From 6208d622ca74789f329fb4e9041a600e1f96659b Mon Sep 17 00:00:00 2001
From: Woosuk Kwon <woosuk.kwon@berkeley.edu>
Date: Fri, 12 May 2023 18:07:09 -0700
Subject: [PATCH] Minor code cleaning for SamplingParams (#99)

---
 cacheflow/sampling_params.py | 99 ++++++++++++++++++------------------
 1 file changed, 50 insertions(+), 49 deletions(-)

diff --git a/cacheflow/sampling_params.py b/cacheflow/sampling_params.py
index d1b36c4108274..0a2fa0196daf2 100644
--- a/cacheflow/sampling_params.py
+++ b/cacheflow/sampling_params.py
@@ -1,4 +1,4 @@
-from typing import Dict, Set
+from typing import Set
 
 
 class SamplingParams:
@@ -16,54 +16,6 @@ def __init__(
         max_tokens: int = 16,
         logprobs: int = 0,
     ) -> None:
-        if n < 1:
-            raise ValueError(f"n must be at least 1, got {n}.")
-        if not -2.0 <= presence_penalty <= 2.0:
-            raise ValueError(
-                f"presence_penalty must be in [-2, 2], got {presence_penalty}.")
-        if not -2.0 <= frequency_penalty <= 2.0:
-            raise ValueError(
-                f"frequency_penalty must be in [-2, 2], got {frequency_penalty}.")
-        if temperature < 0.0:
-            raise ValueError(
-                f"temperature must be non-negative, got {temperature}.")
-        if not 0.0 < top_p <= 1.0:
-            raise ValueError(f"top_p must be in (0, 1], got {top_p}.")
-        if top_k < -1 or top_k == 0:
-            raise ValueError(f"top_k must be -1 (disable), or at least 1, "
-                             f"got {top_k}.")
-        if max_tokens < 1:
-            raise ValueError(
-                f"max_tokens must be at least 1, got {max_tokens}.")
-        if logprobs < 0:
-            raise ValueError(
-                f"logprobs must be non-negative, got {logprobs}.")
-
-        if use_beam_search:
-            if n == 1:
-                raise ValueError(
-                    "n must be greater than 1 when using beam search.")
-            if temperature > 0.0:
-                raise ValueError(
-                    "temperature must be 0 when using beam search.")
-            if top_p < 1.0:
-                raise ValueError(
-                    "top_p must be 1 when using beam search.")
-            if top_k != -1:
-                raise ValueError(
-                    "top_k must be -1 when using beam search.")
-        elif temperature == 0.0:
-            # Zero temperature means greedy sampling.
-            if n > 1:
-                raise ValueError(
-                    "n must be 1 when using greedy sampling.")
-            if top_p < 1.0:
-                raise ValueError(
-                    "top_p must be 1 when using greedy sampling.")
-            if top_k != -1:
-                raise ValueError(
-                    "top_k must be -1 when using greedy sampling.")
-
         self.n = n
         self.presence_penalty = presence_penalty
         self.frequency_penalty = frequency_penalty
@@ -75,6 +27,55 @@ def __init__(
         self.max_tokens = max_tokens
         self.logprobs = logprobs
 
+        self._verify_args()
+        if self.use_beam_search:
+            self._verity_beam_search()
+        elif self.temperature == 0.0:
+            # Zero temperature means greedy sampling.
+            self._verify_greedy_sampling()
+
+    def _verify_args(self) -> None:
+        if self.n < 1:
+            raise ValueError(f"n must be at least 1, got {self.n}.")
+        if not -2.0 <= self.presence_penalty <= 2.0:
+            raise ValueError("presence_penalty must be in [-2, 2], got "
+                             f"{self.presence_penalty}.")
+        if not -2.0 <= self.frequency_penalty <= 2.0:
+            raise ValueError("frequency_penalty must be in [-2, 2], got "
+                             f"{self.frequency_penalty}.")
+        if self.temperature < 0.0:
+            raise ValueError(
+                f"temperature must be non-negative, got {self.temperature}.")
+        if not 0.0 < self.top_p <= 1.0:
+            raise ValueError(f"top_p must be in (0, 1], got {self.top_p}.")
+        if self.top_k < -1 or self.top_k == 0:
+            raise ValueError(f"top_k must be -1 (disable), or at least 1, "
+                             f"got {self.top_k}.")
+        if self.max_tokens < 1:
+            raise ValueError(
+                f"max_tokens must be at least 1, got {self.max_tokens}.")
+        if self.logprobs < 0:
+            raise ValueError(
+                f"logprobs must be non-negative, got {self.logprobs}.")
+
+    def _verity_beam_search(self) -> None:
+        if self.n == 1:
+            raise ValueError("n must be greater than 1 when using beam search.")
+        if self.temperature > 0.0:
+            raise ValueError("temperature must be 0 when using beam search.")
+        if self.top_p < 1.0:
+            raise ValueError("top_p must be 1 when using beam search.")
+        if self.top_k != -1:
+            raise ValueError("top_k must be -1 when using beam search.")
+
+    def _verify_greedy_sampling(self) -> None:
+        if self.n > 1:
+            raise ValueError("n must be 1 when using greedy sampling.")
+        if self.top_p < 1.0:
+            raise ValueError("top_p must be 1 when using greedy sampling.")
+        if self.top_k != -1:
+            raise ValueError("top_k must be -1 when using greedy sampling.")
+
     def __repr__(self) -> str:
         return (f"SamplingParams(n={self.n}, "
                 f"presence_penalty={self.presence_penalty}, "