[https://nvbugs/5429636][feat] Add KV cache transfer timeout #8178
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Signed-off-by: raayandhar <[email protected]>
pcastonguay
requested review from
chuangz0,
schetlur-nv,
QiJune and
Shixiaowei02
📝 WalkthroughWalkthroughAdds an optional KV cache transfer timeout to CacheTransceiverConfig across C++ API, bindings (nanobind/pybind), Python args, and docs. Implements timeout tracking and cancellation in the Python executor, initializing per-request timing, checking timeouts in main loops, and cleaning up timed-out requests. Changes
Sequence Diagram(s)sequenceDiagram
autonumber
participant Client as Client
participant PyExec as PyExecutor
participant KvTx as KvCacheTransceiver
participant Req as Request
rect rgba(230,240,255,0.4)
note over PyExec: Initiate KV transfer (ctx/gen)
PyExec->>Req: set py_kv_transfer_start_time (if timeout configured)
PyExec->>KvTx: send/recv KV cache
end
loop Main/Overlap loops
PyExec->>PyExec: _check_kv_transfer_timeout()
alt timeout configured AND elapsed > timeout
PyExec->>Req: mark py_kv_transfer_timed_out = True
PyExec-->>KvTx: cancel_request(req_id)
note right of PyExec: Cleanup/terminate request
PyExec-->>Client: return/notify timed-out request
else transfer ongoing
PyExec->>KvTx: poll transfer status
KvTx-->>PyExec: status (in progress/done)
opt done
PyExec->>Req: clear py_kv_transfer_start_time
end
end
end
Estimated code review effort🎯 4 (Complex) | ⏱️ ~60 minutes Pre-merge checks and finishing touches❌ Failed checks (2 warnings)
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📒 Files selected for processing (9)
cpp/include/tensorrt_llm/executor/executor.h(2 hunks)cpp/tensorrt_llm/executor/cacheTransceiverConfig.cpp(3 hunks)cpp/tensorrt_llm/nanobind/executor/executorConfig.cpp(2 hunks)cpp/tensorrt_llm/pybind/executor/executorConfig.cpp(2 hunks)examples/disaggregated/README.md(1 hunks)tensorrt_llm/_torch/pyexecutor/kv_cache_transceiver.py(1 hunks)tensorrt_llm/_torch/pyexecutor/llm_request.py(1 hunks)tensorrt_llm/_torch/pyexecutor/py_executor.py(10 hunks)tensorrt_llm/llmapi/llm_args.py(1 hunks)
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🧬 Code graph analysis (4)
cpp/tensorrt_llm/nanobind/executor/executorConfig.cpp (1)
cpp/tensorrt_llm/executor/cacheTransceiverConfig.cpp (12)
getBackendType(53-56)getBackendType(53-53)setBackendType(38-41)setBackendType(38-38)getMaxTokensInBuffer(58-61)getMaxTokensInBuffer(58-58)setMaxTokensInBuffer(43-46)setMaxTokensInBuffer(43-43)getKvTransferTimeoutMs(63-66)getKvTransferTimeoutMs(63-63)setKvTransferTimeoutMs(48-51)setKvTransferTimeoutMs(48-48)
cpp/include/tensorrt_llm/executor/executor.h (2)
cpp/tensorrt_llm/executor/cacheTransceiverConfig.cpp (11)
CacheTransceiverConfig(24-30)other(32-36)other(32-32)setBackendType(38-41)setBackendType(38-38)setMaxTokensInBuffer(43-46)setMaxTokensInBuffer(43-43)setKvTransferTimeoutMs(48-51)setKvTransferTimeoutMs(48-48)getKvTransferTimeoutMs(63-66)getKvTransferTimeoutMs(63-63)tensorrt_llm/llmapi/llm_args.py (1)
CacheTransceiverConfig(1275-1299)
tensorrt_llm/_torch/pyexecutor/py_executor.py (4)
tensorrt_llm/_utils.py (1)
nvtx_range(900-919)tensorrt_llm/logger.py (1)
warning(132-133)cpp/include/tensorrt_llm/batch_manager/llmRequest.h (1)
LlmRequestState(47-210)tensorrt_llm/_torch/pyexecutor/kv_cache_transceiver.py (2)
cancel_request(94-95)cancel_request(139-140)
cpp/tensorrt_llm/pybind/executor/executorConfig.cpp (2)
cpp/tensorrt_llm/executor/cacheTransceiverConfig.cpp (13)
CacheTransceiverConfig(24-30)getBackendType(53-56)getBackendType(53-53)setBackendType(38-41)setBackendType(38-38)getMaxTokensInBuffer(58-61)getMaxTokensInBuffer(58-58)setMaxTokensInBuffer(43-46)setMaxTokensInBuffer(43-43)getKvTransferTimeoutMs(63-66)getKvTransferTimeoutMs(63-63)setKvTransferTimeoutMs(48-51)setKvTransferTimeoutMs(48-48)tensorrt_llm/llmapi/llm_args.py (1)
CacheTransceiverConfig(1275-1299)
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tensorrt_llm/_torch/pyexecutor/py_executor.py
1747-1747: Undefined name ctx_in_transmission_requests
(F821)
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🔇 Additional comments (9)
examples/disaggregated/README.md (1)
19-21: LGTM!The documentation clearly describes the new
kv_transfer_timeout_msconfiguration option and its behavior.tensorrt_llm/_torch/pyexecutor/llm_request.py (1)
445-446: LGTM!The new attributes follow the existing naming convention and are initialized with appropriate default values to support KV transfer timeout tracking.
