[https://nvbugs/5404046][fix] Fix Nemotron-H flaky CUDA graph / overlap scheduler test

tests/unittest/_torch/modeling/test_modeling_nemotron_h.py

@@ -1,4 +1,3 @@
-import pytest
 import torch
 from utils.llm_data import llm_models_root
 from utils.util import skip_gpu_memory_less_than
@@ -238,15 +237,15 @@ def test_nemotron_h_correctness():
         nemotron_h.shutdown()
 
 
-@pytest.mark.skip(reason="https://nvbugs/5404046")
 def test_nemotron_h_cuda_graph_overlap_scheduler():
     prompts = [
-        "Tell me something I don't know about the future of AI",
-        "The president of the United States is",
-        "The capital of France is",
-        "Hello, this is a beautiful day and I'm eager to start my day and",
+        "The sky is blue because",
+        "The sum of two and two is",
+        "The largest mammal is the",
+        "The chemical symbol for water is",
     ]
-    sampling_config = SamplingParams(max_tokens=12,
+
+    sampling_config = SamplingParams(max_tokens=10,
                                      temperature=0.0,
                                      return_generation_logits=True)
 
@@ -273,32 +272,46 @@ def test_nemotron_h_cuda_graph_overlap_scheduler():
             prompts, sampling_params=sampling_config, use_tqdm=True)
 
     # Verify outputs are consistent
-    for (no_cg_no_overlap, with_cg_no_overlap,
-         with_cg_with_overlap) in zip(outputs_no_cg_no_overlap,
-                                      outputs_with_cg_no_overlap,
-                                      outputs_with_cg_with_overlap):
-
-        assert (no_cg_no_overlap.outputs[0].text ==
-                with_cg_no_overlap.outputs[0].text)
-        assert (with_cg_no_overlap.outputs[0].text ==
-                with_cg_with_overlap.outputs[0].text)
+    for i, (no_cg_no_overlap, with_cg_no_overlap,
+            with_cg_with_overlap) in enumerate(
+                zip(outputs_no_cg_no_overlap, outputs_with_cg_no_overlap,
+                    outputs_with_cg_with_overlap)):
+
+        assert (
+            no_cg_no_overlap.outputs[0].text ==
+            with_cg_no_overlap.outputs[0].text
+        ), f"Prompt {i}: no CG no overlap generated text != with CG no overlap generated text"
+        assert (
+            with_cg_no_overlap.outputs[0].text ==
+            with_cg_with_overlap.outputs[0].text
+        ), f"Prompt {i}: with CG no overlap generated text != with CG with overlap generated text"
 
         # similar to other unittests comparing with / without CG, compare logits of first generation step (2nd generated token)
         torch.testing.assert_close(
             no_cg_no_overlap.outputs[0].generation_logits[1, :],
             with_cg_no_overlap.outputs[0].generation_logits[1, :],
             atol=0.2,
-            rtol=0.2)
+            rtol=0.2,
+            msg=lambda x:
+            f"Prompt {i}: with/without CG (no overlap) logits for first generated step {x}"
+        )
 
         # compare logprobs of all generated tokens
-        torch.testing.assert_close(extract_decode_logprobs(no_cg_no_overlap),
-                                   extract_decode_logprobs(with_cg_no_overlap),
-                                   atol=0.2,
-                                   rtol=0.2)
+        torch.testing.assert_close(
+            extract_decode_logprobs(no_cg_no_overlap),
+            extract_decode_logprobs(with_cg_no_overlap),
+            atol=0.2,
+            rtol=0.2,
+            msg=lambda x:
+            f"Prompt {i}: with/without CG (no overlap) logprobs for all selected tokens {x}"
+        )
 
         # overlap scheduler should have no effect on all logits - low tolerance
         torch.testing.assert_close(
             with_cg_no_overlap.outputs[0].generation_logits,
             with_cg_with_overlap.outputs[0].generation_logits,
             atol=0.05,
-            rtol=0.05)
+            rtol=0.05,
+            msg=lambda x:
+            f"Prompt {i}: with/without overlap (no CG) all generation logits {x}"
+        )