Classes

Summary

class

class parent

truncated documentation

Abs

Abs === Absolute takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the absolute is, y = …

Add

Add === Performs element-wise binary addition (with Numpy-style broadcasting support). This operator supports **multidirectional …

And

And === Returns the tensor resulted from performing the and logical operation elementwise on the input tensors A and …

ArgMax_11

ArgMax_12

ArgMax ====== Computes the indices of the max elements of the input tensor’s element along the provided axis. The resulting …

ArgMax_12

ArgMax ====== Computes the indices of the max elements of the input tensor’s element along the provided axis. The resulting …

ArgMin_11

ArgMin_12

ArgMin ====== Computes the indices of the min elements of the input tensor’s element along the provided axis. The resulting …

ArgMin_12

ArgMin ====== Computes the indices of the min elements of the input tensor’s element along the provided axis. The resulting …

ArrayFeatureExtractor

ArrayFeatureExtractor (ai.onnx.ml) ================================== Select elements of the input tensor based on the …

ArrayZipMapDictionary

Mocks an array without changing the data it receives. Notebooks Time processing for every ONNX nodes in a graph illustrates the weaknesses …

Atan

Atan ==== Calculates the arctangent (inverse of tangent) of the given input tensor, element-wise. Inputs

AutoAction

Extends the API to automatically look for exporters.

AutoType

Extends the API to automatically look for exporters.

BaseDimensionShape

Base class to DimensionObject, ShapeOperator, ShapeObject.

BatchNormalization

BatchNormalization ================== Carries out batch normalization as described in the paper https://arxiv.org/abs/1502.03167. …

Binarizer

Binarizer (ai.onnx.ml) ====================== Maps the values of the input tensor to either 0 or 1, element-wise, based …

CDist

CDist (mlprodict) ================= Version Onnx name: CDist

CDistSchema

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

Cast

Cast ==== The operator casts the elements of a given input tensor to a data type specified by the ‘to’ argument and returns …

Ceil

Ceil ==== Ceil takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the ceil is, y = ceil(x), …

Celu

Celu ==== Continuously Differentiable Exponential Linear Units: Perform the linear unit element-wise on the input tensor …

Clip_11

Clip ==== Clip operator limits the given input within an interval. The interval is specified by the inputs ‘min’ and ‘max’. …

Clip_11

Clip ==== Clip operator limits the given input within an interval. The interval is specified by the inputs ‘min’ and ‘max’. …

Clip_6

Clip ==== Clip operator limits the given input within an interval. The interval is specified with arguments ‘min’ and …

CodeNodeVisitor

Defines a visitor which walks though the syntax tree of the code.

CodeNodeVisitor

Visits the code, implements verification rules.

CodeTranslator

Class which converts a Python function into something else. It must implements methods visit and depart.

CompilationError

Raised when a compilation error was detected.

Concat

Concat ====== Concatenate a list of tensors into a single tensor. All input tensors must have the same shape, except for …

ConstantOfShape

ConstantOfShape =============== Generate a tensor with given value and shape. Attributes

Constant_11

Constant_12

Constant ======== This operator produces a constant tensor. Exactly one of the provided attributes, either value, sparse_value, …

Constant_12

Constant ======== This operator produces a constant tensor. Exactly one of the provided attributes, either value, sparse_value, …

Constant_9

Conv

Conv ==== The convolution operator consumes an input tensor and a filter, and computes the output. Attributes

ConvDouble

Implements float runtime for operator Conv. The code is inspired from conv.cc

ConvFloat

Implements float runtime for operator Conv. The code is inspired from conv.cc

ConvTranspose

ConvTranspose ============= The convolution transpose operator consumes an input tensor and a filter, and computes the …

ConvTransposeDouble

Implements float runtime for operator Conv. The code is inspired from conv_transpose.cc

ConvTransposeFloat

Implements float runtime for operator Conv. The code is inspired from conv_transpose.cc

CumSum

CumSum ====== Performs cumulative sum of the input elements along the given axis. By default, it will do the sum inclusively …

CustomScorerTransform

Wraps a scoring function into a transformer. Function @see fn register_scorers must be called to register the converter …

DequantizeLinear

DequantizeLinear ================ The linear dequantization operator. It consumes a quantized tensor, a scale, and a zero …

DictVectorizer

DictVectorizer (ai.onnx.ml) =========================== Uses an index mapping to convert a dictionary to an array. Given …

DimensionObject

One dimension of a shape.

