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Commiteef694c

Browse files
authored
Adds functions to manipulate profiles (#14)
1 parent3966c41 commiteef694c

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13 files changed

+780
-146
lines changed

13 files changed

+780
-146
lines changed

‎_doc/api/ort.rst

Lines changed: 2 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -23,5 +23,7 @@ OrtTensor
2323
Profiling
2424
+++++++++
2525

26+
..autofunction::onnx_array_api.ort.ort_profile.merge_ort_profile
27+
2628
..autofunction::onnx_array_api.ort.ort_profile.ort_profile
2729

‎_doc/api/plotting.rst

Lines changed: 5 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -8,6 +8,11 @@ Dot
88

99
..autofunction::onnx_array_api.plotting.dot_plot.to_dot
1010

11+
Statistics
12+
++++++++++
13+
14+
..autofunction::onnx_array_api.plotting.stat_plot.plot_ort_profile
15+
1116
Text
1217
++++
1318

‎_doc/examples/plot_profiling.py

Lines changed: 50 additions & 131 deletions
Original file line numberDiff line numberDiff line change
@@ -21,17 +21,22 @@
2121
fromonnxruntimeimportget_available_providers
2222
fromonnx_array_api.ext_test_caseimportexample_path
2323
fromonnx_array_api.ort.ort_optimizersimportort_optimized_model
24-
fromonnx_array_api.ort.ort_profileimportort_profile
24+
fromonnx_array_api.ort.ort_profileimportort_profile,merge_ort_profile
25+
fromonnx_array_api.plotting.stat_plotimportplot_ort_profile
2526

2627

27-
filename=example_path("data/small.onnx")
28+
suffix=""
29+
filename=example_path(f"data/small{suffix}.onnx")
2830
optimized=filename+".optimized.onnx"
31+
print(f"model={filename!r}")
2932

3033
ifnotos.path.exists(optimized):
3134
ort_optimized_model(filename,output=optimized)
32-
print(optimized)
35+
print(f"optimized={optimized!r}")
3336

3437
#############################
38+
# .. _l-example-ort-profiling:
39+
#
3540
# Profiling
3641
# +++++++++
3742

@@ -43,50 +48,31 @@
4348
disable_optimization=True,
4449
providers=["CPUExecutionProvider"],
4550
)
46-
prof_base.to_excel("prof_base.xlsx",index=False)
51+
prof_base.to_excel(f"prof_base{suffix}.xlsx",index=False)
4752
prof_base
4853

4954
#######################################
5055
# And the optimized model.
5156

52-
prof_opt=ort_profile(
57+
prof_opti=ort_profile(
5358
optimized,
5459
feeds,
5560
repeat=6,
5661
disable_optimization=True,
5762
providers=["CPUExecutionProvider"],
5863
)
59-
prof_opt
64+
prof_opti.to_excel(f"prof_opti{suffix}.xlsx",index=False)
65+
prof_opti
6066

6167
#######################################
6268
# And the graph is:
6369

64-
65-
defplot_profile(df,ax0,ax1=None,title=None):
66-
gr_dur= (
67-
df[["dur","args_op_name"]].groupby("args_op_name").sum().sort_values("dur")
68-
)
69-
gr_dur.plot.barh(ax=ax0)
70-
iftitleisnotNone:
71-
ax0.set_title(title)
72-
ifax1isnotNone:
73-
gr_n= (
74-
df[["dur","args_op_name"]]
75-
.groupby("args_op_name")
76-
.count()
77-
.sort_values("dur")
78-
)
79-
gr_n=gr_n.loc[gr_dur.index, :]
80-
gr_n.plot.barh(ax=ax1)
81-
ax1.set_title("n occurences")
82-
83-
8470
unique_op=set(prof_base["args_op_name"])
8571
fig,ax=plt.subplots(2,2,figsize=(10,len(unique_op)),sharex="col")
86-
plot_profile(prof_base,ax[0,0],ax[0,1],title="baseline")
87-
plot_profile(prof_opt,ax[1,0],ax[1,1],title="optimized")
88-
89-
fig.savefig("plot_profiling.png")
72+
plot_ort_profile(prof_base,ax[0,0],ax[0,1],title="baseline")
73+
plot_ort_profile(prof_opti,ax[1,0],ax[1,1],title="optimized")
74+
fig.tight_layout()
75+
fig.savefig(f"plot_profiling{suffix}.png")
9076

9177
##################################################
9278
# Merging profiles
@@ -96,103 +82,14 @@ def plot_profile(df, ax0, ax1=None, title=None):
9682
# process the same image and the input and output size are the
9783
# same at every iteration.
9884

