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Commit8b54ad1

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Supports other domain for light API (#54)
* ut* first sketch* finalize other domain epxressions* docuemntation* extend the support of translate to other domain* documentation
1 parent06a15a9 commit8b54ad1

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12 files changed

+333
-10
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12 files changed

+333
-10
lines changed

‎_doc/api/light_api.rst

Lines changed: 17 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -19,10 +19,15 @@ translate
1919
Classes for the Light API
2020
=========================
2121

22-
ProtoType
23-
+++++++++
22+
domain
23+
++++++
2424

25-
..autoclass::onnx_array_api.light_api.model.ProtoType
25+
..autofunction:: onnx_array_api.light_api.domain
26+
27+
BaseVar
28+
+++++++
29+
30+
..autoclass::onnx_array_api.light_api.var.BaseVar
2631
:members:
2732

2833
OnnxGraph
@@ -31,10 +36,16 @@ OnnxGraph
3136
..autoclass::onnx_array_api.light_api.OnnxGraph
3237
:members:
3338

34-
BaseVar
35-
+++++++
39+
ProtoType
40+
+++++++++
3641

37-
..autoclass::onnx_array_api.light_api.var.BaseVar
42+
..autoclass::onnx_array_api.light_api.model.ProtoType
43+
:members:
44+
45+
SubDomain
46+
+++++++++
47+
48+
..autoclass::onnx_array_api.light_api.var.SubDomain
3849
:members:
3950

4051
Var

‎_doc/tutorial/light_api.rst

Lines changed: 29 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -76,3 +76,32 @@ operator `+` to be available as well and that the case. They are
7676
defined in class:class:`Var <onnx_array_api.light_api.Var>` or
7777
:class:`Vars <onnx_array_api.light_api.Vars>` depending on the number of
7878
inputs they require. Their name starts with a lower letter.
79+
80+
Other domains
81+
=============
82+
83+
The following example uses operator *Normalizer* from domain
84+
*ai.onnx.ml*. The operator name is called with the syntax
85+
`<domain>.<operator name>`. The domain may have dots in its name
86+
but it must follow the python definition of a variable.
87+
The operator *Normalizer* becomes `ai.onnx.ml.Normalizer`.
88+
89+
..runpython::
90+
:showcode:
91+
92+
import numpy as np
93+
from onnx_array_api.light_api import start
94+
from onnx_array_api.plotting.text_plot import onnx_simple_text_plot
95+
96+
model = (
97+
start(opset=19, opsets={"ai.onnx.ml": 3})
98+
.vin("X")
99+
.reshape((-1, 1))
100+
.rename("USE")
101+
.ai.onnx.ml.Normalizer(norm="MAX")
102+
.rename("Y")
103+
.vout()
104+
.to_onnx()
105+
)
106+
107+
print(onnx_simple_text_plot(model))

‎_unittests/ut_light_api/test_light_api.py

Lines changed: 39 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1,3 +1,4 @@
1+
importinspect
12
importunittest
23
fromtypingimportCallable,Optional
34
importnumpyasnp
@@ -12,6 +13,7 @@
1213
fromonnx.referenceimportReferenceEvaluator
1314
fromonnx_array_api.ext_test_caseimportExtTestCase,skipif_ci_windows
1415
fromonnx_array_api.light_apiimportstart,OnnxGraph,Var,g
16+
fromonnx_array_api.light_api.varimportSubDomain
1517
fromonnx_array_api.light_api._op_varimportOpsVar
1618
fromonnx_array_api.light_api._op_varsimportOpsVars
1719

@@ -472,7 +474,43 @@ def test_if(self):
472474
got=ref.run(None, {"X":-x})
473475
self.assertEqualArray(np.array([0],dtype=np.int64),got[0])
474476

477+
deftest_domain(self):
478+
onx=start(opsets={"ai.onnx.ml":3}).vin("X").reshape((-1,1)).rename("USE")
479+
480+
classA:
481+
defg(self):
482+
returnTrue
483+
484+
defah(self):
485+
returnTrue
486+
487+
setattr(A,"h",ah)
488+
489+
self.assertTrue(A().h())
490+
self.assertIn("(self)",str(inspect.signature(A.h)))
491+
self.assertTrue(issubclass(onx._ai,SubDomain))
492+
self.assertIsInstance(onx.ai,SubDomain)
493+
self.assertIsInstance(onx.ai.parent,Var)
494+
self.assertTrue(issubclass(onx._ai._onnx,SubDomain))
495+
self.assertIsInstance(onx.ai.onnx,SubDomain)
496+
self.assertIsInstance(onx.ai.onnx.parent,Var)
497+
self.assertTrue(issubclass(onx._ai._onnx._ml,SubDomain))
498+
self.assertIsInstance(onx.ai.onnx.ml,SubDomain)
499+
self.assertIsInstance(onx.ai.onnx.ml.parent,Var)
500+
self.assertIn("(self,",str(inspect.signature(onx._ai._onnx._ml.Normalizer)))
501+
onx=onx.ai.onnx.ml.Normalizer(norm="MAX")
502+
onx=onx.rename("Y").vout().to_onnx()
503+
self.assertIsInstance(onx,ModelProto)
504+
self.assertIn("Normalizer",str(onx))
505+
self.assertIn('domain: "ai.onnx.ml"',str(onx))
506+
self.assertIn('input: "USE"',str(onx))
507+
ref=ReferenceEvaluator(onx)
508+
a=np.arange(10).astype(np.float32)
509+
got=ref.run(None, {"X":a})[0]
510+
expected= (a>0).astype(int).astype(np.float32).reshape((-1,1))
511+
self.assertEqualArray(expected,got)
512+
475513

