module onnxrt.ops_cpu.op_scaler

Short summary

module mlprodict.onnxrt.ops_cpu.op_scaler

Runtime operator.

source on GitHub

Classes

class	truncated documentation
Scaler	Scaler (ai.onnx.ml) =================== Rescale input data, for example to standardize features by removing the mean and …

Properties

property	truncated documentation
args_default	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
args_default_modified	Returns the list of modified parameters.
args_mandatory	Returns the list of optional arguments.
args_optional	Returns the list of optional arguments.
atts_value	Returns all parameters in a dictionary.

Methods

method	truncated documentation
__init__
_run
_run_inplace
_run_no_checks_

Documentation

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_scaler.Scaler(ai.onnx.ml)

Bases: OpRunUnary

---

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

Attributes

• offset: 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. default value cannot be automatically retrieved (FLOATS)

• scale: 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’ default value cannot be automatically retrieved (FLOATS)

Inputs

• X (heterogeneous)T: Data to be scaled.

Outputs

• Y (heterogeneous)tensor(float): Scaled output data.

Type Constraints

• T tensor(float), tensor(double), tensor(int64), tensor(int32): The input must be a tensor of a numeric type.

Version

Onnx name: Scaler

This version of the operator has been available since version 1 of domain ai.onnx.ml.

Runtime implementation: Scaler

__init__(onnx_node, desc=None, **options)

_run(x, attributes=None, verbose=0, fLOG=None)

Should be overwritten.

source on GitHub

_run_inplace(x)

_run_no_checks_(x, verbose=0, fLOG=None)