path: root/third_party/gpus/cuda_configure.bzl

# -*- Python -*-
"""Repository rule for CUDA autoconfiguration.

`cuda_configure` depends on the following environment variables:

  * `TF_NEED_CUDA`: Whether to enable building with CUDA.
  * `GCC_HOST_COMPILER_PATH`: The GCC host compiler path
  * `TF_CUDA_CLANG`: Whether to use clang as a cuda compiler.
  * `CLANG_CUDA_COMPILER_PATH`: The clang compiler path that will be used for
    both host and device code compilation if TF_CUDA_CLANG is 1.
  * `TF_DOWNLOAD_CLANG`: Whether to download a recent release of clang
    compiler and use it to build tensorflow. When this option is set
    CLANG_CUDA_COMPILER_PATH is ignored.
  * `CUDA_TOOLKIT_PATH`: The path to the CUDA toolkit. Default is
    `/usr/local/cuda`.
  * `TF_CUDA_VERSION`: The version of the CUDA toolkit. If this is blank, then
    use the system default.
  * `TF_CUDNN_VERSION`: The version of the cuDNN library.
  * `CUDNN_INSTALL_PATH`: The path to the cuDNN library. Default is
    `/usr/local/cuda`.
  * `TF_CUDA_COMPUTE_CAPABILITIES`: The CUDA compute capabilities. Default is
    `3.5,5.2`.
  * `PYTHON_BIN_PATH`: The python binary path
"""

_GCC_HOST_COMPILER_PATH = "GCC_HOST_COMPILER_PATH"
_CLANG_CUDA_COMPILER_PATH = "CLANG_CUDA_COMPILER_PATH"
_CUDA_TOOLKIT_PATH = "CUDA_TOOLKIT_PATH"
_TF_CUDA_VERSION = "TF_CUDA_VERSION"
_TF_CUDNN_VERSION = "TF_CUDNN_VERSION"
_CUDNN_INSTALL_PATH = "CUDNN_INSTALL_PATH"
_TF_CUDA_COMPUTE_CAPABILITIES = "TF_CUDA_COMPUTE_CAPABILITIES"
_TF_CUDA_CONFIG_REPO = "TF_CUDA_CONFIG_REPO"
_TF_DOWNLOAD_CLANG = "TF_DOWNLOAD_CLANG"
_PYTHON_BIN_PATH = "PYTHON_BIN_PATH"

_DEFAULT_CUDA_VERSION = ""
_DEFAULT_CUDNN_VERSION = ""
_DEFAULT_CUDA_TOOLKIT_PATH = "/usr/local/cuda"
_DEFAULT_CUDNN_INSTALL_PATH = "/usr/local/cuda"
_DEFAULT_CUDA_COMPUTE_CAPABILITIES = ["3.5", "5.2"]

# Lookup paths for CUDA / cuDNN libraries, relative to the install directories.
#
# Paths will be tried out in the order listed below. The first successful path
# will be used. For example, when looking for the cudart libraries, the first
# attempt will be lib64/cudart inside the CUDA toolkit.
CUDA_LIB_PATHS = [
    "lib64/",
    "lib64/stubs/",
    "lib/powerpc64le-linux-gnu/",
    "lib/x86_64-linux-gnu/",
    "lib/x64/",
    "lib/",
    "",
]

# Lookup paths for cupti.h, relative to the CUDA toolkit directory.
#
# On most systems, the cupti library is not installed in the same directory as
# the other CUDA libraries but rather in a special extras/CUPTI directory.
CUPTI_HEADER_PATHS = [
    "extras/CUPTI/include/",
    "include/cuda/CUPTI/",
    "include/",
]

# Lookup paths for the cupti library, relative to the
#
# On most systems, the cupti library is not installed in the same directory as
# the other CUDA libraries but rather in a special extras/CUPTI directory.
CUPTI_LIB_PATHS = [
    "extras/CUPTI/lib64/",
    "lib/powerpc64le-linux-gnu/",
    "lib/x86_64-linux-gnu/",
    "lib64/",
    "extras/CUPTI/libx64/",
    "extras/CUPTI/lib/",
    "lib/",
]

# Lookup paths for CUDA headers (cuda.h) relative to the CUDA toolkit directory.
CUDA_INCLUDE_PATHS = [
    "include/",
    "include/cuda/",
]

# Lookup paths for cudnn.h relative to the CUDNN install directory.
CUDNN_INCLUDE_PATHS = [
    "",
    "include/",
    "include/cuda/",
]

