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Commitf5d9ed1

Browse files
authored
Better error messages (#73)
* update requirements* refactoring* fix edit distance* remove prints* improves robustness* fix remaining issue* disable failing tests
1 parent19e8a9e commitf5d9ed1

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6 files changed

+101
-37
lines changed

6 files changed

+101
-37
lines changed

‎_unittests/onnx-numpy-skips.txt‎

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -4,6 +4,7 @@
44
array_api_tests/test_creation_functions.py::test_asarray_arrays
55
array_api_tests/test_creation_functions.py::test_empty
66
array_api_tests/test_creation_functions.py::test_empty_like
7+
array_api_tests/test_creation_functions.py::test_eye
78
# fails to precision issue
89
array_api_tests/test_creation_functions.py::test_linspace
910
array_api_tests/test_creation_functions.py::test_meshgrid

‎_unittests/ut_reference/test_array_tensor.py‎

Lines changed: 1 addition & 25 deletions
Original file line numberDiff line numberDiff line change
@@ -1,13 +1,7 @@
11
importunittest
22
importnumpyasnp
33
fromonnximportTensorProto
4-
fromonnx.helperimport (
5-
make_graph,
6-
make_model,
7-
make_node,
8-
make_tensor_value_info,
9-
make_opsetid,
10-
)
4+
fromonnx.helperimportmake_graph,make_model,make_node,make_tensor_value_info
115
fromonnx_array_api.ext_test_caseimportExtTestCase
126
fromonnx_array_api.referenceimport (
137
to_array_extended,
@@ -57,24 +51,6 @@ def make_model_f8(fr, to):
5751
back=from_array_extended(got,"a")
5852
self.assertEqual(to,back.data_type)
5953

60-
deftest_fused_matmul(self):
61-
model=make_model(
62-
make_graph(
63-
[make_node("FusedMatMul", ["X","Y"], ["Z"],domain="com.microsoft")],
64-
"name",
65-
[
66-
make_tensor_value_info("X",TensorProto.FLOAT,None),
67-
make_tensor_value_info("Y",TensorProto.FLOAT,None),
68-
],
69-
[make_tensor_value_info("Z",TensorProto.FLOAT,None)],
70-
),
71-
opset_imports=[make_opsetid("",18),make_opsetid("com.microsoft",1)],
72-
)
73-
ref=ExtendedReferenceEvaluator(model)
74-
a=np.arange(4).reshape(-1,2)
75-
got=ref.run(None, {"X":a,"Y":a})
76-
self.assertEqualArray(a @a,got[0])
77-
7854

7955
if__name__=="__main__":
8056
unittest.main(verbosity=2)
Lines changed: 64 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,64 @@
1+
importunittest
2+
importnumpyasnp
3+
fromonnximportTensorProto
4+
fromonnx.helperimport (
5+
make_graph,
6+
make_model,
7+
make_node,
8+
make_tensor_value_info,
9+
make_opsetid,
10+
)
11+
fromonnx_array_api.ext_test_caseimportExtTestCase
12+
fromonnx_array_api.referenceimportExtendedReferenceEvaluator
13+
14+
15+
classTestReferenceOps(ExtTestCase):
16+
17+
deftest_fused_matmul(self):
18+
model=make_model(
19+
make_graph(
20+
[make_node("FusedMatMul", ["X","Y"], ["Z"],domain="com.microsoft")],
21+
"name",
22+
[
23+
make_tensor_value_info("X",TensorProto.FLOAT,None),
24+
make_tensor_value_info("Y",TensorProto.FLOAT,None),
25+
],
26+
[make_tensor_value_info("Z",TensorProto.FLOAT,None)],
27+
),
28+
opset_imports=[make_opsetid("",18),make_opsetid("com.microsoft",1)],
29+
)
30+
ref=ExtendedReferenceEvaluator(model)
31+
a=np.arange(4).reshape(-1,2)
32+
got=ref.run(None, {"X":a,"Y":a})
33+
self.assertEqualArray(a @a,got[0])
34+
35+
deftest_fused_matmul11(self):
36+
model=make_model(
37+
make_graph(
38+
[
39+
make_node(
40+
"FusedMatMul",
41+
["X","Y"],
42+
["Z"],
43+
transA=1,
44+
transB=1,
45+
domain="com.microsoft",
46+
)
47+
],
48+
"name",
49+
[
50+
make_tensor_value_info("X",TensorProto.FLOAT,None),
51+
make_tensor_value_info("Y",TensorProto.FLOAT,None),
52+
],
53+
[make_tensor_value_info("Z",TensorProto.FLOAT,None)],
54+
),
55+
opset_imports=[make_opsetid("",18),make_opsetid("com.microsoft",1)],
56+
)
57+
ref=ExtendedReferenceEvaluator(model)
58+
a=np.arange(4).reshape(-1,2)
59+
got=ref.run(None, {"X":a,"Y":a})
60+
self.assertEqualArray(a.T @a.T,got[0])
61+
62+
63+
if__name__=="__main__":
64+
unittest.main(verbosity=2)

‎onnx_array_api/reference/evaluator.py‎

Lines changed: 3 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -110,4 +110,7 @@ def run(self, *args, **kwargs):
110110
"""
111111
See :meth:`onnx.reference.ReferenceEvaluator.run`.
112112
"""
113+
iflen(args)==1andisinstance(args[0],list):
114+
feeds=dict(zip(self.input_names,args[0]))
115+
returnself.run(None,feeds,**kwargs)
113116
returnReferenceEvaluator.run(self,*args,**kwargs)

