module onnxrt.ops_cpu.op_neg

Short summary

module mlprodict.onnxrt.ops_cpu.op_neg

Runtime operator.

source on GitHub

Classes

class	truncated documentation
Neg	Neg === Neg takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where each element flipped sign, …

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_neg.Neg(onnx_node, desc=None, **options)

Bases: OpRunUnaryNum

===

Neg takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where each element flipped sign, y = -x, is applied to the tensor elementwise.

Inputs

• X (heterogeneous)T: Input tensor

Outputs

• Y (heterogeneous)T: Output tensor

Type Constraints

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

Version

Onnx name: Neg

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

Runtime implementation: Neg

__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