Note
Click here to download the full example code
Benchmark, comparison scikit-learn - onnxruntime-training#
The benchmark compares the processing time between scikit-learn and onnxruntime-training on a linear regression and a neural network. It uses the model trained in Train a scikit-learn neural network with onnxruntime-training on GPU.
First comparison: neural network#
import warnings
from pprint import pprint
import time
import numpy
import matplotlib.pyplot as plt
from pandas import DataFrame
from onnxruntime import get_device
from pyquickhelper.pycode.profiling import profile, profile2graph
from sklearn.datasets import make_regression
from sklearn.model_selection import train_test_split
from sklearn.neural_network import MLPRegressor
from mlprodict.onnx_conv import to_onnx
from onnxcustom.utils.orttraining_helper import (
add_loss_output, get_train_initializer)
from onnxcustom.training.optimizers import OrtGradientOptimizer
X, y = make_regression(1000, n_features=100, bias=2)
X = X.astype(numpy.float32)
y = y.astype(numpy.float32)
X_train, X_test, y_train, y_test = train_test_split(X, y)
Benchmark function.
def benchmark(skl_model, train_session, name, verbose=True):
"""
:param skl_model: model from scikit-learn
:param train_session: instance of OrtGradientOptimizer
:param name: experiment name
:param verbose: to debug
"""
print("[benchmark] %s" % name)
begin = time.perf_counter()
skl_model.fit(X, y)
duration_skl = time.perf_counter() - begin
length_skl = len(skl_model.loss_curve_)
print("[benchmark] skl=%r iterations - %r seconds" % (
length_skl, duration_skl))
begin = time.perf_counter()
train_session.fit(X, y)
duration_ort = time.perf_counter() - begin
length_ort = len(train_session.train_losses_)
print("[benchmark] ort=%r iterations - %r seconds" % (
length_ort, duration_ort))
return dict(skl=duration_skl, ort=duration_ort, name=name,
iter_skl=length_skl, iter_ort=length_ort,
losses_skl=skl_model.loss_curve_,
losses_ort=train_session.train_losses_)
Common parameters and model
batch_size = 15
max_iter = 100
nn = MLPRegressor(hidden_layer_sizes=(50, 10), max_iter=max_iter,
solver='sgd', learning_rate_init=5e-4, alpha=0,
n_iter_no_change=max_iter * 3, batch_size=batch_size,
nesterovs_momentum=False, momentum=0,
learning_rate='invscaling')
with warnings.catch_warnings():
warnings.simplefilter('ignore')
nn.fit(X_train, y_train)
Conversion to ONNX and trainer initialization
onx = to_onnx(nn, X_train[:1].astype(numpy.float32), target_opset=15)
onx_train = add_loss_output(onx)
weights = get_train_initializer(onx)
pprint(list((k, v[0].shape) for k, v in weights.items()))
train_session = OrtGradientOptimizer(
onx_train, list(weights), device='cpu', learning_rate=1e-5,
warm_start=False, max_iter=max_iter, batch_size=batch_size)
benches = [benchmark(nn, train_session, name='NN-CPU')]
Out:
[('coefficient', (100, 50)),
('intercepts', (1, 50)),
('coefficient1', (50, 10)),
('intercepts1', (1, 10)),
('coefficient2', (10, 1)),
('intercepts2', (1, 1))]
[benchmark] NN-CPU
somewhere/workspace/onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:702: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.
warnings.warn(
[benchmark] skl=100 iterations - 16.660431453958154 seconds
[benchmark] ort=100 iterations - 6.080705474014394 seconds
Profiling#
def clean_name(text):
pos = text.find('onnxruntime')
if pos >= 0:
return text[pos:]
pos = text.find('onnxcustom')
if pos >= 0:
return text[pos:]
pos = text.find('site-packages')
if pos >= 0:
return text[pos:]
return text
ps = profile(lambda: benchmark(nn, train_session, name='NN-CPU'))[0]
root, nodes = profile2graph(ps, clean_text=clean_name)
text = root.to_text()
print(text)
Out:
[benchmark] NN-CPU
somewhere/workspace/onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:702: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.
warnings.warn(
[benchmark] skl=100 iterations - 18.625929814996198 seconds
[benchmark] ort=100 iterations - 6.248123665980529 seconds
filter -- 18 18 -- 0.00011 0.00025 -- /usr/local/lib/python3.9/logging/__init__.py:787:filter (filter)
filter -- 12 12 -- 0.00003 0.00003 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sphinx/util/logging.py:350:filter (filter)
filter -- 6 6 -- 0.00006 0.00009 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sphinx/util/logging.py:483:filter (filter)
<built-in method builtins.isinstance> -- 18 18 -- 0.00002 0.00002 -- ~:0:<built-in method builtins.isinstance> (<built-in method builtins.isinstance>) +++
<built-in method builtins.hasattr> -- 18 18 -- 0.00003 0.00003 -- ~:0:<built-in method builtins.hasattr> (<built-in method builtins.hasattr>) +++
acquire -- 30 30 -- 0.00010 0.00016 -- /usr/local/lib/python3.9/logging/__init__.py:892:acquire (acquire)
<method 'acquire' of '_thread.RLock' objects> -- 30 30 -- 0.00006 0.00006 -- ~:0:<method 'acquire' of '_thread.RLock' objects> (<method 'acquire' of '_thread.RLock' objects>)
release -- 30 30 -- 0.00008 0.00011 -- /usr/local/lib/python3.9/logging/__init__.py:899:release (release)
<method 'release' of '_thread.RLock' objects> -- 30 30 -- 0.00002 0.00002 -- ~:0:<method 'release' of '_thread.RLock' objects> (<method 'release' of '_thread.RLock' objects>)
emit -- 12 12 -- 0.00012 0.00149 -- /usr/local/lib/python3.9/logging/__init__.py:1067:emit (emit)
