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Merged
merged 16 commits into from
Feb 6, 2024
Merged

Add class to yield results form onnx model and computes differences between two runs #71

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6eb6adf
update requirements
xadupre Feb 2, 2024
4f0a994
Merge branch 'main' of https://github.com/sdpython/onnx-array-api
xadupre Feb 2, 2024
c7bb055
Merge branch 'main' of https://github.com/sdpython/onnx-array-api
xadupre Feb 2, 2024
cc7ab30
Merge branch 'main' of https://github.com/sdpython/onnx-array-api int…
xadupre Feb 5, 2024
d520cfa
Add class to yield results
xadupre Feb 5, 2024
d616c58
black
xadupre Feb 5, 2024
fe32241
add sumarry
xadupre Feb 5, 2024
a8c2932
add distance
xadupre Feb 5, 2024
09e79d2
text
xadupre Feb 5, 2024
e1e30dc
compare function
xadupre Feb 5, 2024
12b1031
fix FusedMatMul
xadupre Feb 5, 2024
0986399
fix alpha
xadupre Feb 5, 2024
d1f276b
example
xadupre Feb 5, 2024
42c5e69
documentation
xadupre Feb 5, 2024
e222441
fix length
xadupre Feb 5, 2024
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doc
xadupre Feb 6, 2024
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add distance
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@xadupre
xadupre committed Feb 5, 2024
commit a8c2932e1c65a392fe127b168fa9e3cba27af9c1
1 change: 1 addition & 0 deletions CHANGELOGS.rst
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Expand Up @@ -4,6 +4,7 @@ Change Logs
0.2.0
+++++

* :pr:`71`: adds tools to compare two onnx graphs
* :pr:`61`: adds function to plot onnx model as graphs
* :pr:`60`: supports translation of local functions
* :pr:`59`: add methods to update nodes in GraphAPI
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7 changes: 7 additions & 0 deletions _doc/api/reference.rst
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Expand Up @@ -15,3 +15,10 @@ YieldEvaluator

.. autoclass:: onnx_array_api.reference.YieldEvaluator
:members:

DistanceExecution
+++++++++++++++++

.. autoclass:: onnx_array_api.reference.DistanceExecution
:members:

198 changes: 192 additions & 6 deletions _unittests/ut_reference/test_evaluator_yield.py
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Expand Up @@ -10,7 +10,7 @@
make_tensor_value_info,
)
from onnx_array_api.ext_test_case import ExtTestCase
from onnx_array_api.reference import YieldEvaluator, ResultType
from onnx_array_api.reference import YieldEvaluator, ResultType, DistanceExecution


class TestArrayTensor(ExtTestCase):
Expand Down Expand Up @@ -147,18 +147,19 @@ def test_evaluator_yield_summary(self):
yield_eval.enumerate_summarized(None, {"A": cst, "B": cst, "X": cst})
)
expected = [
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "A"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "B"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "X"),
(
ResultType.RESULT,
np.dtype("float32"),
(2, 2),
"CEIO",
"LinearRegression",
"Y1",
),
(ResultType.RESULT, np.dtype("float32"), (2, 2), "CEIO", "Abs"),
(ResultType.OUTPUT, np.dtype("float32"), (2, 2), "CEIO", None),
(ResultType.RESULT, np.dtype("float32"), (2, 2), "CEIO", "Abs", "Y"),
(ResultType.OUTPUT, np.dtype("float32"), (2, 2), "CEIO", None, "Y"),
]
self.assertEqual(len(expected), len(results))
for a, b in zip(expected, results):
Expand All @@ -168,6 +169,191 @@ def test_evaluator_yield_summary(self):
self.assertEqual(a[2], b[2])
self.assertEqual(a[3], b[3])
self.assertEqual(a[4], b[4])
self.assertEqual(a[5], b[5])

def test_distance_pair(self):
el1 = (ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None)
el2 = el1
dc = DistanceExecution()
self.assertEqual(dc.distance_pair(el1, el2), 0)
el2 = (ResultType.INPUT, np.dtype("float16"), (2, 2), "ABCD", None)
self.assertEqual(dc.distance_pair(el1, el2), 2)
el2 = (ResultType.OUTPUT, np.dtype("float16"), (2, 2, 4), "GBCD", "Abs")
self.assertEqual(dc.distance_pair(el1, el2), 1130)
el2 = (ResultType.OUTPUT, np.dtype("float16"), (2, 3), "GBCD", "Abs")
self.assertEqual(dc.distance_pair(el1, el2), 1021)

def test_distance_sequence_0(self):
expected = [
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "A"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "B"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "X"),
(
ResultType.RESULT,
np.dtype("float32"),
(2, 2),
"CEIO",
"LinearRegression",
"Y1",
),
(ResultType.RESULT, np.dtype("float32"), (2, 2), "CEIO", "Abs", "Y"),
(ResultType.OUTPUT, np.dtype("float32"), (2, 2), "CEIO", None, "Y"),
]

dc = DistanceExecution()
d, align = dc.distance_sequence(expected, expected)
self.assertEqual(d, 0)
self.assertEqual(align, [(0, 0), (1, 1), (2, 2), (3, 3), (4, 4)])

