fix: avoid frequency and repetition penalty on padding tokens (#1765)

This PR resolves an issue with the penalty processors during batched
generation where extra padding tokens incorrectly impact the penalty
scores.

generation is impacted in the case where at least one item in the batch
includes a `frequency_penalty`

reproduction script below
```python
import requests
from concurrent import futures
import time

headers = {
    "Content-Type": "application/json",
}

json_data = {
    "inputs": "[INST] Whats the capitol of France? [/INST]",
    "parameters": {
        "max_new_tokens": 100,
        "seed": 20,
        "do_sample": False,
    },
}


json_data2 = {
    "inputs": "<s>[INST]Write a mind bending story: I saw a puppy a cat a rat and a raccoon during my bike ride in the park[/INST]",
    "parameters": {
        "max_new_tokens": 100,
        "seed": 2,
        "do_sample": False,
        # OFFENDING LINE
        "frequency_penalty": 1.05,
    },
}

base_url = "http://localhost:3000/generate"


def req():
    response = requests.post(base_url, headers=headers, json=json_data)
    print("[req ]", response.json())


def req2():
    response = requests.post(base_url, headers=headers, json=json_data2)
    print("[req2]", response.json())


n = 1

for i in range(0, 3):
    print(f"- {n} threads -")
    with futures.ThreadPoolExecutor(max_workers=n) as executor:
        executor.submit(req)
        for i in range(3):
            executor.submit(req2)

    n += 1

# - 1 threads -
# [req ] {'generated_text': ' The capital of France is Paris.'}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# - 2 threads -
# [req ] {'generated_text': ' The capital city'}
# [req2] {'generated_text': ' As""%\n================'}
# [req2] {'generated_text': ' As""%%$\n================'}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}

# output with this PR's changes:
# - 1 threads -
# [req ] {'generated_text': ' The capital of France is Paris.'}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# - 2 threads -
# [req ] {'generated_text': ' The capital city'}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}

```

**divergence from expected generation is easier to reproduce with
batched grammar requests as they are more sensitive to unexpected
outputs.

this PR resolves the issue by setting the penalty score to 0 where input
ids are padding tokens (0).

---------

Co-authored-by: OlivierDehaene <olivier@huggingface.co>

server/text_generation_server/utils/logits_process.py

@@ -143,6 +143,8 @@ class FrequencyPenaltyLogitsProcessor(LogitsProcessor):
         score = torch.gather(scores, 1, input_ids)
         # if score < 0 then penalty has to be multiplied to reduce the previous token probability
         score = -torch.where(score < 0, score * self.penalty, score / self.penalty)
+        # set score to 0 where input_ids is a padding token
+        score *= input_ids.ne(0)
 
         return scores.scatter_add_(1, input_ids, score)
 
@@ -168,6 +170,8 @@ class HeterogeneousFrequencyPenaltyLogitsProcessor(LogitsProcessor):
         score = -torch.where(
             score < 0, score * self.penalty_tensor, score / self.penalty_tensor
         )
+        # set score to 0 where input_ids is a padding token
+        score *= input_ids.ne(0)
 
         return scores.scatter_add_(1, input_ids, score)