[https://nvbugs/5625743][fix] Cherry-pick support for n>1 with pytorch backend for openai completion and add tests. #9471
Conversation
|
/bot run |
📝 WalkthroughWalkthroughThe PR replaces backend validation logic with a new tool call ID generation utility, removes pre-flight validation checks from OpenAI server execution paths, and extends test coverage with new beam search fixtures and test scenarios alongside GPU memory fraction configurations. Changes
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~20 minutes
Pre-merge checks and finishing touches❌ Failed checks (2 warnings)
✅ Passed checks (1 passed)
✨ Finishing touches
🧪 Generate unit tests (beta)
Tip 📝 Customizable high-level summaries are now available in beta!You can now customize how CodeRabbit generates the high-level summary in your pull requests — including its content, structure, tone, and formatting.
Example instruction:
Note: This feature is currently in beta for Pro-tier users, and pricing will be announced later. Thanks for using CodeRabbit! It's free for OSS, and your support helps us grow. If you like it, consider giving us a shout-out. Comment |
![coderabbitai[bot]](https://avatars.githubusercontent.com/in/347564?s=60&v=4){kind=small}
There was a problem hiding this comment.
Actionable comments posted: 2
📜 Review details
Configuration used: Path: .coderabbit.yaml
Review profile: CHILL
Plan: Pro
📒 Files selected for processing (4)
tensorrt_llm/serve/chat_utils.py(1 hunks)tensorrt_llm/serve/openai_server.py(1 hunks)tests/unittest/llmapi/apps/_test_openai_chat.py(5 hunks)tests/unittest/llmapi/apps/_test_openai_completions.py(4 hunks)
🧰 Additional context used
📓 Path-based instructions (2)
**/*.py
📄 CodeRabbit inference engine (CODING_GUIDELINES.md)
**/*.py: The code developed for TensorRT-LLM should conform to Python 3.8+
Indent Python code with 4 spaces; do not use tabs
Always maintain the namespace when importing in Python, even if only one class or function from a module is used (e.g., usefrom package.subpackage import fooand thenfoo.SomeClass()instead offrom package.subpackage.foo import SomeClass)
Python filenames should use snake_case (e.g.,some_file.py)
Python class names should use PascalCase (e.g.,class SomeClass)
Python function and method names should use snake_case (e.g.,def my_awesome_function():)
Python local variable names should use snake_case, with prefixkfor variable names that start with a number (e.g.,k_99th_percentile = ...)
Python global variables should use upper snake_case with prefixG(e.g.,G_MY_GLOBAL = ...)
Python constants should use upper snake_case (e.g.,MY_CONSTANT = ...)
Avoid shadowing variables declared in an outer scope in Python
Initialize all externally visible members of a Python class in the constructor
For Python interfaces that may be used outside a file, prefer docstrings over comments
Python comments should be reserved for code within a function, or interfaces that are local to a file
Use Google style docstrings for Python classes and functions, which can be parsed by Sphinx
Python attributes and variables can be documented inline with type and description (e.g.,self.x = 5followed by"""<type>: Description of 'x'""")
Avoid using reflection in Python when functionality can be easily achieved without reflection
When using try-except blocks in Python, limit the except clause to the smallest set of specific errors possible instead of catching all exceptions
When using try-except blocks in Python to handle multiple possible variable types (duck-typing), keep the body of the try as small as possible and use the else block to implement the logic
Files:
tensorrt_llm/serve/openai_server.pytensorrt_llm/serve/chat_utils.pytests/unittest/llmapi/apps/_test_openai_chat.pytests/unittest/llmapi/apps/_test_openai_completions.py
**/*.{cpp,h,cu,py}
📄 CodeRabbit inference engine (CODING_GUIDELINES.md)
All TensorRT-LLM Open Source Software code files should contain an NVIDIA copyright header that includes the current year at the top
Files:
tensorrt_llm/serve/openai_server.pytensorrt_llm/serve/chat_utils.pytests/unittest/llmapi/apps/_test_openai_chat.pytests/unittest/llmapi/apps/_test_openai_completions.py
🧠 Learnings (2)
📓 Common learnings
Learnt from: venkywonka
Repo: NVIDIA/TensorRT-LLM PR: 6029
File: .github/pull_request_template.md:45-53
Timestamp: 2025-08-27T17:50:13.264Z
Learning: For PR templates in TensorRT-LLM, avoid suggesting changes that would increase developer overhead, such as converting plain bullets to mandatory checkboxes. The team prefers guidance-style bullets that don't require explicit interaction to reduce friction in the PR creation process.
Learnt from: dcampora
Repo: NVIDIA/TensorRT-LLM PR: 6867
File: tensorrt_llm/_torch/pyexecutor/sampler.py:67-72
Timestamp: 2025-08-13T16:20:37.987Z
Learning: In TensorRT-LLM sampler code, performance is prioritized over additional validation checks. The beam_width helper method intentionally returns the first request's beam_width without validating consistency across all requests to avoid performance overhead from iterating through the entire batch.