def test_distance_sequence_ins(self):
s1 = [
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "A"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "B"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "X"),
(
ResultType.RESULT,
np.dtype("float32"),
(2, 2),
"CEIO",
"LinearRegression",
"Y1",
),
(ResultType.RESULT, np.dtype("float32"), (2, 2), "CEIO", "Abs", "Y"),
(ResultType.OUTPUT, np.dtype("float32"), (2, 2), "CEIO", None, "Y"),
]
s2 = [
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "A"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "B"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "X"),
(
ResultType.RESULT,
np.dtype("float32"),
(2, 2),
"CEIO",
"LinearRegression",
"Y1",
),
(ResultType.OUTPUT, np.dtype("float32"), (2, 2), "CEIO", None, "Y"),
]

dc = DistanceExecution()
d, align = dc.distance_sequence(s1, s2)
self.assertEqual(d, dc.insert_cost)
self.assertEqual(align, [(0, 0), (1, 1), (2, 2), (3, 3), (4, 3)])
d, align = dc.distance_sequence(s2, s1)
self.assertEqual(d, dc.insert_cost)
self.assertEqual(align, [(0, 0), (1, 1), (2, 2), (3, 3), (3, 4)])

def test_distance_sequence_equal(self):
s1 = [
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "A"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "B"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "X"),
(
ResultType.RESULT,
np.dtype("float32"),
(2, 2),
"CEIO",
"LinearRegression",
"Y1",
),
(ResultType.RESULT, np.dtype("float32"), (2, 2), "CEIO", "Abs", "Y"),
(ResultType.OUTPUT, np.dtype("float32"), (2, 2), "CEIO", None, "Y"),
]
s2 = [
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "A"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "B"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "X"),
(
ResultType.RESULT,
np.dtype("float32"),
(2, 2),
"CEIO",
"LinearRegression",
"Y1",
),
(ResultType.RESULT, np.dtype("float32"), (2, 2), "CEIO", "Abs", "Z"),
(ResultType.OUTPUT, np.dtype("float32"), (2, 2), "CEIO", None, "Y"),
]

dc = DistanceExecution()
d, align = dc.distance_sequence(s1, s2)
self.assertEqual(d, 0)
self.assertEqual(align, [(0, 0), (1, 1), (2, 2), (3, 3), (4, 4)])

def test_distance_sequence_diff(self):
s1 = [
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "A"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "B"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "X"),
(
ResultType.RESULT,
np.dtype("float32"),
(2, 2),
"CEIO",
"LinearRegression",
"Y1",
),
(ResultType.RESULT, np.dtype("float32"), (2, 2), "CEIO", "Abs", "Y"),
(ResultType.OUTPUT, np.dtype("float32"), (2, 2), "CEIO", None, "Y"),
]
s2 = [
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "A"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "B"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "X"),
(
ResultType.RESULT,
np.dtype("float32"),
(2, 2),
"CEIO",
"LinearRegression",
"Y1",
),
(ResultType.RESULT, np.dtype("float32"), (2, 2), "CEIP", "Abs", "Z"),
(ResultType.OUTPUT, np.dtype("float32"), (2, 2), "CEIO", None, "Y"),
]

dc = DistanceExecution()
d, align = dc.distance_sequence(s1, s2)
self.assertEqual(d, 1)
self.assertEqual(align, [(0, 0), (1, 1), (2, 2), (3, 3), (4, 4)])

def test_distance_sequence_diff2(self):
s1 = [
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "A"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "B"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "X"),
(
ResultType.RESULT,
np.dtype("float32"),
(2, 2),
"CEIO",
"LinearRegression",
"Y1",
),
(ResultType.RESULT, np.dtype("float32"), (2, 2), "CEIO", "Abs", "Y"),
(ResultType.OUTPUT, np.dtype("float32"), (2, 2), "CEIO", None, "Y"),
]
s2 = [
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "A"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "B"),
(ResultType.INPUT, np.dtype("float32"), (2, 2), "ABCD", None, "X"),
(
ResultType.RESULT,
np.dtype("float32"),
(2, 2),
"CEIO",
"LinearRegression",
"Y1",
),
(ResultType.RESULT, np.dtype("float32"), (2, 3), "CEIP", "Abs", "Z"),
(ResultType.OUTPUT, np.dtype("float32"), (2, 2), "CEIP", None, "Y"),
]

dc = DistanceExecution()
d, align = dc.distance_sequence(s1, s2)
self.assertEqual(d, 5)
self.assertEqual(align, [(0, 0), (1, 1), (2, 2), (3, 3), (4, 4)])


if __name__ == "__main__":
Expand Down
2 changes: 1 addition & 1 deletion onnx_array_api/reference/__init__.py
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Expand Up @@ -11,7 +11,7 @@
)
from onnx.reference.op_run import to_array_extended
from .evaluator import ExtendedReferenceEvaluator
from .evaluator_yield import YieldEvaluator, ResultType
from .evaluator_yield import DistanceExecution, ResultType, YieldEvaluator


def from_array_extended(tensor: np.array, name: Optional[str] = None) -> TensorProto:
Expand Down
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