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tensorflow/third_party/mkl_dnn/mkldnn_v1.BUILD
Yimei Sun bd213ccfc8 PR #15491: [XLA:CPU][oneDNN] Enable oneDNN Graph build 
Imported from GitHub PR https://github.com/openxla/xla/pull/15491

This PR enables oneDNN Graph functionality in oneDNN library which is a prep work for supporting fusions such as MHA via oneDNN graph.
Copybara import of the project:

--
06aed953869b5a91f9d2618d5d36eee372a9a18a by Yimei Sun <yimei.sun@intel.com>:

[XLA:CPU][oneDNN] Enable oneDNN Graph build
This PR enables oneDNN Graph functionality in oneDNN library which is a prep work for supporting fusions
such as MHA via oneDNN graph.

Merging this change closes #15491

PiperOrigin-RevId: 659891498
2024-08-06 05:00:37 -07:00

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load("@bazel_skylib//rules:expand_template.bzl", "expand_template")
load("@local_xla//xla/tsl:tsl.bzl", "tf_openmp_copts")
load("@local_xla//xla/tsl/mkl:build_defs.bzl", "if_mkl", "if_mkl_ml", "if_mkldnn_openmp")
exports_files(["LICENSE"])
_CMAKE_COMMON_LIST = {
"#cmakedefine DNNL_GPU_RUNTIME DNNL_RUNTIME_${DNNL_GPU_RUNTIME}": "#define DNNL_GPU_RUNTIME DNNL_RUNTIME_NONE",
"#cmakedefine DNNL_USE_RT_OBJECTS_IN_PRIMITIVE_CACHE": "#undef DNNL_USE_RT_OBJECTS_IN_PRIMITIVE_CACHE",
"#cmakedefine DNNL_WITH_SYCL": "#undef DNNL_WITH_SYCL",
"#cmakedefine DNNL_WITH_LEVEL_ZERO": "#undef DNNL_WITH_LEVEL_ZERO",
"#cmakedefine DNNL_SYCL_CUDA": "#undef DNNL_SYCL_CUDA",
"#cmakedefine DNNL_SYCL_HIP": "#undef DNNL_SYCL_HIP",
"#cmakedefine DNNL_ENABLE_STACK_CHECKER": "#undef DNNL_ENABLE_STACK_CHECKER",
"#cmakedefine ONEDNN_BUILD_GRAPH": "#define ONEDNN_BUILD_GRAPH",
"#cmakedefine DNNL_EXPERIMENTAL_SPARSE": "#define DNNL_EXPERIMENTAL_SPARSE",
"#cmakedefine DNNL_EXPERIMENTAL": "#undef DNNL_EXPERIMENTAL",
"#cmakedefine01 BUILD_TRAINING": "#define BUILD_TRAINING 1",
"#cmakedefine01 BUILD_INFERENCE": "#define BUILD_INFERENCE 0",
"#cmakedefine01 BUILD_PRIMITIVE_ALL": "#define BUILD_PRIMITIVE_ALL 1",
"#cmakedefine01 BUILD_BATCH_NORMALIZATION": "#define BUILD_BATCH_NORMALIZATION 0",
"#cmakedefine01 BUILD_BINARY": "#define BUILD_BINARY 0",
"#cmakedefine01 BUILD_CONCAT": "#define BUILD_CONCAT 0",
"#cmakedefine01 BUILD_CONVOLUTION": "#define BUILD_CONVOLUTION 0",
"#cmakedefine01 BUILD_DECONVOLUTION": "#define BUILD_DECONVOLUTION 0",
"#cmakedefine01 BUILD_ELTWISE": "#define BUILD_ELTWISE 0",
"#cmakedefine01 BUILD_GEMM_KERNELS_ALL": "#define BUILD_GEMM_KERNELS_ALL 1",
"#cmakedefine01 BUILD_GEMM_KERNELS_NONE": "#define BUILD_GEMM_KERNELS_NONE 0",
"#cmakedefine01 BUILD_GEMM_SSE41": "#define BUILD_GEMM_SSE41 1",
"#cmakedefine01 BUILD_GEMM_AVX2": "#define BUILD_GEMM_AVX2 1",
"#cmakedefine01 BUILD_GEMM_AVX512": "#define BUILD_GEMM_AVX512 1",
"#cmakedefine01 BUILD_GROUP_NORMALIZATION": "#define BUILD_GROUP_NORMALIZATION 1",
"#cmakedefine01 BUILD_INNER_PRODUCT": "#define BUILD_INNER_PRODUCT 0",
