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UpdatedOctober 29, 2025

5D

Description

Adds to the ptr input array a 5D array (of type BOOL,Β SGL,Β INT,Β UINT, orΒ STRING) at a specified name. Type : polymorphic.

 

 

Input parameters

 

Β 5D Input Data : array,Β 5D array of data with any type : integers (signed/unsigned), floats, doubles, booleans, or strings.

Β Data in :Β array,

Β input_name :Β string,Β specifies the identifier of the input. It corresponds to the name given to the input during its creation (via the optionalΒ nameΒ parameter).
Β Inputs Info :Β cluster

Β inputs_ptr :Β integer,Β represents a pre-allocated device memory address (for example, a CUDA device pointer) where the input tensor data is already stored.
Β inputs_shapes :Β array,Β specifies the shape of the output tensor. Since the data is written into a pre-allocated device buffer, this shape allows the runtime to interpret the memory layout correctly.
Β inputs_ranks :Β integer,Β indicates the rank of the tensor, i.e. the number of dimensions (Scalar = 0, 1D = 1, 2D = 2, etc.).
Β inputs_types :Β enum,Β defines the ONNX tensor type as an enumerated value (e.g. FLOAT, INT64, STRING).

Β input name :Β string,Β specifies the identifier of the input. It corresponds to the name given to the input during its creation (via the optionalΒ nameΒ parameter).

Output parameters

 

Β Data in :Β array,

Β input_name :Β string,Β specifies the identifier of the input. It corresponds to the name given to the input during its creation (via the optionalΒ nameΒ parameter).
Β Inputs Info :Β cluster

Β inputs_ptr :Β integer,Β represents a pre-allocated device memory address (for example, a CUDA device pointer) where the input tensor data is already stored.
Β inputs_shapes :Β array,Β specifies the shape of the output tensor. Since the data is written into a pre-allocated device buffer, this shape allows the runtime to interpret the memory layout correctly.
Β inputs_ranks :Β integer,Β indicates the rank of the tensor, i.e. the number of dimensions (Scalar = 0, 1D = 1, 2D = 2, etc.).
Β inputs_types :Β enum,Β defines the ONNX tensor type as an enumerated value (e.g. FLOAT, INT64, STRING).

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 Accelerator library to run it).

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