format -- 12 12 -- 0.00006 0.00080 -- /usr/local/lib/python3.9/logging/__init__.py:912:format (format)
format -- 12 12 -- 0.00014 0.00074 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sphinx/util/logging.py:528:format (format)
format -- 12 12 -- 0.00011 0.00055 -- /usr/local/lib/python3.9/logging/__init__.py:646:format (format)
usesTime -- 12 12 -- 0.00003 0.00012 -- /usr/local/lib/python3.9/logging/__init__.py:624:usesTime (usesTime)
usesTime -- 12 12 -- 0.00005 0.00008 -- /usr/local/lib/python3.9/logging/__init__.py:417:usesTime (usesTime)
<method 'find' of 'str' objects> -- 12 12 -- 0.00003 0.00003 -- ~:0:<method 'find' of 'str' objects> (<method 'find' of 'str' objects>)
formatMessage -- 12 12 -- 0.00003 0.00012 -- /usr/local/lib/python3.9/logging/__init__.py:630:formatMessage (formatMessage)
format -- 12 12 -- 0.00003 0.00010 -- /usr/local/lib/python3.9/logging/__init__.py:428:format (format)
_format -- 12 12 -- 0.00007 0.00007 -- /usr/local/lib/python3.9/logging/__init__.py:425:_format (_format)
getMessage -- 12 12 -- 0.00009 0.00019 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sphinx/util/logging.py:88:getMessage (getMessage)
getMessage -- 12 12 -- 0.00008 0.00008 -- /usr/local/lib/python3.9/logging/__init__.py:354:getMessage (getMessage)
<built-in method builtins.getattr> -- 12 12 -- 0.00002 0.00002 -- ~:0:<built-in method builtins.getattr> (<built-in method builtins.getattr>) +++
colorize -- 2 2 -- 0.00002 0.00003 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sphinx/util/console.py:81:colorize (colorize)
escseq -- 4 4 -- 0.00001 0.00001 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sphinx/util/console.py:82:escseq (escseq)
<built-in method builtins.getattr> -- 12 12 -- 0.00001 0.00001 -- ~:0:<built-in method builtins.getattr> (<built-in method builtins.getattr>) +++
flush -- 12 12 -- 0.00010 0.00049 -- /usr/local/lib/python3.9/logging/__init__.py:1056:flush (flush)
acquire -- 12 12 -- 0.00003 0.00005 -- /usr/local/lib/python3.9/logging/__init__.py:892:acquire (acquire) +++
release -- 12 12 -- 0.00004 0.00005 -- /usr/local/lib/python3.9/logging/__init__.py:899:release (release) +++
flush -- 6 6 -- 0.00003 0.00028 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sphinx/util/logging.py:554:flush (flush)
<method 'flush' of '_io.TextIOWrapper' objects> -- 6 6 -- 0.00024 0.00024 -- ~:0:<method 'flush' of '_io.TextIOWrapper' objects> (<method 'flush' of '_io.TextIOWrapper' objects>)
<built-in method builtins.hasattr> -- 12 12 -- 0.00002 0.00002 -- ~:0:<built-in method builtins.hasattr> (<built-in method builtins.hasattr>) +++
write -- 6 6 -- 0.00003 0.00004 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sphinx/util/logging.py:546:write (write)
write -- 6 6 -- 0.00003 0.00004 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sphinx/util/logging.py:564:write (write)
isEnabledFor -- 12 12 -- 0.00003 0.00003 -- /usr/local/lib/python3.9/logging/__init__.py:1677:isEnabledFor (isEnabledFor)
__init__ -- 2 2 -- 0.00002 0.00002 -- /usr/local/lib/python3.9/warnings.py:403:__init__ (__init__)
<lambda> -- 1 1 -- 0.00001 24.87718 -- onnxcustom/onnxcustom_UT_39_std/_doc/examples/plot_orttraining_benchmark.py:124:<lambda> (<lambda>)
benchmark -- 1 1 -- 0.00016 24.87717 -- onnxcustom/onnxcustom_UT_39_std/_doc/examples/plot_orttraining_benchmark.py:46:benchmark (benchmark)
fit -- 1 1 -- 0.00894 6.24807 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/optimizers.py:79:fit (fit)
__init__ -- 1 1 -- 0.00007 0.00015 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/data_loader.py:31:__init__ (__init__)
get_ort_device -- 1 1 -- 0.00000 0.00000 -- onnxruntime_helper.py:63:get_ort_device (get_ort_device)
numpy_to_ort_value -- 2 2 -- 0.00002 0.00005 -- onnxruntime_helper.py:134:numpy_to_ort_value (numpy_to_ort_value) +++
<listcomp> -- 1 1 -- 0.00004 0.00004 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/optimizers.py:96:<listcomp> (<listcomp>)
<listcomp> -- 1 1 -- 0.00002 0.00002 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/optimizers.py:131:<listcomp> (<listcomp>)
<listcomp> -- 1 1 -- 0.00001 0.00001 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/optimizers.py:132:<listcomp> (<listcomp>)
_iteration -- 100 100 -- 5.15099 6.20589 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/optimizers.py:195:_iteration (_iteration)
iter_bind -- 6800 6800 -- 0.08629 1.00053 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/data_loader.py:188:iter_bind (iter_bind)
_next_iter -- 6700 6700 -- 0.04694 0.46129 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/data_loader.py:98:_next_iter (_next_iter)
<method 'randint'...mState' objects> -- 6700 6700 -- 0.39202 0.39202 -- ~:0:<method 'randint' of 'numpy.random.mtrand.RandomState' objects> (<method 'randint' of 'numpy.random.mtrand.RandomState' objects>)
<built-in method builtins.len> -- 6700 6700 -- 0.01383 0.02234 -- ~:0:<built-in method builtins.len> (<built-in method builtins.len>) +++
local_bind -- 6700 6700 -- 0.39891 0.39891 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/data_loader.py:209:local_bind (local_bind)
<built-in method builtins.len> -- 7100 7100 -- 0.03065 0.05404 -- ~:0:<built-in method builtins.len> (<built-in method builtins.len>) +++
_bind_input_ortvalue -- 100 100 -- 0.00223 0.00236 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/optimizers.py:167:_bind_input_ortvalue (_bind_input_ortvalue)
