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Commitdd11424

Browse files
authored
Fixes light API for operators with two outputs (#45)
* fix operators with two outputs* version* add more checks
1 parent70d6f64 commitdd11424

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7 files changed

+166
-49
lines changed

7 files changed

+166
-49
lines changed

‎CHANGELOGS.rst‎

Lines changed: 5 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -1,6 +1,11 @@
11
Change Logs
22
===========
33

4+
0.1.3
5+
+++++
6+
7+
*:pr:`45`: fixes light API for operators with two outputs
8+
49
0.1.2
510
+++++
611

‎_unittests/ut_light_api/test_light_api.py‎

Lines changed: 39 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -402,6 +402,45 @@ def test_operator_bool(self):
402402
got=ref.run(None, {"X":a,"Y":b})[0]
403403
self.assertEqualArray(f(a,b),got)
404404

405+
deftest_topk(self):
406+
onx= (
407+
start()
408+
.vin("X",np.float32)
409+
.vin("K",np.int64)
410+
.bring("X","K")
411+
.TopK()
412+
.rename("Values","Indices")
413+
.vout()
414+
.to_onnx()
415+
)
416+
self.assertIsInstance(onx,ModelProto)
417+
ref=ReferenceEvaluator(onx)
418+
x=np.array([[0,1,2,3], [9,8,7,6]],dtype=np.float32)
419+
k=np.array([2],dtype=np.int64)
420+
got=ref.run(None, {"X":x,"K":k})
421+
self.assertEqualArray(np.array([[3,2], [9,8]],dtype=np.float32),got[0])
422+
self.assertEqualArray(np.array([[3,2], [0,1]],dtype=np.int64),got[1])
423+
424+
deftest_topk_reverse(self):
425+
onx= (
426+
start()
427+
.vin("X",np.float32)
428+
.vin("K",np.int64)
429+
.bring("X","K")
430+
.TopK(largest=0)
431+
.rename("Values","Indices")
432+
.vout()
433+
.to_onnx()
434+
)
435+
self.assertIsInstance(onx,ModelProto)
436+
ref=ReferenceEvaluator(onx)
437+
x=np.array([[0,1,2,3], [9,8,7,6]],dtype=np.float32)
438+
k=np.array([2],dtype=np.int64)
439+
got=ref.run(None, {"X":x,"K":k})
440+
self.assertEqualArray(np.array([[0,1], [6,7]],dtype=np.float32),got[0])
441+
self.assertEqualArray(np.array([[0,1], [3,2]],dtype=np.int64),got[1])
442+
405443

406444
if__name__=="__main__":
445+
# TestLightApi().test_topk()
407446
unittest.main(verbosity=2)

‎onnx_array_api/__init__.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -3,5 +3,5 @@
33
APIs to create ONNX Graphs.
44
"""
55

6-
__version__="0.1.2"
6+
__version__="0.1.3"
77
__author__="Xavier Dupré"

‎onnx_array_api/light_api/_op_var.py‎

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -30,7 +30,7 @@ def ArgMin(
3030

3131
defAveragePool(
3232
self,
33-
auto_pad:str=b"NOTSET",
33+
auto_pad:str="NOTSET",
3434
ceil_mode:int=0,
3535
count_include_pad:int=0,
3636
dilations:Optional[List[int]]=None,
@@ -68,7 +68,7 @@ def Cast(self, saturate: int = 1, to: int = 0) -> "Var":
6868
defCelu(self,alpha:float=1.0)->"Var":
6969
returnself.make_node("Celu",self,alpha=alpha)
7070

71-
defDepthToSpace(self,blocksize:int=0,mode:str=b"DCR")->"Var":
71+
defDepthToSpace(self,blocksize:int=0,mode:str="DCR")->"Var":
7272
returnself.make_node("DepthToSpace",self,blocksize=blocksize,mode=mode)
7373

7474
defDynamicQuantizeLinear(
@@ -137,7 +137,7 @@ def LpNormalization(self, axis: int = -1, p: int = 2) -> "Var":
137137

138138
defLpPool(
139139
self,
140-
auto_pad:str=b"NOTSET",
140+
auto_pad:str="NOTSET",
141141
ceil_mode:int=0,
142142
dilations:Optional[List[int]]=None,
143143
kernel_shape:Optional[List[int]]=None,

‎onnx_array_api/light_api/_op_vars.py‎

Lines changed: 25 additions & 20 deletions
Original file line numberDiff line numberDiff line change
@@ -6,7 +6,7 @@ class OpsVars:
66
Operators taking multiple inputs.
77
"""
88

9-
defBitShift(self,direction:str=b"")->"Var":
9+
defBitShift(self,direction:str="")->"Var":
1010
returnself.make_node("BitShift",*self.vars_,direction=direction)
1111

1212
defCenterCropPad(self,axes:Optional[List[int]]=None)->"Var":
@@ -42,7 +42,7 @@ def Concat(self, axis: int = 0) -> "Var":
4242

4343
defConv(
4444
self,
45-
auto_pad:str=b"NOTSET",
45+
auto_pad:str="NOTSET",
4646
dilations:Optional[List[int]]=None,
4747
group:int=1,
4848
kernel_shape:Optional[List[int]]=None,
@@ -66,7 +66,7 @@ def Conv(
6666

6767
defConvInteger(
6868
self,
69-
auto_pad:str=b"NOTSET",
69+
auto_pad:str="NOTSET",
7070
dilations:Optional[List[int]]=None,
7171
group:int=1,
7272
kernel_shape:Optional[List[int]]=None,
@@ -90,7 +90,7 @@ def ConvInteger(
9090

