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Resume

In this section you’ll find a list of all model fonctionalities.

  ICONS RESUME
Open Log Folder When an error occurs during the execution of the model it is recorded in a temporary file.
Reset GPU Device Close all references.
Toolkit Version Gets the Deep Learning library version.
Summary Returns the summary of the model.
Netron Summary Open Netron visualization of the given model.
Add Graph Adds the “FollowingModel” to the model.
Merge Merge multiple branches of graphs to create a single graph and avoid duplication.
One To Mult Allows you to retrieve the different merged graphs.
Load ONNX File Loads an ONNX model from file and creates the corresponding execution graph.
Save ONNX File This VI exports a model to a .onnx file.
Convert H5 To ONNX This VI uses the keras2onnx Python utility to perform the conversion.
Convert Keras To ONNX This VI transforms a .keras model file (in the new Keras v3 format) into a standard .onnx file using a Python conversion tool.
Convert ONNX To H5 This VI transforms a .onnx model into the HDF5 format (.h5) commonly used in TensorFlow/Keras workflows. 
Convert ONNX To Keras This VI transforms a .onnx model file into the native .keras format introduced in Keras 3.x.
Convert ONNX To Pytorch This VI exports an ONNX model into the PyTorch .pt format using a Python-based toolchain.
Convert To TF SavedModel This VI transforms a .onnx file into a TensorFlow model using the standard SavedModel directory structure.
Convert Pytorch To ONNX This VI uses a Python-based export pipeline to convert a PyTorch model saved as .pt (TorchScript) into a .onnx file.
Convert TF SavedModel To ONNX This VI converts a TensorFlow model saved in the SavedModel directory format into a .onnx file, using the tf2onnx converter.
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