<built-in method builtins.isinstance> -- 200 200 -- 0.00014 0.00014 -- ~:0:<built-in method builtins.isinstance> (<built-in method builtins.isinstance>) +++
<method 'mean' of 'numpy.ndarray' objects> -- 100 100 -- 0.00092 0.02040 -- ~:0:<method 'mean' of 'numpy.ndarray' objects> (<method 'mean' of 'numpy.ndarray' objects>) +++
<built-in method numpy.array> -- 100 100 -- 0.02090 0.02090 -- ~:0:<built-in method numpy.array> (<built-in method numpy.array>) +++
<method 'append' of 'list' objects> -- 6700 6700 -- 0.01070 0.01070 -- ~:0:<method 'append' of 'list' objects> (<method 'append' of 'list' objects>) +++
_create_training_session -- 1 1 -- 0.00027 0.02200 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/optimizers.py:277:_create_training_session (_create_training_session)
<dictcomp> -- 1 1 -- 0.00001 0.00001 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/optimizers.py:325:<dictcomp> (<dictcomp>)
<dictcomp> -- 1 1 -- 0.00000 0.00000 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/optimizers.py:327:<dictcomp> (<dictcomp>)
__init__ -- 1 1 -- 0.02116 0.02129 -- onnxruntime/capi/training/training_session.py:19:__init__ (__init__)
check_and_normalize_provider_args -- 1 1 -- 0.00006 0.00011 -- onnxruntime/capi/onnxruntime_inference_collection.py:24:check_and_normalize_provider_args (check_and_normalize_provider_args)
set_provider_options -- 1 1 -- 0.00002 0.00002 -- onnxruntime/capi/onnxruntime_inference_collection.py:52:set_provider_options (set_provider_options)
<dictcomp> -- 1 1 -- 0.00000 0.00000 -- onnxruntime/capi/onnxruntime_inference_collection.py:63:<dictcomp> (<dictcomp>)
__init__ -- 1 1 -- 0.00001 0.00001 -- onnxruntime/capi/onnxruntime_inference_collection.py:107:__init__ (__init__)
device_to_providers -- 1 1 -- 0.00002 0.00003 -- onnxruntime_helper.py:150:device_to_providers (device_to_providers)
<method 'SerializeToS...e.CMessage' objects> -- 1 1 -- 0.00040 0.00040 -- ~:0:<method 'SerializeToString' of 'google.protobuf.pyext._message.CMessage' objects> (<method 'SerializeToString' of 'google.protobuf.pyext._message.CMessage' objects>)
get_state -- 1 1 -- 0.00002 0.00056 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/optimizers.py:342:get_state (get_state)
get_state -- 1 1 -- 0.00054 0.00054 -- onnxruntime/capi/training/training_session.py:52:get_state (get_state) +++
set_state -- 1 1 -- 0.00001 0.00012 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/optimizers.py:374:set_state (set_state)
load_state -- 1 1 -- 0.00011 0.00011 -- onnxruntime/capi/training/training_session.py:64:load_state (load_state)
value -- 101 101 -- 0.00020 0.00020 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/sgd_learning_rate.py:186:value (value)
init_learning_rate -- 1 1 -- 0.00001 0.00001 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/sgd_learning_rate.py:205:init_learning_rate (init_learning_rate)
update_learning_rate -- 100 100 -- 0.00429 0.00429 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/sgd_learning_rate.py:226:update_learning_rate (update_learning_rate)
get_inputs -- 1 1 -- 0.00000 0.00000 -- onnxruntime/capi/onnxruntime_inference_collection.py:117:get_inputs (get_inputs)
get_outputs -- 1 1 -- 0.00000 0.00000 -- onnxruntime/capi/onnxruntime_inference_collection.py:121:get_outputs (get_outputs)
io_binding -- 1 1 -- 0.00001 0.00003 -- onnxruntime/capi/onnxruntime_inference_collection.py:272:io_binding (io_binding)
__init__ -- 1 1 -- 0.00003 0.00003 -- onnxruntime/capi/onnxruntime_inference_collection.py:427:__init__ (__init__)
__del__ -- 1 1 -- 0.00001 0.00001 -- onnxruntime/capi/training/training_session.py:48:__del__ (__del__)
get_state -- 1 1 -- 0.00012 0.00012 -- onnxruntime/capi/training/training_session.py:52:get_state (get_state) +++
numpy_to_ort_value -- 100 100 -- 0.00060 0.00319 -- onnxruntime_helper.py:134:numpy_to_ort_value (numpy_to_ort_value) +++
<method 'randn' of 'num....RandomState' objects> -- 6 6 -- 0.00102 0.00102 -- ~:0:<method 'randn' of 'numpy.random.mtrand.RandomState' objects> (<method 'randn' of 'numpy.random.mtrand.RandomState' objects>)
<built-in method numpy.array> -- 100 100 -- 0.00127 0.00127 -- ~:0:<built-in method numpy.array> (<built-in method numpy.array>) +++
<method 'append' of 'list' objects> -- 100 100 -- 0.00011 0.00011 -- ~:0:<method 'append' of 'list' objects> (<method 'append' of 'list' objects>) +++
fit -- 1 1 -- 0.00003 18.62591 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:745:fit (fit)
_fit -- 1 1 -- 0.00019 18.62589 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:377:_fit (_fit)
any -- 1 1 -- 0.00002 0.00013 -- <__array_function__ internals>:177:any (any)
_any_dispatcher -- 1 1 -- 0.00000 0.00000 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py:2300:_any_dispatcher (_any_dispatcher)
<built-in method nu...nt_array_function> -- 1 1 -- 0.00002 0.00011 -- ~:0:<built-in method numpy.core._multiarray_umath.implement_array_function> (<built-in method numpy.core._multiarray_umath.implement_array_function>) +++
_initialize -- 1 1 -- 0.00008 0.00086 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:320:_initialize (_initialize)
is_classifier -- 1 1 -- 0.00000 0.00000 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/base.py:1001:is_classifier (is_classifier)
