module `asv_benchmark.common_asv_skl`#

Short summary#

module mlprodict.asv_benchmark.common_asv_skl

Common class for all benchmarks testing converted models from scikit-learn with asv. The benchmark can be run through file run_asv.sh on Linux or run_asv.bat on Windows.

Classes#

class	truncated documentation
`_CommonAsvSklBenchmark`	Common tests to all benchmarks testing converted scikit-learn models. See benchmark attributes. …
`_CommonAsvSklBenchmarkClassifier`	Common class for a classifier.
`_CommonAsvSklBenchmarkClassifierRawScore`	Common class for a classifier.
`_CommonAsvSklBenchmarkClustering`	Common class for a clustering algorithm.
`_CommonAsvSklBenchmarkMultiClassifier`	Common class for a multi-classifier.
`_CommonAsvSklBenchmarkOutlier`	Common class for outlier detection.
`_CommonAsvSklBenchmarkRegressor`	Common class for a regressor.
`_CommonAsvSklBenchmarkTrainableTransform`	Common class for a trainable transformer.
`_CommonAsvSklBenchmarkTransform`	Common class for a transformer.
`_CommonAsvSklBenchmarkTransformPositive`	Common class for a transformer for positive features.

Methods#

method	truncated documentation
`_check_rt`	Checks that runtime has the appropriate method.
`_check_rt`	Checks that runtime has the appropriate method.
`_check_rt`	Checks that runtime has the appropriate method.
`_check_rt`	Checks that runtime has the appropriate method.
`_check_rt`	Checks that runtime has the appropriate method.
`_check_rt`	Checks that runtime has the appropriate method.
`_check_rt`	Checks that runtime has the appropriate method.
`_check_rt`	Checks that runtime has the appropriate method.
`_check_rt`	Checks that runtime has the appropriate method.
`_check_rt`	Checks that runtime has the appropriate method.
`_create_model`
`_create_model`
`_create_model`
`_create_model`
`_create_model`
`_create_model`
`_create_model`
`_create_model`
`_create_model`
`_create_model`
`_create_onnx_and_runtime`
`_create_onnx_and_runtime`
`_create_onnx_and_runtime`
`_create_onnx_and_runtime`
`_create_onnx_and_runtime`
`_create_onnx_and_runtime`
`_create_onnx_and_runtime`
`_create_onnx_and_runtime`
`_create_onnx_and_runtime`
`_create_onnx_and_runtime`
`_create_onnx_inference`
`_create_onnx_inference`
`_create_onnx_inference`
`_create_onnx_inference`
`_create_onnx_inference`
`_create_onnx_inference`
`_create_onnx_inference`
`_create_onnx_inference`
`_create_onnx_inference`
`_create_onnx_inference`
`_get_dataset`
`_get_dataset`
`_get_dataset`
`_get_dataset`
`_get_dataset`
`_get_dataset`
`_get_dataset`
`_get_dataset`
`_get_dataset`
`_get_dataset`
`_get_xdtype`
`_get_xdtype`
`_get_xdtype`
`_get_xdtype`
`_get_xdtype`
`_get_xdtype`
`_get_xdtype`
`_get_xdtype`
`_get_xdtype`
`_get_xdtype`
`_name`
`_name`
`_name`
`_name`
`_name`
`_name`
`_name`
`_name`
`_name`
`_name`
`_optimize_onnx`
`_optimize_onnx`
`_optimize_onnx`
`_optimize_onnx`
`_optimize_onnx`
`_optimize_onnx`
`_optimize_onnx`
`_optimize_onnx`
`_optimize_onnx`
`_optimize_onnx`
`_score_metric`
`_score_metric`
`_score_metric`
`_score_metric`
`_score_metric`
`_score_metric`
`_score_metric`
`_score_metric`
`_score_metric`
`_score_metric`
`_to_onnx`
`_to_onnx`
`_to_onnx`
`_to_onnx`
`_to_onnx`
`_to_onnx`
`_to_onnx`
`_to_onnx`
`_to_onnx`
`_to_onnx`
`check_method_name`	Does some verifications. Fails if inconsistencies.
`check_method_name`	Does some verifications. Fails if inconsistencies.
`check_method_name`	Does some verifications. Fails if inconsistencies.
