ai.onnx.ml - FeatureVectorizer#
shape inference: False
This version of the operator has been available since version 1 of domain ai.onnx.ml.
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.
inputdimensions: The size of each input in the input list
Between 1 and 2147483647 inputs.
X (variadic, heterogeneous) - T1: An ordered collection of tensors, all with the same element type.
Y (heterogeneous) - tensor(float): The output array, elements ordered as the inputs.
T1 in ( tensor(double), tensor(float), tensor(int32), tensor(int64) ): The input type must be a tensor of a numeric type.