_init_coef -- 3 3 -- 0.00015 0.00077 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:360:_init_coef (_init_coef)
<method 'uniform'...mState' objects> -- 6 6 -- 0.00054 0.00054 -- ~:0:<method 'uniform' of 'numpy.random.mtrand.RandomState' objects> (<method 'uniform' of 'numpy.random.mtrand.RandomState' objects>)
<listcomp> -- 1 1 -- 0.00001 0.00003 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:417:<listcomp> (<listcomp>)
<listcomp> -- 1 1 -- 0.00001 0.00004 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:422:<listcomp> (<listcomp>)
_validate_hyperparameters -- 1 1 -- 0.00003 0.00003 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:455:_validate_hyperparameters (_validate_hyperparameters)
_fit_stochastic -- 1 1 -- 0.45483 18.62231 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:563:_fit_stochastic (_fit_stochastic)
clip -- 1 1 -- 0.00001 0.00027 -- <__array_function__ internals>:177:clip (clip)
_clip_dispatcher -- 1 1 -- 0.00000 0.00000 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py:2079:_clip_dispatcher (_clip_dispatcher)
<built-in method ..._array_function> -- 1 1 -- 0.00001 0.00026 -- ~:0:<built-in method numpy.core._multiarray_umath.implement_array_function> (<built-in method numpy.core._multiarray_umath.implement_array_function>) +++
_backprop -- 6700 6700 -- 1.09085 13.76888 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:241:_backprop (_backprop)
dot -- 20100 20100 -- 0.12184 0.50699 -- <__array_function__ internals>:177:dot (dot)
dot -- 20100 20100 -- 0.02143 0.02143 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/multiarray.py:736:dot (dot)
<built-in metho...rray_function> -- 20100 20100 -- 0.36372 0.36372 -- ~:0:<built-in method numpy.core._multiarray_umath.implement_array_function> (<built-in method numpy.core._multiarray_umath.implement_array_function>) +++
inplace_relu_derivative -- 13400 13400 -- 0.74868 0.74868 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_base.py:132:inplace_relu_derivative (inplace_relu_derivative)
squared_loss -- 6700 6700 -- 0.45299 1.52005 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_base.py:158:squared_loss (squared_loss)
<method 'mean' ...rray' objects> -- 6700 6700 -- 0.04647 1.06707 -- ~:0:<method 'mean' of 'numpy.ndarray' objects> (<method 'mean' of 'numpy.ndarray' objects>) +++
_forward_pass -- 6700 6700 -- 0.88413 2.65981 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:119:_forward_pass (_forward_pass)
inplace_identity -- 6700 6700 -- 0.00726 0.00726 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_base.py:13:inplace_identity (inplace_identity)
inplace_relu -- 13400 13400 -- 0.58756 0.58756 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_base.py:47:inplace_relu (inplace_relu)
safe_sparse_dot -- 20100 20100 -- 1.10206 1.18086 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/extmath.py:119:safe_sparse_dot (safe_sparse_dot) +++
_compute_loss_grad -- 20100 20100 -- 2.32738 6.59576 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:177:_compute_loss_grad (_compute_loss_grad)
mean -- 20100 20100 -- 0.13067 3.04094 -- <__array_function__ internals>:177:mean (mean)
_mean_dispatcher -- 20100 20100 -- 0.02538 0.02538 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py:3351:_mean_dispatcher (_mean_dispatcher)
<built-in met...ay_function> -- 20100 20100 -- 0.12035 2.88490 -- ~:0:<built-in method numpy.core._multiarray_umath.implement_array_function> (<built-in method numpy.core._multiarray_umath.implement_array_function>) +++
safe_sparse_dot -- 20100 20100 -- 1.14765 1.22744 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/extmath.py:119:safe_sparse_dot (safe_sparse_dot) +++
safe_sparse_dot -- 13400 13400 -- 0.53313 0.58644 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/extmath.py:119:safe_sparse_dot (safe_sparse_dot) +++
<method 'ravel' o...darray' objects> -- 20100 20100 -- 0.06029 0.06029 -- ~:0:<method 'ravel' of 'numpy.ndarray' objects> (<method 'ravel' of 'numpy.ndarray' objects>)
_update_no_improvement_count -- 100 100 -- 0.00102 0.00102 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:716:_update_no_improvement_count (_update_no_improvement_count)
update_params -- 6700 6700 -- 0.80567 3.67259 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_stochastic_optimizers.py:29:update_params (update_params)
<genexpr> -- 46900 46900 -- 0.05928 0.05928 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_stochastic_optimizers.py:43:<genexpr> (<genexpr>)
_get_updates -- 6700 6700 -- 0.11860 2.80765 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_stochastic_optimizers.py:169:_get_updates (_get_updates)
<listcomp> -- 6700 6700 -- 2.68904 2.68904 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_stochastic_optimizers.py:183:<listcomp> (<listcomp>)
__init__ -- 1 1 -- 0.00002 0.00054 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_stochastic_optimizers.py:121:__init__ (__init__)
__init__ -- 1 1 -- 0.00001 0.00001 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_stochastic_optimizers.py:25:__init__ (__init__)
<listcomp> -- 1 1 -- 0.00004 0.00052 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_stochastic_optimizers.py:136:<listcomp> (<listcomp>)
zeros_like -- 6 6 -- 0.00003 0.00048 -- <__array_function__ internals>:177:zeros_like (zeros_like)
