.. _l-onnx-docai.onnx.ml-FeatureVectorizer: ============================== ai.onnx.ml - FeatureVectorizer ============================== .. contents:: :local: .. _l-onnx-opai-onnx-ml-featurevectorizer-1: 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. 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**