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Commitc1f0a77

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Supports OrtValue in function ort_profile (#22)
* Supports OrtValue in function ort_profile* improves post processing of the profiler* support args_op_name
1 parentc82f9f3 commitc1f0a77

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4 files changed

+147
-4
lines changed

4 files changed

+147
-4
lines changed

‎.gitignore‎

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Original file line numberDiff line numberDiff line change
@@ -10,8 +10,11 @@ build/*
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.eggs/*
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.hypothesis/*
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*egg-info/*
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onnxruntime_profile*
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prof
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_doc/auto_examples/*
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_doc/examples/_cache/*
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_doc/examples/onnxruntime_profile*
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_doc/examples/plot_*.png
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_doc/examples/plot_*.xlsx
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_doc/examples/data/*.optimized.onnx

‎CHANGELOGS.rst‎

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Original file line numberDiff line numberDiff line change
@@ -4,5 +4,6 @@ Change Logs
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0.2.0
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+++++
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*:pr:`22`: support OrtValue in function:func:`ort_profile`
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*:pr:`17`: implements ArrayAPI
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*:pr:`3`: fixes Array API with onnxruntime and scikit-learn

‎_unittests/ut_ort/test_ort_profile.py‎

Lines changed: 74 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -6,6 +6,10 @@
66
fromonnx_array_api.ext_test_caseimportExtTestCase
77
fromonnx_array_api.ort.ort_optimizersimportort_optimized_model
88
fromonnx_array_api.ort.ort_profileimportort_profile,merge_ort_profile
9+
fromonnxruntime.capi._pybind_stateimport (
10+
OrtValueasC_OrtValue,
11+
OrtDeviceasC_OrtDevice,
12+
)
913

1014

1115
classTestOrtProfile(ExtTestCase):
@@ -28,7 +32,76 @@ def myloss(x, y):
2832
self.assertRaise(lambda:ort_optimized_model(onx,"NO"),ValueError)
2933
optimized=ort_optimized_model(onx)
3034
prof=ort_profile(optimized,feeds)
31-
prof.to_csv("prof.csv",index=False)
35+
self.assertIsInstance(prof,DataFrame)
36+
prof=ort_profile(optimized,feeds,as_df=False)
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self.assertIsInstance(prof,list)
38+
39+
deftest_ort_profile_first_it_out(self):
40+
defl1_loss(x,y):
41+
returnabsolute(x-y).sum()
42+
43+
defl2_loss(x,y):
44+
return ((x-y)**2).sum()
45+
46+
defmyloss(x,y):
47+
returnl1_loss(x[:,0],y[:,0])+l2_loss(x[:,1],y[:,1])
48+
49+
jitted_myloss=jit_onnx(myloss)
50+
x=np.array([[0.1,0.2], [0.3,0.4]],dtype=np.float32)
51+
y=np.array([[0.11,0.22], [0.33,0.44]],dtype=np.float32)
52+
jitted_myloss(x,y)
53+
onx=jitted_myloss.get_onnx()
54+
feeds= {"x0":x,"x1":y}
55+
self.assertRaise(lambda:ort_optimized_model(onx,"NO"),ValueError)
56+
optimized=ort_optimized_model(onx)
57+
prof=ort_profile(optimized,feeds)
58+
events= {
59+
"kernel_time",
60+
"fence_before",
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"fence_after",
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"SequentialExecutor::Execute",
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"model_run",
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"model_loading_array",
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"session_initialization",
66+
}
67+
self.assertEqual(set(prof["event_name"]),events)
68+
agg=ort_profile(optimized,feeds,first_it_out=True,agg=True)
69+
self.assertIsInstance(agg,DataFrame)
70+
self.assertLess(agg.shape[0],prof.shape[0])
71+
self.assertEqual(set(agg.reset_index(drop=False)["event_name"]),events)
72+
agg=ort_profile(
73+
optimized,feeds,first_it_out=True,agg=True,agg_op_name=False
74+
)
75+
self.assertIsInstance(agg,DataFrame)
76+
self.assertLess(agg.shape[0],prof.shape[0])
77+
self.assertEqual(set(agg.reset_index(drop=False)["event_name"]),events)
78+
79+
deftest_ort_profile_ort_value(self):
80+
defto_ort_value(m):
81+
device=C_OrtDevice(C_OrtDevice.cpu(),C_OrtDevice.default_memory(),0)
82+
ort_value=C_OrtValue.ortvalue_from_numpy(m,device)
83+
returnort_value
84+
85+
defl1_loss(x,y):
86+
returnabsolute(x-y).sum()
87+
88+
defl2_loss(x,y):
89+
return ((x-y)**2).sum()
90+
91+
defmyloss(x,y):
92+
returnl1_loss(x[:,0],y[:,0])+l2_loss(x[:,1],y[:,1])
93+
94+
jitted_myloss=jit_onnx(myloss)
95+
x=np.array([[0.1,0.2], [0.3,0.4]],dtype=np.float32)
96+
y=np.array([[0.11,0.22], [0.33,0.44]],dtype=np.float32)
97+
jitted_myloss(x,y)
98+
onx=jitted_myloss.get_onnx()
99+
np_feeds= {"x0":x,"x1":y}
100+
feeds= {k:to_ort_value(v)fork,vinnp_feeds.items()}
101+
102+
self.assertRaise(lambda:ort_optimized_model(onx,"NO"),ValueError)
103+
optimized=ort_optimized_model(onx)
104+
prof=ort_profile(optimized,feeds)
32105
self.assertIsInstance(prof,DataFrame)
33106
prof=ort_profile(optimized,feeds,as_df=False)
34107
self.assertIsInstance(prof,list)