# Lookup paths for NVVM libdevice relative to the CUDA directory toolkit.
#
# libdevice implements mathematical functions for GPU kernels, and is provided
# in NVVM bitcode (a subset of LLVM bitcode).
NVVM_LIBDEVICE_PATHS = [
    "nvvm/libdevice/",
    "share/cuda/",
    "lib/nvidia-cuda-toolkit/libdevice/",
]

# Files used to detect the NVVM libdevice path.
NVVM_LIBDEVICE_FILES = [
    # CUDA 9.0 has a single file.
    "libdevice.10.bc",

    # CUDA 8.0 has separate files for compute versions 2.0, 3.0, 3.5 and 5.0.
    # Probing for one of them is sufficient.
    "libdevice.compute_20.10.bc",
]

load("//third_party/clang_toolchain:download_clang.bzl", "download_clang")
load(
    "@bazel_tools//tools/cpp:lib_cc_configure.bzl",
    "escape_string",
    "get_env_var",
)
load(
    "@bazel_tools//tools/cpp:windows_cc_configure.bzl",
    "find_msvc_tool",
    "find_vc_path",
    "setup_vc_env_vars",
)

def _get_python_bin(repository_ctx):
    """Gets the python bin path."""
    python_bin = repository_ctx.os.environ.get(_PYTHON_BIN_PATH)
    if python_bin != None:
        return python_bin
    python_bin_name = "python.exe" if _is_windows(repository_ctx) else "python"
    python_bin_path = repository_ctx.which(python_bin_name)
    if python_bin_path != None:
        return str(python_bin_path)
    auto_configure_fail("Cannot find python in PATH, please make sure " +
                        "python is installed and add its directory in PATH, or --define " +
                        "%s='/something/else'.\nPATH=%s" % (
                            _PYTHON_BIN_PATH,
                            repository_ctx.os.environ.get("PATH", ""),
                        ))

def _get_nvcc_tmp_dir_for_windows(repository_ctx):
    """Return the tmp directory for nvcc to generate intermediate source files."""
    escaped_tmp_dir = escape_string(
        get_env_var(repository_ctx, "TMP", "C:\\Windows\\Temp").replace("\\", "\\\\"),
    )
    return escaped_tmp_dir + "\\\\nvcc_inter_files_tmp_dir"

def _get_msvc_compiler(repository_ctx):
    vc_path = find_vc_path(repository_ctx)
    return find_msvc_tool(repository_ctx, vc_path, "cl.exe").replace("\\", "/")

def _get_win_cuda_defines(repository_ctx):
    """Return CROSSTOOL defines for Windows"""

    # If we are not on Windows, return empty vaules for Windows specific fields.
    # This ensures the CROSSTOOL file parser is happy.
    if not _is_windows(repository_ctx):
        return {
            "%{msvc_env_tmp}": "",
            "%{msvc_env_path}": "",
            "%{msvc_env_include}": "",
            "%{msvc_env_lib}": "",
            "%{msvc_cl_path}": "",
            "%{msvc_ml_path}": "",
            "%{msvc_link_path}": "",
            "%{msvc_lib_path}": "",
            "%{cxx_builtin_include_directory}": "",
        }

    vc_path = find_vc_path(repository_ctx)
    if not vc_path:
        auto_configure_fail("Visual C++ build tools not found on your machine." +
                            "Please check your installation following https://docs.bazel.build/versions/master/windows.html#using")
        return {}

    env = setup_vc_env_vars(repository_ctx, vc_path)
    escaped_paths = escape_string(env["PATH"])
    escaped_include_paths = escape_string(env["INCLUDE"])
    escaped_lib_paths = escape_string(env["LIB"])
    escaped_tmp_dir = escape_string(
        get_env_var(repository_ctx, "TMP", "C:\\Windows\\Temp").replace("\\", "\\\\"),
    )

    msvc_cl_path = "windows/msvc_wrapper_for_nvcc.bat"
    msvc_ml_path = find_msvc_tool(repository_ctx, vc_path, "ml64.exe").replace("\\", "/")
    msvc_link_path = find_msvc_tool(repository_ctx, vc_path, "link.exe").replace("\\", "/")
    msvc_lib_path = find_msvc_tool(repository_ctx, vc_path, "lib.exe").replace("\\", "/")

