module onnxrt.ops_cpu.op_round

Short summary

module mlprodict.onnxrt.ops_cpu.op_round

Runtime operator.

source on GitHub

Classes

class	truncated documentation
Round	Round ===== Round takes one input Tensor and rounds the values, element-wise, meaning it finds the nearest integer for …

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
to_python

Documentation

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_round.Round(onnx_node, desc=None, **options)

Bases: OpRunUnaryNum

---

Round takes one input Tensor and rounds the values, element-wise, meaning it finds the nearest integer for each value. In case of halfs, the rule is to round them to the nearest even integer. The output tensor has the same shape and type as the input.

Examples: `` round([0.9]) = [1.0] round([2.5]) = [2.0] round([2.3]) = [2.0] round([1.5]) = [2.0] round([-4.5]) = [-4.0] ``

Inputs

• X (heterogeneous)T: Input tensor

Outputs

• Y (heterogeneous)T: Output tensor

Type Constraints

• T tensor(float16), tensor(float), tensor(double): Constrain input and output types to float tensors.

Version

Onnx name: Round

This version of the operator has been available since version 11.

Runtime implementation: Round

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

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

Should be overwritten.

source on GitHub

_run_inplace(x)

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