📚 Learning: 2025-07-28T17:06:08.621Z
Learnt from: moraxu
Repo: NVIDIA/TensorRT-LLM PR: 6303
File: tests/integration/test_lists/qa/examples_test_list.txt:494-494
Timestamp: 2025-07-28T17:06:08.621Z
Learning: In TensorRT-LLM testing, it's common to have both CLI flow tests (test_cli_flow.py) and PyTorch API tests (test_llm_api_pytorch.py) for the same model. These serve different purposes: CLI flow tests validate the traditional command-line workflow, while PyTorch API tests validate the newer LLM API backend. Both are legitimate and should coexist.
Applied to files:
tests/unittest/llmapi/apps/_test_openai_chat.pytests/unittest/llmapi/apps/_test_openai_completions.py
🧬 Code graph analysis (3)
tensorrt_llm/serve/openai_server.py (1)
tensorrt_llm/serve/chat_utils.py (1)
parse_chat_messages_coroutines(175-199)
tests/unittest/llmapi/apps/_test_openai_chat.py (2)
tests/unittest/llmapi/apps/openai_server.py (1)
get_client(109-113)tensorrt_llm/_torch/pyexecutor/model_engine.py (1)
use_beam_search(418-419)
tests/unittest/llmapi/apps/_test_openai_completions.py (2)
tests/unittest/llmapi/apps/openai_server.py (2)
RemoteOpenAIServer(17-118)get_async_client(115-118)tests/integration/defs/stress_test/stress_test.py (1)
get_model_path(310-312)
🪛 Ruff (0.14.5)
tensorrt_llm/serve/chat_utils.py
207-207: Undefined name uuid
(F821)
tests/unittest/llmapi/apps/_test_openai_completions.py
221-221: Comment contains ambiguous × (MULTIPLICATION SIGN). Did you mean x (LATIN SMALL LETTER X)?
(RUF003)
⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (1)
- GitHub Check: Pre-commit Check
🔇 Additional comments (8)
tensorrt_llm/serve/openai_server.py (1)
34-34: LGTM!The import change is consistent with the removal of
check_multiple_responsevalidation, enablingn>1support for the PyTorch backend as intended by this PR.tests/unittest/llmapi/apps/_test_openai_completions.py (2)
36-53: LGTM on fixture additions.The
kv_cache_free_gpu_memory_fractionparameter enables co-existence of multiple server instances, andserver_with_beam_searchcorrectly configures beam search withmax_beam_width=2.
167-184: LGTM!The test correctly uses the new
async_client_with_beam_searchfixture and validates beam search behavior withn=2.tests/unittest/llmapi/apps/_test_openai_chat.py (5)
71-72: LGTM!The
kv_cache_free_gpu_memory_fractionparameter enables server co-existence during parallel test execution.
83-98: LGTM!The
server_with_beam_searchfixture correctly configures beam search withmax_beam_width=2for both backends, enabling consistent beam search testing.
204-226: LGTM!Good separation of concerns by moving beam search testing to dedicated test functions while keeping
best_oftesting here.
229-266: Approve with note on duplication.The test correctly validates beam search with the base server. Note that lines 257-266 duplicate the
best_oftest fromtest_multiple_responses- this may be intentional for test isolation but could be considered for consolidation.
269-291: LGTM!This test validates beam search support for both backends using the dedicated
server_with_beam_searchfixture, aligning with the PR objective of enablingn>1support for the PyTorch backend.
|
PR_Github #25814 [ run ] triggered by Bot. Commit: |
|
PR_Github #25814 [ run ] completed with state |
…VIDIA#8951) Signed-off-by: ixlmar <[email protected]>
…treaming Signed-off-by: SimengLiu-nv <[email protected]>
SimengLiu-nv
force-pushed
the
fix-5625743
branch
from
f9a90a9 to
c362159
Compare
|
/bot run |
|
PR_Github #25898 [ run ] triggered by Bot. Commit: |
|
PR_Github #25898 [ run ] completed with state |
Signed-off-by: SimengLiu-nv <[email protected]>
Signed-off-by: SimengLiu-nv <[email protected]>
|
/bot run --disable-fail-fast |
|
Okay to close it for now. |
|
Contribute the changes to the main branch: #9802 |
4 participants
Summary by CodeRabbit
Refactor
Tests
✏️ Tip: You can customize this high-level summary in your review settings.
Description
Test Coverage
PR Checklist
Please review the following before submitting your PR:
PR description clearly explains what and why. If using CodeRabbit's summary, please make sure it makes sense.
PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.
Test cases are provided for new code paths (see test instructions)
Any new dependencies have been scanned for license and vulnerabilities
CODEOWNERS updated if ownership changes
Documentation updated as needed
Update tava architecture diagram if there is a significant design change in PR.
The reviewers assigned automatically/manually are appropriate for the PR.
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.
Details
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.