diff --git a/server/text_generation_server/utils/tokens.py b/server/text_generation_server/utils/tokens.py
index 0647b765..e06afcb6 100644
--- a/server/text_generation_server/utils/tokens.py
+++ b/server/text_generation_server/utils/tokens.py
@@ -22,13 +22,6 @@ from text_generation_server.utils.logits_process import (
 from text_generation_server.utils.watermark import WatermarkLogitsProcessor
 from transformers import PreTrainedTokenizerBase, RepetitionPenaltyLogitsProcessor
 
-from outlines.fsm.fsm import RegexFSM
-from outlines.fsm.json_schema import build_regex_from_object
-from functools import lru_cache
-
-# TODO: remove when done debugging
-import time
-
 
 class NextTokenChooser:
     def __init__(
@@ -481,7 +474,7 @@ class Sampling:
         self.generator.manual_seed(seed)
         self.seed = seed
 
-    def __call__(self, logits, *args):
+    def __call__(self, logits):
         probs = torch.nn.functional.softmax(logits, -1)
         # Avoid GPU<->CPU sync done by torch multinomial
         # See: https://github.com/pytorch/pytorch/blob/925a3788ec5c06db62ca732a0e9425a26a00916f/aten/src/ATen/native/Distributions.cpp#L631-L637
@@ -490,13 +483,9 @@ class Sampling:
 
 
 class Greedy:
-    def __call__(self, logits, *args):
+    def __call__(self, logits):
         return logits.argmax(dim=-1)
 
-    def filter(self, indices, *args):
-        return self
-
-
 class HeterogeneousSampling:
     r"""
     Mixed greedy and probabilistic sampling. Compute both and pick the right one for each sample.