[https://nvbugs/5764627][fix] Fix generation logits with streaming and improve runtime of logits testcase. Also fixes https://nvbugs/5573238

tensorrt_llm/_torch/pyexecutor/llm_request.py

@@ -84,7 +84,7 @@ def __init__(
         self.use_device_memory = use_device_memory
         self.use_chunked_generation_logits = use_chunked_generation_logits
         self.chunk_size = chunk_size
-        self._logits_indices = []
+        self._logits_indices: list[tuple[int, int]] = []
 
         # Lazily initialized by _init() upon first append()
         self._storage: torch.Tensor | None = None
@@ -765,13 +765,35 @@ def create_response(self,
         result, is_final = super().create_serialized_result(
             use_fast_logits, mpi_world_rank)
 
-        # Performs a deep copy of py_result._log_probs to eliminate race conditions that may occur between IPC communication and the overriding of newly generated log_probs in streaming mode.
-        if self.streaming and self.py_result.log_probs and self.sampling_config.beam_width <= 1:
+        # When using beam search we cannot incrementically update the logprobs in the result.
+        # Instead we need to update all logprobs. In that case no deep copy is needed.
+        need_deep_copy_logprobs = self.py_result.log_probs and self.sampling_config.beam_width <= 1
+        need_deep_copy_generation_logits = self.py_result._generation_logits is not None
+        need_any_deep_copy = need_deep_copy_logprobs or need_deep_copy_generation_logits
+        # Performs a deep copy of py_result._log_probs or py_result._generation_logits to eliminate race conditions
+        # that may occur between IPC communication and the overriding of newly generated log_probs
+        # or the updating of py_result._generation_logits._logits_indices in streaming mode.
+        if self.streaming and need_any_deep_copy:
             py_result = copy(self.py_result)
-            py_result._log_probs = deepcopy(self.py_result._log_probs)
-
-            for log_prob in self.py_result.log_probs:
-                log_prob.clear()
+            # Move _log_probs to py_result and create a new empty LogProbStorage in self.py_result
+            # This avoids performing a deepcopy
+            if need_deep_copy_logprobs:
+                py_result._log_probs = self.py_result._log_probs
+                self.py_result._log_probs = LogProbStorage()
+                # Initialize the storage and adjust the cum_log_probs to the previous value
+                self.py_result._log_probs._init(py_result.log_probs)
+                self.py_result._log_probs.cum_log_probs = py_result.cum_log_probs
+
+            # Perform copies of py_result._generation_logits
+            if need_deep_copy_generation_logits:
+                # shallow copy of generation_logits to avoid copying the logits tensor
+                py_result._generation_logits = copy(
+                    self.py_result._generation_logits)
+                # deep copy the indices to avoid the race condition
+                # In streaming mode LogitsStorage only accesses either the last
+                # or second to last pair of indices. Therefore, copying only these two pairs is sufficient.
+                py_result._generation_logits._logits_indices = py_result._generation_logits._logits_indices[
+                    -2:]
         else:
             py_result = self.py_result
 

tensorrt_llm/_torch/pyexecutor/py_executor.py

@@ -1369,6 +1369,9 @@ def _executor_loop_pp(self):
                                 scheduled_batch, guided_decoder_failed_requests)
 
                             self._update_request_states(scheduled_batch)
+                            if not self.disable_overlap_scheduler:
+                                self._update_generation_requests_that_will_complete_next_iteration(
+                                    scheduled_batch.generation_requests)
 
                     if self.enable_iter_perf_stats:
                         iter_stats.inflight_batching_stats.num_ctx_tokens = self.model_engine.iter_states[
@@ -2179,6 +2182,13 @@ def _executor_loop_overlap(self):
                 else:
                     self._enqueue_responses([])
 
+                # Call set_exclude_last_generation_logits after _process_previous_batch.
+                # If set before, the response of a request may be incorrect, as it will
+                # use the wrong indices for generation logits when streaming is enabled.
+                if can_queue:
+                    self._update_generation_requests_that_will_complete_next_iteration(
+                        scheduled_batch.generation_requests)
+
                 if can_queue:
                     if self.enable_iter_perf_stats:
                         iter_stats.inflight_batching_stats.num_ctx_tokens = self.model_engine.iter_states[
@@ -3000,6 +3010,19 @@ def forward(scheduled_requests, resource_manager, new_tensors_device,
             self._handle_errors(error_msg)
             return None
 
+    def _update_generation_requests_that_will_complete_next_iteration(
+            self, generation_requests: list[LlmRequest]):
+        """ Update the generation requests that will complete next iteration.
+
+        If overlap scheduling is enabled, we need update the state of generation requests that will complete next iteration
+        and adjust the exclude_last_generation_logits flag accordingly.
+        """
+        for request in generation_requests:
+            if request.state != LlmRequestState.GENERATION_COMPLETE and request.will_complete_next_iteration(
+            ):
+                request.set_exclude_last_generation_logits(False)
+                request.state = LlmRequestState.GENERATION_TO_COMPLETE
+
     def _update_request_states_tp(self, scheduled_requests: ScheduledRequests):
         # handle potential attention dp dummy request
         if self.active_requests and self.active_requests[
@@ -3025,13 +3048,6 @@ def _update_request_states_tp(self, scheduled_requests: ScheduledRequests):
                 else:
                     request.state = LlmRequestState.GENERATION_IN_PROGRESS
 
-        for request in scheduled_requests.generation_requests:
-            if request.state != LlmRequestState.GENERATION_COMPLETE:
-                if not self.disable_overlap_scheduler and request.will_complete_next_iteration(
-                ):
-                    request.set_exclude_last_generation_logits(False)
-                    request.state = LlmRequestState.GENERATION_TO_COMPLETE
-
     def _update_request_states_star_attention(
             self, scheduled_requests: ScheduledRequests):
         for request in scheduled_requests.context_requests:

tests/integration/test_lists/waives.txt

@@ -215,9 +215,6 @@ unittest/_torch/speculative/test_dynamic_spec_decode.py::test_dynamic_spec_decod
 triton_server/test_triton.py::test_gpt_disaggregated_serving_bls[gpt-disaggregated-serving-bls] SKIP (https://nvbugs/5582118)
 triton_server/test_triton.py::test_gpt_speculative_decoding[gpt-speculative-decoding] SKIP (https://nvbugs/5762854)
 accuracy/test_llm_api_pytorch.py::TestLlama3_1_8B_Instruct_RocketKV::test_auto_dtype SKIP (https://nvbugs/5762822)
-unittest/_torch/sampler/test_return_logits.py SKIP (https://nvbugs/5764627)
-unittest/_torch/sampler/test_logits_logprobs.py::test_generate_with_return_logits SKIP (https://nvbugs/5764627)
-unittest/_torch/sampler/test_logits_logprobs.py::test_generate_async_with_return_logits SKIP (https://nvbugs/5764627)
 examples/test_ray.py::test_ray_disaggregated_serving[tp2] SKIP (https://nvbugs/5612502)
 unittest/executor/test_rpc_proxy.py SKIP (https://nvbugs/5605741)
 unittest/executor/test_rpc_worker.py SKIP (https://nvbugs/5605741)