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resolve multi-CUDA_ARCHITECTURES compilation conflicts #241
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| Original file line number | Diff line number | Diff line change | ||||||
|---|---|---|---|---|---|---|---|---|
|
|
@@ -66,22 +66,56 @@ def get_nvcc_cuda_version(cuda_dir: str) -> Version: | |||||||
| nvcc_cuda_version = parse(output[release_idx].split(",")[0]) | ||||||||
| return nvcc_cuda_version | ||||||||
|
|
||||||||
| # Iterate over all GPUs on the current machine. Also you can modify this part to specify the architecture if you want to build for specific GPU architectures. | ||||||||
| def filter_nvcc_flags_for_arch(nvcc_flags, arch_substrings): | ||||||||
| """Filter NVCC flags, only keep gencode flags for specified architectures""" | ||||||||
| filtered_flags = [] | ||||||||
| skip_next = False | ||||||||
| for i, flag in enumerate(nvcc_flags): | ||||||||
| if skip_next: | ||||||||
| skip_next = False | ||||||||
| continue | ||||||||
| if flag == "-gencode": | ||||||||
| if i + 1 < len(nvcc_flags): | ||||||||
| arch_flag = nvcc_flags[i + 1] | ||||||||
| if any(sub in arch_flag for sub in arch_substrings): | ||||||||
| filtered_flags.append(flag) | ||||||||
| filtered_flags.append(arch_flag) | ||||||||
| skip_next = True | ||||||||
| elif flag not in ["-gencode"]: | ||||||||
| filtered_flags.append(flag) | ||||||||
| return filtered_flags | ||||||||
|
|
||||||||
| compute_capabilities = set() | ||||||||
| device_count = torch.cuda.device_count() | ||||||||
| for i in range(device_count): | ||||||||
| major, minor = torch.cuda.get_device_capability(i) | ||||||||
| if major < 8: | ||||||||
| warnings.warn(f"skipping GPU {i} with compute capability {major}.{minor}") | ||||||||
| continue | ||||||||
| compute_capabilities.add(f"{major}.{minor}") | ||||||||
| cuda_architectures = os.environ.get("CUDA_ARCHITECTURES") | ||||||||
| if cuda_architectures is not None: | ||||||||
| for arch in cuda_architectures.split(","): | ||||||||
| arch = arch.strip() | ||||||||
| if arch: | ||||||||
| compute_capabilities.add(arch) | ||||||||
| else: | ||||||||
| #Iterate over all GPUs on the current machine. Also you can modify this part to specify the architecture if you want to build for specific GPU architectures. | ||||||||
| device_count = torch.cuda.device_count() | ||||||||
| for i in range(device_count): | ||||||||
| major, minor = torch.cuda.get_device_capability(i) | ||||||||
| if major < 8: | ||||||||
| warnings.warn(f"skipping GPU {i} with compute capability {major}.{minor}") | ||||||||
| continue | ||||||||
| compute_capabilities.add(f"{major}.{minor}") | ||||||||
|
|
||||||||
| nvcc_cuda_version = get_nvcc_cuda_version(CUDA_HOME) | ||||||||
| if not compute_capabilities: | ||||||||
| raise RuntimeError("No GPUs found. Please specify the target GPU architectures or build on a machine with GPUs.") | ||||||||
| else: | ||||||||
|
|
||||||||
| unsupported_archs = compute_capabilities - SUPPORTED_ARCHS | ||||||||
| if unsupported_archs: | ||||||||
| warnings.warn(f"Unsupported GPU architectures detected: {unsupported_archs}. Supported architectures: {SUPPORTED_ARCHS}") | ||||||||
| compute_capabilities = compute_capabilities & SUPPORTED_ARCHS | ||||||||
| if not compute_capabilities: | ||||||||
| raise RuntimeError(f"No supported GPU architectures found. Detected: {compute_capabilities | unsupported_archs}, Supported: {SUPPORTED_ARCHS}") | ||||||||
|
|
||||||||
| print(f"Detect GPUs with compute capabilities: {compute_capabilities}") | ||||||||
