Generate: Fix flaky indexing error in `test_constrained_beam_search_generate_dict_output`
# What does this PR do?

Fixes a random indexing error in `test_constrained_beam_search_generate_dict_output` -- For models without integer inputs (like whisper), we were requesting to force a random token between 3 and 99 (inclusive), but the vocab size was also 99. 

This means that when the test attempted to force a `99`, the test would fail with an indexing error.
> For models without integer inputs (like whisper), we were requesting to force a random token between 3 and 99

Sorry, I lack of a bit the context. `models without integer inputs`, but in this failed test, the `input_ids` is still passed to the model, and the model use it (and get index error)? I am a bit confused by reading it literally. <|||||>_The documentation is not available anymore as the PR was closed or merged._<|||||>@ydshieh `input_ids` is a poor variable name in this test (and in many others). It holds a dummy input with the format expected by the model -- for `Whisper`, it is a tensor of type fp32. See below what the debugger prints for this test on `Whisper`

![Screenshot 2023-02-10 at 12 33 14](https://user-images.githubusercontent.com/12240844/218093435-8fb7a755-3a91-4ef4-a943-693a7d1387a1.png)

The touched variables (`min_id` and `max_id`) are used to force a random token (selected between those ids) at generate time. These were the indices triggering the indexing error. Since `generate` always outputs tokens, regardless of the model, the if/else I removed didn't make much sense :)