Fix the output of hidden states after HTTP requests (#4269)

examples/runtime/hidden_states/hidden_states_engine.py

@@ -7,6 +7,8 @@ the cuda graph will be recaptured, which might lead to a performance hit.
 So avoid getting hidden states and completions alternately.
 """
 
+import torch
+
 import sglang as sgl
 
 
@@ -31,11 +33,29 @@ def main():
     outputs = llm.generate(
         prompts, sampling_params=sampling_params, return_hidden_states=True
     )
+
+    llm.shutdown()
+
     for prompt, output in zip(prompts, outputs):
+        for i in range(len(output["meta_info"]["hidden_states"])):
+            output["meta_info"]["hidden_states"][i] = torch.tensor(
+                output["meta_info"]["hidden_states"][i], dtype=torch.bfloat16
+            )
         print("===============================")
         print(
-            f"Prompt: {prompt}\nGenerated text: {output['text']}\nPrompt_Tokens: {output['meta_info']['prompt_tokens']}\tCompletion_tokens: {output['meta_info']['completion_tokens']}\nHidden states: {[i.shape for i in output['meta_info']['hidden_states']]}"
+            f"Prompt: {prompt}\n"
+            f"Generated text: {output['text']}\n"
+            f"Prompt_Tokens: {output['meta_info']['prompt_tokens']}\t"
+            f"Completion_tokens: {output['meta_info']['completion_tokens']}"
+        )
+        print("Hidden states: ")
+        hidden_states = torch.cat(
+            [
+                i.unsqueeze(0) if len(i.shape) == 1 else i
+                for i in output["meta_info"]["hidden_states"]
+            ]
         )
+        print(hidden_states)
         print()
 
 

examples/runtime/hidden_states/hidden_states_server.py

@@ -9,6 +9,7 @@ So avoid getting hidden states and completions alternately.
 """
 
 import requests
+import torch
 
 from sglang.test.test_utils import is_in_ci
 from sglang.utils import print_highlight, terminate_process, wait_for_server
@@ -50,20 +51,31 @@ def main():
         json=json_data,
     )
 
+    terminate_process(server_process)
+
     outputs = response.json()
     for prompt, output in zip(prompts, outputs):
+        for i in range(len(output["meta_info"]["hidden_states"])):
+            output["meta_info"]["hidden_states"][i] = torch.tensor(
+                output["meta_info"]["hidden_states"][i], dtype=torch.bfloat16
+            )
         print("===============================")
         print(
             f"Prompt: {prompt}\n"
             f"Generated text: {output['text']}\n"
             f"Prompt_Tokens: {output['meta_info']['prompt_tokens']}\t"
-            f"Completion_tokens: {output['meta_info']['completion_tokens']}\n"
-            f"Hidden states: {output['meta_info']['hidden_states']}"
+            f"Completion_tokens: {output['meta_info']['completion_tokens']}"
+        )
+        print("Hidden states: ")
+        hidden_states = torch.cat(
+            [
+                i.unsqueeze(0) if len(i.shape) == 1 else i
+                for i in output["meta_info"]["hidden_states"]
+            ]
         )
+        print(hidden_states)
         print()
 
-    terminate_process(server_process)
-
 
 if __name__ == "__main__":
     main()

python/sglang/srt/managers/schedule_batch.py

@@ -361,7 +361,7 @@ class Req:
             ) = self.output_top_logprobs_idx = self.output_token_ids_logprobs_val = (
                 self.output_token_ids_logprobs_idx
             ) = None
-        self.hidden_states = []
+        self.hidden_states: List[List[float]] = []
 
         # Embedding (return values)
         self.embedding = None

python/sglang/srt/managers/scheduler_output_processor_mixin.py

@@ -111,6 +111,7 @@ class SchedulerOutputProcessorMixin:
                             ]
                             .cpu()
                             .clone()
+                            .tolist()
                         )
 
                     if req.grammar is not None:
@@ -245,7 +246,9 @@ class SchedulerOutputProcessorMixin:
                     )
 
             if req.return_hidden_states and logits_output.hidden_states is not None:
-                req.hidden_states.append(logits_output.hidden_states[i].cpu().clone())
+                req.hidden_states.append(
+                    logits_output.hidden_states[i].cpu().clone().tolist()
+                )
 
             if req.grammar is not None and batch.spec_algorithm.is_none():
                 req.grammar.accept_token(next_token_id)

test/srt/test_hidden_states.py

@@ -33,8 +33,11 @@ class TestHiddenState(unittest.TestCase):
 
         for output in outputs:
             self.assertEqual(len(output["meta_info"]["hidden_states"]), 8)
-            for hidden_state in output["meta_info"]["hidden_states"]:
-                self.assertIsInstance(hidden_state, torch.Tensor)
+            for i in range(len(output["meta_info"]["hidden_states"])):
+                assert isinstance(output["meta_info"]["hidden_states"][i], list)
+                output["meta_info"]["hidden_states"][i] = torch.tensor(
+                    output["meta_info"]["hidden_states"][i], dtype=torch.bfloat16
+                )
         # Checks that splicing of the batch was done correctly
         self.assertGreater(
             outputs[1]["meta_info"]["hidden_states"][0].shape[0],