module onnxrt.ops_cpu.op_lp_normalization#

Inheritance diagram of mlprodict.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)#