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Commit2c739f9

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committed
improve code coverage
1 parentf513e4b commit2c739f9

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2 files changed

+175
-28
lines changed

2 files changed

+175
-28
lines changed

‎_unittests/ut_graph_api/test_graph_builder.py‎

Lines changed: 140 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -3,9 +3,12 @@
33
importunittest
44
importnumpyasnp
55
importonnx
6-
fromonnx.referenceimportReferenceEvaluator
76
fromonnx_array_api.ext_test_caseimportExtTestCase
8-
fromonnx_array_api.graph_api.graph_builderimportGraphBuilder
7+
fromonnx_array_api.graph_api.graph_builderimportGraphBuilder,OptimizationOptions
8+
fromonnx_array_api.referenceimport (
9+
from_array_extended,
10+
ExtendedReferenceEvaluatorasReferenceEvaluator,
11+
)
912

1013

1114
classTestGraphBuilder(ExtTestCase):
@@ -130,6 +133,35 @@ def test_constant_folding(self):
130133
got=ref.run(None,feeds)
131134
self.assertEqualArray(expected,got[0])
132135

136+
deftest_constant_folding2(self):
137+
g=GraphBuilder(
138+
optimization_options=OptimizationOptions(constant_folding=True)
139+
)
140+
141+
shape= (10,4)
142+
w=np.random.randn(*shape).astype(np.float32)
143+
x=g.make_tensor_input("X",np.float32,shape)
144+
weight=g.make_initializer(w)
145+
cst=g.get_constant(weight)
146+
self.assertEqualArray(w,cst)
147+
one=g.make_initializer(np.array([-1,1],dtype=np.int64))
148+
transposed=g.make_node("Transpose", [weight],perm=[1,0])
149+
res=g.op.MatMul(x,transposed)
150+
g.op.Reshape(res,one,outputs="y")
151+
g.make_tensor_output("y",np.float32, (10,1))
152+
153+
g.optimize()
154+
155+
onx=g.to_onnx()
156+
node_types= [n.op_typeforninonx.graph.node]
157+
self.assertNotIn("Transpose",node_types)
158+
ref=ReferenceEvaluator(onx)
159+
x=np.random.randn(*shape).astype(np.float32)
160+
expected= (x @w.T).reshape((-1,1))
161+
feeds= {"X":x}
162+
got=ref.run(None,feeds)
163+
self.assertEqualArray(expected,got[0])
164+
133165
deftest_remove_identity(self):
134166
withcontextlib.redirect_stdout(io.StringIO()):
135167
g=GraphBuilder(verbose=10)
@@ -238,6 +270,112 @@ def test_remove_unused_nodes_simple(self):
238270
got=ref.run(None,feeds)
239271
self.assertEqualArray(expected,got[0])
240272

