kse-01/tensorflow/third_party/toolchains/preconfig/generate/generate.bzl
github-classroom[bot] 1122cdd8b0
Initial commit
2023-10-09 11:37:31 +00:00

83 lines
3.2 KiB (Stored with Git LFS)
Python

load(
"@bazel_toolchains//rules:docker_config.bzl",
"docker_toolchain_autoconfig",
)
def _tensorflow_rbe_config(name, compiler, python_version, os, rocm_version = None, cuda_version = None, cudnn_version = None, tensorrt_version = None, tensorrt_install_path = None, cudnn_install_path = None, compiler_prefix = None, build_bazel_src = False, sysroot = None):
base = "@%s//image" % os
config_repos = [
"local_config_python",
"local_config_cc",
]
env = {
"ABI_VERSION": "gcc",
"ABI_LIBC_VERSION": "glibc_2.19",
"BAZEL_COMPILER": compiler,
"BAZEL_HOST_SYSTEM": "i686-unknown-linux-gnu",
"BAZEL_TARGET_LIBC": "glibc_2.19",
"BAZEL_TARGET_CPU": "k8",
"BAZEL_TARGET_SYSTEM": "x86_64-unknown-linux-gnu",
"CC_TOOLCHAIN_NAME": "linux_gnu_x86",
"CC": compiler,
"PYTHON_BIN_PATH": "/usr/bin/python%s" % python_version,
"CLEAR_CACHE": "1",
"HOST_CXX_COMPILER": compiler,
"HOST_C_COMPILER": compiler,
}
if cuda_version != None and rocm_version != None:
fail("Specifying both cuda_version and rocm_version is not supported.")
if cuda_version != None:
base = "@cuda%s-cudnn%s-%s//image" % (cuda_version, cudnn_version, os)
# The cuda toolchain currently contains its own C++ toolchain definition,
# so we do not fetch local_config_cc.
config_repos = [
"local_config_python",
"local_config_cuda",
"local_config_tensorrt",
]
env.update({
"TF_NEED_CUDA": "1",
"TF_CUDA_CLANG": "1" if compiler.endswith("clang") else "0",
"TF_CUDA_COMPUTE_CAPABILITIES": "3.5,6.0",
"TF_ENABLE_XLA": "1",
"TF_CUDNN_VERSION": cudnn_version,
"TF_CUDA_VERSION": cuda_version,
"CUDNN_INSTALL_PATH": cudnn_install_path if cudnn_install_path != None else "/usr/lib/x86_64-linux-gnu",
"TF_NEED_TENSORRT": "1",
"TF_TENSORRT_VERSION": tensorrt_version,
"TENSORRT_INSTALL_PATH": tensorrt_install_path if tensorrt_install_path != None else "/usr/lib/x86_64-linux-gnu",
"GCC_HOST_COMPILER_PATH": compiler if not compiler.endswith("clang") else "",
"GCC_HOST_COMPILER_PREFIX": compiler_prefix if compiler_prefix != None else "/usr/bin",
"CLANG_CUDA_COMPILER_PATH": compiler if compiler.endswith("clang") else "",
"TF_SYSROOT": sysroot if sysroot else "",
})
if rocm_version != None:
base = "@rocm-%s//image" % (os)
# The rocm toolchain currently contains its own C++ toolchain definition,
# so we do not fetch local_config_cc.
config_repos = [
"local_config_python",
"local_config_rocm",
]
env.update({
"TF_NEED_ROCM": "1",
"TF_ENABLE_XLA": "0",
})
docker_toolchain_autoconfig(
name = name,
base = base,
bazel_version = "1.2.1",
build_bazel_src = build_bazel_src,
config_repos = config_repos,
env = env,
mount_project = "$(mount_project)",
tags = ["manual"],
)
tensorflow_rbe_config = _tensorflow_rbe_config