tensorrt_llm/_torch/pyexecutor/kv_cache_transceiver.py (1)
112-113: LGTM!The
kv_transfer_timeout_msis correctly initialized from the configuration, following the existing pattern in the constructor.tensorrt_llm/llmapi/llm_args.py (2)
1289-1293: LGTM!The
kv_transfer_timeout_msfield is correctly defined with an appropriate type, default value, and clear description.
1298-1299: LGTM!The
_to_pybindmethod correctly includes the newkv_transfer_timeout_msparameter in the_CacheTransceiverConfigconstruction.cpp/tensorrt_llm/nanobind/executor/executorConfig.cpp (1)
474-475: LGTM!The property binding for
kv_transfer_timeout_mscorrectly exposes the getter and setter methods.cpp/tensorrt_llm/executor/cacheTransceiverConfig.cpp (3)
34-35: LGTM!The equality operator correctly includes the new
mKvTransferTimeoutMsfield in the comparison.
48-51: LGTM!The
setKvTransferTimeoutMssetter is correctly implemented.
63-66: LGTM!The
getKvTransferTimeoutMsgetter is correctly implemented and properly const-qualified.
| std::optional<BackendType> backendType, std::optional<size_t> maxNumTokens, std::optional<int> kvTransferTimeoutMs) | ||
| : mBackendType(backendType) | ||
| , mMaxTokensInBuffer(maxNumTokens) | ||
| : mMaxTokensInBuffer(maxNumTokens) | ||
| , mKvTransferTimeoutMs(kvTransferTimeoutMs) |
There was a problem hiding this comment.
Fix the syntax error in the constructor initializer list.
The initializer list has an incorrect colon on line 27. C++ initializer lists should have only one colon after the constructor signature, with subsequent members separated by commas.
Apply this diff to fix the syntax error:
CacheTransceiverConfig::CacheTransceiverConfig(
std::optional<BackendType> backendType, std::optional<size_t> maxNumTokens, std::optional<int> kvTransferTimeoutMs)
: mBackendType(backendType)
- : mMaxTokensInBuffer(maxNumTokens)
+ , mMaxTokensInBuffer(maxNumTokens)
, mKvTransferTimeoutMs(kvTransferTimeoutMs)📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| std::optional<BackendType> backendType, std::optional<size_t> maxNumTokens, std::optional<int> kvTransferTimeoutMs) | |
| : mBackendType(backendType) | |
| , mMaxTokensInBuffer(maxNumTokens) | |
| : mMaxTokensInBuffer(maxNumTokens) | |
| , mKvTransferTimeoutMs(kvTransferTimeoutMs) | |
| CacheTransceiverConfig::CacheTransceiverConfig( | |
| std::optional<BackendType> backendType, | |
| std::optional<size_t> maxNumTokens, | |
| std::optional<int> kvTransferTimeoutMs) | |
| : mBackendType(backendType) | |
| , mMaxTokensInBuffer(maxNumTokens) | |
| , mKvTransferTimeoutMs(kvTransferTimeoutMs) | |
| { | |
| // … | |
| } |
🤖 Prompt for AI Agents
In cpp/tensorrt_llm/executor/cacheTransceiverConfig.cpp around lines 25-28 the
constructor initializer list incorrectly uses a second colon before
mMaxTokensInBuffer, causing a syntax error; change that second colon to a comma
so the initializer list has a single leading colon after the constructor
signature and subsequent members separated by commas (i.e., :
mBackendType(backendType), mMaxTokensInBuffer(maxNumTokens),
mKvTransferTimeoutMs(kvTransferTimeoutMs)).
