HW09留学生代写、代做Python设计、代写TODO items、Python编程语言调试-代写Python编程

HW09

The instructions are very simple: download the file and fill in the TODO items. You will submit

your solution as a .py file。

Several notes:

1. The TODO items are the least tricky parts of the code and have substantial hints. Also,

there aren't very many of them.

2. At the same time, there's some fairly interesting/useful stuff in there (like how to do things

manually with gradient values in Keras, which is surprisingly non-trivial to figure out from

scratch), for those who might want to spend more time investigating and experimenting

with the code.

3. Even when you implement all of the methods correctly, it won't work that great most of the

time. In my experience, it gets significant traction sometimes (which shows that there's

not just a gradient ascent sign error or something), but it seems highly dependent on the

luck of the initialization of the weights. You are not responsible for making the algorithm

perform well. You are just responsible for implementing it correctly. However, if someone

does figure out how to tweak the hyper-parameters or otherwise modify the code to get

better results, please share that information with the rest of us.

4. There are some sample method calls in the last function, to help you with incremental

troubleshooting.

5. You can call A.diagnostics() to see some information about what's going on during

training. This is not necessary for the assignment but would be helpful if you want to

troubleshoot the performance .

6. There's a file on the internet which bears some superficial similarity to this one. It doesn't

carry risk of academic dishonesty issues, though, because it is going to be seriously

useless. Just a heads up.

7. The code is kind of intended to be run in a Jupyter notebook, because of the fancy

progress meter. If you want to run it in another context, replace the tqdm import with from

tqdm import tqdm

8. I updated the last page of the RL lesson on Data Gymnasia to reflect the specific method

used in this homework. This is also not really necessary but might be helpful.