[None][fix] Restrict tinygemm use to certain SMs #8182
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📝 WalkthroughWalkthroughAdds SM version checks to tinygemm2_forward to restrict execution to SM90/SM100. Updates GPT OSS model gating to use tinygemm2 only when SM is 90/100 and token count is within the small-sequence threshold, otherwise falls back to the standard path. Introduces get_sm_version usage in Python. Changes
Sequence Diagram(s)sequenceDiagram
autonumber
participant M as GPT OSS Model
participant U as _utils.get_sm_version
participant T as tinygemm2 (C++)
participant S as Standard Gate
M->>U: get_sm_version()
U-->>M: sm_version
alt sm_version in {90,100} AND tokens <= threshold
M->>T: tinygemm2_forward(x, w, b)
note over T: Early check: SM must be 90/100<br/>else TORCH_CHECK error
T-->>M: gate_output
else Fallback
M->>S: compute standard gate
S-->>M: gate_output
end
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~20 minutes Pre-merge checks and finishing touches❌ Failed checks (2 warnings)
✅ Passed checks (1 passed)
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Actionable comments posted: 2
🧹 Nitpick comments (2)
cpp/tensorrt_llm/thop/tinygemm2.cpp (1)
33-34: Prefer named constants over magic literals.The hardcoded values
90and100violate the coding guideline that requires magic numbers to be named constants with akprefix in uppercase SNAKE_CASE.As per coding guidelines.
Apply this diff to use named constants:
+namespace +{ +constexpr int kSM_VERSION_90 = 90; +constexpr int kSM_VERSION_100 = 100; +} // namespace + torch::Tensor tinygemm2_forward(torch::Tensor input, torch::Tensor weight, torch::Tensor bias) { auto const smVersion = tensorrt_llm::common::getSMVersion(); - TORCH_CHECK(smVersion == 90 || smVersion == 100, "tinygemm2 only supports SM90 and SM100."); + TORCH_CHECK(smVersion == kSM_VERSION_90 || smVersion == kSM_VERSION_100, "tinygemm2 only supports SM90 and SM100.");tensorrt_llm/_torch/models/modeling_gpt_oss.py (1)
229-231: Prefer named constants over magic literals.The hardcoded values
90and100violate the coding guideline that requires constants to use uppercase SNAKE_CASE naming.As per coding guidelines.
Apply this diff to use named constants:
+# SM versions that support tinygemm2 +SM_VERSION_90 = 90 +SM_VERSION_100 = 100 +SUPPORTED_TINYGEMM2_SM_VERSIONS = [SM_VERSION_90, SM_VERSION_100] + # Use TinyGEMM when the number of tokens is not larger than this threshold MIN_LATENCY_TINYGEMM_NUM_TOKENS = 128Then update the condition:
def compute_gate_output(self, x: torch.Tensor) -> torch.Tensor: - if get_sm_version() in [ - 90, 100 - ] and x.shape[0] <= MIN_LATENCY_TINYGEMM_NUM_TOKENS: + if get_sm_version() in SUPPORTED_TINYGEMM2_SM_VERSIONS and x.shape[0] <= MIN_LATENCY_TINYGEMM_NUM_TOKENS:
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cpp/tensorrt_llm/thop/tinygemm2.cpp(1 hunks)tensorrt_llm/_torch/models/modeling_gpt_oss.py(2 hunks)
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**/*.{h,hpp,hh,hxx,cpp,cxx,cc,cu,cuh}
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**/*.{h,hpp,hh,hxx,cpp,cxx,cc,cu,cuh}: Namespace closing braces must include a trailing comment with the namespace name (e.g., '} // namespace foo').
Prefer const or constexpr variables over #define for constants.
Declare variables that are not modified after initialization as const.
Avoid magic literals in code; except for 0, nullptr, true, false. Use named constants for comparisons and logic.
Use Allman brace style for formatting.
Place the semicolon of an empty for/while loop on a new line.
Bodies of switch/while/do-while/for must be compound statements (brace-delimited), and if/else must always be followed by brace-delimited statements.