    # nvcc will generate some temporary source files under %{nvcc_tmp_dir}
    # The generated files are guranteed to have unique name, so they can share the same tmp directory
    escaped_cxx_include_directories = ["cxx_builtin_include_directory: \"%s\"" % _get_nvcc_tmp_dir_for_windows(repository_ctx)]
    for path in escaped_include_paths.split(";"):
        if path:
            escaped_cxx_include_directories.append("cxx_builtin_include_directory: \"%s\"" % path)

    return {
        "%{msvc_env_tmp}": escaped_tmp_dir,
        "%{msvc_env_path}": escaped_paths,
        "%{msvc_env_include}": escaped_include_paths,
        "%{msvc_env_lib}": escaped_lib_paths,
        "%{msvc_cl_path}": msvc_cl_path,
        "%{msvc_ml_path}": msvc_ml_path,
        "%{msvc_link_path}": msvc_link_path,
        "%{msvc_lib_path}": msvc_lib_path,
        "%{cxx_builtin_include_directory}": "\n".join(escaped_cxx_include_directories),
    }

# TODO(dzc): Once these functions have been factored out of Bazel's
# cc_configure.bzl, load them from @bazel_tools instead.
# BEGIN cc_configure common functions.
def find_cc(repository_ctx):
    """Find the C++ compiler."""
    if _is_windows(repository_ctx):
        return _get_msvc_compiler(repository_ctx)

    if _use_cuda_clang(repository_ctx):
        target_cc_name = "clang"
        cc_path_envvar = _CLANG_CUDA_COMPILER_PATH
        if _flag_enabled(repository_ctx, _TF_DOWNLOAD_CLANG):
            return "extra_tools/bin/clang"
    else:
        target_cc_name = "gcc"
        cc_path_envvar = _GCC_HOST_COMPILER_PATH
    cc_name = target_cc_name

    if cc_path_envvar in repository_ctx.os.environ:
        cc_name_from_env = repository_ctx.os.environ[cc_path_envvar].strip()
        if cc_name_from_env:
            cc_name = cc_name_from_env
    if cc_name.startswith("/"):
        # Absolute path, maybe we should make this supported by our which function.
        return cc_name
    cc = repository_ctx.which(cc_name)
    if cc == None:
        fail(("Cannot find {}, either correct your path or set the {}" +
              " environment variable").format(target_cc_name, cc_path_envvar))
    return cc

_INC_DIR_MARKER_BEGIN = "#include <...>"

# OSX add " (framework directory)" at the end of line, strip it.
_OSX_FRAMEWORK_SUFFIX = " (framework directory)"
_OSX_FRAMEWORK_SUFFIX_LEN = len(_OSX_FRAMEWORK_SUFFIX)

def _cxx_inc_convert(path):
    """Convert path returned by cc -E xc++ in a complete path."""
    path = path.strip()
    if path.endswith(_OSX_FRAMEWORK_SUFFIX):
        path = path[:-_OSX_FRAMEWORK_SUFFIX_LEN].strip()
    return path

def _normalize_include_path(repository_ctx, path):
    """Normalizes include paths before writing them to the crosstool.

    If path points inside the 'crosstool' folder of the repository, a relative
    path is returned.
    If path points outside the 'crosstool' folder, an absolute path is returned.
    """
    path = str(repository_ctx.path(path))
    crosstool_folder = str(repository_ctx.path(".").get_child("crosstool"))

    if path.startswith(crosstool_folder):
        # We drop the path to "$REPO/crosstool" and a trailing path separator.
        return path[len(crosstool_folder) + 1:]
    return path

def _get_cxx_inc_directories_impl(repository_ctx, cc, lang_is_cpp):
    """Compute the list of default C or C++ include directories."""
    if lang_is_cpp:
        lang = "c++"
    else:
        lang = "c"
    result = repository_ctx.execute([cc, "-E", "-x" + lang, "-", "-v"])
    index1 = result.stderr.find(_INC_DIR_MARKER_BEGIN)
    if index1 == -1:
        return []
    index1 = result.stderr.find("\n", index1)
    if index1 == -1:
        return []
    index2 = result.stderr.rfind("\n ")
    if index2 == -1 or index2 < index1:
        return []
    index2 = result.stderr.find("\n", index2 + 1)
    if index2 == -1:
        inc_dirs = result.stderr[index1 + 1:]
    else:
        inc_dirs = result.stderr[index1 + 1:index2].strip()

    return [
        _normalize_include_path(repository_ctx, _cxx_inc_convert(p))
        for p in inc_dirs.split("\n")
    ]

def get_cxx_inc_directories(repository_ctx, cc):
    """Compute the list of default C and C++ include directories."""

