Hello communit,
i saved a model which i trained for a deep-q learning project. Tensorflow/keras 2.7.0 on Python 3.9.9 64bit on Windows 10. When i load the model again and use it for inference, it works fine.
It is not a very special model:
        model = Sequential()
        model.add(Conv2D(256, (3, 3), input_shape=self.env.OBSERVATION_SPACE_VALUES))
        model.add(Activation('relu'))
        model.add(MaxPooling2D(pool_size=(2, 2)))
        model.add(Dropout(0.2))
        model.add(Conv2D(256, (3, 3)))
        model.add(Activation('relu'))
        model.add(MaxPooling2D(pool_size=(2, 2)))
        model.add(Dropout(0.2))
        model.add(Flatten())  # this converts our 3D feature maps to 1D feature vectors
        model.add(Dense(64))
        model.add(Dense(self.env.ACTION_SPACE_SIZE, activation='linear'))
        model.compile(loss="mse", optimizer=Adam(learning_rate=LEARNING_RATE), metrics=['accuracy'])

Savig
model.save(model_filename)

Loading
model = keras.models.load_model(model_filename)

I want to use the model on a tf/keras 2.7.0 setup on a Raspberry Pi OS 64bit (bullseye) machine. When i use the same code for loading the model as on the Windows machine, i get the following error:
/usr/local/lib/python3.9/dist-packages/keras/saving/saved_model/load.py:116: RuntimeWarning: Unexpected end-group tag: Not all data was converted
  metadata.ParseFromString(file_content)

What does this mean?