CastLike

CastLike

Description

The operator casts the elements of a given input tensor (the first input) to the same data type as the elements of the second input tensor. See documentation of the Cast operator for further details.

Documentation illustration (illustration unavailable in the archive).

Input parameters

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

 Graphs in : cluster, ONNX model architecture.

input (heterogeneous) – T1 : object, input tensor to be cast.
target_type (heterogeneous) – T2 : object, the (first) input tensor will be cast to produce a tensor of the same type as this (second input) tensor.

Documentation illustration (illustration unavailable in the archive).

 Parameters : cluster,

 saturate : boolean, the parameter defines how the conversion behaves if an input value is out of range of the destination type. It only applies for float 8 conversion (float8e4m3fn, float8e4m3fnuz, float8e5m2, float8e5m2fnuz). It is true by default. Please refer to operator Cast description for further details.
Default value “True”.
 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.

Documentation illustration (illustration unavailable in the archive).

Output parameters

output (heterogeneous) – T2 : object, output tensor produced by casting the first input tensor to have the same type as the second input tensor.

Type Constraints

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).