Test that TORCH_FEATURE_VERSION guards are used where needed

[hila-f-qodo]

User description

Splits each torch library registration in the 2.10 folder into its own file -- I had a script that parsed kernel.cpp to do this but I felt like forcing this responsibility on the user might be less error prone

Compiles each file targetting 2.9 and asserts that compilation fails. (There are 2 2.9 kernels we use as negative tests where compilation is expected to succeed)

Stack from ghstack (oldest at bottom):

• Add sum and sum_out to stable ops pytorch/pytorch#168062
• Move MemoryFormat/Layout to headeronly pytorch/pytorch#168034
• -> Test that TORCH_FEATURE_VERSION guards are used where needed pytorch/pytorch#167962
• Test libtorch_agnostic with TORCH_TARGET_VERSION on target pytorch version pytorch/pytorch#167804
• Split libtorch agnostic tests by feature version pytorch/pytorch#167803
• Fix TORCH_FEATURE_VERSION guards pytorch/pytorch#167802
• Follow up on #161891 move additions to stable shim and use version guards pytorch/pytorch#168025

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PR Type

Tests, Enhancement

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Description

• Split monolithic kernel.cpp into individual function files for better organization and maintainability

• Added comprehensive test suite to verify TORCH_FEATURE_VERSION guards are properly used

• Compiles each .cpp and .cu file with TORCH_TARGET_VERSION=2.9.0 and validates compilation fails

• Includes negative tests (mv_tensor_accessor_cpu.cpp and mv_tensor_accessor_cuda.cu) to verify test infrastructure correctness

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Diagram Walkthrough

flowchart LR
  A["kernel.cpp<br/>monolithic file"] -->|"split into"| B["Individual function files<br/>15+ .cpp/.cu files"]
  B -->|"tested by"| C["test_version_compatibility.py<br/>version guard validator"]
  C -->|"compiles with"| D["TORCH_TARGET_VERSION=2.9.0"]
  D -->|"expects failure"| E["Compilation fails<br/>guards working"]
  D -->|"negative tests"| F["mv_tensor_accessor files<br/>should succeed"]

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File Walkthrough

	Relevant files
Tests	3 files test_version_compatibility.py Comprehensive test suite for version compatibility validation +300/-0  mv_tensor_accessor_cpu.cpp Added negative test file for CPU tensor accessor compatibility +40/-0    mv_tensor_accessor_cuda.cu Added negative test file for CUDA tensor accessor compatibility +47/-0
Refactoring	16 files kernel.cpp Removed monolithic kernel file split into individual files +0/-205  my__foreach_mul.cpp Extracted foreach_mul function into separate file                +20/-0    my__foreach_mul_.cpp Extracted foreach_mul_ function into separate file              +19/-0    make_tensor_clones_and_call_foreach.cpp Extracted make_tensor_clones_and_call_foreach function into separate file +41/-0    my_empty.cpp Extracted my_empty function into separate file                      +25/-0    my_reshape.cpp Extracted my_reshape function into separate file                  +17/-0    my_view.cpp Extracted my_view function into separate file                        +20/-0    test_tensor_device.cpp Extracted test_tensor_device function into separate file  +17/-0    test_device_constructor.cpp Extracted test_device_constructor function into separate file +37/-0    test_device_equality.cpp Extracted test_device_equality function into separate file +14/-0    test_device_set_index.cpp Extracted test_device_set_index function into separate file +17/-0    test_device_index.cpp Extracted test_device_index function into separate file    +14/-0    test_device_is_cuda.cpp Extracted test_device_is_cuda function into separate file +14/-0    test_device_is_cpu.cpp Extracted test_device_is_cpu function into separate file  +14/-0    test_parallel_for.cpp Extracted test_parallel_for function into separate file    +49/-0    test_get_num_threads.cpp Extracted test_get_num_threads function into separate file +14/-0
Enhancement	1 files tensor_accessor_kernel.h Added shared tensor accessor kernel header for CPU and CUDA +28/-0

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[qodo-code-review]

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🟢	Generic: Meaningful Naming and Self-Documenting Code Objective: Ensure all identifiers clearly express their purpose and intent, making code self-documenting Status: Passed Learn more about managing compliance generic rules or creating your own custom rules
	Generic: Secure Error Handling Objective: To prevent the leakage of sensitive system information through error messages while providing sufficient detail for internal debugging. Status: Passed Learn more about managing compliance generic rules or creating your own custom rules
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	Generic: Security-First Input Validation and Data Handling Objective: Ensure all data inputs are validated, sanitized, and handled securely to prevent vulnerabilities Status: Passed Learn more about managing compliance generic rules or creating your own custom rules
⚪	Generic: Comprehensive Audit Trails Objective: To create a detailed and reliable record of critical system actions for security analysis and compliance. Status: No Audit Logs: The new test and helper compilation functions perform critical compile/validation actions without emitting structured audit logs of who ran them, when, or their outcomes. Referred Code def _compile_cpp_file( self, source_file: Path, output_file: Path ) -> tuple[bool, str]: """ Compile a C++ file with TORCH_TARGET_VERSION=2.9.0. Returns (success, error_message). """ torch_version_2_9 = "0x0209000000000000" cmd = [ "g++", "-c", "-std=c++17", f"-DTORCH_TARGET_VERSION={torch_version_2_9}", f"-I{source_file.parent}", # For includes in same directory *self.pytorch_includes, ] # Add CUDA flags if available if self.cuda_available: cmd.extend(self.cuda_includes) ... (clipped 75 lines) Learn more about managing compliance generic rules or creating your own custom rules
	Generic: Robust Error Handling and Edge Case Management Objective: Ensure comprehensive error handling that provides meaningful context and graceful degradation Status: Timeout Handling: Subprocess compilation uses a fixed 30s timeout without retry or differentiating tool-not-found vs actual compile errors, which may cause flaky failures without robust handling. Referred Code result = subprocess.run(cmd, capture_output=True, text=True, timeout=30) if result.returncode == 0: return True, "" else: return False, result.stderr Learn more about managing compliance generic rules or creating your own custom rules

