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Commit75d62a0

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Add an export to convert an onnx graph into light API code (#46)
* Add an export to convert an onnx graph into light API code* fix unit tests* fix annotations* fix documentation* doc
1 parentdd11424 commit75d62a0

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9 files changed

+489
-11
lines changed

9 files changed

+489
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‎CHANGELOGS.rst

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@@ -4,6 +4,7 @@ Change Logs
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0.1.3
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+++++
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*:pr:`46`: adds an export to convert an onnx graph into light API code
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*:pr:`45`: fixes light API for operators with two outputs
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0.1.2

‎README.rst

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@@ -141,4 +141,4 @@ The euclidean distance looks like the following:
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The library is released on
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`pypi/onnx-array-api<https://pypi.org/project/onnx-array-api/>`_
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and its documentation is published at
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`(Numpy) Array API forONNX<https://sdpython.github.io/doc/onnx-array-api/dev/>`_.
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`APIs to createONNX Graphs<https://sdpython.github.io/doc/onnx-array-api/dev/>`_.

‎_doc/api/light_api.rst

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@@ -2,33 +2,67 @@
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onnx_array_api.light_api
33
========================
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Main API
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========
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59
start
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=====
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+++++
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..autofunction::onnx_array_api.light_api.start
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translate
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+++++++++
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..autofunction::onnx_array_api.light_api.translate
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Classes for the Light API
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=========================
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OnnxGraph
11-
=========
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+++++++++
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..autoclass::onnx_array_api.light_api.OnnxGraph
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:members:
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BaseVar
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=======
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+++++++
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..autoclass::onnx_array_api.light_api.var.BaseVar
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:members:
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Var
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===
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+++
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..autoclass::onnx_array_api.light_api.Var
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:members:
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:inherited-members:
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Vars
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====
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++++
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..autoclass::onnx_array_api.light_api.Vars
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:members:
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:inherited-members:
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Classes for the Translater
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==========================
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Emitter
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+++++++
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..autoclass::onnx_array_api.light_api.translate.Emitter
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:members:
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EventType
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+++++++++
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..autoclass::onnx_array_api.light_api.translate.EventType
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:members:
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Translater
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++++++++++
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..autoclass::onnx_array_api.light_api.translate.Translater
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:members:
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‎_doc/index.rst

