module onnxrt.ops_cpu.op_array_feature_extractor#

Inheritance diagram of mlprodict.onnxrt.ops_cpu.op_array_feature_extractor

Short summary#

module mlprodict.onnxrt.ops_cpu.op_array_feature_extractor

Runtime operator.

source on GitHub

Classes#

class

truncated documentation

ArrayFeatureExtractor

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

Functions#

function

truncated documentation

_array_feature_extrator

Implementation of operator ArrayFeatureExtractor with numpy.

sizeof_dtype

Properties#

property

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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_mandatory

Returns the list of optional arguments.

args_optional

Returns the list of optional arguments.

atts_value

Returns all parameters in a dictionary.

Methods#

method

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__init__

_infer_shapes

Infer the shapes for the output.

_infer_types

Returns the type of the output.

_run

Runtime for operator ArrayFeatureExtractor.

Documentation#

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_array_feature_extractor.ArrayFeatureExtractor(ai.onnx.ml)#

Bases: OpRun

Select elements of the input tensor based on the indices passed.

The indices are applied to the last axes of the tensor.

Inputs

  • X (heterogeneous)T: Data to be selected

  • Y (heterogeneous)tensor(int64): The indices, based on 0 as the first index of any dimension.

Outputs

  • Z (heterogeneous)T: Selected output data as an array

Type Constraints

  • T tensor(float), tensor(double), tensor(int64), tensor(int32), tensor(string): The input must be a tensor of a numeric type or string. The output will be of the same tensor type.

Version

Onnx name: ArrayFeatureExtractor

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

Runtime implementation: ArrayFeatureExtractor

__init__(onnx_node, desc=None, **options)#
_infer_shapes(data, indices)#

Infer the shapes for the output.

source on GitHub

_infer_types(data, indices)#

Returns the type of the output.

source on GitHub

_run(data, indices, attributes=None, verbose=0, fLOG=None)#

Runtime for operator ArrayFeatureExtractor.

Warning

ONNX specifications may be imprecise in some cases. When the input data is a vector (one dimension), the output has still two like a matrix with one row. The implementation follows what onnxruntime does in array_feature_extractor.cc.

source on GitHub

mlprodict.onnxrt.ops_cpu.op_array_feature_extractor._array_feature_extrator(data, indices)#

Implementation of operator ArrayFeatureExtractor with numpy.

source on GitHub