    # For some reason `clang -xc` sometimes returns include paths that are
    # different from the ones from `clang -xc++`. (Symlink and a dir)
    # So we run the compiler with both `-xc` and `-xc++` and merge resulting lists
    includes_cpp = _get_cxx_inc_directories_impl(repository_ctx, cc, True)
    includes_c = _get_cxx_inc_directories_impl(repository_ctx, cc, False)

    includes_cpp_set = depset(includes_cpp)
    return includes_cpp + [
        inc
        for inc in includes_c
        if inc not in includes_cpp_set
    ]

def auto_configure_fail(msg):
    """Output failure message when cuda configuration fails."""
    red = "\033[0;31m"
    no_color = "\033[0m"
    fail("\n%sCuda Configuration Error:%s %s\n" % (red, no_color, msg))

# END cc_configure common functions (see TODO above).

def _host_compiler_includes(repository_ctx, cc):
    """Generates the cxx_builtin_include_directory entries for gcc inc dirs.

    Args:
      repository_ctx: The repository context.
      cc: The path to the gcc host compiler.

    Returns:
      A string containing the cxx_builtin_include_directory for each of the gcc
      host compiler include directories, which can be added to the CROSSTOOL
      file.
    """
    inc_dirs = get_cxx_inc_directories(repository_ctx, cc)
    inc_entries = []
    for inc_dir in inc_dirs:
        inc_entries.append("  cxx_builtin_include_directory: \"%s\"" % inc_dir)
    return "\n".join(inc_entries)

def _cuda_include_path(repository_ctx, cuda_config):
    """Generates the cxx_builtin_include_directory entries for cuda inc dirs.

    Args:
      repository_ctx: The repository context.
      cc: The path to the gcc host compiler.

    Returns:
      A string containing the cxx_builtin_include_directory for each of the gcc
      host compiler include directories, which can be added to the CROSSTOOL
      file.
    """
    nvcc_path = repository_ctx.path("%s/bin/nvcc%s" %
                                    (
                                        cuda_config.cuda_toolkit_path,
                                        ".exe" if cuda_config.cpu_value == "Windows" else "",
                                    ))
    result = repository_ctx.execute([
        nvcc_path,
        "-v",
        "/dev/null",
        "-o",
        "/dev/null",
    ])
    target_dir = ""
    for one_line in result.stderr.splitlines():
        if one_line.startswith("#$ _TARGET_DIR_="):
            target_dir = (cuda_config.cuda_toolkit_path + "/" +
                          one_line.replace("#$ _TARGET_DIR_=", "") + "/include")
    inc_entries = []
    if target_dir != "":
        inc_entries.append("  cxx_builtin_include_directory: \"%s\"" % target_dir)
    default_include = cuda_config.cuda_toolkit_path + "/include"
    inc_entries.append("  cxx_builtin_include_directory: \"%s\"" %
                       default_include)
    return "\n".join(inc_entries)

def _enable_cuda(repository_ctx):
    if "TF_NEED_CUDA" in repository_ctx.os.environ:
        enable_cuda = repository_ctx.os.environ["TF_NEED_CUDA"].strip()
        return enable_cuda == "1"
    return False

def _cuda_toolkit_path(repository_ctx):
    """Finds the cuda toolkit directory.

    Args:
      repository_ctx: The repository context.

    Returns:
      A speculative real path of the cuda toolkit install directory.
    """
    cuda_toolkit_path = _DEFAULT_CUDA_TOOLKIT_PATH
    if _CUDA_TOOLKIT_PATH in repository_ctx.os.environ:
        cuda_toolkit_path = repository_ctx.os.environ[_CUDA_TOOLKIT_PATH].strip()
    if not repository_ctx.path(cuda_toolkit_path).exists:
        auto_configure_fail("Cannot find cuda toolkit path.")
    return str(repository_ctx.path(cuda_toolkit_path).realpath)

def _cudnn_install_basedir(repository_ctx):
    """Finds the cudnn install directory."""
    cudnn_install_path = _DEFAULT_CUDNN_INSTALL_PATH
    if _CUDNN_INSTALL_PATH in repository_ctx.os.environ:
        cudnn_install_path = repository_ctx.os.environ[_CUDNN_INSTALL_PATH].strip()
    if not repository_ctx.path(cudnn_install_path).exists:
        auto_configure_fail("Cannot find cudnn install path.")
    return cudnn_install_path

def matches_version(environ_version, detected_version):
    """Checks whether the user-specified version matches the detected version.

