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SOTA
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Accelerator Toolkit
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Deep Learning Toolkit
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- Resume
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- Exp
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- Add
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- RestorePadding
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- Slice
- SparseToDenseMatMul
- SplitToSequence
- Squeeze
- STFT
- StringConcat
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- Tile
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- Where
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- Attention
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- AdditiveAttention
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- AdditiveAttention
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- Conv3DTranspose
- DepthwiseConv2D
- Dense
- Embedding
- LayerNormalization
- GRU
- PReLU 2D
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- MultiHeadAttention
- LSTM
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- RNN (GRU)
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- AdditiveAttention
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- Dense
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- Embedding
- GRU
- LayerNormalization
- LSTM
- MultiHeadAttention
- PReLU 2D
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- Resume
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- Dense
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- BatchNormalization
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- PReLU 2D
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- PReLU 5D
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- Accuracy
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- RootMeanSquaredError
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- Dense
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- PReLU 2D
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Computer Vision Toolkit
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CUDA Toolkit
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- Resume
- Array size
- Index Array
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- Insert Into Array
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- Increment Array Element
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- Remove Duplicate From 1D Array
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- Add Array Element
- Multiply Array Element
- Absolute
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- Scale By Power Of Two
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Read Streaming
Description
Retrieves the most recent training outputs produced during asynchronous streaming fit. Unlike FIFO mode, this VI does not buffer multiple records, it always returns the latest available values.
Input parameters
Β Training inΒ :Β object,Β training session.
stop fit? : boolean, when set to TRUE, signals the training loop to stop before completing all requested epochs.
Output parameters
Β Training outΒ :Β object,Β training session.
Fit OutputsΒ : cluster, contains the training status information read from the FIFO.
epochΒ : integer, current epoch number reached during training.
iteration : integer, current iteration within the epoch.
LossesΒ : array, array of loss values.
name : string, the identifier of the loss function.
valueΒ : float, the numeric value of the loss at this step.