Type names (e.g., classes) must be CamelCase starting with an uppercase letter (e.g., FooBar).
Local variables, methods, and namespaces use lowerCamelCase (e.g., localFooBar).
Non-magic-number global variables that are non-static and not in an anonymous namespace must be lowerCamelCase prefixed with 'g' (e.g., gDontUseGlobalFoos).
Non-magic-number globals that are static or in an anonymous namespace use lowerCamelCase prefixed with 's' (e.g., sMutableStaticGlobal).
Locally visible static variables use lowerCamelCase with 's' prefix (e.g., static std::once_flag sFlag).
Private/protected member variables use 'm' prefix with CamelCase (e.g., mNbFooValues). Public members may omit, but 'm' is encouraged for clarity.
Constants (enums, global constants, static constants, and function-scope magic/literal constants) use uppercase SNAKE_CASE with 'k' prefix (e.g., kDIGIT_NUM).
Function-scope constants that are not magic numbers or literals are named like non-constant variables (e.g., bool const pass = a && b).
If macros are necessary, name them in UPPER_SNAKE_CASE (e.g., FOO_VERSION) and prefer constants over #define.
Use LLVM clang-format; wrap lines at a maximum of 120 columns; use '// clang-format off/on' sparingly with justification.
Use smart pointers for heap allocations; prefer unique_ptr for sole ownership, shared_ptr for shared...
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**/*.{cpp,cxx,cc,cu,h,hpp,hh,hxx,cuh}
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Use only spaces, no tabs; indent with 4 spaces.
Files:
cpp/tensorrt_llm/thop/tinygemm2.cpptensorrt_llm/_torch/models/modeling_gpt_oss.py
**/*.{h,hpp,hh,hxx,cpp,cxx,cc}
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**/*.{h,hpp,hh,hxx,cpp,cxx,cc}: Prefer anonymous namespaces over 'static' for internal linkage of functions.
All templates (class/function/member/static) must be instantiated at least once; non-POD classes should have private data members.
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cpp/tensorrt_llm/thop/tinygemm2.cpp
**/*.{cpp,cxx,cc,h,hpp,hh,hxx,cu,cuh,py}
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**/*.py
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**/*.py: Python code must target Python 3.8+.
Indent Python code with 4 spaces; do not use tabs.
Maintain module namespace when importing; prefer 'from package.subpackage import foo' then 'foo.SomeClass()' instead of importing the class directly.
Python filenames should be snake_case (e.g., some_file.py).
Python classes use PascalCase names.
Functions and methods use snake_case names.
Local variables use snake_case; prefix 'k' for variables that start with a number (e.g., k_99th_percentile).
Global variables use upper SNAKE_CASE prefixed with 'G' (e.g., G_MY_GLOBAL).
Constants use upper SNAKE_CASE (e.g., MY_CONSTANT).
Avoid shadowing variables from an outer scope.
Initialize all externally visible members of a class in the constructor.
Prefer docstrings for interfaces that may be used outside a file; comments for in-function or file-local interfaces.
Use Google-style docstrings for classes and functions (Sphinx-parsable).
Document attributes and variables inline so they render under the class/function docstring.
Avoid reflection when a simpler, explicit approach suffices (e.g., avoid dict(**locals()) patterns).
In try/except, catch the most specific exceptions possible.
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Files:
tensorrt_llm/_torch/models/modeling_gpt_oss.py
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tensorrt_llm/_torch/models/modeling_gpt_oss.py (1)
cpp/include/tensorrt_llm/common/cudaUtils.h (1)
tensorrt_llm(48-374)
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tensorrt_llm/_torch/models/modeling_gpt_oss.py (1)
10-10: LGTM!The import follows Python coding guidelines by maintaining module namespace.
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Signed-off-by: Dongfeng Yu <[email protected]>
Signed-off-by: dongfengy <[email protected]>
Signed-off-by: dongfengy <[email protected]>
Signed-off-by: dongfengy <[email protected]>
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