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@@ -45,7 +45,8 @@ The objective is to speed up the implementation of converter libraries.
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CHANGELOGS
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license
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**Numpy API**
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Numpy API
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+++++++++
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Sources available on
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`github/onnx-array-api<https://github.com/sdpython/onnx-array-api>`_.
@@ -109,7 +110,8 @@ Sources available on
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res = jitted_myloss(x, y)
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print(to_dot(jitted_myloss.get_onnx()))
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112-
**Light API**
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Light API
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+++++++++
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114116
..runpython::
115117
:showcode:
@@ -135,3 +137,9 @@ Sources available on
135137
)
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137139
print(onnx_simple_text_plot(model))
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Older versions
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++++++++++++++
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* `0.1.2<../v0.1.2/index.html>`_
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@@ -0,0 +1,131 @@
1+
importunittest
2+
fromtextwrapimportdedent
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importnumpyasnp
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fromonnximportModelProto,TensorProto
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fromonnx.defsimportonnx_opset_version
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fromonnx.referenceimportReferenceEvaluator
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fromonnx_array_api.ext_test_caseimportExtTestCase
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fromonnx_array_api.light_apiimportstart,translate
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OPSET_API=min(19,onnx_opset_version()-1)
11+
12+
13+
classTestTranslate(ExtTestCase):
14+
deftest_exp(self):
15+
onx=start(opset=19).vin("X").Exp().rename("Y").vout().to_onnx()
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self.assertIsInstance(onx,ModelProto)
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self.assertIn("Exp",str(onx))
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ref=ReferenceEvaluator(onx)
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a=np.arange(10).astype(np.float32)
20+
got=ref.run(None, {"X":a})[0]
21+
self.assertEqualArray(np.exp(a),got)
22+
23+
code=translate(onx)
24+
expected=dedent(
25+
"""
26+
(
27+
start(opset=19)
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.vin('X', elem_type=TensorProto.FLOAT)
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.bring('X')
30+
.Exp()
31+
.rename('Y')
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.bring('Y')
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.vout(elem_type=TensorProto.FLOAT)
34+
.to_onnx()
35+
)"""
36+
).strip("\n")
37+
self.assertEqual(expected,code)
38+
39+
onx2= (
40+
start(opset=19)
41+
.vin("X",elem_type=TensorProto.FLOAT)
42+
.bring("X")
43+
.Exp()
44+
.rename("Y")
45+
.bring("Y")
46+
.vout(elem_type=TensorProto.FLOAT)
47+
.to_onnx()
48+
)
49+
ref=ReferenceEvaluator(onx2)
50+
a=np.arange(10).astype(np.float32)
51+
got=ref.run(None, {"X":a})[0]
52+
self.assertEqualArray(np.exp(a),got)
53+
54+
deftest_transpose(self):
55+
onx= (
56+
start(opset=19)
57+
.vin("X")
58+
.reshape((-1,1))
59+
.Transpose(perm=[1,0])
60+
.rename("Y")
61+
.vout()
62+
.to_onnx()
63+
)
64+
self.assertIsInstance(onx,ModelProto)
65+
self.assertIn("Transpose",str(onx))
66+
ref=ReferenceEvaluator(onx)
67+
a=np.arange(10).astype(np.float32)
68+
got=ref.run(None, {"X":a})[0]
69+
self.assertEqualArray(a.reshape((-1,1)).T,got)
70+
71+
code=translate(onx)
72+
expected=dedent(
73+
"""
74+
(
75+
start(opset=19)
76+
.vin('X', elem_type=TensorProto.FLOAT)
77+
.bring('X', 'r')
78+
.Reshape()
79+
.rename('r0_0')
80+
.bring('r0_0')
81+
.Transpose(perm=[1, 0])
82+
.rename('Y')
83+
.bring('Y')
84+
.vout(elem_type=TensorProto.FLOAT)
85+
.to_onnx()
86+
)"""
87+
).strip("\n")
88+
self.assertEqual(expected,code)
89+
90+
deftest_topk_reverse(self):
91+
onx= (
92+
start(opset=19)
93+
.vin("X",np.float32)
94+
.vin("K",np.int64)
95+
.bring("X","K")
96+
.TopK(largest=0)
97+
.rename("Values","Indices")
98+
.vout()
99+
.to_onnx()
100+
)
101+
self.assertIsInstance(onx,ModelProto)
102+
ref=ReferenceEvaluator(onx)
103+
x=np.array([[0,1,2,3], [9,8,7,6]],dtype=np.float32)
104+
k=np.array([2],dtype=np.int64)
105+
got=ref.run(None, {"X":x,"K":k})
106+
self.assertEqualArray(np.array([[0,1], [6,7]],dtype=np.float32),got[0])
107+
self.assertEqualArray(np.array([[0,1], [3,2]],dtype=np.int64),got[1])
108+
109+
code=translate(onx)
110+
expected=dedent(
111+
"""
112+
(
113+
start(opset=19)
114+
.vin('X', elem_type=TensorProto.FLOAT)
115+
.vin('K', elem_type=TensorProto.INT64)
116+
.bring('X', 'K')
117+
.TopK(axis=-1, largest=0, sorted=1)
118+
.rename('Values', 'Indices')
119+
.bring('Values')
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.vout(elem_type=TensorProto.FLOAT)
121+
.bring('Indices')
122+
.vout(elem_type=TensorProto.FLOAT)
123+
.to_onnx()
124+
)"""
125+
).strip("\n")
126+
self.assertEqual(expected,code)
127+
128+
129+
if__name__=="__main__":
130+
# TestLightApi().test_topk()
131+
unittest.main(verbosity=2)

‎onnx_array_api/light_api/__init__.py

Lines changed: 43 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1,5 +1,7 @@
11
fromtypingimportDict,Optional
2+
fromonnximportModelProto
23
from .modelimportOnnxGraph
4+
from .translateimportTranslater
35
from .varimportVar,Vars
46

57

@@ -34,8 +36,48 @@ def start(
3436
from onnx_array_api.light_api import start
3537
3638
onx = (
37-
start().vin("X").vin("Y").bring("X", "Y").Add().rename("Z").vout().to_onnx()
39+
start()
40+
.vin("X")
41+
.vin("Y")
42+
.bring("X", "Y")
43+
.Add()
44+
.rename("Z")
45+
.vout()
46+
.to_onnx()
3847
)
3948
print(onx)
4049
"""
4150
returnOnnxGraph(opset=opset,opsets=opsets,is_function=is_function)
51+
52+
53+
deftranslate(proto:ModelProto,single_line=False)->str:
54+
"""
55+
Translates an ONNX proto into a code using :ref:`l-light-api`
56+
to describe the ONNX graph.
57+
58+
:param proto: model to translate
59+
:param single_line: as a single line or not
60+
:return: code
61+
62+
.. runpython::
63+
:showcode:
64+
65+
from onnx_array_api.light_api import start, translate
66+
67+
onx = (
68+
start()
69+
.vin("X")
70+
.reshape((-1, 1))
71+
.Transpose(perm=[1, 0])
72+
.rename("Y")
73+
.vout()
74+
.to_onnx()
75+
)
76+
code = translate(onx)
77+
print(code)
78+
"""
79+
tr=Translater(proto)
80+
rows=tr.export()
81+
ifsingle_line:
82+
return".".join(rows)
83+
return"".join(["(\n ","\n .".join(rows),"\n)"])

‎onnx_array_api/light_api/annotations.py

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@@ -12,7 +12,7 @@
1212
ELEMENT_TYPE_NAME= {
1313
getattr(TensorProto,k):k
1414
forkindir(TensorProto)
15-
ifisinstance(getattr(TensorProto,k),int)
15+
ifisinstance(getattr(TensorProto,k),int)and"_"notink
1616
}
1717

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_type_numpy= {

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