[nvbug/5322354] fix PD + MTP + overlap scheduler accuracy issue

tensorrt_llm/_torch/pyexecutor/model_engine.py

@@ -1323,7 +1323,6 @@ def previous_seq_slots_device():
 
         num_tokens = len(input_ids)
         num_draft_tokens = len(draft_tokens)
-        num_requests = len(request_ids)
         total_num_tokens = len(position_ids)
         assert total_num_tokens <= self.max_num_tokens, (
             "total_num_tokens should be less than or equal to max_num_tokens")
@@ -1340,6 +1339,10 @@ def previous_seq_slots_device():
             self.draft_tokens_cuda[:len(draft_tokens)].copy_(draft_tokens,
                                                              non_blocking=True)
         if next_draft_tokens_device is not None:
+            # Initialize these two values to zeros
+            self.previous_pos_id_offsets_cuda *= 0
+            self.previous_kv_lens_offsets_cuda *= 0
+
             if previous_batch_len > 0:
                 previous_slots = previous_seq_slots_device()
                 # previous input ids
@@ -1364,24 +1367,37 @@ def previous_seq_slots_device():
                                                          pin_memory=True)
                 self.previous_pos_indices_cuda[0:previous_batch_tokens].copy_(
                     previous_pos_indices_host, non_blocking=True)
+
+                # The order of requests in a batch: [context requests, generation requests]
+                # generation requests: ['requests that do not have previous batch', 'requests that already have previous batch', 'dummy requests']
+                #   1) 'requests that do not have previous batch': disable overlap scheduler or the first step in the generation server of disaggregated serving.
+                #   2) 'requests that already have previous batch': previous iteration's requests.
+                #   3) 'dummy requests': pad dummy requests for CUDA graph or attention dp.
+                # Therefore, both of self.previous_pos_id_offsets_cuda and self.previous_kv_lens_offsets_cuda are also 3 segments.
+                #   For 1) 'requests that do not have previous batch': disable overlap scheduler or the first step in the generation server of disaggregated serving.
+                #       Set these requests' previous_pos_id_offsets and previous_kv_lens_offsets to '0' to skip the value changes in _preprocess_inputs.
+                #       Already set to '0' during initialization.
+                #   For 2) 'requests that already have previous batch': enable overlap scheduler.
+                #       Set their previous_pos_id_offsets and previous_kv_lens_offsets according to new_tokens_lens_device and kv_len_offsets_device.
+                #   For 3) 'dummy requests': pad dummy requests for CUDA graph or attention dp.
+                #       Already set to '0' during initialization.
+
+                num_extend_reqeust_wo_dummy = len(extend_requests) - len(
+                    extend_dummy_requests)
                 self.previous_pos_id_offsets_cuda[
-                    0:previous_batch_tokens].copy_(
+                    (num_extend_reqeust_wo_dummy - previous_batch_len) *
+                    (1 + self.max_draft_len):num_extend_reqeust_wo_dummy *
+                    (1 + self.max_draft_len)].copy_(
                         new_tokens_lens_device[self.previous_pos_indices_cuda[
                             0:previous_batch_tokens]],
                         non_blocking=True)
-                self.previous_kv_lens_offsets_cuda[0:previous_batch_len].copy_(
-                    kv_len_offsets_device[previous_slots], non_blocking=True)
-                # for the requests that do not have previous batch, set the previous_pos_id_offsets and
-                # previous_kv_lens_offsets to zeros to skip the value changes in _preprocess_inputs
-                self.previous_pos_id_offsets_cuda[
-                    previous_batch_tokens:num_requests *
-                    (1 + self.max_draft_len)] *= 0
+
                 self.previous_kv_lens_offsets_cuda[
-                    previous_batch_len:num_requests] *= 0
-            else:
-                # change the data to zeros to skip the value changes in _preprocess_inputs
-                self.previous_pos_id_offsets_cuda *= 0
-                self.previous_kv_lens_offsets_cuda *= 0
+                    num_extend_reqeust_wo_dummy -
+                    previous_batch_len:num_extend_reqeust_wo_dummy].copy_(
+                        kv_len_offsets_device[previous_slots],
+                        non_blocking=True)
+
         elif new_tokens_device is not None:
             seq_slots_device = previous_seq_slots_device()
             max_draft_len = max(draft_lens)

tensorrt_llm/_torch/pyexecutor/py_executor.py

@@ -1022,10 +1022,6 @@ def _executor_loop_overlap(self):
                     )
 
                     if self.kv_cache_transceiver:
-                        # For generation requests which have completed KV cache transfer
-                        self._prepare_disagg_gen_transmission_complete(
-                            scheduled_batch)
-
                         # Return the first token to the client
                         self._handle_first_token_response(scheduled_batch)
 

tests/integration/test_lists/waives.txt

@@ -371,8 +371,6 @@ perf/test_perf.py::test_perf[bert_large-bench-float16-maxbs:32-input_len:128+512
 perf/test_perf.py::test_perf[roberta_base-bench-float16-maxbs:32-input_len:128+512] SKIP (https://nvbugspro.nvidia.com/bug/5295411)
 disaggregated/test_disaggregated.py::test_disaggregated_single_gpu_with_mpirun[TinyLlama-1.1B-Chat-v1.0] SKIP (https://nvbugs/5328160)
 stress_test/stress_test.py::test_run_stress_test[llama-v3-8b-instruct-hf_tp1-stress_time_300s_timeout_450s-MAX_UTILIZATION-pytorch-stress-test] SKIP (https://nvbugs/5328495)
-accuracy/test_disaggregated_serving.py::TestDeepSeekV3Lite::test_auto_dtype[mtp_nextn=0-overlap_scheduler=True] SKIP (https://nvbugs/5322354)
-accuracy/test_disaggregated_serving.py::TestDeepSeekV3Lite::test_auto_dtype[mtp_nextn=2-overlap_scheduler=True] SKIP (https://nvbugs/5322354)
 full:B200/examples/test_gemma.py::test_llm_gemma_1gpu_summary_vswa[gemma-3-1b-it-other-bfloat16-8] SKIP (https://nvbugs/5292737)
 full:B200/accuracy/test_llm_api_pytorch.py::TestGemma3_1BInstruct::test_auto_dtype SKIP (https://nvbugs/5295470)
 examples/test_mistral.py::test_llm_mistral_v1_1gpu[mistral-7b-v0.1-float16-max_attention_window_size_4096-summarization_long] SKIP (https://nvbugs/5324976)