|
|
||||||||
| nvcc_cuda_version = get_nvcc_cuda_version(CUDA_HOME) | ||||||||
| # Validate the NVCC CUDA version. | ||||||||
| if nvcc_cuda_version < Version("12.0"): | ||||||||
| raise RuntimeError("CUDA 12.0 or higher is required to build the package.") | ||||||||
|
|
@@ -119,54 +153,66 @@ def get_nvcc_cuda_version(cuda_dir: str) -> Version: | |||||||
| ext_modules = [] | ||||||||
|
|
||||||||
| if HAS_SM80 or HAS_SM86 or HAS_SM89 or HAS_SM90 or HAS_SM120: | ||||||||
| qattn_extension = CUDAExtension( | ||||||||
| sm80_sources = [ | ||||||||
| "csrc/qattn/pybind_sm80.cpp", | ||||||||
| "csrc/qattn/qk_int_sv_f16_cuda_sm80.cu", | ||||||||
| ] | ||||||||
|
|
||||||||
| qattn_extension_sm80 = CUDAExtension( | ||||||||
| name="sageattention._qattn_sm80", | ||||||||
| sources=[ | ||||||||
| "csrc/qattn/pybind_sm80.cpp", | ||||||||
| "csrc/qattn/qk_int_sv_f16_cuda_sm80.cu", | ||||||||
| ], | ||||||||
| sources=sm80_sources, | ||||||||
| extra_compile_args={ | ||||||||
| "cxx": CXX_FLAGS, | ||||||||
| "nvcc": NVCC_FLAGS, | ||||||||
| }, | ||||||||
| ) | ||||||||
| ext_modules.append(qattn_extension) | ||||||||
| ext_modules.append(qattn_extension_sm80) | ||||||||
|
|
||||||||
| if HAS_SM89 or HAS_SM120: | ||||||||
| qattn_extension = CUDAExtension( | ||||||||
| sm89_sources = [ | ||||||||
| "csrc/qattn/pybind_sm89.cpp", | ||||||||
| "csrc/qattn/sm89_qk_int8_sv_f8_accum_f32_attn_inst_buf.cu", | ||||||||
| "csrc/qattn/sm89_qk_int8_sv_f8_accum_f16_attn_inst_buf.cu", | ||||||||
| "csrc/qattn/sm89_qk_int8_sv_f8_accum_f32_attn.cu", | ||||||||
| "csrc/qattn/sm89_qk_int8_sv_f8_accum_f32_fuse_v_scale_fuse_v_mean_attn.cu", | ||||||||
| "csrc/qattn/sm89_qk_int8_sv_f8_accum_f32_fuse_v_scale_attn.cu", | ||||||||
| "csrc/qattn/sm89_qk_int8_sv_f8_accum_f32_fuse_v_scale_attn_inst_buf.cu", | ||||||||
| "csrc/qattn/sm89_qk_int8_sv_f8_accum_f16_fuse_v_scale_attn_inst_buf.cu" | ||||||||
| #"csrc/qattn/qk_int_sv_f8_cuda_sm89.cu", | ||||||||
| ] | ||||||||
|
|
||||||||
| arch_substrings = ["sm_89", "compute_89", "sm_90a", "compute_90a", "sm_120", "compute_120"] | ||||||||
| filtered_flags = filter_nvcc_flags_for_arch(NVCC_FLAGS, arch_substrings) | ||||||||
|
|
||||||||
|
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. The flag filtering logic is duplicated between sm89 and sm90 extensions. Consider extracting this into a helper function to reduce code duplication and improve maintainability.
Suggested change
Copilot uses AI. Check for mistakes. Positive FeedbackNegative Feedback |
||||||||
| qattn_extension_sm89 = CUDAExtension( | ||||||||
| name="sageattention._qattn_sm89", | ||||||||
| sources=[ | ||||||||
| "csrc/qattn/pybind_sm89.cpp", | ||||||||
| "csrc/qattn/sm89_qk_int8_sv_f8_accum_f32_attn_inst_buf.cu", | ||||||||
| "csrc/qattn/sm89_qk_int8_sv_f8_accum_f16_attn_inst_buf.cu", | ||||||||
| "csrc/qattn/sm89_qk_int8_sv_f8_accum_f32_attn.cu", | ||||||||
| "csrc/qattn/sm89_qk_int8_sv_f8_accum_f32_fuse_v_scale_fuse_v_mean_attn.cu", | ||||||||
| "csrc/qattn/sm89_qk_int8_sv_f8_accum_f32_fuse_v_scale_attn.cu", | ||||||||
| "csrc/qattn/sm89_qk_int8_sv_f8_accum_f32_fuse_v_scale_attn_inst_buf.cu", | ||||||||
| "csrc/qattn/sm89_qk_int8_sv_f8_accum_f16_fuse_v_scale_attn_inst_buf.cu" | ||||||||
| #"csrc/qattn/qk_int_sv_f8_cuda_sm89.cu", | ||||||||
| ], | ||||||||
| sources=sm89_sources, | ||||||||
| extra_compile_args={ | ||||||||
| "cxx": CXX_FLAGS, | ||||||||
| "nvcc": NVCC_FLAGS, | ||||||||
| "nvcc": filtered_flags if filtered_flags else NVCC_FLAGS, | ||||||||
| }, | ||||||||
| ) | ||||||||
| ext_modules.append(qattn_extension) | ||||||||