| .def(nb::init<std::optional<tle::CacheTransceiverConfig::BackendType>, std::optional<size_t>>, | ||
| std::optional < int >> (), nb::arg("backend") = std::nullopt, | ||
| nb::arg("max_tokens_in_buffer") = std::nullopt, nb::arg("kv_transfer_timeout_ms") = std::nullopt) |
There was a problem hiding this comment.
Fix the syntax error in constructor binding.
The template parameter list is incorrectly split across lines. The comma after std::optional<size_t>> on line 467 breaks the template syntax.
Apply this diff to fix the syntax error:
-.def(nb::init<std::optional<tle::CacheTransceiverConfig::BackendType>, std::optional<size_t>>,
- std::optional < int >> (), nb::arg("backend") = std::nullopt,
+.def(nb::init<std::optional<tle::CacheTransceiverConfig::BackendType>, std::optional<size_t>,
+ std::optional<int>>(), nb::arg("backend") = std::nullopt,📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| .def(nb::init<std::optional<tle::CacheTransceiverConfig::BackendType>, std::optional<size_t>>, | |
| std::optional < int >> (), nb::arg("backend") = std::nullopt, | |
| nb::arg("max_tokens_in_buffer") = std::nullopt, nb::arg("kv_transfer_timeout_ms") = std::nullopt) | |
| .def(nb::init<std::optional<tle::CacheTransceiverConfig::BackendType>, std::optional<size_t>, | |
| std::optional<int>>(), nb::arg("backend") = std::nullopt, | |
| nb::arg("max_tokens_in_buffer") = std::nullopt, nb::arg("kv_transfer_timeout_ms") = std::nullopt) |
🤖 Prompt for AI Agents
In cpp/tensorrt_llm/nanobind/executor/executorConfig.cpp around lines 467 to
469, the nb::init template parameter list is split across lines causing a syntax
error (the comma after std::optional<size_t>> breaks the template). Fix by using
a single, correct template parameter list (e.g.
nb::init<std::optional<tle::CacheTransceiverConfig::BackendType>,
std::optional<size_t>, std::optional<int>>() ) and keep the nb::arg(...)
defaults as before so the constructor binding compiles.
| py::class_<tle::CacheTransceiverConfig>(m, "CacheTransceiverConfig") | ||
| .def(py::init<std::optional<tle::CacheTransceiverConfig::BackendType>, std::optional<size_t>>(), | ||
| py::arg("backend") = std::nullopt, py::arg("max_tokens_in_buffer") = std::nullopt) | ||
| .def(py::init<std::optional<tle::CacheTransceiverConfig::BackendType>, std::optional<size_t>>, | ||
| std::optional < int >> (), py::arg("backend") = std::nullopt, | ||
| py::arg("max_tokens_in_buffer") = std::nullopt, py::arg("kv_transfer_timeout_ms") = std::nullopt) |
There was a problem hiding this comment.
Fix malformed py::init signature
The py::init template parameter list is broken—std::optional<int>> ended up outside the template argument list, so this won’t compile. Keep all three optionals inside the template parameters.