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<built-in met...ay_function> -- 6 6 -- 0.00004 0.00045 -- ~:0:<built-in method numpy.core._multiarray_umath.implement_array_function> (<built-in method numpy.core._multiarray_umath.implement_array_function>) +++
iteration_ends -- 100 100 -- 0.00143 0.00143 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_stochastic_optimizers.py:138:iteration_ends (iteration_ends)
_safe_indexing -- 6700 6700 -- 0.09052 0.59403 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/__init__.py:290:_safe_indexing (_safe_indexing) +++
shuffle -- 100 100 -- 0.00150 0.05132 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/__init__.py:585:shuffle (shuffle)
resample -- 100 100 -- 0.00409 0.04982 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/__init__.py:435:resample (resample)
<listcomp> -- 100 100 -- 0.00057 0.00099 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/__init__.py:576:<listcomp> (<listcomp>)
isspmatrix -- 100 100 -- 0.00022 0.00042 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/scipy/sparse/_base.py:1294:isspmatrix (isspmatrix) +++
<listcomp> -- 100 100 -- 0.00048 0.00790 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/__init__.py:577:<listcomp> (<listcomp>)
_safe_indexing -- 100 100 -- 0.00131 0.00742 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/__init__.py:290:_safe_indexing (_safe_indexing) +++
check_consistent_length -- 100 100 -- 0.00143 0.02154 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/validation.py:373:check_consistent_length (check_consistent_length) +++
check_random_state -- 100 100 -- 0.00086 0.00266 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/validation.py:1161:check_random_state (check_random_state) +++
<method 'shuffl...tate' objects> -- 100 100 -- 0.01018 0.01018 -- ~:0:<method 'shuffle' of 'numpy.random.mtrand.RandomState' objects> (<method 'shuffle' of 'numpy.random.mtrand.RandomState' objects>)
<built-in method numpy.arange> -- 100 100 -- 0.00198 0.00198 -- ~:0:<built-in method numpy.arange> (<built-in method numpy.arange>) +++
<built-in metho...ltins.hasattr> -- 100 100 -- 0.00028 0.00028 -- ~:0:<built-in method builtins.hasattr> (<built-in method builtins.hasattr>) +++
<built-in method builtins.len> -- 200 200 -- 0.00021 0.00021 -- ~:0:<built-in method builtins.len> (<built-in method builtins.len>) +++
gen_batches -- 6800 6800 -- 0.07472 0.07562 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/__init__.py:695:gen_batches (gen_batches)
<built-in method ...tins.isinstance> -- 100 100 -- 0.00040 0.00090 -- ~:0:<built-in method builtins.isinstance> (<built-in method builtins.isinstance>) +++
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check_consistent_length -- 1 1 -- 0.00001 0.00027 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/validation.py:373:check_consistent_length (check_consistent_length) +++
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check_array -- 1 1 -- 0.00006 0.00045 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/validation.py:619:check_array (check_array) +++
check_random_state -- 1 1 -- 0.00001 0.00001 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/validation.py:1161:check_random_state (check_random_state) +++
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<genexpr> -- 7 7 -- 0.00015 0.00037 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:447:<genexpr> (<genexpr>)
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<method 'redu...nc' objects> -- 6 6 -- 0.00017 0.00017 -- ~:0:<method 'reduce' of 'numpy.ufunc' objects> (<method 'reduce' of 'numpy.ufunc' objects>) +++
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<built-in method numpy.co...th.normalize_axis_index> -- 33800 33800 -- 0.06268 0.06268 -- ~:0:<built-in method numpy.core._multiarray_umath.normalize_axis_index> (<built-in method numpy.core._multiarray_umath.normalize_axis_index>)
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<method 'reduce' of 'numpy.ufunc' objects> -- 26900 26900 -- 0.87406 0.87406 -- ~:0:<method 'reduce' of 'numpy.ufunc' objects> (<method 'reduce' of 'numpy.ufunc' objects>) +++
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<dictcomp> -- 3 3 -- 0.00001 0.00001 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py:70:<dictcomp> (<dictcomp>)
<method 'reduce' of 'numpy.ufunc' objects> -- 3 3 -- 0.00055 0.00055 -- ~:0:<method 'reduce' of 'numpy.ufunc' objects> (<method 'reduce' of 'numpy.ufunc' objects>) +++
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isspmatrix -- 6800 6800 -- 0.01097 0.01948 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/scipy/sparse/_base.py:1294:isspmatrix (isspmatrix) +++
<built-in method builtins.isinstance> -- 6800 6800 -- 0.00479 0.00479 -- ~:0:<built-in method builtins.isinstance> (<built-in method builtins.isinstance>) +++
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<method 'keys' of 'dict' objects> -- 6800 6800 -- 0.00981 0.00981 -- ~:0:<method 'keys' of 'dict' objects> (<method 'keys' of 'dict' objects>)
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<built-in method builtins.hasattr> -- 13600 13600 -- 0.02267 0.02267 -- ~:0:<built-in method builtins.hasattr> (<built-in method builtins.hasattr>) +++
safe_sparse_dot -- 53600 53600 -- 2.78284 2.99475 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/extmath.py:119:safe_sparse_dot (safe_sparse_dot)
