Issue With Adamoptimizer

I'm using a simple network and i'm trying to use AdamOptimizer to minimize the loss in a Q learning contexte. Here the code : ### DATASET IMPORT from DataSet import * ### NETWORK

Solution 1:

In TF2 the loss parameter of the minimize method must be a Python callable.

Thus, you can change your loss definition to:

defloss():
    return tf.square(target_Q - curent_Q)

and use it without converting it to a Tensor:

self.optimizer.minimize(loss, self.model.trainable_variables)