‎onnx_array_api/ort/ort_profile.py‎

Lines changed: 69 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -6,6 +6,56 @@
66
frompandasimportDataFrame
77

88

9+
defpost_process_df_profile(
10+
df:DataFrame,
11+
first_it_out:bool=False,
12+
agg:bool=False,
13+
agg_op_name:bool=True,
14+
)->DataFrame:
15+
"""
16+
Post-processed a dataframe obtained after profiling onnxruntime.
17+
It adds a column for a more explicit event name and adds
18+
a column for the iteration number
19+
20+
:param agg: aggregate the result
21+
:param first_it_out: leave the first iteration
22+
out of the aggregation
23+
:param agg_op_name: aggregate on operator name or operator index
24+
:return: DataFrame
25+
"""
26+
events= {"kernel_time","fence_after","fence_before"}
27+
28+
defsep_event(s):
29+
foreinevents:
30+
ifs.endswith(e):
31+
returne
32+
returns
33+
34+
df=df.copy()
35+
df["event_name"]=df["name"].apply(sep_event)
36+
df["iteration"]=-1
37+
current=-1
38+
foriinrange(df.shape[0]):
39+
ifdf.loc[i,"name"]=="SequentialExecutor::Execute":
40+
current+=1
41+
df.loc[i,"iteration"]=current
42+
43+
ifnotagg:
44+
returndf
45+
46+
agg_cols= ["cat","args_node_index","args_op_name","args_provider","event_name"]
47+
iffirst_it_out:
48+
df["it==0"]= (df["iteration"]<=0).astype(int)
49+
agg_cols.insert(0,"it==0")
50+
ifagg_op_name:
51+
delagg_cols[agg_cols.index("args_node_index")]
52+
forcinagg_cols:
53+
df[c]=df[c].fillna("")
54+
df["dur"]=df["dur"].fillna(0)
55+
agg=df[agg_cols+ ["dur"]].groupby(agg_cols).sum()
56+
returnagg
57+
58+
959
defort_profile(
1060
filename_or_bytes:Union[str,bytes,ModelProto],
1161
feeds:Dict[str,numpy.ndarray],
@@ -14,6 +64,9 @@ def ort_profile(
1464
repeat:int=10,
1565
as_df:bool=True,
1666
providers:Optional[List[str]]=None,
67+
first_it_out:bool=False,
68+
agg:bool=False,
69+
agg_op_name:bool=False,
1770
**kwargs,
1871
)->Union[List,DataFrame]:
1972
"""
@@ -27,6 +80,9 @@ def ort_profile(
2780
:param as_df: returns the
2881
:param providers: list of providers to use when initializing the inference session,
2982
if None, the default value is `["CPUExecutionProvider"]`
83+
:param first_it_out: if aggregated, leaves the first iteration out
84+
:param agg: aggregate by event
85+
:param agg_op_name: aggregate on operator name or operator index
3086
:param kwargs: additional parameters when initializing the inference session
3187
:return: DataFrame or dictionary
3288
"""
@@ -45,8 +101,16 @@ def ort_profile(
45101
ifprovidersisNone:
46102
providers= ["CPUExecutionProvider"]
47103
sess=InferenceSession(obj,sess_options,providers=providers,**kwargs)
48-
foriinrange(repeat):
49-
sess.run(None,feeds)
104+
first=list(feeds.values())[0]
105+
106+
ifisinstance(first,numpy.ndarray):
107+
foriinrange(repeat):
108+
sess.run(None,feeds)
109+
else:
110+
out_names= [o.nameforoinsess.get_outputs()]
111+
foriinrange(repeat):
112+
sess._sess.run_with_ort_values(feeds,out_names,None)
113+
50114
prof=sess.end_profiling()
51115
withopen(prof,"r")asf:
52116
content=f.read()
@@ -68,7 +132,9 @@ def ort_profile(
68132
break
69133
rows.append(row)
70134
ifas_df:
71-
returnDataFrame(rows)
135+
returnpost_process_df_profile(
136+
DataFrame(rows),first_it_out=first_it_out,agg=agg,agg_op_name=agg_op_name
137+
)
72138
returnrows
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