99-
100-
defpreprocess(df):
101-
groupkey= [
102-
"args_op_name",
103-
"args_output_type_shape",
104-
"args_input_type_shape",
105-
"args_provider",
106-
]
107-
108-
def_idx(row):
109-
"""
110-
There may be multiple node with the same
111-
input/output types and shapes.
112-
This function gives every instance a distinct id.
113-
First unique op with same I/O receives the index 0.
114-
The counter restart when the session goes to the
115-
next image.
116-
"""
117-
ifrow["cat"]=="Session":
118-
occurences[0]= {}
119-
return-1
120-
assert"idx"notingroupkey
121-
vals= [row[k]forkingroupkey]
122-
key=tuple(map(str,vals))
123-
ifkeynotinoccurences[0]:
124-
occurences[0][key]=0
125-
else:
126-
occurences[0][key]+=1
127-
returnoccurences[0][key]
128-
129-
df=df.copy()
130-
occurences= [{}]
131-
df["idx"]=df.apply(_idx,axis=1)
132-
df=df[(df["cat"]=="Node")&df["name"].str.contains("kernel_time")]
133-
groupkey.append("idx")
134-
forcingroupkey:
135-
ifc!="idx":
136-
df[c]=df[c].apply(str)
137-
gr=df[groupkey+ ["dur"]].groupby(groupkey)
138-
returngr.sum()
139-
140-
141-
base=preprocess(prof_base)
142-
opti=preprocess(prof_opt)
143-
merge=base.merge(
144-
opti,how="outer",suffixes=("base","opti"),left_index=True,right_index=True
145-
)
146-
merge=merge.reset_index(drop=False)
147-
merge.to_excel("plot_profiling_merged.xlsx",index=False)
85+
merge,gr=merge_ort_profile(prof_base,prof_opti)
86+
merge.to_excel(f"plot_profiling_merged{suffix}.xlsx",index=False)
14887
merge
14988

150-
15189
#####################################################
152-
# Aggregation
153-
154-
155-
defclassify(row):
156-
ifnumpy.isnan(row["duropti"]):
157-
return"-"
158-
ifnumpy.isnan(row["durbase"]):
159-
return"+"
160-
return"="
90+
# More detailed
16191

162-
163-
keys= {"float":"f"}
164-
165-
166-
defprocess_shape(s):
167-
value=eval(s)
168-
ns= []
169-
forvinvalue:
170-
iflen(v)!=1:
171-
raiseNotImplementedError(f"Unexpected value{v} in{s!r}.")
172-
k,v=list(v.items())[0]
173-
n="-".join([keys[k],"x".join(map(str,v))])
174-
ns.append(n)
175-
return",".join(ns)
176-
177-
178-
deflabel(row):
179-
name=row["args_op_name"]
180-
inshape=process_shape(row["args_input_type_shape"])
181-
outshape=process_shape(row["args_output_type_shape"])
182-
side=row["side"][0]
183-
prov=row["args_provider"][:3]
184-
idx=row["idx"]
185-
returnf"[{side}{prov}]{name}({inshape})->{outshape}[{idx}]"
186-
187-
188-
df=merge.copy()
189-
df["side"]=df.apply(classify,axis=1)
190-
df["label"]=df.apply(label,axis=1)
191-
gr= (
192-
df[["label","durbase","duropti","idx"]]
193-
.groupby("label")
194-
.agg({"durbase":numpy.sum,"duropti":numpy.sum,"idx":max})
195-
)
92+
gr.to_excel(f"plot_profiling_merged_details{suffix}.xlsx",index=False)
19693
gr
19794

19895
################################
@@ -210,11 +107,10 @@ def label(row):
210107
gr[["durbase","duropti"]].plot.barh(ax=ax[0])
211108
ax[0].set_title("Side by side duration")
212109
gr=gr.copy()
213-
gr["idx"]+=1
214-
gr[["idx"]].plot.barh(ax=ax[1])
110+
gr[["countbase","countopti"]].plot.barh(ax=ax[1])
215111
ax[1].set_title("Side by side count")
216112
fig.tight_layout()
217-
fig.savefig("plot_profiling_side_by_side.png")
113+
fig.savefig(f"plot_profiling_side_by_side{suffix}.png")
218114

219115

220116
########################################
@@ -231,21 +127,44 @@ def label(row):
231127
disable_optimization=True,
232128
providers=["CUDAExecutionProvider"],
233129
)
130+
prof_base.to_excel(f"prof_cuda_base{suffix}.xlsx",index=False)
131+
234132
prof_opti=ort_profile(
235133
optimized,
236134
feeds,
237135
repeat=6,
238136
disable_optimization=True,
239-
providers=["CUDAExecutionProvider"],
137+
providers=["CUDAExecutionProvider","CPUExecutionProvider"],
240138
)
139+
prof_opti.to_excel(f"prof_cuda_opti{suffix}.xlsx",index=False)
241140