273+
deftest_constant_array(self):
274+
withcontextlib.redirect_stdout(io.StringIO()):
275+
g=GraphBuilder(verbose=10)
276+
277+
shape= (10,4)
278+
w=np.random.randn(*shape).astype(np.float32)
279+
280+
x=g.make_tensor_input("X",np.float32,shape)
281+
one=g.make_initializer(np.array([-1,1],dtype=np.int64))
282+
res=g.op.MatMul(x,w.T)
283+
g.op.Reshape(res,one,outputs="y")
284+
g.make_tensor_output("y",np.float32, (10,1))
285+
onx=g.to_onnx()
286+
ref=ReferenceEvaluator(onx)
287+
x=np.random.randn(*shape).astype(np.float32)
288+
expected= (x @w.T).reshape((-1,1))
289+
feeds= {"X":x}
290+
got=ref.run(None,feeds)
291+
self.assertEqualArray(expected,got[0])
292+
293+
deftest_constant_array_2(self):
294+
withcontextlib.redirect_stdout(io.StringIO()):
295+
g=GraphBuilder(verbose=10)
296+
297+
shape= (10,4)
298+
w=np.random.randn(*shape).astype(np.float32)
299+
300+
x=g.make_tensor_input("X",np.float32,shape)
301+
one=g.make_initializer(np.array([-1,1],dtype=np.int64))
302+
opc=g.op.Constant(value=from_array_extended(w.T))
303+
res=g.op.MatMul(x,opc)
304+
g.op.Reshape(res,one,outputs="y")
305+
g.make_tensor_output("y",np.float32, (10,1))
306+
self.assertTrue(g.has_shape("X"))
307+
self.assertTrue(g.has_type("X"))
308+
self.assertEqual(g.get_type("X"),1)
309+
self.assertEqual(g.get_shape("X"), (10,4))
310+
self.assertEqual(g.rank("X"),2)
311+
onx=g.to_onnx()
312+
ref=ReferenceEvaluator(onx)
313+
x=np.random.randn(*shape).astype(np.float32)
314+
expected= (x @w.T).reshape((-1,1))
315+
feeds= {"X":x}
316+
got=ref.run(None,feeds)
317+
self.assertEqualArray(expected,got[0])
318+
319+
deftest_get_type(self):
320+
g=GraphBuilder()
321+
self.assertEqual(g._get_type(np.float32),onnx.TensorProto.FLOAT)
322+
self.assertEqual(g._get_type(np.int64),onnx.TensorProto.INT64)
323+
self.assertEqual(g._get_type(None),onnx.TensorProto.UNDEFINED)
324+
325+
deftest_make_nodes_prefix(self):
326+
g1=GraphBuilder()
327+
g1.make_tensor_input("X",np.float32,shape=None)
328+
g1.op.Add("X",np.array([1],dtype=np.float32),outputs=["y"])
329+
g1.make_tensor_output("y",np.float32,shape=None)
330+
331+
g=GraphBuilder()
332+
333+
shape= (10,4)
334+
w=np.random.randn(*shape).astype(np.float32)
335+
336+
x=g.make_tensor_input("X",np.float32,shape)
337+
weight=g.make_initializer(w)
338+
one=g.make_initializer(np.array([-1,1],dtype=np.int64))
339+
transposed=g.make_node("Transpose", [weight],perm=[1,0])
340+
res=g.op.MatMul(x,transposed)
341+
res2=g.make_nodes(g1, [res], ["k"],prefix="J")
342+
g.op.Reshape(res2,one,outputs="y")
343+
g.make_tensor_output("y",np.float32, (10,1))
344+
onx=g.to_onnx()
345+
ref=ReferenceEvaluator(onx)
346+
x=np.random.randn(*shape).astype(np.float32)
347+
expected= (x @w.T).reshape((-1,1))+1
348+
feeds= {"X":x}
349+
got=ref.run(None,feeds)
350+
self.assertEqualArray(expected,got[0])
351+
352+
deftest_make_nodes_noprefix(self):
353+
g1=GraphBuilder()
354+
g1.make_tensor_input("X",np.float32,shape=None)
355+
g1.op.Add("X",np.array([1],dtype=np.float32),outputs=["y"])
356+
g1.make_tensor_output("y",np.float32,shape=None)
357+
358+
g=GraphBuilder()
359+
360+
shape= (10,4)
361+
w=np.random.randn(*shape).astype(np.float32)
362+
363+
x=g.make_tensor_input("X",np.float32,shape)
364+
weight=g.make_initializer(w)
365+
one=g.make_initializer(np.array([-1,1],dtype=np.int64))
366+
transposed=g.make_node("Transpose", [weight],perm=[1,0])
367+
res=g.op.MatMul(x,transposed)
368+
res2=g.make_nodes(g1, [res], ["k"])
369+
g.op.Reshape(res2,one,outputs="y")
370+
g.make_tensor_output("y",np.float32, (10,1))
371+
onx=g.to_onnx()
372+
ref=ReferenceEvaluator(onx)
373+
x=np.random.randn(*shape).astype(np.float32)
374+
expected= (x @w.T).reshape((-1,1))+1
375+
feeds= {"X":x}
376+
got=ref.run(None,feeds)
377+
self.assertEqualArray(expected,got[0])
378+
241379

242380
if__name__=="__main__":
243381
unittest.main(verbosity=2)

‎onnx_array_api/graph_api/graph_builder.py‎

Lines changed: 35 additions & 26 deletions
Original file line numberDiff line numberDiff line change
@@ -18,6 +18,18 @@
1818
T="TENSOR"
1919

