module onnxrt.ops_cpu.op_binarizer

Short summary

module mlprodict.onnxrt.ops_cpu.op_binarizer

Runtime operator.

source on GitHub

Classes

class	truncated documentation
Binarizer	Binarizer (ai.onnx.ml) ====================== Maps the values of the input tensor to either 0 or 1, element-wise, based …

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

Documentation

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_binarizer.Binarizer(ai.onnx.ml)

Bases: OpRunUnaryNum

---

Maps the values of the input tensor to either 0 or 1, element-wise, based on the outcome of a comparison against a threshold value.

Attributes

• threshold: Values greater than this are mapped to 1, others to 0. Default value is namethresholdf0.0typeFLOAT (FLOAT)

Inputs

• X (heterogeneous)T: Data to be binarized

Outputs

• Y (heterogeneous)T: Binarized output data

Type Constraints

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

Version

Onnx name: Binarizer

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

Runtime implementation: Binarizer

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

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

Should be overwritten.

source on GitHub