242141
unique_op=set(prof_base["args_op_name"])
243142
fig,ax=plt.subplots(2,2,figsize=(10,len(unique_op)),sharex="col")
244-
plot_profile(prof_base,ax[0,0],ax[0,1],title="baseline")
245-
plot_profile(prof_opt,ax[1,0],ax[1,1],title="optimized")
246-
fig.savefig("plot_profiling_cuda.png")
143+
plot_ort_profile(prof_base,ax[0,0],ax[0,1],title="baseline")
144+
plot_ort_profile(prof_opti,ax[1,0],ax[1,1],title="optimized")
145+
fig.tight_layout()
146+
fig.savefig(f"plot_profiling_cuda{suffix}.png")
147+
148+
merge,gr=merge_ort_profile(prof_base,prof_opti)
149+
merge.to_excel(f"plot_profiling_merged{suffix}.xlsx",index=False)
150+
gr.to_excel(f"plot_profiling_merged_details{suffix}.xlsx",index=False)
151+
152+
grmax=gr["durbase"]+gr["duropti"]
153+
total=grmax.sum()
154+
grmax/=total
155+
gr=gr[grmax>=0.01]
156+
157+
fig,ax=plt.subplots(1,2,figsize=(14,min(gr.shape[0],500)),sharey=True)
158+
gr[["durbase","duropti"]].plot.barh(ax=ax[0])
159+
ax[0].set_title("Side by side duration")
160+
gr=gr.copy()
161+
gr[["countbase","countopti"]].plot.barh(ax=ax[1])
162+
ax[1].set_title("Side by side count")
163+
fig.tight_layout()
164+
fig.savefig(f"plot_profiling_side_by_side_cuda{suffix}.png")
165+
247166
else:
248-
print(f"CUDA not available in{get_available_providers()}")
167+
print(f"CUDA not available in{get_available_providers()}.")
249168
fig,ax=None,None
250169

251170
ax

‎_unittests/ut_ort/data/prof_base.xlsx

30.2 KB
Binary file not shown.

‎_unittests/ut_ort/data/prof_opti.xlsx

38.3 KB
Binary file not shown.

‎_unittests/ut_ort/test_ort_profile.py

Lines changed: 29 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -1,10 +1,11 @@
11
importunittest
2+
importos
23
importnumpyasnp
3-
frompandasimportDataFrame
4+
frompandasimportDataFrame,read_excel
45
fromonnx_array_api.npximportabsolute,jit_onnx
56
fromonnx_array_api.ext_test_caseimportExtTestCase
67
fromonnx_array_api.ort.ort_optimizersimportort_optimized_model
7-
fromonnx_array_api.ort.ort_profileimportort_profile
8+
fromonnx_array_api.ort.ort_profileimportort_profile,merge_ort_profile
89

910

1011
classTestOrtProfile(ExtTestCase):
@@ -27,10 +28,36 @@ def myloss(x, y):
2728
self.assertRaise(lambda:ort_optimized_model(onx,"NO"),ValueError)
2829
optimized=ort_optimized_model(onx)
2930
prof=ort_profile(optimized,feeds)
31+
prof.to_csv("prof.csv",index=False)
3032
self.assertIsInstance(prof,DataFrame)
3133
prof=ort_profile(optimized,feeds,as_df=False)
3234
self.assertIsInstance(prof,list)
3335

36+
deftest_merge_ort_profile(self):
37+
data=os.path.join(os.path.dirname(__file__),"data")
38+
df1=read_excel(os.path.join(data,"prof_base.xlsx"))
39+
df2=read_excel(os.path.join(data,"prof_opti.xlsx"))
40+
merged,gr=merge_ort_profile(df1,df2)
41+
self.assertEqual(merged.shape, (23,9))
42+
self.assertEqual(
43+
list(merged.columns),
44+
[
45+
"args_op_name",
46+
"args_output_type_shape",
47+
"args_input_type_shape",
48+
"args_provider",
49+
"idx",
50+
"durbase",
51+
"countbase",
52+
"duropti",
53+
"countopti",
54+
],
55+
)
56+
self.assertEqual(gr.shape, (19,4))
57+
self.assertEqual(
58+
list(gr.columns), ["durbase","duropti","countbase","countopti"]
59+
)
60+
3461

3562
if__name__=="__main__":
3663
unittest.main(verbosity=2)

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