476514
if__name__=="__main__":
477-
TestLightApi().test_if()
515+
TestLightApi().test_domain()
478516
unittest.main(verbosity=2)

‎_unittests/ut_light_api/test_translate.py

Lines changed: 33 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -185,6 +185,39 @@ def test_export_if(self):
185185
self.maxDiff=None
186186
self.assertEqual(expected,code)
187187

188+
deftest_aionnxml(self):
189+
onx= (
190+
start(opset=19,opsets={"ai.onnx.ml":3})
191+
.vin("X")
192+
.reshape((-1,1))
193+
.rename("USE")
194+
.ai.onnx.ml.Normalizer(norm="MAX")
195+
.rename("Y")
196+
.vout()
197+
.to_onnx()
198+
)
199+
code=translate(onx)
200+
expected=dedent(
201+
"""
202+
(
203+
start(opset=19, opsets={'ai.onnx.ml': 3})
204+
.cst(np.array([-1, 1], dtype=np.int64))
205+
.rename('r')
206+
.vin('X', elem_type=TensorProto.FLOAT)
207+
.bring('X', 'r')
208+
.Reshape()
209+
.rename('USE')
210+
.bring('USE')
211+
.ai.onnx.ml.Normalizer(norm='MAX')
212+
.rename('Y')
213+
.bring('Y')
214+
.vout(elem_type=TensorProto.FLOAT)
215+
.to_onnx()
216+
)"""
217+
).strip("\n")
218+
self.maxDiff=None
219+
self.assertEqual(expected,code)
220+
188221

189222
if__name__=="__main__":
190223
TestTranslate().test_export_if()

‎_unittests/ut_light_api/test_translate_classic.py

Lines changed: 66 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -252,6 +252,72 @@ def test_fft(self):
252252
)
253253
raiseAssertionError(f"ERROR{e}\n{new_code}")
254254

255+
deftest_aionnxml(self):
256+
onx= (
257+
start(opset=19,opsets={"ai.onnx.ml":3})
258+
.vin("X")
259+
.reshape((-1,1))
260+
.rename("USE")
261+
.ai.onnx.ml.Normalizer(norm="MAX")
262+
.rename("Y")
263+
.vout()
264+
.to_onnx()
265+
)
266+
code=translate(onx,api="onnx")
267+
print(code)
268+
expected=dedent(
269+
"""
270+
opset_imports = [
271+
make_opsetid('', 19),
272+
make_opsetid('ai.onnx.ml', 3),
273+
]
274+
inputs = []
275+
outputs = []
276+
nodes = []
277+
initializers = []
278+
sparse_initializers = []
279+
functions = []
280+
initializers.append(
281+
from_array(
282+
np.array([-1, 1], dtype=np.int64),
283+
name='r'
284+
)
285+
)
286+
inputs.append(make_tensor_value_info('X', TensorProto.FLOAT, shape=[]))
287+
nodes.append(
288+
make_node(
289+
'Reshape',
290+
['X', 'r'],
291+
['USE']
292+
)
293+
)
294+
nodes.append(
295+
make_node(
296+
'Normalizer',
297+
['USE'],
298+
['Y'],
299+
domain='ai.onnx.ml',
300+
norm='MAX'
301+
)
302+
)
303+
outputs.append(make_tensor_value_info('Y', TensorProto.FLOAT, shape=[]))
304+
graph = make_graph(
305+
nodes,
306+
'light_api',
307+
inputs,
308+
outputs,
309+
initializers,
310+
sparse_initializer=sparse_initializers,
311+
)
312+
model = make_model(
313+
graph,
314+
functions=functions,
315+
opset_imports=opset_imports
316+
)"""
317+
).strip("\n")
318+
self.maxDiff=None
319+
self.assertEqual(expected,code)
320+
255321

256322
if__name__=="__main__":
257323
# TestLightApi().test_topk()

