ai.onnx.ml - FeatureVectorizer#
FeatureVectorizer - 1 (ai.onnx.ml)#
Version
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.
All input shapes are 2-D and are concatenated along the second dimention. 1-D tensors are treated as [1,C]. Inputs are copied to the output maintaining the order of the input arguments.
All inputs must be integers or floats, while the output will be all floating point values.
Attributes
inputdimensions: 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.
Examples