Remove smoke wording from tests and comments (#23355)
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@@ -130,7 +130,7 @@ class TestMoriTransferEngineE2E(PDDisaggregationServerBase):
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other_args=decode_args,
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)
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def test_generate_smoke(self):
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def test_generate_basic(self):
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resp = requests.post(
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self.lb_url + "/generate",
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json={
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@@ -273,7 +273,7 @@ class TestMoriTransferEngineTPMismatchE2E(PDDisaggregationServerBase):
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other_args=decode_args,
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)
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def test_generate_smoke_tp_mismatch(self):
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def test_generate_with_tp_mismatch(self):
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resp = requests.post(
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self.lb_url + "/generate",
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json={
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@@ -285,7 +285,7 @@ class TestEntrypointGroupingRaw:
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assert summary.total == 2
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assert summary.passed == 2
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def test_text_output_smoke(self, tmp_path, capsys):
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def test_text_output_format(self, tmp_path, capsys):
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"""Text output format renders without errors and contains Config/Summary sections."""
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baseline_path, target_path = _create_dumps(tmp_path, ["tensor_a"])
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argv = _make_argv(
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+3
-3
@@ -1,7 +1,7 @@
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"""Smoke test: intentionally trigger a CUDA illegal memory access
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"""Intentionally trigger a CUDA illegal memory access
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to verify the coredump collection pipeline works end-to-end.
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Manual use: python3 test/registered/debug_utils/test_cuda_coredump_smoke.py
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Manual use: python3 test/registered/debug_utils/test_cuda_coredump.py
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"""
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import unittest
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@@ -17,7 +17,7 @@ register_cuda_ci(
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)
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class TestCudaCoredumpSmoke(unittest.TestCase):
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class TestCudaCoredump(unittest.TestCase):
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def test_trigger_illegal_memory_access(self):
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x = torch.zeros(10, device="cuda")
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y = torch.arange(10, device="cuda")
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@@ -1,5 +1,5 @@
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"""
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E2E smoke test for HiCache storage runtime attach/detach.
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E2E check for HiCache storage runtime attach/detach.
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This test launches an SGLang server with hierarchical cache enabled but WITHOUT
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any storage backend at startup, then attaches/detaches a storage backend via the
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@@ -581,7 +581,7 @@ class TestCuteDslV2(unittest.TestCase):
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Also checks both match the pure-PyTorch reference, and that a second
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cuda_graph pass reuses buffers deterministically (subsumes the former
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cuda_graph_smoke test).
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cuda_graph check).
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"""
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test_cases = [
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# (num_tokens, hidden_size, intermediate_size, num_experts, top_k)
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