- .def(py::init<std::optional<tle::CacheTransceiverConfig::BackendType>, std::optional<size_t>>,
- std::optional < int >> (), py::arg("backend") = std::nullopt,
+ .def(py::init<std::optional<tle::CacheTransceiverConfig::BackendType>, std::optional<size_t>,
+ std::optional<int>>(),
+ py::arg("backend") = std::nullopt,
py::arg("max_tokens_in_buffer") = std::nullopt, py::arg("kv_transfer_timeout_ms") = std::nullopt)📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| py::class_<tle::CacheTransceiverConfig>(m, "CacheTransceiverConfig") | |
| .def(py::init<std::optional<tle::CacheTransceiverConfig::BackendType>, std::optional<size_t>>(), | |
| py::arg("backend") = std::nullopt, py::arg("max_tokens_in_buffer") = std::nullopt) | |
| .def(py::init<std::optional<tle::CacheTransceiverConfig::BackendType>, std::optional<size_t>>, | |
| std::optional < int >> (), py::arg("backend") = std::nullopt, | |
| py::arg("max_tokens_in_buffer") = std::nullopt, py::arg("kv_transfer_timeout_ms") = std::nullopt) | |
| py::class_<tle::CacheTransceiverConfig>(m, "CacheTransceiverConfig") | |
| .def(py::init<std::optional<tle::CacheTransceiverConfig::BackendType>, std::optional<size_t>, | |
| std::optional<int>>(), | |
| py::arg("backend") = std::nullopt, | |
| py::arg("max_tokens_in_buffer") = std::nullopt, py::arg("kv_transfer_timeout_ms") = std::nullopt) |
| for req in self.ctx_in_transmission_requests: | ||
| if req.py_kv_transfer_start_time is None: | ||
| continue | ||
| elapsed_time = (current_time - req.py_kv_transfer_start_time) * 1000 | ||
| if elapsed_time > timeout_ms and not req.py_kv_transfer_timed_out: | ||
| logger.warning( | ||
| f"Terminating context request {req.py_request_id} due to KV cache transfer timeout" | ||
| ) | ||
| req.py_kv_transfer_timed_out = True | ||
|
|
There was a problem hiding this comment.
Fix AttributeError when checking context transfer timeouts
self.ctx_in_transmission_requests holds (request, blockId) tuples, so iterating directly over it and accessing req.py_kv_transfer_start_time will throw at runtime. Unpack the tuple (or index into it) before touching request attributes.
- for req in self.ctx_in_transmission_requests:
+ for req, _ in self.ctx_in_transmission_requests:
if req.py_kv_transfer_start_time is None:
continue📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| for req in self.ctx_in_transmission_requests: | |
| if req.py_kv_transfer_start_time is None: | |
| continue | |
| elapsed_time = (current_time - req.py_kv_transfer_start_time) * 1000 | |
| if elapsed_time > timeout_ms and not req.py_kv_transfer_timed_out: | |
| logger.warning( | |
| f"Terminating context request {req.py_request_id} due to KV cache transfer timeout" | |
| ) | |
| req.py_kv_transfer_timed_out = True | |
| for req, _ in self.ctx_in_transmission_requests: | |
| if req.py_kv_transfer_start_time is None: | |
| continue | |
| elapsed_time = (current_time - req.py_kv_transfer_start_time) * 1000 | |
| if elapsed_time > timeout_ms and not req.py_kv_transfer_timed_out: | |
| logger.warning( | |
| f"Terminating context request {req.py_request_id} due to KV cache transfer timeout" | |
| ) | |
| req.py_kv_transfer_timed_out = True |
🤖 Prompt for AI Agents
In tensorrt_llm/_torch/pyexecutor/py_executor.py around lines 1589 to 1598, the
loop treats items in self.ctx_in_transmission_requests as request objects but
they are (request, blockId) tuples; unpack the tuple before accessing attributes
(e.g., for req, _ in self.ctx_in_transmission_requests or req = item[0]), then
use req.py_kv_transfer_start_time, compute elapsed_time and set
req.py_kv_transfer_timed_out as before to avoid the AttributeError.
| if self.kv_cache_transceiver.kv_transfer_timeout_ms is not None: | ||
| for req in ctx_in_transmission_requests: | ||
| if req.state == LlmRequestState.DISAGG_CONTEXT_TRANS_IN_PROGRESS: | ||
| req.py_kv_transfer_start_time = time.time() |
There was a problem hiding this comment.
Fix NameError when arming context timeout clock
ctx_in_transmission_requests is undefined here, so this block will raise immediately. The intent is to walk the freshly built ctx_transmission_reqs.
- if self.kv_cache_transceiver.kv_transfer_timeout_ms is not None:
- for req in ctx_in_transmission_requests:
+ if self.kv_cache_transceiver.kv_transfer_timeout_ms is not None:
+ for req in ctx_transmission_reqs:
if req.state == LlmRequestState.DISAGG_CONTEXT_TRANS_IN_PROGRESS:
req.py_kv_transfer_start_time = time.time()📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| if self.kv_cache_transceiver.kv_transfer_timeout_ms is not None: | |
| for req in ctx_in_transmission_requests: | |
| if req.state == LlmRequestState.DISAGG_CONTEXT_TRANS_IN_PROGRESS: | |
| req.py_kv_transfer_start_time = time.time() | |
| if self.kv_cache_transceiver.kv_transfer_timeout_ms is not None: | |
| for req in ctx_transmission_reqs: | |
| if req.state == LlmRequestState.DISAGG_CONTEXT_TRANS_IN_PROGRESS: | |
| req.py_kv_transfer_start_time = time.time() |
🧰 Tools
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1747-1747: Undefined name ctx_in_transmission_requests
(F821)
pcastonguay
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Signed-off-by: Patrice Castonguay <[email protected]>
Summary by CodeRabbit
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PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.
