ai.onnx.ml - Scaler#

Scaler - 1 (ai.onnx.ml)#

Version#

  • name: Scaler (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#

Rescale input data, for example to standardize features by removing the mean and scaling to unit variance.

Attributes#

  • offset - FLOATS :

    First, offset by this.
    Can be length of features in an [N,F] tensor or length 1, in which case it applies to all features, regardless of dimension count.

  • scale - FLOATS :

    Second, multiply by this.
    Can be length of features in an [N,F] tensor or length 1, in which case it applies to all features, regardless of dimension count.
    Must be same length as ‘offset’

Inputs#

  • X (heterogeneous) - T:

    Data to be scaled.

Outputs#

  • Y (heterogeneous) - tensor(float):

    Scaled output data.

Type Constraints#

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

    The input must be a tensor of a numeric type.