module asv_benchmark._create_asv_helper

Short summary

module mlprodict.asv_benchmark._create_asv_helper

Functions to creates a benchmark based on asv for many regressors and classifiers.

source on GitHub

Functions

function	truncated documentation
_additional_imports	Adds additional imports for experimental models.
_asv_class_name
_display_code_lines
_format_dict	Formats a dictionary as code.
_handle_init_files	Returns created, location_model, prefix_import.
_read_patterns	Reads the testing pattern.
_select_pattern_problem	Selects a benchmark type based on the problem kind.
_sklearn_subfolder	Returns the list of subfolders for a model.
add_model_import_init	Modifies a template such as TemplateBenchmarkClassifier with code associated to the model model.
find_missing_sklearn_imports	Finds in scikit-learn the missing pieces.
find_sklearn_module	Finds the corresponding modulee for an element of scikit-learn.

Documentation

Functions to creates a benchmark based on asv for many regressors and classifiers.

source on GitHub

mlprodict.asv_benchmark._create_asv_helper._additional_imports(model_name)

Adds additional imports for experimental models.

source on GitHub

mlprodict.asv_benchmark._create_asv_helper._asv_class_name(model, scenario, optimisation, extra, dofit, conv_options, problem, shorten=True)

mlprodict.asv_benchmark._create_asv_helper._display_code_lines(code)

mlprodict.asv_benchmark._create_asv_helper._format_dict(opts, indent)

Formats a dictionary as code.

source on GitHub

mlprodict.asv_benchmark._create_asv_helper._handle_init_files(model, flat, location, verbose, location_pyspy, fLOG)

Returns created, location_model, prefix_import.

mlprodict.asv_benchmark._create_asv_helper._read_patterns()

Reads the testing pattern.

source on GitHub

mlprodict.asv_benchmark._create_asv_helper._select_pattern_problem(prob, patterns)

Selects a benchmark type based on the problem kind.

source on GitHub

mlprodict.asv_benchmark._create_asv_helper._sklearn_subfolder(model)

Returns the list of subfolders for a model.

source on GitHub

mlprodict.asv_benchmark._create_asv_helper.add_model_import_init(class_content, model, optimisation=None, extra=None, conv_options=None)

Modifies a template such as TemplateBenchmarkClassifier with code associated to the model model.

Parameters:

• class_content – template (as a string)

• model – model class

• optimisation – model optimisation

• extra – addition parameter to the constructor

• conv_options – options for the conversion to ONNX

@returm modified template

source on GitHub

mlprodict.asv_benchmark._create_asv_helper.find_missing_sklearn_imports(pieces)

Finds in scikit-learn the missing pieces.

Parameters:

pieces – list of names in scikit-learn

Returns:

list of corresponding imports

source on GitHub

mlprodict.asv_benchmark._create_asv_helper.find_sklearn_module(piece)

Finds the corresponding modulee for an element of scikit-learn.

Parameters:

piece – name to import

Returns:

module name

The implementation is not intelligence and should be improved. It is a kind of white list.

source on GitHub