2020

21+
classOptimizationOptions:
22+
def__init__(
23+
self,
24+
remove_unused:bool=True,
25+
constant_folding:bool=False,
26+
constant_size:int=1024,
27+
):
28+
self.remove_unused=remove_unused
29+
self.constant_folding=constant_folding
30+
self.constant_size=constant_size
31+
32+
2133
classOpset:
2234
# defined for opset >= 18
2335
# name: number of expected outputs
@@ -76,7 +88,7 @@ def make_node(
7688
foriininputs:
7789
ifnotisinstance(i,str):
7890
name=self.builder.unique_name("cst")
79-
self.builder.make_initializer(i,name=name)
91+
self.builder.make_initializer(i,name=name,exists=True)
8092
new_inputs.append(name)
8193
else:
8294
new_inputs.append(i)
@@ -86,18 +98,6 @@ def make_node(
8698
)
8799

88100

89-
classOptimizationOptions:
90-
def__init__(
91-
self,
92-
remove_unused:bool=True,
93-
constant_folding:bool=False,
94-
constant_size:int=1024,
95-
):
96-
self.remove_unused=remove_unused
97-
self.constant_folding=constant_folding
98-
self.constant_size=constant_size
99-
100-
101101
classGraphBuilder:
102102
def__init__(
103103
self,
@@ -304,12 +304,18 @@ def _get_type(self, elem_type: Any, exc: bool = True) -> int:
304304
returnelem_type
305305

306306
defmake_initializer(
307-
self,value:Any,name:str="",external:bool=False
307+
self,value:Any,name:str="",external:bool=False,exists:bool=False
308308
)->str:
309309
ifexternal:
310310
raiseNotImplementedError("External initializers are not implemented yet.")
311311
ifname=="":
312+
ifexists:
313+
raiseValueError("Undefined name cannot exist.")
312314
name=self.unique_name("cst")
315+
elifnotexists:
316+
ifnameinself._unique_names:
317+
raiseValueError(f"{name!r} is already assigned.")
318+
self._unique_names.add(name)
313319
self.set_shape(name,value.shape)
314320
self.set_type(name,self._get_type(value.dtype))
315321
self.initializers_dict[name]=value
@@ -330,6 +336,9 @@ def make_tensor_input(
330336
else:
331337
self.input_names.append(name)
332338
input_name=name
339+
ifnameinself._unique_names:
340+
raiseValueError(f"{name!r} is already assigned.")
341+
self._unique_names.add(name)
333342
self.current_input+=1
334343
elem_type=self._get_type(elem_type)
335344
self.inputs.append(oh.make_tensor_value_info(input_name,elem_type,shape))
@@ -397,15 +406,11 @@ def make_node(
397406
try:
398407
node=oh.make_node(op_type,inputs,output_names,domain=domain,**kwargs)
399408
exceptTypeErrorase:
400-
iti= [type(i)foriininputs]
401-
ito= (
402-
[type(o)foroinoutputs]
403-
ifisinstance(outputs, (tuple,list))
404-
elseoutputs
405-
)
406409
raiseTypeError(
407410
f"A node{op_type!r} cannot be created with "
408-
f"inputs={inputs} (types={iti}), outputs={outputs} (types={ito}), "
411+
f"inputs={inputs} (types={[type(i)foriininputs]}), "
412+
f"outputs={outputs} "
413+
f"(types={[type(o)foroinoutputs]ifisinstance(outputs, (tuple,list))elseoutputs}), "
409414
f"domain={domain!r}, kwargs={kwargs}."
410415
)frome
411416
ifattributes:
@@ -474,14 +479,18 @@ def make_nodes(
474479
self.set_shape(name,builder._known_shapes[init])
475480
self.set_type(name,builder._known_types[init])
476481

477-
assertlen(input_names)==len(
478-
builder.inputs
479-
),f"Inconsistency between input_names={input_names} and inputs={builder.inputs}."
482+
assertlen(input_names)==len(builder.inputs), (
483+
f"Inconsistency between input_names={input_names} "
484+
f"and the other builder inputs={builder.inputs}."
485+
)
486+
480487
forname,inpinzip(input_names,builder.inputs):
481488
new_name=self.unique_name(f"{prefix}{inp.name}")
482-
self.set_shape(new_name,builder.get_shape(inp.name))
483-
self.set_type(new_name,builder.get_type(inp.name))
484489
renaming[inp.name]=new_name
490+
ifbuilder.has_shape(inp.name):
491+
self.set_shape(new_name,builder.get_shape(inp.name))
492+
ifbuilder.has_type(inp.name):
493+
self.set_type(new_name,builder.get_type(inp.name))
485494
self.make_node("Identity", [name], [new_name])
486495

487496
fornodeinbuilder.nodes:

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