
from jyquickhelper import add_notebook_menu
add_notebook_menu()


%matplotlib inline


%load_ext mlprodict


from sklearn.datasets import make_classification
X, y = make_classification(100000)


from sklearn.cluster import KMeans
km = KMeans(max_iter=10)
km.fit(X)

KMeans(max_iter=10)


import numpy
from mlprodict.onnx_conv import to_onnx
onx = to_onnx(km, X[:1].astype(numpy.float32))


%onnxview onx


from mlprodict.onnxrt import OnnxInference

oinf = OnnxInference(onx)
js = oinf.to_json()


import json
from io import StringIO
from jyquickhelper import JSONJS
JSONJS(json.load(StringIO(oinf.to_json())))


from mlprodict.onnxrt import OnnxInference

oinf = OnnxInference(onx, runtime="onnxruntime1",
                     runtime_options={"enable_profiling": True})


for i in range(0, 111):
    oinf.run({"X": X.astype(numpy.float32)})


df = oinf.get_profiling(as_df=True)
df


import matplotlib.pyplot as plt
gr_dur = df[['dur', "args_op_name"]].groupby("args_op_name").sum().sort_values('dur')
gr_n = df[['dur', "args_op_name"]].groupby("args_op_name").count().sort_values('dur')
gr_n = gr_n.loc[gr_dur.index, :]

fig, ax = plt.subplots(1, 2, figsize=(8, 4))
gr_dur.plot.barh(ax=ax[0])
gr_n.plot.barh(ax=ax[1])
ax[0].set_title("duration")
ax[1].set_title("n occurences");


gr2 = df.loc[(df.args_op_name == 'Add') & (df.dur > 10), ['dur', "name"]].groupby("name").sum().sort_values('dur')
gr2.plot.barh(figsize=(10, 4));


from onnxruntime import InferenceSession, RunOptions, SessionOptions
so = SessionOptions()
so.enable_profiling = True
sess = InferenceSession(onx.SerializeToString(), so)


for i in range(0, 111):
    sess.run(None, {'X': X.astype(numpy.float32)}, )


prof = sess.end_profiling()
prof

'onnxruntime_profile__2021-03-18_23-16-39.json'


with open(prof, "r") as f:
    js = json.load(f)
    
js[:3]

[{'cat': 'Session',
  'pid': 504784,
  'tid': 424180,
  'dur': 353,
  'ts': 6,
  'ph': 'X',
  'name': 'model_loading_array',
  'args': {}},
 {'cat': 'Session',
  'pid': 504784,
  'tid': 424180,
  'dur': 3921,
  'ts': 393,
  'ph': 'X',
  'name': 'session_initialization',
  'args': {}},
 {'cat': 'Node',
  'pid': 504784,
  'tid': 424180,
  'dur': 1,
  'ts': 37730,
  'ph': 'X',
  'name': 'Re_ReduceSumSquare_fence_before',
  'args': {'op_name': 'ReduceSumSquare'}}]


from pandas import DataFrame
from mlprodict.onnxrt.ops_whole.session import OnnxWholeSession

df = DataFrame(OnnxWholeSession.process_profiling(js))
df

	cat	pid	tid	dur	ts	ph	name	args_op_name	args_provider	args_graph_index	args_parameter_size	args_exec_plan_index	args_activation_size	args_output_size
0	Session	504784	424180	772	21	X	model_loading_array	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1	Session	504784	424180	4864	850	X	session_initialization	NaN	NaN	NaN	NaN	NaN	NaN	NaN
2	Node	504784	424180	4	28293	X	Re_ReduceSumSquare_fence_before	ReduceSumSquare	NaN	NaN	NaN	NaN	NaN	NaN
3	Node	504784	424180	4708	28305	X	Re_ReduceSumSquare_kernel_time	ReduceSumSquare	CPUExecutionProvider	0	0	0	8000000	400000
4	Node	504784	424180	0	33104	X	Re_ReduceSumSquare_fence_after	ReduceSumSquare	NaN	NaN	NaN	NaN	NaN	NaN
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
2550	Node	504784	424180	0	2092121	X	Ar_ArgMin_fence_before	ArgMin	NaN	NaN	NaN	NaN	NaN	NaN
2551	Node	504784	424180	3274	2092122	X	Ar_ArgMin_kernel_time	ArgMin	CPUExecutionProvider	5	0	5	3200000	800000
2552	Node	504784	424180	0	2095401	X	Ar_ArgMin_fence_after	ArgMin	NaN	NaN	NaN	NaN	NaN	NaN
2553	Session	504784	424180	11353	2084051	X	SequentialExecutor::Execute	NaN	NaN	NaN	NaN	NaN	NaN	NaN
2554	Session	504784	424180	11367	2084044	X	model_run	NaN	NaN	NaN	NaN	NaN	NaN	NaN

	cat	pid	tid	dur	ts	ph	name	args_op_name	args_provider	args_graph_index	args_parameter_size	args_exec_plan_index	args_activation_size	args_output_size
0	Session	504784	424180	353	6	X	model_loading_array	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1	Session	504784	424180	3921	393	X	session_initialization	NaN	NaN	NaN	NaN	NaN	NaN	NaN
2	Node	504784	424180	1	37730	X	Re_ReduceSumSquare_fence_before	ReduceSumSquare	NaN	NaN	NaN	NaN	NaN	NaN
3	Node	504784	424180	3118	37737	X	Re_ReduceSumSquare_kernel_time	ReduceSumSquare	CPUExecutionProvider	0	0	0	8000000	400000
4	Node	504784	424180	0	40868	X	Re_ReduceSumSquare_fence_after	ReduceSumSquare	NaN	NaN	NaN	NaN	NaN	NaN
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
2550	Node	504784	424180	0	2038167	X	Ar_ArgMin_fence_before	ArgMin	NaN	NaN	NaN	NaN	NaN	NaN
2551	Node	504784	424180	3276	2038168	X	Ar_ArgMin_kernel_time	ArgMin	CPUExecutionProvider	5	0	5	3200000	800000
2552	Node	504784	424180	0	2041449	X	Ar_ArgMin_fence_after	ArgMin	NaN	NaN	NaN	NaN	NaN	NaN
2553	Session	504784	424180	11386	2030066	X	SequentialExecutor::Execute	NaN	NaN	NaN	NaN	NaN	NaN	NaN
2554	Session	504784	424180	11401	2030058	X	model_run	NaN	NaN	NaN	NaN	NaN	NaN	NaN

Profiling KMeans with onnxruntime¶

Builds a KMeans¶

Json¶

Profiling¶

onnxruntime¶