module onnxrt.ops_cpu.op_div

Short summary

module mlprodict.onnxrt.ops_cpu.op_div

Runtime operator.

source on GitHub

Classes

class	truncated documentation
Div	Div === Performs element-wise binary division (with Numpy-style broadcasting support). This operator supports **multidirectional …

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_div.Div(onnx_node, desc=None, **options)

Bases: OpRunBinaryNumpy

===

Performs element-wise binary division (with Numpy-style broadcasting support).

This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.

(Opset 14 change): Extend supported types to include uint8, int8, uint16, and int16.

Inputs

• A (heterogeneous)T: First operand.

• B (heterogeneous)T: Second operand.

Outputs

• C (heterogeneous)T: Result, has same element type as two inputs

Type Constraints

• T tensor(uint8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(int8), tensor(int16), tensor(int32), tensor(int64), tensor(float16), tensor(float), tensor(double), tensor(bfloat16): Constrain input and output types to all numeric tensors.

Version

Onnx name: Div

This version of the operator has been available since version 14.

Runtime implementation: Div

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

_run(a, b, attributes=None, verbose=0, fLOG=None)

Should be overwritten.

source on GitHub