"#cmakedefine01 BUILD_LAYER_NORMALIZATION": "#define BUILD_LAYER_NORMALIZATION 0",
"#cmakedefine01 BUILD_LRN": "#define BUILD_LRN 0",
"#cmakedefine01 BUILD_MATMUL": "#define BUILD_MATMUL 0",
"#cmakedefine01 BUILD_POOLING": "#define BUILD_POOLING 0",
"#cmakedefine01 BUILD_PRELU": "#define BUILD_PRELU 0",
"#cmakedefine01 BUILD_REDUCTION": "#define BUILD_REDUCTION 0",
"#cmakedefine01 BUILD_REORDER": "#define BUILD_REORDER 0",
"#cmakedefine01 BUILD_RESAMPLING": "#define BUILD_RESAMPLING 0",
"#cmakedefine01 BUILD_RNN": "#define BUILD_RNN 0",
"#cmakedefine01 BUILD_SHUFFLE": "#define BUILD_SHUFFLE 0",
"#cmakedefine01 BUILD_SOFTMAX": "#define BUILD_SOFTMAX 0",
"#cmakedefine01 BUILD_SUM": "#define BUILD_SUM 0",
"#cmakedefine01 BUILD_PRIMITIVE_CPU_ISA_ALL": "#define BUILD_PRIMITIVE_CPU_ISA_ALL 1",
"#cmakedefine01 BUILD_SSE41": "#define BUILD_SSE41 0",
"#cmakedefine01 BUILD_AVX2": "#define BUILD_AVX2 0",
"#cmakedefine01 BUILD_AVX512": "#define BUILD_AVX512 0",
"#cmakedefine01 BUILD_AMX": "#define BUILD_AMX 0",
"#cmakedefine01 BUILD_PRIMITIVE_GPU_ISA_ALL": "#define BUILD_PRIMITIVE_GPU_ISA_ALL 0",
"#cmakedefine01 BUILD_GEN9": "#define BUILD_GEN9 0",
"#cmakedefine01 BUILD_GEN11": "#define BUILD_GEN11 0",
"#cmakedefine01 BUILD_XE2": "#define BUILD_XE2 0",
"#cmakedefine01 BUILD_XELP": "#define BUILD_XELP 0",
"#cmakedefine01 BUILD_XEHPG": "#define BUILD_XEHPG 0",
"#cmakedefine01 BUILD_XEHPC": "#define BUILD_XEHPC 0",
"#cmakedefine01 BUILD_XEHP": "#define BUILD_XEHP 0",
}
_DNNL_RUNTIME_OMP = {
"#cmakedefine DNNL_CPU_THREADING_RUNTIME DNNL_RUNTIME_${DNNL_CPU_THREADING_RUNTIME}": "#define DNNL_CPU_THREADING_RUNTIME DNNL_RUNTIME_OMP",
"#cmakedefine DNNL_CPU_RUNTIME DNNL_RUNTIME_${DNNL_CPU_RUNTIME}": "#define DNNL_CPU_RUNTIME DNNL_RUNTIME_OMP",
}
_DNNL_RUNTIME_OMP.update(_CMAKE_COMMON_LIST)
_DNNL_RUNTIME_THREADPOOL = {
"#cmakedefine DNNL_CPU_THREADING_RUNTIME DNNL_RUNTIME_${DNNL_CPU_THREADING_RUNTIME}": "#define DNNL_CPU_THREADING_RUNTIME DNNL_RUNTIME_THREADPOOL",
"#cmakedefine DNNL_CPU_RUNTIME DNNL_RUNTIME_${DNNL_CPU_RUNTIME}": "#define DNNL_CPU_RUNTIME DNNL_RUNTIME_THREADPOOL",
}
_DNNL_RUNTIME_THREADPOOL.update(_CMAKE_COMMON_LIST)
expand_template(
name = "dnnl_config_h",
out = "include/oneapi/dnnl/dnnl_config.h",
substitutions = select({
"@local_xla//xla/tsl/mkl:build_with_mkldnn_openmp": _DNNL_RUNTIME_OMP,
"//conditions:default": _DNNL_RUNTIME_THREADPOOL,
}),
template = "include/oneapi/dnnl/dnnl_config.h.in",
)
# Create the file dnnl_version.h with DNNL version numbers.
# Currently, the version numbers are hard coded here. If DNNL is upgraded then
# the version numbers have to be updated manually. The version numbers can be
# obtained from the PROJECT_VERSION settings in CMakeLists.txt. The variable is
# set to "version_major.version_minor.version_patch". The git hash version can
# be set to NA.
# TODO(agramesh1): Automatically get the version numbers from CMakeLists.txt.
expand_template(