isspmatrix -- 53600 53600 -- 0.11635 0.21191 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/scipy/sparse/_base.py:1294:isspmatrix (isspmatrix) +++
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unique -- 101 101 -- 0.00066 0.01404 -- <__array_function__ internals>:177:unique (unique)
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<built-in method numpy.co...mplement_array_function> -- 101 101 -- 0.00095 0.01325 -- ~:0:<built-in method numpy.core._multiarray_umath.implement_array_function> (<built-in method numpy.core._multiarray_umath.implement_array_function>) +++
<listcomp> -- 101 101 -- 0.00050 0.00625 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/utils/validation.py:384:<listcomp> (<listcomp>)
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simplefilter -- 2 2 -- 0.00002 0.00009 -- /usr/local/lib/python3.9/warnings.py:165:simplefilter (simplefilter)
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_log -- 6 6 -- 0.00007 0.00363 -- /usr/local/lib/python3.9/logging/__init__.py:1553:_log (_log)
findCaller -- 6 6 -- 0.00012 0.00021 -- /usr/local/lib/python3.9/logging/__init__.py:1502:findCaller (findCaller)
<lambda> -- 6 6 -- 0.00003 0.00004 -- /usr/local/lib/python3.9/logging/__init__.py:156:<lambda> (<lambda>)
normcase -- 12 12 -- 0.00003 0.00004 -- /usr/local/lib/python3.9/posixpath.py:52:normcase (normcase)
<built-in met...osix.fspath> -- 12 12 -- 0.00001 0.00001 -- ~:0:<built-in method posix.fspath> (<built-in method posix.fspath>) +++
<built-in metho...ltins.hasattr> -- 12 12 -- 0.00001 0.00001 -- ~:0:<built-in method builtins.hasattr> (<built-in method builtins.hasattr>) +++
makeRecord -- 6 6 -- 0.00008 0.00105 -- /usr/local/lib/python3.9/logging/__init__.py:1538:makeRecord (makeRecord)
__init__ -- 6 6 -- 0.00043 0.00097 -- /usr/local/lib/python3.9/logging/__init__.py:278:__init__ (__init__)
getLevelName -- 6 6 -- 0.00006 0.00007 -- /usr/local/lib/python3.9/logging/__init__.py:119:getLevelName (getLevelName)
<method 'ge...' objects> -- 12 12 -- 0.00001 0.00001 -- ~:0:<method 'get' of 'dict' objects> (<method 'get' of 'dict' objects>) +++
current_process -- 6 6 -- 0.00001 0.00001 -- /usr/local/lib/python3.9/multiprocessing/process.py:37:current_process (current_process)
name -- 6 6 -- 0.00001 0.00001 -- /usr/local/lib/python3.9/multiprocessing/process.py:189:name (name)
splitext -- 6 6 -- 0.00004 0.00013 -- /usr/local/lib/python3.9/posixpath.py:117:splitext (splitext)
_splitext -- 6 6 -- 0.00006 0.00008 -- /usr/local/lib/python3.9/genericpath.py:121:_splitext (_splitext)
<method '...objects> -- 12 12 -- 0.00002 0.00002 -- ~:0:<method 'rfind' of 'str' objects> (<method 'rfind' of 'str' objects>) +++
basename -- 6 6 -- 0.00007 0.00012 -- /usr/local/lib/python3.9/posixpath.py:140:basename (basename)
_get_sep -- 6 6 -- 0.00001 0.00002 -- /usr/local/lib/python3.9/posixpath.py:41:_get_sep (_get_sep)
name -- 6 6 -- 0.00001 0.00001 -- /usr/local/lib/python3.9/threading.py:1053:name (name)
current_thread -- 6 6 -- 0.00002 0.00003 -- /usr/local/lib/python3.9/threading.py:1318:current_thread (current_thread)
handle -- 6 6 -- 0.00003 0.00229 -- /usr/local/lib/python3.9/logging/__init__.py:1579:handle (handle)
filter -- 6 6 -- 0.00001 0.00001 -- /usr/local/lib/python3.9/logging/__init__.py:787:filter (filter) +++
callHandlers -- 6 6 -- 0.00009 0.00224 -- /usr/local/lib/python3.9/logging/__init__.py:1633:callHandlers (callHandlers)
handle -- 12 12 -- 0.00011 0.00215 -- /usr/local/lib/python3.9/logging/__init__.py:935:handle (handle)
filter -- 12 12 -- 0.00009 0.00024 -- /usr/local/lib/python3.9/logging/__init__.py:787:filter (filter) +++
acquire -- 12 12 -- 0.00005 0.00008 -- /usr/local/lib/python3.9/logging/__init__.py:892:acquire (acquire) +++
release -- 12 12 -- 0.00003 0.00003 -- /usr/local/lib/python3.9/logging/__init__.py:899:release (release) +++
emit -- 6 6 -- 0.00005 0.00055 -- /usr/local/lib/python3.9/logging/__init__.py:1067:emit (emit) +++
emit -- 6 6 -- 0.00014 0.00114 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sphinx/util/logging.py:150:emit (emit)
acquire -- 6 6 -- 0.00002 0.00002 -- /usr/local/lib/python3.9/logging/__init__.py:892:acquire (acquire) +++
release -- 6 6 -- 0.00002 0.00002 -- /usr/local/lib/python3.9/logging/__init__.py:899:release (release) +++
emit -- 6 6 -- 0.00006 0.00094 -- /usr/local/lib/python3.9/logging/__init__.py:1067:emit (emit) +++
isEnabledFor -- 6 6 -- 0.00001 0.00001 -- /usr/local/lib/python3.9/logging/__init__.py:1677:isEnabledFor (isEnabledFor) +++
isEnabledFor -- 6 6 -- 0.00002 0.00004 -- /usr/local/lib/python3.9/logging/__init__.py:1834:isEnabledFor (isEnabledFor)
isEnabledFor -- 6 6 -- 0.00002 0.00002 -- /usr/local/lib/python3.9/logging/__init__.py:1677:isEnabledFor (isEnabledFor) +++
process -- 6 6 -- 0.00007 0.00008 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sphinx/util/logging.py:130:process (process)
get_state -- 2 2 -- 0.00065 0.00065 -- onnxruntime/capi/training/training_session.py:52:get_state (get_state)
numpy_to_ort_value -- 102 102 -- 0.00062 0.00325 -- onnxruntime_helper.py:134:numpy_to_ort_value (numpy_to_ort_value)
<built-in method onnxruntim...state.ortvalue_from_numpy> -- 102 102 -- 0.00263 0.00263 -- ~:0:<built-in method onnxruntime.capi.onnxruntime_pybind11_state.ortvalue_from_numpy> (<built-in method onnxruntime.capi.onnxruntime_pybind11_state.ortvalue_from_numpy>)
