module onnxrt.ops_cpu.op_svm_classifier

Short summary

module mlprodict.onnxrt.ops_cpu.op_svm_classifier

Runtime operator.

source on GitHub

Classes

class	truncated documentation
SVMClassifier	SVMClassifier (ai.onnx.ml) ========================== Support Vector Machine classifier Attributes
SVMClassifierCommon
SVMClassifierDouble	SVMClassifierDouble (mlprodict) =============================== Version Onnx name: SVMClassifierDouble …
SVMClassifierDoubleSchema	Defines a schema for operators added in this package such as SVMClassifierDouble.

Properties

property	truncated documentation
args_default	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
args_default	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
args_default	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
args_default_modified	Returns the list of modified parameters.
args_default_modified	Returns the list of modified parameters.
args_default_modified	Returns the list of modified parameters.
args_mandatory	Returns the list of optional arguments.
args_mandatory	Returns the list of optional arguments.
args_mandatory	Returns the list of optional arguments.
args_optional	Returns the list of optional arguments.
args_optional	Returns the list of optional arguments.
args_optional	Returns the list of optional arguments.
atts_value	Returns all parameters in a dictionary.
atts_value	Returns all parameters in a dictionary.
atts_value	Returns all parameters in a dictionary.
nb_classes	Returns the number of expected classes.
nb_classes	Returns the number of expected classes.
nb_classes	Returns the number of expected classes.

Methods

method	truncated documentation
__init__
__init__
__init__
__init__
_find_custom_operator_schema	Finds a custom operator defined by this runtime.
_find_custom_operator_schema	Finds a custom operator defined by this runtime.
_find_custom_operator_schema	Finds a custom operator defined by this runtime.
_get_typed_attributes
_get_typed_attributes
_get_typed_attributes
_init
_init
_init
_run	This is a C++ implementation coming from onnxruntime. svm_classifier.cc. …
_run	This is a C++ implementation coming from onnxruntime. svm_classifier.cc. …
_run	This is a C++ implementation coming from onnxruntime. svm_classifier.cc. …

Documentation

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_svm_classifier.SVMClassifier(ai.onnx.ml)

Bases: SVMClassifierCommon

---

Support Vector Machine classifier

Attributes

• classlabels_ints: Class labels if using integer labels. One and only one of the ‘classlabels_*’ attributes must be defined. default value cannot be automatically retrieved (INTS)

• classlabels_strings: Class labels if using string labels. One and only one of the ‘classlabels_*’ attributes must be defined. default value cannot be automatically retrieved (STRINGS)

• coefficients: default value cannot be automatically retrieved (FLOATS)

• kernel_params: List of 3 elements containing gamma, coef0, and degree, in that order. Zero if unused for the kernel. default value cannot be automatically retrieved (FLOATS)

• kernel_type: The kernel type, one of ‘LINEAR,’ ‘POLY,’ ‘RBF,’ ‘SIGMOID’. Default value is namekerneltypesLINEARtypeSTRING (STRING)

• post_transform: Indicates the transform to apply to the score. One of ‘NONE,’ ‘SOFTMAX,’ ‘LOGISTIC,’ ‘SOFTMAX_ZERO,’ or ‘PROBIT’ Default value is nameposttransformsNONEtypeSTRING (STRING)

• prob_a: First set of probability coefficients. default value cannot be automatically retrieved (FLOATS)

• prob_b: Second set of probability coefficients. This array must be same size as prob_a. If these are provided then output Z are probability estimates, otherwise they are raw scores. default value cannot be automatically retrieved (FLOATS)

• rho: default value cannot be automatically retrieved (FLOATS)

• support_vectors: default value cannot be automatically retrieved (FLOATS)

• vectors_per_class: default value cannot be automatically retrieved (INTS)

Inputs

• X (heterogeneous)T1: Data to be classified.

Outputs

• Y (heterogeneous)T2: Classification outputs (one class per example).

• Z (heterogeneous)tensor(float): Class scores (one per class per example), if prob_a and prob_b are provided they are probabilities for each class, otherwise they are raw scores.

Type Constraints

• T1 tensor(float), tensor(double), tensor(int64), tensor(int32): The input must be a tensor of a numeric type, either [C] or [N,C].

• T2 tensor(string), tensor(int64): The output type will be a tensor of strings or integers, depending on which of the classlabels_* attributes is used. Its size will match the bactch size of the input.

Version

Onnx name: SVMClassifier

This version of the operator has been available since version 1 of domain ai.onnx.ml.

Runtime implementation: SVMClassifier

__init__(onnx_node, desc=None, **options)

class mlprodict.onnxrt.ops_cpu.op_svm_classifier.SVMClassifierCommon(dtype, onnx_node, desc=None, expected_attributes=None, **options)

Bases: OpRunClassifierProb, _ClassifierCommon

__init__(dtype, onnx_node, desc=None, expected_attributes=None, **options)

_find_custom_operator_schema(op_name)

Finds a custom operator defined by this runtime.

source on GitHub

_get_typed_attributes(k)

_init(dtype)

_run(x, attributes=None, verbose=0, fLOG=None)

This is a C++ implementation coming from onnxruntime. svm_classifier.cc. See class RuntimeSVMClassifier.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_svm_classifier.SVMClassifierDouble(mlprodict)

Bases: SVMClassifierCommon

---

Version

Onnx name: SVMClassifierDouble

This version of the operator has been available since version of domain mlprodict.

Runtime implementation: SVMClassifierDouble

__init__(onnx_node, desc=None, **options)

class mlprodict.onnxrt.ops_cpu.op_svm_classifier.SVMClassifierDoubleSchema

Bases: OperatorSchema

Defines a schema for operators added in this package such as SVMClassifierDouble.

source on GitHub

__init__()