module onnxrt.ops_cpu.op_reciprocal#

Inheritance diagram of mlprodict.onnxrt.ops_cpu.op_reciprocal

Short summary#

module mlprodict.onnxrt.ops_cpu.op_reciprocal

Runtime operator.

source on GitHub

Classes#

class

truncated documentation

Reciprocal

Reciprocal ========== Reciprocal takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the reciprocal …

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_reciprocal.Reciprocal(onnx_node, desc=None, **options)#

Bases: OpRunUnaryNum

Reciprocal takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the reciprocal is, y = 1/x, is applied to the tensor elementwise.

Inputs

  • X (heterogeneous)T: Input tensor

Outputs

  • Y (heterogeneous)T: Output tensor

Type Constraints

  • T tensor(float16), tensor(float), tensor(double), tensor(bfloat16): Constrain input and output types to float tensors.

Version

Onnx name: Reciprocal

This version of the operator has been available since version 13.

Runtime implementation: Reciprocal

__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