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