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- Dense
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- Dense
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- Dense
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- PReLU 2D
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- Dense
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- PReLU 2D
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- Bidirectional
- GRU
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- RNN (GRU)
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- Add
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- AlphaDropout
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- GRU
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- Resume
- Accuracy
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- RootMeanSquaredError
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- SparseCategoricalAccuracy
- SparseCategoricalCrossentropy
- SparseTopKCategoricalAccuracy
- Specificity
- SpecificityAtSensitivity
- SquaredHinge
- Sum
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- TrueNegatives
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- Resume
- Constant
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- Identity
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Updated
Attention
Description
Gets the weights of the Attention layer selected by the name. Type : polymorphic.
Input parameters
Model in : model architecture.
name : string, name of layer.
Output parameters
Model out : model architecture.
weights_info : cluster
index : integer, index of layer.
name : string, name of layer.
weights : cluster
scale : float, scale value.
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 HAIBAL library to run it).
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