module onnxrt.ops_cpu.op_lp_normalization

Short summary

module mlprodict.onnxrt.ops_cpu.op_lp_normalization

Runtime operator.

source on GitHub

Classes

class	truncated documentation
LpNormalization	LpNormalization =============== Given a matrix, apply Lp-normalization along the provided axis. 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
_run_inplace

Documentation

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_lp_normalization.LpNormalization(onnx_node, desc=None, **options)

Bases: OpRunUnaryNum

---

Given a matrix, apply Lp-normalization along the provided axis.

Attributes

• axis: The axis on which to apply normalization, -1 mean last axis. Default value is nameaxisi-1typeINT (INT)

• p: The order of the normalization, only 1 or 2 are supported. Default value is namepi2typeINT (INT)

Inputs

• input (heterogeneous)T: Input matrix

Outputs

• output (heterogeneous)T: Matrix after normalization

Type Constraints

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

Version

Onnx name: LpNormalization

This version of the operator has been available since version 1.

Runtime implementation: LpNormalization

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

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

Should be overwritten.

source on GitHub

_run_inplace(x, norm)