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[TDF] Announcing LabVIEW Deep Learning module - HAIBAL

Dear Community,

 

TDF is proud to announced the coming soon release of HAIBAL library to do Deep Learning on LabVIEW.

 



 

The project consists of more than 3000 VIs including, all is coded in LabVIEW native:😱😱😱

  • 16 activations (ELU, Exponential, GELU, HardSigmoid, LeakyReLU, Linear, PReLU, ReLU, SELU, Sigmoid, SoftMax, SoftPlus, SoftSign, Swish, TanH, ThresholdedReLU), nonlinear mathematical function generally placed after each layer having weights.
  • 84 functional layers/layers (Dense, Conv, MaxPool, RNN, Dropout, etc…).
  • 14 loss functions (BinaryCrossentropy, BinaryCrossentropyWithLogits, Crossentropy, CrossentropyWithLogits, Hinge, Huber, KLDivergence, LogCosH, MeanAbsoluteError, MeanAbsolutePercentage, MeanSquare, MeanSquareLog, Poisson, SquaredHinge), function evaluating the prediction in relation to the target.
  • 15 initialization functions (Constant, GlorotNormal, GlorotUniform, HeNormal, HeUniform, Identity, LeCunNormal, LeCunUniform, Ones, Orthogonal, RandomNormal, Random,Uniform, TruncatedNormal, VarianceScaling, Zeros), function initializing the weights.
  • 7 Optimizers (Adagrad, Adam, Inertia, Nadam, Nesterov, RMSProp, SGD), function to update the weights.

 Release soon

#deep learning  #pytorch  #computer vision  #keras #haibal #TDF #LabVIEW #inference #neural network #cuda #DNN #CuDNN #yolo #MLP #HPC #ngene


Youssef Menjour


Graiphic


www.Graiphic.io


y.menjour@graiphic.io


LabVIEW architect passionate about robotics and deep learning.



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