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 …

ArgMax

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

ArgMin

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

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 …

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.

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), …

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.

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 Attributes

ConstantOfShape

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

CustomScorerTransform

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

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 …

Equal

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

Exp

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

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), …

GatherElements

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

Gemm

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

Greater

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

Identity

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

Imputer

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

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

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

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.

MLNumTypeInt32

A numpy.int32.

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 …

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 …

Mul

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

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. …

OnnxInference

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

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

OnnxTransformer

Calls onnxruntime inference following scikit-learn API so that it can be included in a scikit-learn

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 posution of extremas. Checks that inputs type …

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.

OpRunOnnxRuntime

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

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.

Pow

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

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 …

ReduceSum

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

ReduceSumSquare

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

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 …

RuntimeSVMClassifier

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

RuntimeSVMRegressor

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

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

RuntimeTypeError

Raised when a type of a variable is unexpected.

SVMClassifier

SVMClassifier (ai.onnx.ml) ========================== Support Vector Machine classifier Attributes

SVMRegressor

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

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 …

ShapeOperator

Base class for all shapes operator.

ShapeOperatorAdd

Shape addition.

ShapeOperatorMax

Shape multiplication.

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. …

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 softmax (normalized exponential) values for each layer in the batch of the …

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 a parameter axes with a list of …

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 …

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.

Where

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

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 subet of the same methods.

_CommonTopK