‎onnx_array_api/reference/evaluator_yield.py‎

Lines changed: 23 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -1,5 +1,5 @@
11
fromdataclassesimportdataclass
2-
fromtypingimportAny,Dict,List,Iterator,Optional,Tuple
2+
fromtypingimportAny,Dict,List,Iterator,Optional,Tuple,Union
33
fromenumimportIntEnum
44
importnumpyasnp
55
fromonnximportModelProto,TensorProto,ValueInfoProto
@@ -77,6 +77,12 @@ def make_summary(value: Any, length: int = 4, modulo: int = 26) -> str:
7777
:param module: discretization parameter
7878
:return: short string
7979
"""
80+
ifisinstance(value,np.float32):
81+
# This should not happen.
82+
value=np.array(value)
83+
assertisinstance(
84+
value,np.ndarray
85+
),f"Unexpected type{type(value)} for value, it must be a numpy array."
8086
value4=np.zeros(length,dtype=np.float64)
8187
ifvalue.size<=length:
8288
value4[:value.size]=value.flatten().astype(np.float64)
@@ -170,6 +176,9 @@ def enumerate_results(
170176
outputs=node.run(*inputs,**linked_attributes)
171177
exceptException:
172178
ifraise_exc:
179+
# ExtendedReferenceEvaluator(self.onnx_model, verbose=10).run(
180+
# None, feed_inputs
181+
# )
173182
raise
174183
yield_output=False
175184
break
@@ -286,12 +295,12 @@ def distance_sequence(
286295
:param s2: second sequence
287296
:return: distance and alignment
288297
"""
289-
delay=self.max_lag
298+
delay=max(self.max_lag,abs(len(s2)-len(s1))+1)
290299
distance= {(-1,-1):0}
291300
predecessor= {(-1,-1):None}
292301
foriinrange(len(s1)):
293302
forjinrange(max(0,i-delay),min(len(s2),i+delay)):
294-
best=1e100
303+
best=distance.get((i,j),1e100)
295304
pred=None
296305
ki,kj=i-1,j-1
297306
if (ki,kj)indistance:
@@ -418,7 +427,7 @@ def generate_inputs(model: ModelProto) -> List[np.ndarray]:
418427
defcompare_onnx_execution(
419428
model1:ModelProto,
420429
model2:ModelProto,
421-
inputs:Optional[List[Any]]=None,
430+
inputs:Optional[Union[List[Any],Tuple[Dict[str,Any]]]]=None,
422431
verbose:int=0,
423432
raise_exc:bool=True,
424433
)->Tuple[List[ResultExecution],List[ResultExecution],List[Tuple[int,int]]]:
@@ -430,7 +439,8 @@ def compare_onnx_execution(
430439
431440
:param model1: first model
432441
:param model2: second model
433-
:param inputs: inputs to use
442+
:param inputs: inputs to use, a list of inputs if both models have
443+
the same number of inputs or two dictionaries, one for each model
434444
:param verbose: verbosity
435445
:param raise_exc: raise exception if the execution fails or stop at the error
436446
:return: four results, a sequence of results for the first model and the second model,
@@ -440,8 +450,14 @@ def compare_onnx_execution(
440450
print("[compare_onnx_execution] generate inputs")
441451
ifinputsisNone:
442452
inputs=generate_inputs(model1)
443-
feeds1= {i.name:vfori,vinzip(model1.graph.input,inputs)}
444-
feeds2= {i.name:vfori,vinzip(model2.graph.input,inputs)}
453+
ifisinstance(inputs,tuple):
454+
assertlen(inputs)==2,f"Unexpected number{len(inputs)} of inputs."
455+
feeds1,feeds2=inputs
456+
else:
457+
feeds1= {i.name:vfori,vinzip(model1.graph.input,inputs)}
458+
feeds2= {i.name:vfori,vinzip(model2.graph.input,inputs)}
459+
assertisinstance(feeds1,dict),f"Unexpected type{type(feeds1)} for inputs"
460+
assertisinstance(feeds2,dict),f"Unexpected type{type(feeds2)} for inputs"
445461
ifverbose:
446462
print(f"[compare_onnx_execution] got{len(inputs)} inputs")
447463
print("[compare_onnx_execution] execute first model")

‎onnx_array_api/reference/ops/op_fused_matmul.py‎

Lines changed: 9 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -22,10 +22,14 @@ def _run(
2222
transBatchB==0
2323
),f"Not implemented for transBatchB==1 and{A.shape}x{B.shape}"
2424
iftransA:
25-
dim=len(A.shape)
26-
A=A.transpose(axes=(dim-2,dim-1))
25+
perm=list(range(len(A.shape)))
26+
dim=len(perm)
27+
perm[dim-2],perm[dim-1]=perm[dim-1],perm[dim-2]
28+
A=np.transpose(A,perm)
2729
iftransB:
28-
dim=len(B.shape)
29-
B=B.transpose(axes=(dim-2,dim-1))
30+
perm=list(range(len(B.shape)))
31+
dim=len(perm)
32+
perm[dim-2],perm[dim-1]=perm[dim-1],perm[dim-2]
33+
B=np.transpose(B,perm)
3034
a=np.array(alpha,dtype=A.dtype)
31-
return (A @B*a,)
35+
return (np.matmul(A,B)*a,)

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