From a5d48a9fc0f041a25ecc2de20ceb587783f6046f Mon Sep 17 00:00:00 2001
From: Maximilian Kimmich <maximilian.kimmich@ims.uni-stuttgart.de>
Date: Thu, 17 Oct 2024 11:57:45 +0200
Subject: [PATCH] Allow to directly control temperature
---
evoprompt/models.py | 39 ++++++++++++++++++++++++++++++---------
1 file changed, 30 insertions(+), 9 deletions(-)
diff --git a/evoprompt/models.py b/evoprompt/models.py
index 4b0b4ab..f80a582 100644
--- a/evoprompt/models.py
+++ b/evoprompt/models.py
@@ -101,6 +101,7 @@ class LLMModel(ABC):
grammar: llama_cpp.LlamaGrammar | None = None,
stop: str | None = None,
use_randomness: bool = False,
+ temperature: float | None = None,
**kwargs,
) -> tuple[str, ChatMessages | None, ChatMessages, ModelUsage]:
raise NotImplementedError("Non-chat models are currently not supported")
@@ -168,6 +169,7 @@ class LLMModel(ABC):
stop: str | None = None,
max_tokens: int | None = None,
use_randomness: bool = False,
+ temperature: float | None = None,
): ...
def _get_user_message(self, content: Any) -> ChatMessage:
@@ -318,6 +320,7 @@ class Llama(LLMModel):
stop: str | None = None,
max_tokens: int | None = None,
use_randomness: bool = False,
+ temperature: float | None = None,
):
# setup kwargs for model call
model_call_kwargs = {
@@ -327,8 +330,11 @@ class Llama(LLMModel):
"max_tokens": max_tokens,
}
if use_randomness:
- # same temperature as in evoprompt paper reference implementation
- model_call_kwargs["temperature"] = 0.5
+ if temperature is None:
+ # same temperature as in evoprompt paper reference implementation
+ model_call_kwargs["temperature"] = 0.5
+ else:
+ model_call_kwargs["temperature"] = temperature
model_call_kwargs["seed"] = random.randint(0, 2**32 - 1)
else:
model_call_kwargs["temperature"] = 0.0
@@ -400,6 +406,7 @@ class ChatModel:
stop: str | None = None,
history: ChatMessages | None = None,
use_randomness: bool = False,
+ temperature: float | None = None,
**kwargs,
) -> tuple[str, ChatMessages | None, ChatMessages, ModelUsage]:
if messages is None:
@@ -425,6 +432,7 @@ class ChatModel:
use_cache=use_cache,
max_tokens=self.max_tokens,
use_randomness=use_randomness,
+ temperature=temperature,
)
return (
@@ -447,6 +455,7 @@ class LlamaChat(ChatModel, Llama):
stop: str | None,
max_tokens: int | None,
use_randomness: bool,
+ temperature: float | None = None,
):
# input(
# f"The input for a Llama3.x model will look like this:\n{format_llama3(messages).prompt}"
@@ -459,8 +468,11 @@ class LlamaChat(ChatModel, Llama):
"max_tokens": max_tokens,
}
if use_randomness:
- # same temperature as in evoprompt paper reference implementation
- model_call_kwargs["temperature"] = 0.5
+ if temperature is None:
+ # same temperature as in evoprompt paper reference implementation
+ model_call_kwargs["temperature"] = 0.5
+ else:
+ model_call_kwargs["temperature"] = temperature
model_call_kwargs["seed"] = random.randint(0, 2**32 - 1)
else:
model_call_kwargs["temperature"] = 0.0
@@ -533,17 +545,22 @@ class HfChat(ChatModel, LLMModel):
stop: str | None,
max_tokens: int | None,
use_randomness: bool,
+ temperature: float | None = None,
**kwargs,
):
# setup kwargs for model call
model_call_kwargs = {
"text_inputs": messages,
"stop": stop,
- "max_length": max_tokens if max_tokens is not None else 16384,
+ # "max_length": max_tokens if max_tokens is not None else 16384,
+ "max_new_tokens": 1000,
}
if use_randomness:
- # same temperature as in evoprompt paper reference implementation
- model_call_kwargs["temperature"] = 0.5
+ if temperature is None:
+ # same temperature as in evoprompt paper reference implementation
+ model_call_kwargs["temperature"] = 0.5
+ else:
+ model_call_kwargs["temperature"] = temperature
model_call_kwargs["do_sample"] = True
else:
model_call_kwargs["do_sample"] = False
@@ -633,6 +650,7 @@ class OpenAIChat(ChatModel, LLMModel):
stop: str | None,
max_tokens: int | None,
use_randomness: bool,
+ temperature: float | None = None,
):
# setup kwargs for model call
model_call_kwargs = {
@@ -642,8 +660,11 @@ class OpenAIChat(ChatModel, LLMModel):
"max_completion_tokens": max_tokens if max_tokens is not None else 1024,
}
if use_randomness:
- # same temperature as in evoprompt paper reference implementation
- model_call_kwargs["temperature"] = 0.5
+ if temperature is None:
+ # same temperature as in evoprompt paper reference implementation
+ model_call_kwargs["temperature"] = 0.5
+ else:
+ model_call_kwargs["temperature"] = temperature
else:
model_call_kwargs["temperature"] = 0.0
--
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