standardize prompt formatting for vllm

eval/vllm_runner.py

@@ -121,8 +121,19 @@ def chunk_dataframe(df, chunk_size):
         for batch in (pbar := tqdm(df_chunks, total=len(df))):
             prompts = batch["prompt"].tolist()
             print(f"Generating completions for {len(prompts)} prompts")
+            prompt_tokens = []
+            prompt_token_sizes = []
+            for prompt in prompts:
+                token_ids = tokenizer.encode(prompt, add_special_tokens=False)
+                # add bos token if not already present in prompt
+                if token_ids[0] != tokenizer.bos_token_id:
+                    token_ids = [tokenizer.bos_token_id] + token_ids
+                prompt_tokens.append(token_ids)
+                prompt_token_sizes.append(len(token_ids))
+            print(f"Average prompt size: {sum(prompt_token_sizes)/len(prompt_token_sizes):.0f}")
             start_time = time.time()
-            outputs = llm.generate(prompts, sampling_params)
+            # outputs = llm.generate(prompts, sampling_params) # if you prefer to use prompts instead of token_ids
+            outputs = llm.generate(sampling_params=sampling_params, prompt_token_ids=prompt_tokens)
             print(
                 f"Generated {len(outputs)} completions in {time.time() - start_time:.2f} seconds"
             )