‎onnx_array_api/light_api/__init__.py

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -1,5 +1,6 @@
11
fromtypingimportDict,Optional
22
fromonnximportModelProto
3+
from .annotationsimportdomain
34
from .modelimportOnnxGraph,ProtoType
45
from .translateimportTranslater
56
from .varimportVar,Vars

‎onnx_array_api/light_api/_op_var.py

Lines changed: 5 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,5 @@
11
fromtypingimportList,Optional,Union
2+
from .annotationsimportAI_ONNX_ML,domain
23

34

45
classOpsVar:
@@ -319,6 +320,10 @@ def Transpose(self, perm: Optional[List[int]] = None) -> "Var":
319320
perm=permor []
320321
returnself.make_node("Transpose",self,perm=perm)
321322

323+
@domain(AI_ONNX_ML)
324+
defNormalizer(self,norm:str="MAX"):
325+
returnself.make_node("Normalizer",self,norm=norm,domain=AI_ONNX_ML)
326+
322327

323328
def_complete():
324329
ops_to_add= [

‎onnx_array_api/light_api/annotations.py

Lines changed: 36 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
1-
fromtypingimportTuple,Union
1+
fromtypingimportAny,Callable,Dict,List,Optional,Tuple,Union
22
importnumpyasnp
33
fromonnximportFunctionProto,GraphProto,ModelProto,TensorProto,TensorShapeProto
44
fromonnx.helperimportnp_dtype_to_tensor_dtype
@@ -9,12 +9,47 @@
99
VAR_CONSTANT_TYPE=Union["Var",TensorProto,np.ndarray]
1010
GRAPH_PROTO=Union[FunctionProto,GraphProto,ModelProto]
1111

12+
AI_ONNX_ML="ai.onnx.ml"
13+
1214
ELEMENT_TYPE_NAME= {
1315
getattr(TensorProto,k):k
1416
forkindir(TensorProto)
1517
ifisinstance(getattr(TensorProto,k),int)and"_"notink
1618
}
1719

20+
21+
classSubDomain:
22+
pass
23+
24+
25+
defdomain(domain:str,op_type:Optional[str]=None)->Callable:
26+
"""
27+
Registers one operator into a sub domain. It should be used as a
28+
decorator. One example:
29+
30+
.. code-block:: python
31+
32+
@domain("ai.onnx.ml")
33+
def Normalizer(self, norm: str = "MAX"):
34+
return self.make_node("Normalizer", self, norm=norm, domain="ai.onnx.ml")
35+
"""
36+
names= [op_type]
37+
38+
defdecorate(op_method:Callable)->Callable:
39+
ifnames[0]isNone:
40+
names[0]=op_method.__name__
41+
42+
defwrapper(self,*args:List[Any],**kwargs:Dict[str,Any])->Any:
43+
returnop_method(self.parent,*args,**kwargs)
44+
45+
wrapper.__qual__name__=f"[{domain}]{names[0]}"
46+
wrapper.__name__=f"[{domain}]{names[0]}"
47+
wrapper.__domain__=domain
48+
returnwrapper
49+
50+
returndecorate
51+
52+
1853
_type_numpy= {
1954
np.float32:TensorProto.FLOAT,
2055
np.float64:TensorProto.DOUBLE,

‎onnx_array_api/light_api/emitter.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -241,7 +241,7 @@ def _emit_node(self, **kwargs: Dict[str, Any]) -> List[str]:
241241
outputs=kwargs["outputs"]
242242
ifkwargs.get("domain","")!="":
243243
domain=kwargs["domain"]
244-
raiseNotImplementedError(f"domain={domain!r} not supported yet.")
244+
op_type=f"{domain}.{op_type}"
245245
atts=kwargs.get("atts", {})
246246
args= []
247247
fork,vinatts.items():

‎onnx_array_api/light_api/inner_emitter.py

Lines changed: 0 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -120,7 +120,6 @@ def _emit_node(self, **kwargs: Dict[str, Any]) -> List[str]:
120120
outputs=kwargs["outputs"]
121121
ifkwargs.get("domain","")!="":
122122
domain=kwargs["domain"]
123-
raiseNotImplementedError(f"domain={domain!r} not supported yet.")
124123

125124
before_lines= []
126125
lines= [

‎onnx_array_api/light_api/model.py

Lines changed: 3 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -248,6 +248,9 @@ def make_node(
248248

249249
node=make_node(op_type,input_names,output_names,domain=domain,**kwargs)
250250
self.nodes.append(node)
251+
ifdomain!="":
252+
ifnotself.opsetsordomainnotinself.opsets:
253+
raiseRuntimeError(f"No opset value was given for domain{domain!r}.")
251254
returnnode
252255

253256
defcst(self,value:np.ndarray,name:Optional[str]=None)->"Var":

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