`check_method_name`	Does some verifications. Fails if inconsistencies.
`check_method_name`	Does some verifications. Fails if inconsistencies.
`check_method_name`	Does some verifications. Fails if inconsistencies.
`check_method_name`	Does some verifications. Fails if inconsistencies.
`check_method_name`	Does some verifications. Fails if inconsistencies.
`check_method_name`	Does some verifications. Fails if inconsistencies.
`check_method_name`	Does some verifications. Fails if inconsistencies.
`peakmem_predict`	asv API
`peakmem_predict`	asv API
`peakmem_predict`	asv API
`peakmem_predict`	asv API
`peakmem_predict`	asv API
`peakmem_predict`	asv API
`peakmem_predict`	asv API
`peakmem_predict`	asv API
`peakmem_predict`	asv API
`peakmem_predict`	asv API
`runtime_name`	Returns the runtime shortname.
`runtime_name`	Returns the runtime shortname.
`runtime_name`	Returns the runtime shortname.
`runtime_name`	Returns the runtime shortname.
`runtime_name`	Returns the runtime shortname.
`runtime_name`	Returns the runtime shortname.
`runtime_name`	Returns the runtime shortname.
`runtime_name`	Returns the runtime shortname.
`runtime_name`	Returns the runtime shortname.
`runtime_name`	Returns the runtime shortname.
`setup`	asv API
`setup`	asv API
`setup`	asv API
`setup`	asv API
`setup`	asv API
`setup`	asv API
`setup`	asv API
`setup`	asv API
`setup`	asv API
`setup`	asv API
`setup_cache`	asv API
`setup_cache`	asv API
`setup_cache`	asv API
`setup_cache`	asv API
`setup_cache`	asv API
`setup_cache`	asv API
`setup_cache`	asv API
`setup_cache`	asv API
`setup_cache`	asv API
`setup_cache`	asv API
`time_predict`	asv API
`time_predict`	asv API
`time_predict`	asv API
`time_predict`	asv API
`time_predict`	asv API
`time_predict`	asv API
`time_predict`	asv API
`time_predict`	asv API
`time_predict`	asv API
`time_predict`	asv API
`track_nbnodes`	asv API
`track_nbnodes`	asv API
`track_nbnodes`	asv API
`track_nbnodes`	asv API
`track_nbnodes`	asv API
`track_nbnodes`	asv API
`track_nbnodes`	asv API
`track_nbnodes`	asv API
`track_nbnodes`	asv API
`track_nbnodes`	asv API
`track_onnxsize`	asv API
`track_onnxsize`	asv API
`track_onnxsize`	asv API
`track_onnxsize`	asv API
`track_onnxsize`	asv API
`track_onnxsize`	asv API
`track_onnxsize`	asv API
`track_onnxsize`	asv API
`track_onnxsize`	asv API
`track_onnxsize`	asv API
`track_score`	asv API
`track_score`	asv API
`track_score`	asv API
`track_score`	asv API
`track_score`	asv API
`track_score`	asv API
`track_score`	asv API
`track_score`	asv API
`track_score`	asv API
`track_score`	asv API
`track_vmlprodict`	asv API
`track_vmlprodict`	asv API
`track_vmlprodict`	asv API
`track_vmlprodict`	asv API
`track_vmlprodict`	asv API
`track_vmlprodict`	asv API
`track_vmlprodict`	asv API
`track_vmlprodict`	asv API
`track_vmlprodict`	asv API
`track_vmlprodict`	asv API
`track_vort`	asv API
`track_vort`	asv API
`track_vort`	asv API
`track_vort`	asv API
`track_vort`	asv API
`track_vort`	asv API
`track_vort`	asv API
`track_vort`	asv API
`track_vort`	asv API
`track_vort`	asv API
`track_vsklearn`	asv API
`track_vsklearn`	asv API
`track_vsklearn`	asv API
`track_vsklearn`	asv API
`track_vsklearn`	asv API
`track_vsklearn`	asv API
`track_vsklearn`	asv API
`track_vsklearn`	asv API
`track_vsklearn`	asv API
`track_vsklearn`	asv API

Documentation#

Common class for all benchmarks testing converted models from scikit-learn with asv. The benchmark can be run through file run_asv.sh on Linux or run_asv.bat on Windows.

