Export typical PyTorch onnx / pth. import torch torch.onnx.export(mm, torch.randn(1, 3, *mm.input_shape[2:]), mm.name + ".onnx") # Or by export_onnx mm.export_onnx() # Exported onnx: resmlp12.onnx mm.export_pth() # Exported pth: resmlp12.pth Save weights as h5. This...
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sensors Article Compensation of PVT Variations in ToF Imagers with In-Pixel TDC Ion Vornicu *, Ricardo Carmona-Galán and Ángel Rodríguez-Vázquez Instituto de Microelectrónica de Sevilla, IMSE-CNM (CSIC-Universidad de Sevilla), Avda. Américo Vespucio s/n, Parque Científico y Tecnológico ...
[Deprecated]tensorflow_addonsis not imported by default. While reloading model depending onGroupNormalizationlikeMobileViTV2fromh5directly, needs to importtensorflow_addonsmanually first. importtensorflow_addonsastfa model_path = os.path.expanduser('~/.keras/models/mobilevit_v2_050_256_imagenet.h5')...
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export_pth() # Exported pth: resmlp12.pth Save weights as h5. This h5 can also be loaded in typical TF backend model. Currently it's only weights without model structure supported. mm.save_weights("foo.h5")Recognition ModelsAotNetKeras AotNet is just a ResNet / ResNetV2 like ...