    This function performs a weak matching so that if the user specifies only the
    major or major and minor versions, the versions are still considered matching
    if the version parts match. To illustrate:

        environ_version  detected_version  result
        -----------------------------------------
        5.1.3            5.1.3             True
        5.1              5.1.3             True
        5                5.1               True
        5.1.3            5.1               False
        5.2.3            5.1.3             False

    Args:
      environ_version: The version specified by the user via environment
        variables.
      detected_version: The version autodetected from the CUDA installation on
        the system.

    Returns: True if user-specified version matches detected version and False
      otherwise.
    """
    environ_version_parts = environ_version.split(".")
    detected_version_parts = detected_version.split(".")
    if len(detected_version_parts) < len(environ_version_parts):
        return False
    for i, part in enumerate(detected_version_parts):
        if i >= len(environ_version_parts):
            break
        if part != environ_version_parts[i]:
            return False
    return True

_NVCC_VERSION_PREFIX = "Cuda compilation tools, release "

def _cuda_version(repository_ctx, cuda_toolkit_path, cpu_value):
    """Detects the version of CUDA installed on the system.

    Args:
      repository_ctx: The repository context.
      cuda_toolkit_path: The CUDA install directory.

    Returns:
      String containing the version of CUDA.
    """

    # Run nvcc --version and find the line containing the CUDA version.
    nvcc_path = repository_ctx.path("%s/bin/nvcc%s" %
                                    (
                                        cuda_toolkit_path,
                                        ".exe" if cpu_value == "Windows" else "",
                                    ))
    if not nvcc_path.exists:
        auto_configure_fail("Cannot find nvcc at %s" % str(nvcc_path))
    result = repository_ctx.execute([str(nvcc_path), "--version"])
    if result.stderr:
        auto_configure_fail("Error running nvcc --version: %s" % result.stderr)
    lines = result.stdout.splitlines()
    version_line = lines[len(lines) - 1]
    if version_line.find(_NVCC_VERSION_PREFIX) == -1:
        auto_configure_fail(
            "Could not parse CUDA version from nvcc --version. Got: %s" %
            result.stdout,
        )

    # Parse the CUDA version from the line containing the CUDA version.
    prefix_removed = version_line.replace(_NVCC_VERSION_PREFIX, "")
    parts = prefix_removed.split(",")
    if len(parts) != 2 or len(parts[0]) < 2:
        auto_configure_fail(
            "Could not parse CUDA version from nvcc --version. Got: %s" %
            result.stdout,
        )
    full_version = parts[1].strip()
    if full_version.startswith("V"):
        full_version = full_version[1:]

    # Check whether TF_CUDA_VERSION was set by the user and fail if it does not
    # match the detected version.
    environ_version = ""
    if _TF_CUDA_VERSION in repository_ctx.os.environ:
        environ_version = repository_ctx.os.environ[_TF_CUDA_VERSION].strip()
    if environ_version and not matches_version(environ_version, full_version):
        auto_configure_fail(
            ("CUDA version detected from nvcc (%s) does not match " +
             "TF_CUDA_VERSION (%s)") % (full_version, environ_version),
        )

    # We only use the version consisting of the major and minor version numbers.
    version_parts = full_version.split(".")
    if len(version_parts) < 2:
        auto_configure_fail("CUDA version detected from nvcc (%s) is incomplete.")
    if cpu_value == "Windows":
        version = "64_%s%s" % (version_parts[0], version_parts[1])
    else:
        version = "%s.%s" % (version_parts[0], version_parts[1])
    return version

_DEFINE_CUDNN_MAJOR = "#define CUDNN_MAJOR"
_DEFINE_CUDNN_MINOR = "#define CUDNN_MINOR"
_DEFINE_CUDNN_PATCHLEVEL = "#define CUDNN_PATCHLEVEL"

def find_cuda_define(repository_ctx, header_dir, header_file, define):
    """Returns the value of a #define in a header file.

    Greps through a header file and returns the value of the specified #define.
    If the #define is not found, then raise an error.

    Args:
      repository_ctx: The repository context.
      header_dir: The directory containing the header file.
      header_file: The header file name.
      define: The #define to search for.