Warning

On Windows, you should avoid cloning the repository on a folder with a long full name. Visual Studio tends to abide by the rule of the maximum path length even though the system is told otherwise.

source on GitHub

class mlprodict.asv_benchmark.common_asv_skl._CommonAsvSklBenchmark#

Bases: object

Common tests to all benchmarks testing converted scikit-learn models. See benchmark attributes.

source on GitHub

_check_rt(rt, meth)#

Checks that runtime has the appropriate method.

source on GitHub

_create_model()#

_create_onnx_and_runtime(runtime, model, X, opset, dtype, optim)#

_create_onnx_inference(onx, runtime)#

_get_dataset(nf, dtype)#

_get_xdtype(dtype)#

_name(nf, opset, dtype)#

_optimize_onnx(onx)#

_score_metric(X, y_exp, y_pred)#

_to_onnx(model, X, opset, dtype, optim)#

check_method_name(method_name)#: Does some verifications. Fails if inconsistencies.

par_ydtype#: alias of int64

peakmem_predict(runtime, N, nf, opset, dtype, optim)#: asv API

runtime_name(runtime)#

Returns the runtime shortname.

source on GitHub

setup(runtime, N, nf, opset, dtype, optim)#: asv API

setup_cache()#: asv API

time_predict(runtime, N, nf, opset, dtype, optim)#: asv API

track_nbnodes(runtime, N, nf, opset, dtype, optim)#: asv API

track_onnxsize(runtime, N, nf, opset, dtype, optim)#: asv API

track_score(runtime, N, nf, opset, dtype, optim)#: asv API

track_vmlprodict(runtime, N, nf, opset, dtype, optim)#: asv API

track_vort(runtime, N, nf, opset, dtype, optim)#: asv API

track_vsklearn(runtime, N, nf, opset, dtype, optim)#: asv API

class mlprodict.asv_benchmark.common_asv_skl._CommonAsvSklBenchmarkClassifier#

Bases: _CommonAsvSklBenchmark

Common class for a classifier.

source on GitHub

_create_onnx_and_runtime(runtime, model, X, opset, dtype, optim)#

_score_metric(X, y_exp, y_pred)#

class mlprodict.asv_benchmark.common_asv_skl._CommonAsvSklBenchmarkClassifierRawScore#

Bases: _CommonAsvSklBenchmark

Common class for a classifier.

source on GitHub

_create_onnx_and_runtime(runtime, model, X, opset, dtype, optim)#

_score_metric(X, y_exp, y_pred)#

class mlprodict.asv_benchmark.common_asv_skl._CommonAsvSklBenchmarkClustering#

Bases: _CommonAsvSklBenchmark

Common class for a clustering algorithm.

source on GitHub

_create_onnx_and_runtime(runtime, model, X, opset, dtype, optim)#

_score_metric(X, y_exp, y_pred)#

class mlprodict.asv_benchmark.common_asv_skl._CommonAsvSklBenchmarkMultiClassifier#

Bases: _CommonAsvSklBenchmark

Common class for a multi-classifier.

source on GitHub

_create_onnx_and_runtime(runtime, model, X, opset, dtype, optim)#

_get_dataset(nf, dtype)#

_score_metric(X, y_exp, y_pred)#

class mlprodict.asv_benchmark.common_asv_skl._CommonAsvSklBenchmarkOutlier#

Bases: _CommonAsvSklBenchmark

Common class for outlier detection.

source on GitHub

_create_onnx_and_runtime(runtime, model, X, opset, dtype, optim)#

_score_metric(X, y_exp, y_pred)#

class mlprodict.asv_benchmark.common_asv_skl._CommonAsvSklBenchmarkRegressor#

Bases: _CommonAsvSklBenchmark

Common class for a regressor.

source on GitHub

_create_onnx_and_runtime(runtime, model, X, opset, dtype, optim)#

_score_metric(X, y_exp, y_pred)#

class mlprodict.asv_benchmark.common_asv_skl._CommonAsvSklBenchmarkTrainableTransform#

Bases: _CommonAsvSklBenchmark

Common class for a trainable transformer.

source on GitHub

_create_onnx_and_runtime(runtime, model, X, opset, dtype, optim)#

_score_metric(X, y_exp, y_pred)#

class mlprodict.asv_benchmark.common_asv_skl._CommonAsvSklBenchmarkTransform#

Bases: _CommonAsvSklBenchmark

Common class for a transformer.

source on GitHub

_create_onnx_and_runtime(runtime, model, X, opset, dtype, optim)#

_score_metric(X, y_exp, y_pred)#

class mlprodict.asv_benchmark.common_asv_skl._CommonAsvSklBenchmarkTransformPositive#

Bases: _CommonAsvSklBenchmarkTransform

Common class for a transformer for positive features.

source on GitHub

_get_dataset(nf, dtype)#

module asv_benchmark.common_asv_skl#

Short summary#

Classes#

Methods#

Documentation#

module `asv_benchmark.common_asv_skl`#