module onnxrt.ops_cpu.op_isinf

Short summary

module mlprodict.onnxrt.ops_cpu.op_isinf

Runtime operator.

source on GitHub

Classes

class	truncated documentation
IsInf	IsInf ===== Map infinity to true and other values to false. Attributes

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
to_python

Documentation

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_isinf.IsInf(onnx_node, desc=None, **options)

Bases: OpRunUnary

---

Map infinity to true and other values to false.

Attributes

• detect_negative: (Optional) Whether map negative infinity to true. Default to 1 so that negative infinity induces true. Set this attribute to 0 if negative infinity should be mapped to false. Default value is namedetectnegativei1typeINT (INT)

• detect_positive: (Optional) Whether map positive infinity to true. Default to 1 so that positive infinity induces true. Set this attribute to 0 if positive infinity should be mapped to false. Default value is namedetectpositivei1typeINT (INT)

Inputs

• X (heterogeneous)T1: input

Outputs

• Y (heterogeneous)T2: output

Type Constraints

• T1 tensor(float), tensor(double): Constrain input types to float tensors.

• T2 tensor(bool): Constrain output types to boolean tensors.

Version

Onnx name: IsInf

This version of the operator has been available since version 10.

Runtime implementation: IsInf

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

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

Should be overwritten.

source on GitHub

to_python(inputs)

Returns a python code equivalent to this operator.

Parameters:

inputs – inputs name

Returns:

imports, python code, both as strings

source on GitHub