name = "dnnl_version_h",
out = "include/oneapi/dnnl/dnnl_version.h",
substitutions = {
"@DNNL_VERSION_MAJOR@": "3",
"@DNNL_VERSION_MINOR@": "5",
"@DNNL_VERSION_PATCH@": "0",
"@DNNL_VERSION_HASH@": "N/A",
},
template = "include/oneapi/dnnl/dnnl_version.h.in",
)
_COPTS_LIST = select({
"@local_xla//xla/tsl:windows": [],
"//conditions:default": ["-fexceptions"],
}) + [
"-UUSE_MKL",
"-UUSE_CBLAS",
"-DDNNL_ENABLE_MAX_CPU_ISA",
"-DDNNL_ENABLE_ITT_TASKS",
"-DDNNL_ENABLE_GRAPH_DUMP",
] + tf_openmp_copts()
_INCLUDES_LIST = [
"include",
"src",
"src/common",
"src/common/ittnotify",
"src/cpu",
"src/cpu/gemm",
"src/cpu/x64/xbyak",
"src/graph",
]
_TEXTUAL_HDRS_LIST = glob([
"include/**/*",
"src/common/*.hpp",
"src/common/ittnotify/**/*.h",
"src/cpu/*.hpp",
"src/cpu/**/*.hpp",
"src/cpu/jit_utils/**/*.hpp",
"src/cpu/x64/xbyak/*.h",
"src/graph/interface/*.hpp",
"src/graph/backend/*.hpp",
"src/graph/backend/dnnl/*.hpp",
"src/graph/backend/fake/*.hpp",
"src/graph/backend/dnnl/passes/*.hpp",
"src/graph/backend/dnnl/patterns/*.hpp",
"src/graph/backend/dnnl/kernels/*.hpp",
"src/graph/utils/*.hpp",
"src/graph/utils/pm/*.hpp",
]) + [
":dnnl_config_h",
":dnnl_version_h",
]
# Large autogen files take too long time to compile with usual optimization
# flags. These files just generate binary kernels and are not the hot spots,
# so we factor them out to lower compiler optimizations in ":dnnl_autogen".
# Using -O1 to enable optimizations to reduce stack consumption. (With -O0,
# compiler doesn't clean up stack from temporary objects.)
cc_library(
name = "onednn_autogen",
srcs = glob(["src/cpu/x64/gemm/**/*_kern_autogen*.cpp"]),
copts = [
"-O1",
"-U_FORTIFY_SOURCE",
] + _COPTS_LIST,
includes = _INCLUDES_LIST,
textual_hdrs = _TEXTUAL_HDRS_LIST,
visibility = ["//visibility:public"],
)
cc_library(
name = "mkl_dnn",
srcs = glob(
[
"src/common/*.cpp",
"src/cpu/*.cpp",
"src/cpu/**/*.cpp",
"src/common/ittnotify/*.c",
"src/cpu/jit_utils/**/*.cpp",
"src/cpu/x64/**/*.cpp",
"src/graph/interface/*.cpp",
"src/graph/backend/*.cpp",
"src/graph/backend/dnnl/*.cpp",
"src/graph/backend/fake/*.cpp",
"src/graph/backend/dnnl/passes/*.cpp",
"src/graph/backend/dnnl/patterns/*.cpp",
"src/graph/backend/dnnl/kernels/*.cpp",
"src/graph/utils/*.cpp",
"src/graph/utils/pm/*.cpp",
],
exclude = [
"src/cpu/aarch64/**",
"src/cpu/rv64/**",
"src/cpu/x64/gemm/**/*_kern_autogen.cpp",
],
),
copts = _COPTS_LIST,
includes = _INCLUDES_LIST,
# TODO(penpornk): Use lrt_if_needed from tensorflow.bzl instead.
linkopts = select({
"@local_xla//xla/tsl:linux_aarch64": ["-lrt"],
"@local_xla//xla/tsl:linux_x86_64": ["-lrt"],
"@local_xla//xla/tsl:linux_ppc64le": ["-lrt"],
"//conditions:default": [],
}),
textual_hdrs = _TEXTUAL_HDRS_LIST,
visibility = ["//visibility:public"],
deps = [":onednn_autogen"] + if_mkl_ml(
["@local_xla//xla/tsl/mkl:intel_binary_blob"],
[],
),
)
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