ai.onnx.ml - FeatureVectorizer

FeatureVectorizer - 1 (ai.onnx.ml)

Version

  • name: FeatureVectorizer (GitHub)

  • domain: ai.onnx.ml

  • since_version: 1

  • function: False

  • support_level: SupportType.COMMON

  • shape inference: False

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

Summary

Concatenates input tensors into one continuous output.<br> All input shapes are 2-D and are concatenated along the second dimension. 1-D tensors are treated as [1,C]. Inputs are copied to the output maintaining the order of the input arguments.<br> All inputs must be integers or floats, while the output will be all floating point values.

Attributes

  • inputdimensions - INTS :

    The size of each input in the input list

Inputs

Between 1 and 2147483647 inputs.

  • X (variadic, heterogeneous) - T1:

    An ordered collection of tensors, all with the same element type.

Outputs

  • Y (heterogeneous) - tensor(float):

    The output array, elements ordered as the inputs.

Type Constraints

  • T1 in ( tensor(double), tensor(float), tensor(int32), tensor(int64) ):

    The input type must be a tensor of a numeric type.