What is the meaning of "trainable_weights" in Keras?
Trainable weights are the weights that will be learnt during the training process. If you do trainable=False then those weights are kept as it is and are not changed because they are not learnt. You might see some "strange numbers" because either you are using a pre-trained network that has its weights already learnt or you might be using random initialization when defining the model. When using transfer learning with pre-trained models a common practice is to freeze the weights of base model (pre-trained) and only train the extra layers that you add at the end.
If I freeze my base_model with trainable=false, I get strange numbers with trainable_weights.
Before freezing my model has 162 trainable_weights. After freezing, the model only has 2. I tied 2 layers to the pre-trained network. Does trainable_weights show me the layers to train? I find the number weird, when I see 2,253,335 Trainable params.