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SOTA
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Accelerator Toolkit
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Deep Learning Toolkit
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- Output Predict
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- Exp
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- AveragePool
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- GlobalAveragePool
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- lrfft
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- MeanVarianceNormalization
- MicrosoftGelu
- Mish
- Multinomial
- MurmurHash3
- Neg
- NhwcMaxPool
- NonZero
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- OptionalGetElement
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- Add
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- PackedAttention
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- Attention
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- AdditiveAttention
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- AdditiveAttention
- Attention
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- Dense
- Embedding
- LayerNormalization
- GRU
- PReLU 2D
- PReLU 3D
- PReLU 4D
- MultiHeadAttention
- LSTM
- PReLU 5D
- SeparableConv1D
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- SimpleRNN
- RNN (GRU)
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- AdditiveAttention
- Attention
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- Dense
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- Embedding
- GRU
- LayerNormalization
- LSTM
- MultiHeadAttention
- PReLU 2D
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- PReLU 4D
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- SeparableConv1D
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- Dense
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- Conv2DTranspose
- Conv3DTranspose
- DepthwiseConv2D
- SeparableConv1D
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- BatchNormalization
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- PReLU 2D
- PReLU 3D
- PReLU 4D
- PReLU 5D
- Bidirectional
- GRU
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- Dense
- Embedding
- AdditiveAttention
- Attention
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- Conv1D
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- DepthwiseConv2D
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- BatchNormalization
- LayerNormalization
- PReLU 2D
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- GRU
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- Accuracy
- BinaryAccuracy
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- MeanTensor
- OneHotIoU
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- Poisson
- Precision
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- Recall
- RecallAtPrecision
- RootMeanSquaredError
- SensitivityAtSpecificity
- SparseCategoricalAccuracy
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- Specificity
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- TrueNegatives
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- Dense
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- PReLU 2D
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- Dense
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- DepthwiseConv2D
- SeparableConv1D
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- LayerNormalization
- PReLU 2D
- PReLU 3D
- PReLU 4D
- PReLU 5D
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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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- Short Array
- Reverse 1D array
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- Rotate 1D Array
- Increment Array Element
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- Interpolate 1D Array
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- Absolute
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FREQUENTLY ASKED QUESTIONS
Which layers are supported by the toolkit ?
HAIBAL offers all existing layers and is constantly updated. The detail of the available layers is availableΒ here.
Do we need Python Language installation to run the toolkit ?
No. HAIBAL deep learning toolkit is fully powered in LabVIEW. We worked more than 2 years to rewrite all the layers and functionalities in native LabVIEW.Β
Does the toolkit support evaluation ?
Yes, you will get 30 days evaluation period after the installation.
How many simultaneous installation can i do with a licence ?
We have the same policy as NI with LabVIEWΒ on licencing. The licence is for one user and allow to install on 3 computer simultaneously.
How to move already activated license to another computer ?
You will need to deactivate the toolkit on the PC where it is already activated and activate the same license on the other PC.
What type of hardware is supported by the toolkit ?
HAIBAL supports x86 based PC Windows OS for training and inference (a Linux version is under development).
FPGAs, AMD GPUs, intel GPUs will be integrate in the future (also under development).
Does the toolkit support GPU acceleration ?
Yes, the training and inferences can be accelerated on Nvidia GPUs, more information.
Which version of LabVIEW is supported by the toolkit ?
The latest version of the toolkit supports 64-bit versions of LabVIEWΒ 2020 and LabVIEW 2022. For a specific version pleaseΒ contact us.
