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UpdatedOctober 29, 2025

Log

Description

Calculates the natural log of the given input tensor, element-wise.

 

Input parameters

 

specified_outputs_name :Β array, this parameter lets you manually assign custom names to the output tensors of a node.
Β input (heterogeneous) – T : object, input tensor.

Β Parameters :Β cluster,

Β training?Β :Β boolean, whether the layer is in training mode (can store data for backward).
Default value β€œTrue”.
Β lda coeff :Β float, defines the coefficient by which the loss derivative will be multiplied before being sent to the previous layer (since during the backward run we go backwards).
Default value β€œ1”.

Β name (optional) :Β string, name of the node.

Output parameters

 

Β output (heterogeneous) – T : object, the natural log of the input tensor computed element-wise.

Type Constraints

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

Example

All these exemples are snippets PNG, you can drop these Snippet onto the block diagram and get the depicted code added to your VI (Do not forget to install Deep Learning library to run it).
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