[HANDS-ON mistake] Unit 4 Policy gradient - mistake in exercise explanation

[migolan]

On the hands on section of unit 4 (policy gradient), when building the REINFORCE policy, the exercise has an intentional bug causing the error message
ValueError: The value argument to log_prob must be a Tensor.
The explanation says that this is error occurs because we should sample the probability distribution rather than argmax it - but that's not the reason this error occurs.
The error occurs because we use np.argmax(Categorical(probs)) rather than torch.argmax(probs).
Indeed, we would nevertheless like to substitute the argmax with sampling, but for different reasons, so the reasoning in the notebook is somewhat misleading.