Prem George

Yes, I am waiting for this as well, Thanks

I gone through their code in https://github.com/keras-team/autokeras/blob/master/autokeras/keras_layers.py in line 55 for MultiCategoryEncoding, mentioned Encode the categorical features to numerical features. image I tried manually encoding before building model, it worked,...

Thanks for the Clarification. Actually I thought based on dataset data types, categorical fields to be mentioned as categorical and only numerical fields to be mentioned as numerical, I didn't...

In StructuredDataClassifier model which is ExportedautoKeras_model does not support ExportedautoKeras_model.classes_ and does not have history, where as Keras model supports both, is it possible to get that in StructuredDataClassifier model

getting same error in python==3.9.5 tensorflow==2.5.0 keras2onnx==1.7.0 onnxruntime==1.8.0 keras==2.4.3 ``` onnx_model = keras2onnx.convert_keras(model, model_name, debug_mode=1) content = onnx_model.SerializeToString() sess = onnxruntime.InferenceSession(content) ``` ``` ERROR:AutoMLWebApi:500 Internal Server Error: 'KerasTensor' object has...

Thank you @yan12125, that worked perfect for me in python==3.9.5, tensorflow==2.5.0, keras2onnx==1.7.0, onnxruntime==1.8.0, keras==2.4.3, tf2onnx==1.9.1

I'm getting a strange error from onnxruntime Below code works perfect in standalone (python==3.9.5, tensorflow==2.5.0, keras2onnx==1.7.0, onnxruntime==1.8.0, keras==2.4.3, tf2onnx==1.9.1) ``` autoKeras_model = StructuredDataClassifier(max_trials=10) autoKeras_model.fit(x=X_train, y=y_train, validation_data=(X_valid, y_valid), epochs=100, verbose=1) ExportedautoKeras_model...

For getting input_name ``` model.graph.input[0].name ``` above works, But If that's a converter bug, how should I find the correct opset? (I have tried opset from 9 to 13, all...

issue solved with ``` pip uninstall tf2onnx pip install git+https://github.com/onnx/tensorflow-onnx@tom/keras_hash_tables ```

Hi, Can i have some help on the above please, Using tensorflow == 2.3.0 keras == 2.4.3 Thanks