module onnxrt.ops_cpu.op_lp_normalization
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Short summary#
module mlprodict.onnxrt.ops_cpu.op_lp_normalization
Runtime operator.
Classes#
class |
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LpNormalization =============== Given a matrix, apply Lp-normalization along the provided axis. Attributes |
Properties#
property |
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Returns the list of arguments as well as the list of parameters with the default values (close to the signature). … |
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Returns the list of modified parameters. |
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Returns the list of optional arguments. |
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Returns the list of optional arguments. |
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Returns all parameters in a dictionary. |
Methods#
method |
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Documentation#
Runtime operator.
- class mlprodict.onnxrt.ops_cpu.op_lp_normalization.LpNormalization(onnx_node, desc=None, **options)#
Bases:
mlprodict.onnxrt.ops_cpu._op.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
- Parameters
onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options
- __init__(onnx_node, desc=None, **options)#
- Parameters
onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options
- _run(x)#
Should be overwritten.
- _run_inplace(x, norm)#