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Please check this after reviewing the above items as appropriate for this PR.
GitHub Bot Help
/bot [-h] ['run', 'kill', 'skip', 'reuse-pipeline'] ...Provide a user friendly way for developers to interact with a Jenkins server.
Run
/bot [-h|--help]to print this help message.See details below for each supported subcommand.
run [--reuse-test (optional)pipeline-id --disable-fail-fast --skip-test --stage-list "A10-PyTorch-1, xxx" --gpu-type "A30, H100_PCIe" --test-backend "pytorch, cpp" --add-multi-gpu-test --only-multi-gpu-test --disable-multi-gpu-test --post-merge --extra-stage "H100_PCIe-TensorRT-Post-Merge-1, xxx" --detailed-log --debug(experimental)]Launch build/test pipelines. All previously running jobs will be killed.
--reuse-test (optional)pipeline-id(OPTIONAL) : Allow the new pipeline to reuse build artifacts and skip successful test stages from a specified pipeline or the last pipeline if no pipeline-id is indicated. If the Git commit ID has changed, this option will be always ignored. The DEFAULT behavior of the bot is to reuse build artifacts and successful test results from the last pipeline.--disable-reuse-test(OPTIONAL) : Explicitly prevent the pipeline from reusing build artifacts and skipping successful test stages from a previous pipeline. Ensure that all builds and tests are run regardless of previous successes.--disable-fail-fast(OPTIONAL) : Disable fail fast on build/tests/infra failures.--skip-test(OPTIONAL) : Skip all test stages, but still run build stages, package stages and sanity check stages. Note: Does NOT update GitHub check status.--stage-list "A10-PyTorch-1, xxx"(OPTIONAL) : Only run the specified test stages. Examples: "A10-PyTorch-1, xxx". Note: Does NOT update GitHub check status.--gpu-type "A30, H100_PCIe"(OPTIONAL) : Only run the test stages on the specified GPU types. Examples: "A30, H100_PCIe". Note: Does NOT update GitHub check status.--test-backend "pytorch, cpp"(OPTIONAL) : Skip test stages which don't match the specified backends. Only support [pytorch, cpp, tensorrt, triton]. Examples: "pytorch, cpp" (does not run test stages with tensorrt or triton backend). Note: Does NOT update GitHub pipeline status.--only-multi-gpu-test(OPTIONAL) : Only run the multi-GPU tests. Note: Does NOT update GitHub check status.--disable-multi-gpu-test(OPTIONAL) : Disable the multi-GPU tests. Note: Does NOT update GitHub check status.--add-multi-gpu-test(OPTIONAL) : Force run the multi-GPU tests in addition to running L0 pre-merge pipeline.--post-merge(OPTIONAL) : Run the L0 post-merge pipeline instead of the ordinary L0 pre-merge pipeline.--extra-stage "H100_PCIe-TensorRT-Post-Merge-1, xxx"(OPTIONAL) : Run the ordinary L0 pre-merge pipeline and specified test stages. Examples: --extra-stage "H100_PCIe-TensorRT-Post-Merge-1, xxx".--detailed-log(OPTIONAL) : Enable flushing out all logs to the Jenkins console. This will significantly increase the log volume and may slow down the job.--debug(OPTIONAL) : Experimental feature. Enable access to the CI container for debugging purpose. Note: Specify exactly one stage in thestage-listparameter to access the appropriate container environment. Note: Does NOT update GitHub check status.For guidance on mapping tests to stage names, see
docs/source/reference/ci-overview.mdand the
scripts/test_to_stage_mapping.pyhelper.kill
killKill all running builds associated with pull request.
skip
skip --comment COMMENTSkip testing for latest commit on pull request.
--comment "Reason for skipping build/test"is required. IMPORTANT NOTE: This is dangerous since lack of user care and validation can cause top of tree to break.reuse-pipeline
reuse-pipelineReuse a previous pipeline to validate current commit. This action will also kill all currently running builds associated with the pull request. IMPORTANT NOTE: This is dangerous since lack of user care and validation can cause top of tree to break.