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[qodo-code-review]

PR Code Suggestions ✨

Explore these optional code suggestions:

Category	Suggestion	Impact
Possible issue	Fix operator schema to match implementation Update the operator schema for mv_tensor_accessor_cpu to match its C++ function signature by removing the extra res argument from the m.def string. test/cpp_extensions/libtorch_agnostic_2_10_extension/libtorch_agnostic_2_10/csrc/mv_tensor_accessor_cpu.cpp [34-36] STABLE_TORCH_LIBRARY_FRAGMENT(libtorch_agnostic_2_10, m) { - m.def("mv_tensor_accessor_cpu(Tensor res, Tensor m, Tensor v) -> Tensor"); + m.def("mv_tensor_accessor_cpu(Tensor m, Tensor v) -> Tensor"); } Apply / Chat Suggestion importance[1-10]: 8 __ Why: The suggestion correctly identifies a mismatch between the operator schema in m.def and the C++ function signature, which would cause a runtime registration error.	Medium
	Avoid adding CUDA includes for C++ files Remove the logic that adds CUDA include paths from the _compile_cpp_file function to prevent potential compilation issues with standard C++ files. test/cpp_extensions/libtorch_agnostic_2_10_extension/test_version_compatibility.py [66-95] def _compile_cpp_file( self, source_file: Path, output_file: Path ) -> tuple[bool, str]: """ Compile a C++ file with TORCH_TARGET_VERSION=2.9.0. Returns (success, error_message). """ torch_version_2_9 = "0x0209000000000000" cmd = [ "g++", "-c", "-std=c++17", f"-DTORCH_TARGET_VERSION={torch_version_2_9}", f"-I{source_file.parent}", # For includes in same directory *self.pytorch_includes, ] - # Add CUDA flags if available - if self.cuda_available: - cmd.extend(self.cuda_includes) - cmd.extend([str(source_file), "-o", str(output_file)]) result = subprocess.run(cmd, capture_output=True, text=True, timeout=30) if result.returncode == 0: return True, "" else: return False, result.stderr Apply / Chat Suggestion importance[1-10]: 7 __ Why: The suggestion correctly identifies that adding CUDA include paths during C++ compilation is unnecessary and potentially problematic, improving the robustness and correctness of the test compilation logic.	Medium
High-level	Avoid duplicating code for negative tests To avoid maintenance issues from code duplication, modify the test script to compile the original mv_tensor_accessor files from the libtorch_agnostic_2_9_extension directory for negative testing, instead of using copied versions. Examples: test/cpp_extensions/libtorch_agnostic_2_10_extension/libtorch_agnostic_2_10/csrc/mv_tensor_accessor_cpu.cpp [1-2] // This is duplicated from the libtorch_agnostic_2_9_extension // as a negative test for test_version_compatibility.py test/cpp_extensions/libtorch_agnostic_2_10_extension/test_version_compatibility.py [163-170] def test_mv_tensor_accessor_cpu_works_with_2_9(self): """Test that mv_tensor_accessor_cpu.cpp compiles successfully with 2.9.0. This is a negative test - it ensures that a file we expect to work with 2.9.0 actually does compile. This validates that our test infrastructure correctly distinguishes between files that require 2.10+ and those that don't. """ cpp_file = self.csrc_dir / "mv_tensor_accessor_cpu.cpp" Solution Walkthrough: Before: // test/.../libtorch_agnostic_2_10/csrc/mv_tensor_accessor_cpu.cpp // This is duplicated from the libtorch_agnostic_2_9_extension // as a negative test for test_version_compatibility.py ... (code for mv_tensor_accessor_cpu) ... // test/.../test_version_compatibility.py class FunctionVersionCompatibilityTest(TestCase): def setUpClass(cls): cls.csrc_dir = Path(__file__).parent / "libtorch_agnostic_2_10" / "csrc" ... def test_mv_tensor_accessor_cpu_works_with_2_9(self): # This file is a copy inside the 2_10 directory cpp_file = self.csrc_dir / "mv_tensor_accessor_cpu.cpp" success, _ = self._compile_cpp_file(cpp_file, ...) self.assertTrue(success) After: // test/.../libtorch_agnostic_2_10/csrc/mv_tensor_accessor_cpu.cpp // This file is deleted. // test/.../test_version_compatibility.py class FunctionVersionCompatibilityTest(TestCase): def setUpClass(cls): cls.csrc_dir_2_10 = Path(__file__).parent / "libtorch_agnostic_2_10" / "csrc" # Path to the original 2_9 extension files cls.csrc_dir_2_9 = Path(__file__).parent.parent / "libtorch_agnostic_2_9_extension" / "csrc" ... def test_mv_tensor_accessor_cpu_works_with_2_9(self): # Reference the original file from the 2_9 directory cpp_file = self.csrc_dir_2_9 / "mv_tensor_accessor_cpu.cpp" success, _ = self._compile_cpp_file(cpp_file, ...) self.assertTrue(success) Suggestion importance[1-10]: 7 __ Why: The suggestion correctly identifies code duplication for negative tests, which is a significant maintainability issue, and proposes a robust solution that improves the long-term quality of the test suite.	Medium
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