| ext_modules.append(qattn_extension_sm89) | ||||||||
|
|
||||||||
| if HAS_SM90: | ||||||||
| qattn_extension = CUDAExtension( | ||||||||
| sm90_sources = [ | ||||||||
| "csrc/qattn/pybind_sm90.cpp", | ||||||||
| "csrc/qattn/qk_int_sv_f8_cuda_sm90.cu", | ||||||||
| ] | ||||||||
|
|
||||||||
| arch_substrings = ["sm_90a", "compute_90a"] | ||||||||
| filtered_flags = filter_nvcc_flags_for_arch(NVCC_FLAGS, arch_substrings) | ||||||||
|
|
||||||||
| qattn_extension_sm90 = CUDAExtension( | ||||||||
| name="sageattention._qattn_sm90", | ||||||||
| sources=[ | ||||||||
| "csrc/qattn/pybind_sm90.cpp", | ||||||||
| "csrc/qattn/qk_int_sv_f8_cuda_sm90.cu", | ||||||||
| ], | ||||||||
| sources=sm90_sources, | ||||||||
| extra_compile_args={ | ||||||||
| "cxx": CXX_FLAGS, | ||||||||
| "nvcc": NVCC_FLAGS, | ||||||||
| "nvcc": filtered_flags if filtered_flags else NVCC_FLAGS, | ||||||||
| }, | ||||||||
| extra_link_args=['-lcuda'], | ||||||||
| ) | ||||||||
| ext_modules.append(qattn_extension) | ||||||||
| ext_modules.append(qattn_extension_sm90) | ||||||||
|
|
||||||||
| # Fused kernels. | ||||||||
| fused_extension = CUDAExtension( | ||||||||
|
|
@@ -208,24 +254,32 @@ def compile_new(*args, **kwargs): | |||||||
| **kwargs, | ||||||||
| "output_dir": os.path.join( | ||||||||
| kwargs["output_dir"], | ||||||||
| self.thread_ext_name_map[threading.current_thread().ident]), | ||||||||
| self.thread_ext_name_map.get(threading.current_thread().ident, f"thread_{threading.current_thread().ident}")), | ||||||||
| }) | ||||||||
| self.compiler.compile = compile_new | ||||||||
| self.compiler._compile_separate_output_dir = True | ||||||||
| self.thread_ext_name_map[threading.current_thread().ident] = ext.name | ||||||||
| objects = super().build_extension(ext) | ||||||||
| return objects | ||||||||
|
|
||||||||
| original_build_temp = self.build_temp | ||||||||
| self.build_temp = os.path.join(original_build_temp, ext.name.replace(".", "_")) | ||||||||
| os.makedirs(self.build_temp, exist_ok=True) | ||||||||
|
|
||||||||
| try: | ||||||||
| objects = super().build_extension(ext) | ||||||||
| finally: | ||||||||
| self.build_temp = original_build_temp | ||||||||
|
|
||||||||
| return objects | ||||||||
|
|
||||||||
| setup( | ||||||||
| name='sageattention', | ||||||||
| version='2.2.0', | ||||||||
| name='sageattention', | ||||||||
| version='2.2.0', | ||||||||
| author='SageAttention team', | ||||||||
| license='Apache 2.0 License', | ||||||||
| description='Accurate and efficient plug-and-play low-bit attention.', | ||||||||
| long_description=open('README.md', encoding='utf-8').read(), | ||||||||
| long_description_content_type='text/markdown', | ||||||||
| url='https://github.com/thu-ml/SageAttention', | ||||||||
| license='Apache 2.0 License', | ||||||||
| description='Accurate and efficient plug-and-play low-bit attention.', | ||||||||
| long_description=open('README.md', encoding='utf-8').read(), | ||||||||
| long_description_content_type='text/markdown', | ||||||||
| url='https://github.com/thu-ml/SageAttention', | ||||||||
| packages=find_packages(), | ||||||||
| python_requires='>=3.9', | ||||||||
| ext_modules=ext_modules, | ||||||||
|
|
||||||||
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The code doesn't validate that each architecture value is a valid decimal format as mentioned in the PR description. Consider adding validation to ensure each arch value matches the expected pattern (e.g., regex check for decimal format).
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