9191
defConvTranspose(
9292
self,
93-
auto_pad:str=b"NOTSET",
93+
auto_pad:str="NOTSET",
9494
dilations:Optional[List[int]]=None,
9595
group:int=1,
9696
kernel_shape:Optional[List[int]]=None,
@@ -155,7 +155,7 @@ def DeformConv(
155155
defDequantizeLinear(self,axis:int=1)->"Var":
156156
returnself.make_node("DequantizeLinear",*self.vars_,axis=axis)
157157

158-
defEinsum(self,equation:str=b"")->"Var":
158+
defEinsum(self,equation:str="")->"Var":
159159
returnself.make_node("Einsum",*self.vars_,equation=equation)
160160

161161
defGather(self,axis:int=0)->"Var":
@@ -174,8 +174,8 @@ def Gemm(
174174
defGridSample(
175175
self,
176176
align_corners:int=0,
177-
mode:str=b"bilinear",
178-
padding_mode:str=b"zeros",
177+
mode:str="bilinear",
178+
padding_mode:str="zeros",
179179
)->"Var":
180180
returnself.make_node(
181181
"GridSample",
@@ -240,7 +240,7 @@ def Mod(self, fmod: int = 0) -> "Var":
240240
returnself.make_node("Mod",*self.vars_,fmod=fmod)
241241

242242
defNegativeLogLikelihoodLoss(
243-
self,ignore_index:int=0,reduction:str=b"mean"
243+
self,ignore_index:int=0,reduction:str="mean"
244244
)->"Var":
245245
returnself.make_node(
246246
"NegativeLogLikelihoodLoss",
@@ -257,12 +257,12 @@ def NonMaxSuppression(self, center_point_box: int = 0) -> "Var":
257257
defOneHot(self,axis:int=-1)->"Var":
258258
returnself.make_node("OneHot",*self.vars_,axis=axis)
259259

260-
defPad(self,mode:str=b"constant")->"Var":
260+
defPad(self,mode:str="constant")->"Var":
261261
returnself.make_node("Pad",*self.vars_,mode=mode)
262262

263263
defQLinearConv(
264264
self,
265-
auto_pad:str=b"NOTSET",
265+
auto_pad:str="NOTSET",
266266
dilations:Optional[List[int]]=None,
267267
group:int=1,
268268
kernel_shape:Optional[List[int]]=None,
@@ -431,13 +431,13 @@ def Resize(
431431
self,
432432
antialias:int=0,
433433
axes:Optional[List[int]]=None,
434-
coordinate_transformation_mode:str=b"half_pixel",
434+
coordinate_transformation_mode:str="half_pixel",
435435
cubic_coeff_a:float=-0.75,
436436
exclude_outside:int=0,
437437
extrapolation_value:float=0.0,
438-
keep_aspect_ratio_policy:str=b"stretch",
439-
mode:str=b"nearest",
440-
nearest_mode:str=b"round_prefer_floor",
438+
keep_aspect_ratio_policy:str="stretch",
439+
mode:str="nearest",
440+
nearest_mode:str="round_prefer_floor",
441441
)->"Var":
442442
axes=axesor []
443443
returnself.make_node(
@@ -456,8 +456,8 @@ def Resize(
456456

457457
defRoiAlign(
458458
self,
459-
coordinate_transformation_mode:str=b"half_pixel",
460-
mode:str=b"avg",
459+
coordinate_transformation_mode:str="half_pixel",
460+
mode:str="avg",
461461
output_height:int=1,
462462
output_width:int=1,
463463
sampling_ratio:int=0,
@@ -480,12 +480,12 @@ def STFT(self, onesided: int = 1) -> "Var":
480480
defScatter(self,axis:int=0)->"Var":
481481
returnself.make_node("Scatter",*self.vars_,axis=axis)
482482

483-
defScatterElements(self,axis:int=0,reduction:str=b"none")->"Var":
483+
defScatterElements(self,axis:int=0,reduction:str="none")->"Var":
484484
returnself.make_node(
485485
"ScatterElements",*self.vars_,axis=axis,reduction=reduction
486486
)
487487

488-
defScatterND(self,reduction:str=b"none")->"Var":
488+
defScatterND(self,reduction:str="none")->"Var":
489489
returnself.make_node("ScatterND",*self.vars_,reduction=reduction)
490490

491491
defSlice(
@@ -498,13 +498,18 @@ def Slice(
498498

499499
defTopK(self,axis:int=-1,largest:int=1,sorted:int=1)->"Vars":
500500
returnself.make_node(
501-
"TopK",*self.vars_,axis=axis,largest=largest,sorted=sorted
501+
"TopK",
502+
*self.vars_,
503+
axis=axis,
504+
largest=largest,
505+
sorted=sorted,
506+
n_outputs=2,
502507
)
503508

504509
defTrilu(self,upper:int=1)->"Var":
505510
returnself.make_node("Trilu",*self.vars_,upper=upper)
506511

507-
defUpsample(self,mode:str=b"nearest")->"Var":
512+
defUpsample(self,mode:str="nearest")->"Var":
508513
returnself.make_node("Upsample",*self.vars_,mode=mode)
509514

510515
defWhere(

‎onnx_array_api/light_api/model.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -28,8 +28,8 @@ class OnnxGraph:
2828
This API is meant to be light and allows the description of a graph.
2929
3030
:param opset: main opset version
31+
:param opsets: other opsets as a dictionary
3132
:param is_function: a :class:`onnx.ModelProto` or a :class:`onnx.FunctionProto`
32-
:param opsets: others opsets as a dictionary
3333
"""
3434

3535
def__init__(

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