Div

Div === Performs element-wise binary division (with Numpy-style broadcasting support). This operator supports **multidirectional …

DropoutBase

Dropout_12

Dropout ======= Dropout takes an input floating-point tensor, an optional input ratio (floating-point scalar) and an optional …

Dropout_12

Dropout ======= Dropout takes an input floating-point tensor, an optional input ratio (floating-point scalar) and an optional …

Dropout_7

Dropout ======= Dropout takes one input data (Tensor<float>) and produces two Tensor outputs, output (Tensor<float>) and …

Einsum

Einsum ====== An einsum of the form `term1, term2 -> output-term` produces an output tensor using the following equation …

Equal

Equal ===== Returns the tensor resulted from performing the equal logical operation elementwise on the input tensors …

Erf

Erf === Computes the error function of the given input tensor element-wise. Inputs

Exp

Exp === Calculates the exponential of the given input tensor, element-wise. Inputs

ExpectedAssertionError

Expected failure.

EyeLike

EyeLike ======= Generate a 2D tensor (matrix) with ones on the diagonal and zeros everywhere else. Only 2D tensors are …

FeatureVectorizer

Very similar to Concat.

Flatten

Flatten ======= Flattens the input tensor into a 2D matrix. If input tensor has shape (d_0, d_1, .

Float32InfError

Raised when a float is out of range and cannot be converted into a float32.

Floor

Floor ===== Floor takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the floor is, y = floor(x), …

Gather

Gather ====== Given data tensor of rank r >= 1, and indices tensor of rank q, gather entries of the axis dimension …

GatherDouble

Implements runtime for operator Gather. The code is inspired from tfidfvectorizer.cc

GatherElements

GatherElements ============== GatherElements takes two inputs data and indices of the same rank r >= 1 and an optional …

GatherFloat

Implements runtime for operator Gather. The code is inspired from tfidfvectorizer.cc

GatherInt64

Implements runtime for operator Gather. The code is inspired from tfidfvectorizer.cc

Gemm

Gemm ==== General Matrix multiplication: https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms#Level_3 A’ = transpose(A) …

GlobalAveragePool

GlobalAveragePool ================= GlobalAveragePool consumes an input tensor X and applies average pooling across the …

Greater

Greater ======= Returns the tensor resulted from performing the greater logical operation elementwise on the input tensors …

GreaterOrEqual

GreaterOrEqual ============== Returns the tensor resulted from performing the greater_equal logical operation elementwise …

Identity

Identity ======== Identity operator Inputs

If

If == If conditional Attributes

ImperfectPythonCode

Raised if the code shows errors.

Imputer

Imputer (ai.onnx.ml) ==================== Replaces inputs that equal one value with another, leaving all other elements …

InferenceSession2

Overwrites class InferenceSession to capture the standard output and error.

IsNaN

IsNaN ===== Returns which elements of the input are NaN. Inputs

LabelEncoder

LabelEncoder (ai.onnx.ml) ========================= Maps each element in the input tensor to another value. The mapping …

Less

Less ==== Returns the tensor resulted from performing the less logical operation elementwise on the input tensors A

LessOrEqual

LessOrEqual =========== Returns the tensor resulted from performing the less_equal logical operation elementwise on …

LinearClassifier

LinearClassifier (ai.onnx.ml) ============================= Linear classifier Attributes

LinearRegressor

LinearRegressor (ai.onnx.ml) ============================ Generalized linear regression evaluation. If targets is set …

Log

Log === Calculates the natural log of the given input tensor, element-wise. Inputs

Loop

Loop ==== Generic Looping construct. This loop has multiple termination conditions: 1) Trip count. Iteration count specified …

LpNormalization

LpNormalization =============== Given a matrix, apply Lp-normalization along the provided axis. Attributes

MLAction

Base class for every action.

