Welcome to our Support Center
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Quick start
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API
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- Dense
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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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- DepthwiseConv2D
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- BatchNormalization
- LayerNormalization
- PReLU 2D
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- Bidirectional
- GRU
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- RNN (GRU)
- RNN (LSTM)
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- SimpleRNN
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- Dense
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- AdditiveAttention
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- Conv1D
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- Conv1DTranspose
- Conv2DTranspose
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- DepthwiseConv2D
- SeparableConv1D
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- BatchNormalization
- LayerNormalization
- PReLU 2D
- PReLU 3D
- PReLU 4D
- PReLU 5D
- Bidirectional
- GRU
- LSTM
- RNN (GRU)
- RNN (LSTM)
- RNN (SimpleRNN)
- SimpleRNN
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- Dense
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- Conv1D
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- DepthwiseConv2D
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- BatchNormalization
- LayerNormalization
- PReLU 2D
- PReLU 3D
- PReLU 4D
- PReLU 5D
- Bidirectional
- GRU
- LSTM
- RNN (GRU)
- RNN (LSTM)
- RNN (SimpleRNN)
- SimpleRNN
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- Add
- AdditiveAttention
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- Flatten
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- GRU
- Input
- LayerNormalization
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- MaxPool1D
- MaxPool2D
- MaxPool3D
- MultiHeadAttention
- Multiply
- Permute3D
- Reshape
- RNN
- SeparableConv1D
- SeparableConv2D
- SimpleRNN
- SpatialDropout
- Substract
- TimeDistributed
- UpSampling1D
- UpSampling2D
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- ZeroPadding1D
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- AlphaDropout
- AvgPool1D
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- Conv1D
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- Conv2DTranspose
- Conv3D
- Conv3DTranspose
- Cropping1D
- Cropping2D
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- Dense
- DepthwiseConv2D
- Dropout
- Embedding
- Flatten
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- GlobalAvgPool1D
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- GlobalAvgPool3D
- GlobalMaxPool1D
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- GlobalMaxPool3D
- GRU
- LayerNormalization
- LSTM
- MaxPool1D
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- MaxPool3D
- Permute3D
- Reshape
- RNN
- SeparableConv1D
- SeparableConv2D
- SimpleRNN
- SpatialDropout
- UpSampling1D
- UpSampling2D
- UpSampling3D
- ZeroPadding1D
- ZeroPadding2D
- ZeroPadding3D
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- Resume
- Accuracy
- BinaryAccuracy
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- Poisson
- Precision
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- Recall
- RecallAtPrecision
- RootMeanSquaredError
- SensitivityAtSpecificity
- SparseCategoricalAccuracy
- SparseCategoricalCrossentropy
- SparseTopKCategoricalAccuracy
- Specificity
- SpecificityAtSensitivity
- SquaredHinge
- Sum
- TopKCategoricalAccuracy
- TrueNegatives
- TruePositives
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- Resume
- Constant
- GlorotNormal
- GlorotUniform
- HeNormal
- HeUniform
- Identity
- LecunNormal
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- Ones
- Orthogonal
- RandomNormal
- RandomUnifom
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Updated
Load
Description
Loads a model from a binary file.
Input parameters
file_path : path, binary file path.
weight_mode : enum
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- LOAD
- RANDOM
Output parameters
Model out : model architecture.
models_out : array
model : model architecture.
last layer name : string, name of the last layer.
1 – Load Model
Loading a model saved in a binary file.
2 – Get Function
We use the “Get All Index/Name” function to get the names of all layers in the model.
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).
Using the “Load” function
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