstack(self):
def test_identity(self):
f = identity_inline(2, dtype=np.float64)
onx = f.to_onnx(constraints={(0, False): Float64[None]})
z = np.identity(2)
self.assertIn('name: "dtype"', str(onx))
z = np.identity(2).astype(np.float64)
ref = ReferenceEvaluator(onx)
got = ref.run(None, {})
self.assertEqualArray(z, got[0])

def test_identity_uint8(self):
f = identity_inline(2, dtype=np.uint8)
onx = f.to_onnx(constraints={(0, False): Float64[None]})
self.assertIn('name: "dtype"', str(onx))
z = np.identity(2).astype(np.uint8)
ref = ReferenceEvaluator(onx)
got = ref.run(None, {})
self.assertEqualArray(z, got[0])
Expand DownExpand Up@@ -2318,7 +2351,7 @@ def compute_labels(X, centers):
self.assertEqual(f.n_versions, 1)
self.assertEqual(len(f.available_versions), 1)
self.assertEqual(f.available_versions, [((np.float64, 2), (np.float64, 2))])
key = ((np.dtype("float64"), 2), (np.dtype("float64"), 2))
key = ((DType(TensorProto.DOUBLE), 2), (DType(TensorProto.DOUBLE), 2))
onx = f.get_onnx(key)
self.assertIsInstance(onx, ModelProto)
self.assertRaise(lambda: f.get_onnx(2), ValueError)
Expand DownExpand Up@@ -2379,7 +2412,12 @@ def compute_labels(X, centers, use_sqrt=False):
self.assertEqualArray(got[1], dist)
self.assertEqual(f.n_versions, 1)
self.assertEqual(len(f.available_versions), 1)
key = ((np.dtype("float64"), 2), (np.dtype("float64"), 2), "use_sqrt", True)
key = (
(DType(TensorProto.DOUBLE), 2),
(DType(TensorProto.DOUBLE), 2),
"use_sqrt",
True,
)
self.assertEqual(f.available_versions, [key])
onx = f.get_onnx(key)
self.assertIsInstance(onx, ModelProto)
Expand DownExpand Up@@ -2452,7 +2490,52 @@ def test_take(self):
got = ref.run(None, {"A": data, "B": indices})
self.assertEqualArray(y, got[0])

def test_numpy_all(self):
data = np.array([[1, 0], [1, 1]]).astype(np.bool_)
y = np.all(data, axis=1)

f = all_inline(Input("A"), axis=1)
self.assertIsInstance(f, Var)
onx = f.to_onnx(constraints={"A": Bool[None]})
ref = ReferenceEvaluator(onx)
got = ref.run(None, {"A": data})
self.assertEqualArray(y, got[0])

def test_numpy_all_empty(self):
data = np.zeros((0,), dtype=np.bool_)
y = np.all(data)

f = all_inline(Input("A"))
self.assertIsInstance(f, Var)
onx = f.to_onnx(constraints={"A": Bool[None]})
ref = ReferenceEvaluator(onx)
got = ref.run(None, {"A": data})
self.assertEqualArray(y, got[0])

@unittest.skipIf(True, reason="ReduceMin does not support shape[axis] == 0")
def test_numpy_all_empty_axis_0(self):
data = np.zeros((0, 1), dtype=np.bool_)
y = np.all(data, axis=0)

f = all_inline(Input("A"), axis=0)
self.assertIsInstance(f, Var)
onx = f.to_onnx(constraints={"A": Bool[None]})
ref = ReferenceEvaluator(onx)
got = ref.run(None, {"A": data})
self.assertEqualArray(y, got[0])

def test_numpy_all_empty_axis_1(self):
data = np.zeros((0, 1), dtype=np.bool_)
y = np.all(data, axis=1)

f = all_inline(Input("A"), axis=1)
self.assertIsInstance(f, Var)
onx = f.to_onnx(constraints={"A": Bool[None]})
ref = ReferenceEvaluator(onx)
got = ref.run(None, {"A": data})
self.assertEqualArray(y, got[0])


if __name__ == "__main__":
TestNpx().test_take()
#TestNpx().test_numpy_all_empty_axis_0()
unittest.main(verbosity=2)
5 changes: 4 additions & 1 deletion_unittests/ut_npx/test_sklearn_array_api.py
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Expand Up@@ -4,7 +4,7 @@
from onnx.defs import onnx_opset_version
from sklearn import config_context, __version__ as sklearn_version
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from onnx_array_api.ext_test_case import ExtTestCase
from onnx_array_api.ext_test_case import ExtTestCase, ignore_warnings
from onnx_array_api.npx.npx_numpy_tensors import EagerNumpyTensor


Expand All@@ -16,6 +16,7 @@ class TestSklearnArrayAPI(ExtTestCase):
Version(sklearn_version) <= Version("1.2.2"),
reason="reshape ArrayAPI not followed",
)
@ignore_warnings(DeprecationWarning)
def test_sklearn_array_api_linear_discriminant(self):
X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
y = np.array([1, 1, 1, 2, 2, 2])
Expand All@@ -26,6 +27,8 @@ def test_sklearn_array_api_linear_discriminant(self):
new_x = EagerNumpyTensor(X)
self.assertStartsWith("EagerNumpyTensor(array([[", repr(new_x))
with config_context(array_api_dispatch=True):
# It fails if scikit-learn <= 1.2.2 because the ArrayAPI
# is not strictly applied.
got = ana.predict(new_x)
self.assertEqualArray(expected, got.numpy())

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