MLActionAdd

Addition

MLActionBinary

Any binary operation.

MLActionCast

Cast into another type.

MLActionConcat

Concatenate number of arrays into an array.

MLActionCst

Constant

MLActionFunction

A function.

MLActionFunctionCall

Any function call.

MLActionIfElse

Addition

MLActionReturn

Returns a results.

MLActionSign

Sign of an expression: 1=positive, 0=negative.

MLActionTensorAdd

Tensor addition.

MLActionTensorDiv

Tensor division.

MLActionTensorDot

Scalar product.

MLActionTensorMul

Tensor multiplication.

MLActionTensorSub

Tensor soustraction.

MLActionTensorTake

Extracts an element of the tensor.

MLActionTensorVector

Tensor operation.

MLActionTestEqual

Operator ==.

MLActionTestInf

Operator <.

MLActionUnary

Any binary operation.

MLActionVar

Variable. The constant is only needed to guess the variable type.

MLModel

Base class for every machine learned model

MLNumType

Base class for numerical types.

MLNumTypeBool

A numpy.bool.

MLNumTypeFloat32

A numpy.float32.

MLNumTypeFloat64

A numpy.float64.

MLNumTypeInt32

A numpy.int32.

MLNumTypeInt64

A numpy.int64.

MLNumTypeSingle

int32 or float32

MLTensor

Defines a tensor with a dimension and a single type for what it contains.

MLType

Base class for every type.

MatMul

MatMul ====== Matrix product that behaves like numpy.matmul: https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.matmul.html

Max

Max === Element-wise max of each of the input tensors (with Numpy-style broadcasting support). All inputs and outputs …

MaxPool

MaxPool ======= MaxPool consumes an input tensor X and applies max pooling across the tensor according to kernel sizes, …

MaxPoolDouble

Implements float runtime for operator Conv. The code is inspired from pool.cc

MaxPoolFloat

Implements float runtime for operator Conv. The code is inspired from pool.cc

Mean

Mean ==== Element-wise mean of each of the input tensors (with Numpy-style broadcasting support). All inputs and outputs …

Min

Min === Element-wise min of each of the input tensors (with Numpy-style broadcasting support). All inputs and outputs …

MissingVariableError

Raised when a variable is missing.

MockVariableName

A string.

MockVariableNameShape

A string and a shape.

MockVariableNameShapeType

A string and a shape and a type.

MockWrappedLightGbmBoosterClassifier

Mocked lightgbm.

Mul

Mul === Performs element-wise binary multiplication (with Numpy-style broadcasting support). This operator supports **multidirectional …

Neg

Neg === Neg takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where each element flipped sign, …

NewOperatorSchema

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

Normalizer

Normalizer (ai.onnx.ml) ======================= Normalize the input. There are three normalization modes, which have …

Not

Not === Returns the negation of the input tensor element-wise. Inputs

OneHotEncoder

ONNX specifications does not mention the possibility to change the output type, sparse, dense, float, double. …

OnnxBackendAssertionError

Expected failure.

OnnxBackendMissingNewOnnxOperatorException

Raised when onnxruntime or mlprodict does not implement a new operator defined in the latest onnx. …

OnnxInference

Loads an ONNX file or object or stream. Computes the output of the ONNX graph. Several runtimes …

OnnxInference2

onnxruntime API

OnnxInferenceExport

Implements methods to export a instance of OnnxInference into json or dot.

OnnxInferenceNode

A node to execute.

OnnxNotebook

Defines magic commands to help with notebooks

OnnxPipeline

The pipeline overwrites method fit, it trains and converts every steps into ONNX before training the next step …

OnnxRuntimeMissingNewOnnxOperatorException

Raised when a new operator was added but cannot be found.

OnnxTokenizer_1

Defines a custom operator not defined by ONNX specifications but in onnxruntime.

OnnxTokenizer_1

Defines a custom operator not defined by ONNX specifications but in onnxruntime.

