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RegexFullMatch

Description

RegexFullMatch performs a full regex match on each element of the input tensor. If an element fully matches the regex pattern specified as an attribute, the corresponding element in the output is True and it is False otherwise. RE2 regex syntax is used.

 

Input parameters

 

specified_outputs_name : array, this parameter lets you manually assign custom names to the output tensors of a node.
X (heterogeneous) – T1 : object, tensor with strings to match on.

 Parameters : cluster,

pattern : string, regex pattern to match on. This must be valid RE2 syntax.
 training? : boolean, whether the layer is in training mode (can store data for backward).
Default value “True”.
 lda coeff : 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 “1”.

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

Output parameters

 

 Y (heterogeneous) – T2 : object, tensor of bools indicating if each input string fully matches the regex pattern specified.

Type Constraints

T1 in (tensor(string)) : Inputs must be UTF-8 strings

T2 in (tensor(bool)) : Outputs are bools and are True where there is a full regex match and False otherwise.

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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