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Training custom object detection models with TensorFlow usually means a transfer learning of pre-trained models and, if I understand it correctly, it means only training the few last layers, with previous layers being already trained to save time.

How can I know how many and which layers are trained in such transfer learning process, and can I somehow change the number of layers trained, for example, for "SSD MobileNet V2" model?

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