OnnxTransformer

Calls onnxruntime or the runtime implemented in this package to transform input based on a ONNX graph. It …

OnnxTranslator

Class which converts a Python function into an ONNX function. It must implements methods visit and depart. …

OnnxWholeSession

Runs the prediction for a single ONNX, it lets the runtime handle the graph logic as well.

OpRun

Ancestor to all operators in this subfolder. The runtime for every node can checked into ONNX unit tests. …

OpRunArg

Ancestor to all unary operators in this subfolder and which produces position of extremas (ArgMax, …). Checks …

OpRunBinary

Ancestor to all binary operators in this subfolder. Checks that inputs type are the same.

OpRunBinaryNum

Ancestor to all binary operators in this subfolder. Checks that inputs type are the same.

OpRunBinaryNumpy

Implements the inplaces logic. numpy_fct is a binary numpy function which takes two matrices and has a argument …

OpRunClassifierProb

Ancestor to all binary operators in this subfolder. Checks that inputs type are the same.

OpRunCustom

Automates some methods for custom operators defined outside mlprodict.

OpRunOnnxRuntime

Unique operator which calls onnxruntime to compute predictions for one operator.

OpRunReduceNumpy

Implements the reduce logic. It must have a parameter axes.

OpRunUnary

Ancestor to all unary operators in this subfolder. Checks that inputs type are the same.

OpRunUnaryNum

Ancestor to all unary and numerical operators in this subfolder. Checks that inputs type are the same.

OperatorSchema

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

Or

Or == Returns the tensor resulted from performing the or logical operation elementwise on the input tensors A and …

Pad

Pad === Given a tensor containing the data to be padded (data), a tensor containing the number of start and end pad …

Pow

Pow === Pow takes input data (Tensor<T>) and exponent Tensor, and produces one output data (Tensor<T>) where the function …

QuantizeLinear

QuantizeLinear ============== The linear quantization operator. It consumes a high precision tensor, a scale, and a zero …

RNN

RNN === Computes an one-layer simple RNN. This operator is usually supported via some custom implementation such as CuDNN. …

Reciprocal

Reciprocal ========== Reciprocal takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the reciprocal …

ReduceLogSumExp

ReduceLogSumExp =============== Computes the log sum exponent of the input tensor’s element along the provided axes. The …

ReduceMax

ReduceMax ========= Computes the max of the input tensor’s element along the provided axes. The resulted tensor has the …

ReduceMean

ReduceMean ========== Computes the mean of the input tensor’s element along the provided axes. The resulted tensor has …

ReduceMin

ReduceMin ========= Computes the min of the input tensor’s element along the provided axes. The resulted tensor has the …

ReduceProd

ReduceProd ========== Computes the product of the input tensor’s element along the provided axes. The resulted tensor …

ReduceSumSquare

ReduceSumSquare =============== Computes the sum square of the input tensor’s element along the provided axes. The resulted …

ReduceSum_1

ReduceSum ========= Computes the sum of the input tensor’s element along the provided axes. The resulted tensor has the …

ReduceSum_11

ReduceSum ========= Computes the sum of the input tensor’s element along the provided axes. The resulted tensor has the …

ReduceSum_13

ReduceSum ========= Computes the sum of the input tensor’s element along the provided axes. The resulted tensor has the …

ReduceSum_13

ReduceSum ========= Computes the sum of the input tensor’s element along the provided axes. The resulted tensor has the …

Relu

Relu ==== Relu takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the rectified linear function, …

Reshape

Reshape ======= Reshape the input tensor similar to numpy.reshape. First input is the data tensor, second input is a shape …

RuntimeBadResultsError

Raised when the results are too different from scikit-learn.