<built-in method builtins.len> -- 14329 14329 -- 0.04497 0.07687 -- ~:0:<built-in method builtins.len> (<built-in method builtins.len>)
__len__ -- 13600 13600 -- 0.03189 0.03189 -- onnxcustom/onnxcustom_UT_39_std/_doc/sphinxdoc/source/onnxcustom/training/data_loader.py:94:__len__ (__len__)
<method 'astype' of 'numpy.ndarray' objects> -- 12 12 -- 0.00017 0.00017 -- ~:0:<method 'astype' of 'numpy.ndarray' objects> (<method 'astype' of 'numpy.ndarray' objects>)
<built-in method numpy.array> -- 201 201 -- 0.02219 0.02219 -- ~:0:<built-in method numpy.array> (<built-in method numpy.array>)
<method 'append' of 'list' objects> -- 6906 6906 -- 0.01099 0.01099 -- ~:0:<method 'append' of 'list' objects> (<method 'append' of 'list' objects>)
<method 'mean' of 'numpy.ndarray' objects> -- 6800 6800 -- 0.04739 1.08747 -- ~:0:<method 'mean' of 'numpy.ndarray' objects> (<method 'mean' of 'numpy.ndarray' objects>)
_mean -- 6800 6800 -- 0.51550 1.04008 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/_methods.py:162:_mean (_mean) +++
<built-in method builtins.hasattr> -- 27687 27687 -- 0.04610 0.04610 -- ~:0:<built-in method builtins.hasattr> (<built-in method builtins.hasattr>)
<built-in method builtins.isinstance> -- 135379 135379 -- 0.22862 0.23204 -- ~:0:<built-in method builtins.isinstance> (<built-in method builtins.isinstance>)
__instancecheck__ -- 311 311 -- 0.00059 0.00342 -- /usr/local/lib/python3.9/abc.py:96:__instancecheck__ (__instancecheck__)
<built-in method _abc._abc_instancecheck> -- 311 311 -- 0.00193 0.00283 -- ~:0:<built-in method _abc._abc_instancecheck> (<built-in method _abc._abc_instancecheck>)
__subclasscheck__ -- 104 104 -- 0.00031 0.00090 -- /usr/local/lib/python3.9/abc.py:100:__subclasscheck__ (__subclasscheck__)
<built-in method _abc._abc_subclasscheck> -- 104 104 -- 0.00059 0.00059 -- ~:0:<built-in method _abc._abc_subclasscheck> (<built-in method _abc._abc_subclasscheck>)
<built-in method numpy.empty> -- 107 107 -- 0.00078 0.00078 -- ~:0:<built-in method numpy.empty> (<built-in method numpy.empty>)
<built-in method numpy.arange> -- 101 101 -- 0.00200 0.00200 -- ~:0:<built-in method numpy.arange> (<built-in method numpy.arange>)
<built-in method numpy.core._...th.implement_array_function> -- 40311 40325 -- 0.48526 3.26328 -- ~:0:<built-in method numpy.core._multiarray_umath.implement_array_function> (<built-in method numpy.core._multiarray_umath.implement_array_function>)
clip -- 1 1 -- 0.00001 0.00026 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py:2083:clip (clip)
_wrapfunc -- 1 1 -- 0.00001 0.00025 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py:51:_wrapfunc (_wrapfunc)
_wrapit -- 1 1 -- 0.00003 0.00023 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py:38:_wrapit (_wrapit)
<method 'clip' of 'numpy.ndarray' objects> -- 1 1 -- 0.00001 0.00020 -- ~:0:<method 'clip' of 'numpy.ndarray' objects> (<method 'clip' of 'numpy.ndarray' objects>)
_clip -- 1 1 -- 0.00002 0.00019 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/_methods.py:125:_clip (_clip)
_clip_dep_is_scalar_nan -- 2 2 -- 0.00007 0.00013 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/_methods.py:91:_clip_dep_is_scalar_nan (_clip_dep_is_scalar_nan)
ndim -- 2 2 -- 0.00001 0.00006 -- <__array_function__ internals>:177:ndim (ndim)
_ndim_dispatcher -- 2 2 -- 0.00000 0.00000 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py:3160:_ndim_dispatcher (_ndim_dispatcher)
_clip_dep_is_byte_swapped -- 2 2 -- 0.00001 0.00001 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/_methods.py:101:_clip_dep_is_byte_swapped (_clip_dep_is_byte_swapped)
_clip_dep_invoke_with_casting -- 1 1 -- 0.00002 0.00002 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/_methods.py:106:_clip_dep_invoke_with_casting (_clip_dep_invoke_with_casting)
sum -- 2 2 -- 0.00002 0.00057 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py:2160:sum (sum)
_wrapreduction -- 2 2 -- 0.00003 0.00055 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py:69:_wrapreduction (_wrapreduction) +++
any -- 1 1 -- 0.00001 0.00009 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py:2305:any (any)
_wrapreduction -- 1 1 -- 0.00003 0.00008 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py:69:_wrapreduction (_wrapreduction) +++
ndim -- 2 2 -- 0.00003 0.00004 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py:3164:ndim (ndim)
mean -- 20100 20100 -- 0.26521 2.76455 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py:3356:mean (mean)
_mean -- 20100 20100 -- 1.21655 2.49933 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/_methods.py:162:_mean (_mean) +++
zeros_like -- 6 6 -- 0.00010 0.00041 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/numeric.py:76:zeros_like (zeros_like)
empty_like -- 6 6 -- 0.00005 0.00013 -- <__array_function__ internals>:177:empty_like (empty_like)
empty_like -- 6 6 -- 0.00001 0.00001 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/multiarray.py:80:empty_like (empty_like)
copyto -- 6 6 -- 0.00005 0.00013 -- <__array_function__ internals>:177:copyto (copyto)
copyto -- 6 6 -- 0.00001 0.00001 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/core/multiarray.py:1071:copyto (copyto)
unique -- 101 101 -- 0.00122 0.01230 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/lib/arraysetops.py:138:unique (unique)
