add RecordStreamTest.cpp

[youge325]

新增 record_stream 测试

[Copilot]

Pull request overview

Adds a new compatibility test suite for Tensor::record_stream and updates build configuration to include CUDA Toolkit headers when available, improving compilation in CUDA-enabled environments (especially when headers pull in cuda_runtime_api.h).

Changes:

• Added test/RecordStreamTest.cpp covering multiple record_stream call scenarios (various dtypes/shapes, non-contiguous, CPU tensor cases).
• Updated CMakeLists.txt to find_package(CUDAToolkit) and append CUDA include directories to Torch/Paddle include paths when found.

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 3 comments.

File	Description
test/RecordStreamTest.cpp	Introduces record_stream API coverage and a helper to obtain a CUDA stream across Torch vs Paddle compat builds.
CMakeLists.txt	Adds optional CUDA Toolkit discovery and include paths to support CUDA-dependent headers during compilation.

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[Copilot]

find_package(CUDAToolkit QUIET) + conditional include path append can still leave builds failing later with missing cuda_runtime_api.h (e.g., CUDA-enabled libtorch headers included but CUDA toolkit not found), and the failure will be a compiler error with no actionable CMake message. Consider adding a clear message(FATAL_ERROR ...) (or at least message(WARNING ...)) when CUDA-dependent headers/tests are being built but CUDAToolkit is not found, so the configuration fails early and is easier to debug.

Suggested change

	endif()
	endif()
	if(NOT CUDAToolkit_FOUND)
	message(
	FATAL_ERROR
	"CUDAToolkit was not found, but CUDA-dependent Torch tests are enabled. "
	"Please install the CUDA toolkit or disable building these Torch tests.")
	endif()

[Copilot]

Appending ${CUDAToolkit_INCLUDE_DIRS} to PADDLE_INCLUDE_DIR is guarded on CUDAToolkit_FOUND, but PADDLE_LIBRARIES unconditionally includes GPU libraries (e.g. libphi_gpu.so). If the environment is missing CUDA toolkit headers, the build will fail with confusing compile errors. Consider either (1) making CUDA toolkit a required dependency when linking Paddle GPU libs, or (2) gating the GPU libs and CUDA include dirs behind a single explicit option/check so CPU-only environments fail fast or build a CPU-only variant consistently.