RuntimeSVMClassifierDouble

Implements runtime for operator SVMClassifierDouble. The code is inspired from svm_classifier.cc

RuntimeSVMClassifierFloat

Implements runtime for operator SVMClassifier. The code is inspired from svm_classifier.cc

RuntimeSVMRegressorDouble

Implements Double runtime for operator SVMRegressor. The code is inspired from svm_regressor.cc

RuntimeSVMRegressorFloat

Implements float runtime for operator SVMRegressor. The code is inspired from svm_regressor.cc

RuntimeTfIdfVectorizer

Implements runtime for operator TfIdfVectorizer. The code is inspired from tfidfvectorizer.cc

RuntimeTreeEnsembleClassifierDouble

Implements runtime for operator TreeEnsembleClassifier. The code is inspired from tree_ensemble_classifier.cc

RuntimeTreeEnsembleClassifierFloat

Implements runtime for operator TreeEnsembleClassifier. The code is inspired from tree_ensemble_classifier.cc

RuntimeTreeEnsembleClassifierPDouble

Implements double runtime for operator TreeEnsembleClassifier. The code is inspired from tree_ensemble_Classifier.cc

RuntimeTreeEnsembleClassifierPFloat

Implements float runtime for operator TreeEnsembleClassifier. The code is inspired from tree_ensemble_Classifier.cc

RuntimeTreeEnsembleRegressorDouble

Implements double runtime for operator TreeEnsembleRegressor. The code is inspired from tree_ensemble_regressor.cc

RuntimeTreeEnsembleRegressorFloat

Implements float runtime for operator TreeEnsembleRegressor. The code is inspired from tree_ensemble_regressor.cc

RuntimeTreeEnsembleRegressorPDouble

Implements double runtime for operator TreeEnsembleRegressor. The code is inspired from tree_ensemble_regressor.cc

RuntimeTreeEnsembleRegressorPFloat

Implements float runtime for operator TreeEnsembleRegressor. The code is inspired from tree_ensemble_regressor.cc

RuntimeTypeError

Raised when a type of a variable is unexpected.

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.

SVMRegressor

SVMRegressor (ai.onnx.ml) ========================= Support Vector Machine regression prediction and one-class SVM anomaly …

SVMRegressorCommon

SVMRegressorDouble

SVMRegressorDouble (mlprodict) ============================== Version Onnx name: SVMRegressorDouble

SVMRegressorDoubleSchema

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

Scaler

Scaler (ai.onnx.ml) =================== Rescale input data, for example to standardize features by removing the mean and …

Scan

Scan ==== Scan can be used to iterate over one or more scan_input tensors, constructing zero or more scan_output tensors. …

Shape

Shape ===== Takes a tensor as input and outputs an 1D int64 tensor containing the shape of the input tensor. Inputs

ShapeBinaryFctOperator

Base class for shape binary operator defined by a function.

ShapeBinaryOperator

Base class for shape binary operator.

ShapeObject

Handles mathematical operations around shapes. It stores a type (numpy type), and a name to somehow have …

ShapeObjectFct

Computes a shape depending on a user defined function. See Conv for an example.

ShapeOperator

Base class for all shapes operator.

ShapeOperatorAdd

Shape addition.

ShapeOperatorGreater

Shape comparison.

ShapeOperatorMax

Best on each dimension.

ShapeOperatorMul

Shape multiplication.

Sigmoid

Sigmoid ======= Sigmoid takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the sigmoid function, …

Sign

Sign ==== Calculate the sign of the given input tensor element-wise. If input > 0, output 1. if input < 0, output -1. …

SimplifiedOnnxInference

Simple wrapper around InferenceSession which imitates OnnxInference.

Sin

Sin === Calculates the sine of the given input tensor, element-wise. Inputs

Slice

Slice ===== Produces a slice of the input tensor along multiple axes. Similar to numpy: https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html

Softmax

Softmax ======= The operator computes the normalized exponential values for the given input: Softmax(input, axis) = …

Solve

Solve (mlprodict) ================= Version Onnx name: Solve

SolveSchema

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

Split

Runtime for operator Split.