_unpack_tuple -- 101 101 -- 0.00035 0.00044 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/lib/arraysetops.py:125:_unpack_tuple (_unpack_tuple)
<built-in method builtins.len> -- 101 101 -- 0.00009 0.00009 -- ~:0:<built-in method builtins.len> (<built-in method builtins.len>) +++
_unique1d -- 101 101 -- 0.00739 0.00941 -- onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/numpy/lib/arraysetops.py:320:_unique1d (_unique1d)
<method 'flatten' of 'numpy.ndarray' objects> -- 101 101 -- 0.00099 0.00099 -- ~:0:<method 'flatten' of 'numpy.ndarray' objects> (<method 'flatten' of 'numpy.ndarray' objects>)
<method 'sort' of 'numpy.ndarray' objects> -- 101 101 -- 0.00024 0.00024 -- ~:0:<method 'sort' of 'numpy.ndarray' objects> (<method 'sort' of 'numpy.ndarray' objects>)
<built-in method numpy.asanyarray> -- 101 101 -- 0.00006 0.00006 -- ~:0:<built-in method numpy.asanyarray> (<built-in method numpy.asanyarray>) +++
<built-in method numpy.empty> -- 101 101 -- 0.00074 0.00074 -- ~:0:<built-in method numpy.empty> (<built-in method numpy.empty>) +++
<built-in method numpy.asanyarray> -- 101 101 -- 0.00123 0.00123 -- ~:0:<built-in method numpy.asanyarray> (<built-in method numpy.asanyarray>) +++
<built-in method numpy.asanyarray> -- 27104 27104 -- 0.02591 0.02591 -- ~:0:<built-in method numpy.asanyarray> (<built-in method numpy.asanyarray>)
<method 'reduce' of 'numpy.ufunc' objects> -- 26909 26909 -- 0.87478 0.87478 -- ~:0:<method 'reduce' of 'numpy.ufunc' objects> (<method 'reduce' of 'numpy.ufunc' objects>)
<built-in method builtins.issubclass> -- 53806 53806 -- 0.05887 0.05887 -- ~:0:<built-in method builtins.issubclass> (<built-in method builtins.issubclass>)
<method 'get' of 'dict' objects> -- 33 33 -- 0.00003 0.00003 -- ~:0:<method 'get' of 'dict' objects> (<method 'get' of 'dict' objects>)
<built-in method builtins.getattr> -- 41 41 -- 0.00006 0.00006 -- ~:0:<built-in method builtins.getattr> (<built-in method builtins.getattr>)
<built-in method posix.fspath> -- 24 24 -- 0.00002 0.00002 -- ~:0:<built-in method posix.fspath> (<built-in method posix.fspath>)
<built-in method _thread.get_ident> -- 12 12 -- 0.00001 0.00001 -- ~:0:<built-in method _thread.get_ident> (<built-in method _thread.get_ident>)
<method 'rfind' of 'str' objects> -- 18 18 -- 0.00004 0.00004 -- ~:0:<method 'rfind' of 'str' objects> (<method 'rfind' of 'str' objects>)
if GPU is available#
if get_device().upper() == 'GPU':
train_session = OrtGradientOptimizer(
onx_train, list(weights), device='cuda', learning_rate=5e-4,
warm_start=False, max_iter=max_iter, batch_size=batch_size)
benches.append(benchmark(nn, train_session, name='NN-GPU'))
Linear Regression#
lr = MLPRegressor(hidden_layer_sizes=tuple(), max_iter=max_iter,
solver='sgd', learning_rate_init=5e-2, alpha=0,
n_iter_no_change=max_iter * 3, batch_size=batch_size,
nesterovs_momentum=False, momentum=0,
learning_rate='invscaling')
with warnings.catch_warnings():
warnings.simplefilter('ignore')
lr.fit(X, y)
onx = to_onnx(nn, X_train[:1].astype(numpy.float32), target_opset=15)
onx_train = add_loss_output(onx)
inits = get_train_initializer(onx)
weights = {k: v for k, v in inits.items() if k != "shape_tensor"}
pprint(list((k, v[0].shape) for k, v in weights.items()))
train_session = OrtGradientOptimizer(
onx_train, list(weights), device='cpu', learning_rate=1e-4,
warm_start=False, max_iter=max_iter, batch_size=batch_size)
benches.append(benchmark(lr, train_session, name='LR-CPU'))
if get_device().upper() == 'GPU':
train_session = OrtGradientOptimizer(
onx_train, list(weights), device='cuda', learning_rate=1e-4,
warm_start=False, max_iter=max_iter, batch_size=batch_size)
benches.append(benchmark(nn, train_session, name='LR-GPU'))
Out:
[('coefficient', (100, 50)),
('intercepts', (1, 50)),
('coefficient1', (50, 10)),
('intercepts1', (1, 10)),
('coefficient2', (10, 1)),
('intercepts2', (1, 1))]
[benchmark] LR-CPU
somewhere/workspace/onnxcustom/onnxcustom_UT_39_std/_venv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:702: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.
warnings.warn(
[benchmark] skl=100 iterations - 6.040600605017971 seconds
[benchmark] ort=100 iterations - 6.197875561949331 seconds
GPU profiling#
if get_device().upper() == 'GPU':
ps = profile(lambda: benchmark(nn, train_session, name='LR-GPU'))[0]
root, nodes = profile2graph(ps, clean_text=clean_name)
text = root.to_text()
print(text)
Graphs#
Dataframe first.
df = DataFrame(benches).set_index('name')
df
text output
print(df)
Out:
skl ... losses_ort
name ...
NN-CPU 16.660431 ... [54645.496, 51820.773, 50715.895, 42885.742, 3...
LR-CPU 6.040601 ... [32715.484, 10688.099, 4716.1025, 2686.6328, 2...
[2 rows x 6 columns]
Graphs.
fig, ax = plt.subplots(1, 2, figsize=(10, 4))
df[['skl', 'ort']].plot.bar(title="Processing time", ax=ax[0])
ax[0].tick_params(axis='x', rotation=30)
for bench in benches:
ax[1].plot(bench['losses_skl'][1:], label='skl-' + bench['name'])
ax[1].plot(bench['losses_ort'][1:], label='ort-' + bench['name'])
ax[1].set_title("Losses")
ax[1].set_yscale('log')
ax[1].legend()
Out:
<matplotlib.legend.Legend object at 0x7f1bcc605040>
The gradient update are not exactly the same. It should be improved for a fair comprison.
fig.savefig("plot_orttraining_benchmark.png")
# plt.show()
Total running time of the script: ( 1 minutes 20.968 seconds)