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.