Sqrt

Sqrt ==== Square root takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the square root …

Squeeze

Squeeze ======= Remove single-dimensional entries from the shape of a tensor. Takes an input axes with a list of axes …

StringNormalizer

The operator is not really threadsafe as python cannot play with two locales at the same time. stop words should …

Sub

Sub === Performs element-wise binary subtraction (with Numpy-style broadcasting support). This operator supports **multidirectional …

Sum

Sum === Element-wise sum of each of the input tensors (with Numpy-style broadcasting support). All inputs and outputs …

TemplateBenchmarkClassifier

asv test for a classifier, Full template can be found in common_asv_skl.py. …

TemplateBenchmarkClassifierRawScore

asv test for a classifier, Full template can be found in common_asv_skl.py. …

TemplateBenchmarkClustering

asv example for a clustering algorithm, Full template can be found in common_asv_skl.py. …

TemplateBenchmarkMultiClassifier

asv example for a classifier, Full template can be found in common_asv_skl.py. …

TemplateBenchmarkOutlier

asv example for an outlier detector, Full template can be found in common_asv_skl.py. …

TemplateBenchmarkRegressor

asv example for a regressor, Full template can be found in common_asv_skl.py. …

TemplateBenchmarkTrainableTransform

asv example for a trainable transform, Full template can be found in common_asv_skl.py. …

TemplateBenchmarkTransform

asv example for a transform, Full template can be found in common_asv_skl.py. …

TemplateBenchmarkTransformPositive

asv example for a transform, Full template can be found in common_asv_skl.py. …

TfIdfVectorizer

TfIdfVectorizer =============== This transform extracts n-grams from the input sequence and save them as a vector. Input …

Tokenizer

See Tokenizer.

TokenizerSchema

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

TopK_1

TopK ==== Retrieve the top-K elements along a specified axis. Given an input tensor of shape [a_1, a_2, …, a_n, r] and …

TopK_10

TopK ==== Retrieve the top-K elements along a specified axis. Given an input tensor of shape [a_1, a_2, …, a_n, r] and …

TopK_11

TopK ==== Retrieve the top-K largest or smallest elements along a specified axis. Given an input tensor of shape [a_1, …

TopK_11

TopK ==== Retrieve the top-K largest or smallest elements along a specified axis. Given an input tensor of shape [a_1, …

Transpose

Transpose ========= Transpose the input tensor similar to numpy.transpose. For example, when perm=(1, 0, 2), given an …

TreeEnsembleClassifier

TreeEnsembleClassifier (ai.onnx.ml) =================================== Tree Ensemble classifier. Returns the top class …

TreeEnsembleClassifierCommon

TreeEnsembleClassifierDouble

TreeEnsembleClassifierDouble (mlprodict) ======================================== Version Onnx name: TreeEnsembleClassifierDouble

TreeEnsembleClassifierDoubleSchema

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

TreeEnsembleRegressor

TreeEnsembleRegressor (ai.onnx.ml) ================================== Tree Ensemble regressor. Returns the regressed …

TreeEnsembleRegressorCommon

TreeEnsembleRegressorDouble

TreeEnsembleRegressorDouble (mlprodict) ======================================= Version Onnx name: TreeEnsembleRegressorDouble

TreeEnsembleRegressorDoubleSchema

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

Unsqueeze

Unsqueeze ========= Insert single-dimensional entries to the shape of an input tensor (data). Takes one required input …

Where

Where ===== Return elements, either from X or Y, depending on condition (with Numpy-style broadcasting support). Where …

WrappedLightGbmBooster

A booster can be a classifier, a regressor. Trick to wrap it in a minimal function.

WrappedLightGbmBoosterClassifier

Trick to wrap a LGBMClassifier into a class.

XGBClassifierConverter

converter for XGBClassifier

XGBConverter

common methods for converters

XGBRegressorConverter

converter class

ZipMap

The class does not output a dictionary as specified in ONNX specifications but a ArrayZipMapDictionary

ZipMapDictionary

Custom dictionary class much faster for this runtime, it implements a subset of the same methods.

_ArgMax

Base class for runtime for operator ArgMax. …

_ArgMin

Base class for runtime for operator ArgMin. …

_ClassifierCommon

Labels strings are not natively implemented in C++ runtime. The class stores the strings labels, replaces them by …

_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.

_CommonTopK

Ths class hides a parameter used as a threshold above which the parallelisation is started: th_para.

_MyEncoder