85 lines
2.9 KiB
Python
85 lines
2.9 KiB
Python
def get_blas_gomp_arch_deps():
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return [
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("x86_64", [
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"third-party//IntelComposerXE:{}".format(native.read_config("fbcode", "mkl_lp64", "mkl_lp64_omp")),
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]),
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("aarch64", [
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"third-party//OpenBLAS:OpenBLAS",
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"third-party//openmp:omp",
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]),
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]
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default_compiler_flags = [
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"-Wall",
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"-Wextra",
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"-Wno-unused-function",
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"-Wno-unused-parameter",
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"-Wno-error=strict-aliasing",
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"-Wno-shadow-compatible-local",
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"-Wno-maybe-uninitialized", # aten is built with gcc as part of HHVM
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"-Wno-unknown-pragmas",
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"-Wno-strict-overflow",
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# See https://fb.facebook.com/groups/fbcode/permalink/1813348245368673/
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# These trigger on platform007
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"-Wno-stringop-overflow",
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"-Wno-class-memaccess",
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"-DHAVE_MMAP",
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"-DUSE_GCC_ATOMICS=1",
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"-D_FILE_OFFSET_BITS=64",
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"-DHAVE_SHM_OPEN=1",
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"-DHAVE_SHM_UNLINK=1",
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"-DHAVE_MALLOC_USABLE_SIZE=1",
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"-DTH_HAVE_THREAD",
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"-DCPU_CAPABILITY_DEFAULT",
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"-DTH_INDEX_BASE=0",
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"-DMAGMA_V2",
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"-DNO_CUDNN_DESTROY_HANDLE",
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"-DUSE_EXPERIMENTAL_CUDNN_V8_API", # enable cudnn v8 api
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"-DUSE_FBGEMM",
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"-DUSE_QNNPACK",
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"-DUSE_PYTORCH_QNNPACK",
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# The dynamically loaded NVRTC trick doesn't work in fbcode,
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# and it's not necessary anyway, because we have a stub
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# nvrtc library which we load canonically anyway
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"-DUSE_DIRECT_NVRTC",
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"-DUSE_RUY_QMATMUL",
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] + select({
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# XNNPACK depends on an updated version of pthreadpool interface, whose implementation
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# includes <pthread.h> - a header not available on Windows.
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"DEFAULT": ["-DUSE_XNNPACK"],
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"ovr_config//os:windows": [],
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}) + (["-O1"] if native.read_config("fbcode", "build_mode_test_label", "") == "dev-nosan" else [])
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compiler_specific_flags = {
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"clang": [
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"-Wno-absolute-value",
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"-Wno-pass-failed",
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"-Wno-braced-scalar-init",
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],
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"gcc": [
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"-Wno-error=array-bounds",
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],
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}
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def get_cpu_parallel_backend_flags():
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parallel_backend = native.read_config("pytorch", "parallel_backend", "openmp")
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defs = []
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if parallel_backend == "openmp":
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defs.append("-DAT_PARALLEL_OPENMP_FBCODE=1")
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elif parallel_backend == "tbb":
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defs.append("-DAT_PARALLEL_NATIVE_TBB_FBCODE=1")
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elif parallel_backend == "native":
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defs.append("-DAT_PARALLEL_NATIVE_FBCODE=1")
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else:
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fail("Unsupported parallel backend: " + parallel_backend)
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if native.read_config("pytorch", "exp_single_thread_pool", "0") == "1":
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defs.append("-DAT_EXPERIMENTAL_SINGLE_THREAD_POOL=1")
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mkl_ver = native.read_config("fbcode", "mkl_lp64", "mkl_lp64_omp")
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if mkl_ver == "mkl_lp64_seq":
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defs.append("-DATEN_MKL_SEQUENTIAL_FBCODE=1")
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return defs
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def is_cpu_static_dispatch_build():
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mode = native.read_config("fbcode", "caffe2_static_dispatch_mode", "none")
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return mode == "cpu"
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