[Sampler] Support returning all prompt logprobs (vllm-project#23868)

Signed-off-by: Xingyu Liu <charlotteliu12x@gmail.com>
Co-authored-by: 22quinn <33176974+22quinn@users.noreply.github.com>
Co-authored-by: Cyrus Leung <tlleungac@connect.ust.hk>
Signed-off-by: xuebwang-amd <xuebwang@amd.com>

Author: 3 people

tests/v1/sample/test_logprobs.py

@@ -430,7 +430,7 @@ def test_zero_logprobs(vllm_model, example_prompts,
 
 
 def test_all_logprobs(example_prompts, monkeypatch: pytest.MonkeyPatch):
-    """Engine should return all vocabulary logprobs
+    """Engine should return all vocabulary logprobs and prompt logprobs
 
     Args:
       example_prompts: list of example prompts (test fixture)
@@ -444,16 +444,24 @@ def test_all_logprobs(example_prompts, monkeypatch: pytest.MonkeyPatch):
             # 2 other llms alive during whole session
             gpu_memory_utilization=0.15,
             max_model_len=256)
+
         sampling_params_logprobs_all = SamplingParams(max_tokens=5,
-                                                      logprobs=-1)
+                                                      logprobs=-1,
+                                                      prompt_logprobs=-1)
         results_logprobs_all = runner.llm.generate(
             example_prompts, sampling_params=sampling_params_logprobs_all)
         vocab_size = runner.llm.llm_engine.get_model_config().get_vocab_size()
+
         for i in range(len(results_logprobs_all)):
             logprobs = results_logprobs_all[i].outputs[0].logprobs
+            prompt_logprobs = results_logprobs_all[i].prompt_logprobs
             assert logprobs is not None
             for logprob in logprobs:
                 assert len(logprob) == vocab_size
+            assert prompt_logprobs is not None
+            assert prompt_logprobs[0] is None
+            for prompt_logprob in prompt_logprobs[1:]:
+                assert len(prompt_logprob) == vocab_size
 
 
 @pytest.mark.parametrize("logprobs_mode", list(LogprobsMode))

vllm/sampling_params.py

@@ -165,7 +165,8 @@ class SamplingParams(
     the sampled token, so there may be up to `logprobs+1` elements in the
     response. When set to -1, return all `vocab_size` log probabilities."""
     prompt_logprobs: Optional[int] = None
-    """Number of log probabilities to return per prompt token."""
+    """Number of log probabilities to return per prompt token.
+    When set to -1, return all `vocab_size` log probabilities."""
     # NOTE: This parameter is only exposed at the engine level for now.
     # It is not exposed in the OpenAI API server, as the OpenAI API does
     # not support returning only a list of token IDs.
@@ -409,9 +410,11 @@ def _verify_args(self) -> None:
                 and self.logprobs < 0):
             raise ValueError(
                 f"logprobs must be non-negative or -1, got {self.logprobs}.")
-        if self.prompt_logprobs is not None and self.prompt_logprobs < 0:
-            raise ValueError(f"prompt_logprobs must be non-negative, got "
-                             f"{self.prompt_logprobs}.")
+        if (self.prompt_logprobs is not None and self.prompt_logprobs != -1
+                and self.prompt_logprobs < 0):
+            raise ValueError(
+                f"prompt_logprobs must be non-negative or -1, got "
+                f"{self.prompt_logprobs}.")
         if (self.truncate_prompt_tokens is not None
                 and (self.truncate_prompt_tokens == 0
                      or self.truncate_prompt_tokens < -1)):

vllm/v1/engine/processor.py

@@ -65,19 +65,27 @@ def _validate_logprobs(
     ) -> None:
         max_logprobs = self.model_config.max_logprobs
         if max_logprobs == -1:
-            return
+            max_logprobs = self.model_config.get_vocab_size()
+
         # Validate sample logprobs.
-        if params.logprobs and (params.logprobs == -1
-                                or params.logprobs > max_logprobs):
-            raise ValueError(
-                f"Requested sample logprobs of {params.logprobs}, "
-                f"which is greater than max allowed: {max_logprobs}")
+        if params.logprobs:
+            num_logprobs = params.logprobs
+            if num_logprobs == -1:
+                num_logprobs = self.model_config.get_vocab_size()
+            if num_logprobs > max_logprobs:
+                raise ValueError(
+                    f"Requested sample logprobs of {num_logprobs}, "
+                    f"which is is greater than max allowed: {max_logprobs}")
 
         # Validate prompt logprobs.
-        if params.prompt_logprobs and params.prompt_logprobs > max_logprobs:
-            raise ValueError(
-                f"Requested prompt logprobs of {params.prompt_logprobs}, "
-                f"which is greater than max allowed: {max_logprobs}")
+        if params.prompt_logprobs:
+            num_prompt_logprobs = params.prompt_logprobs
+            if num_prompt_logprobs == -1:
+                num_prompt_logprobs = self.model_config.get_vocab_size()
+            if num_prompt_logprobs > max_logprobs:
+                raise ValueError(
+                    f"Requested prompt logprobs of {num_prompt_logprobs}, "
+                    f"which is is greater than max allowed: {max_logprobs}")
 
     def _validate_sampling_params(
         self,

vllm/v1/worker/gpu_input_batch.py

@@ -360,8 +360,9 @@ def add_request(
                                              if sampling_params.logprobs == -1
                                              else sampling_params.logprobs)
             if sampling_params.prompt_logprobs is not None:
-                self.num_prompt_logprobs[
-                    req_id] = sampling_params.prompt_logprobs
+                self.num_prompt_logprobs[req_id] = (
+                    self.vocab_size if sampling_params.prompt_logprobs == -1
+                    else sampling_params.prompt_logprobs)
 
             if sampling_params.allowed_token_ids:
                 self.has_allowed_token_ids.add(req_id)