Forum
Login
Register

Welcome to our Support Center
UpdatedAugust 20, 2025

MicrosoftGatherND

Description

GivenΒ dataΒ tensor of rank r >= 1, andΒ indicesΒ tensor of rank q >= 1, gather slices ofΒ dataΒ into an output tensor of rank q – 1 + r – indices[-1]. Example 1: data = [[0,1],[2,3]] indices = [[0,0],[1,1]] output = [0,3] Example 2: data = [[0,1],[2,3]] indices = [[1],[0]] output = [[2,3],[0,1]] Example 3: data = [[[0,1],[2,3]],[[4,5],[6,7]]] indices = [[0,1],[1,0]] output = [[2,3],[4,5]] Example 4: data = [[[0,1],[2,3]],[[4,5],[6,7]]] indices = [[[0,1]],[[1,0]]] output = [[[2,3]],[[4,5]]]

 

Β 

Input parameters

 

specified_outputs_name :Β array, this parameter lets you manually assign custom names to the output tensors of a node.

Β Graphs in :Β cluster, ONNX model architecture.

Β dataΒ (heterogeneous) – T :Β object, tensor of rank r >= 1.
Β indices (heterogeneous) – Tind : object, tensor of rank q >= 1.

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 outputΒ (heterogeneous) – T :Β object, tensor of rank q-1+r-indices[-1].

Type Constraints

T in (tensor(uint8),Β tensor(uint16),Β tensor(uint32),Β tensor(uint64),Β tensor(int8),Β tensor(int16),Β tensor(int32),
tensor(int64),Β tensor(float16),Β tensor(float),Β tensor(double),Β tensor(string),Β tensor(bool),Β tensor(complex64),Β tensor(complex128)) : Constrain input and output types to any tensor type.

Tind in (tensor(int32),Β tensor(int64)) : Constrain indice type to int32 or int64.

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).
Table of Contents