    Returns:
      The value of the #define found in the header.
    """

    # Confirm location of the header and grep for the line defining the macro.
    h_path = repository_ctx.path("%s/%s" % (header_dir, header_file))
    if not h_path.exists:
        auto_configure_fail("Cannot find %s at %s" % (header_file, str(h_path)))
    result = repository_ctx.execute(
        # Grep one more lines as some #defines are splitted into two lines.
        ["grep", "--color=never", "-A1", "-E", define, str(h_path)],
    )
    if result.stderr:
        auto_configure_fail("Error reading %s: %s" % (str(h_path), result.stderr))

    # Parse the version from the line defining the macro.
    if result.stdout.find(define) == -1:
        auto_configure_fail("Cannot find line containing '%s' in %s" %
                            (define, h_path))

    # Split results to lines
    lines = result.stdout.split("\n")
    num_lines = len(lines)
    for l in range(num_lines):
        line = lines[l]
        if define in line:  # Find the line with define
            version = line
            if l != num_lines - 1 and line[-1] == "\\":  # Add next line, if multiline
                version = version[:-1] + lines[l + 1]
            break

    # Remove any comments
    version = version.split("//")[0]

    # Remove define name
    version = version.replace(define, "").strip()

    # Remove the code after the version number.
    version_end = version.find(" ")
    if version_end != -1:
        if version_end == 0:
            auto_configure_fail(
                "Cannot extract the version from line containing '%s' in %s" %
                (define, str(h_path)),
            )
        version = version[:version_end].strip()
    return version

def _cudnn_version(repository_ctx, cudnn_install_basedir, cpu_value):
    """Detects the version of cuDNN installed on the system.

    Args:
      repository_ctx: The repository context.
      cpu_value: The name of the host operating system.
      cudnn_install_basedir: The cuDNN install directory.

    Returns:
      A string containing the version of cuDNN.
    """
    cudnn_header_dir = _find_cudnn_header_dir(
        repository_ctx,
        cudnn_install_basedir,
    )
    major_version = find_cuda_define(
        repository_ctx,
        cudnn_header_dir,
        "cudnn.h",
        _DEFINE_CUDNN_MAJOR,
    )
    minor_version = find_cuda_define(
        repository_ctx,
        cudnn_header_dir,
        "cudnn.h",
        _DEFINE_CUDNN_MINOR,
    )
    patch_version = find_cuda_define(
        repository_ctx,
        cudnn_header_dir,
        "cudnn.h",
        _DEFINE_CUDNN_PATCHLEVEL,
    )
    full_version = "%s.%s.%s" % (major_version, minor_version, patch_version)

    # Check whether TF_CUDNN_VERSION was set by the user and fail if it does not
    # match the detected version.
    environ_version = ""
    if _TF_CUDNN_VERSION in repository_ctx.os.environ:
        environ_version = repository_ctx.os.environ[_TF_CUDNN_VERSION].strip()
    if environ_version and not matches_version(environ_version, full_version):
        cudnn_h_path = repository_ctx.path("%s/include/cudnn.h" %
                                           cudnn_install_basedir)
        auto_configure_fail(
            ("cuDNN version detected from %s (%s) does not match " +
             "TF_CUDNN_VERSION (%s)") %
            (str(cudnn_h_path), full_version, environ_version),
        )

    # We only use the major version since we use the libcudnn libraries that are
    # only versioned with the major version (e.g. libcudnn.so.5).
    version = major_version
    if cpu_value == "Windows":
        version = "64_" + version
    return version

def _compute_capabilities(repository_ctx):
    """Returns a list of strings representing cuda compute capabilities."""
    if _TF_CUDA_COMPUTE_CAPABILITIES not in repository_ctx.os.environ:
        return _DEFAULT_CUDA_COMPUTE_CAPABILITIES
    capabilities_str = repository_ctx.os.environ[_TF_CUDA_COMPUTE_CAPABILITIES]
    capabilities = capabilities_str.split(",")
    for capability in capabilities:
        # Workaround for Skylark's lack of support for regex. This check should
        # be equivalent to checking:
        #     if re.match("[0-9]+.[0-9]+", capability) == None:
        parts = capability.split(".")
        if len(parts) != 2 or not parts[0].isdigit() or not parts[1].isdigit():
            auto_configure_fail("Invalid compute capability: %s" % capability)
    return capabilities

def get_cpu_value(repository_ctx):
    """Returns the name of the host operating system.

    Args:
      repository_ctx: The repository context.

    Returns:
      A string containing the name of the host operating system.
    """
    os_name = repository_ctx.os.name.lower()
    if os_name.startswith("mac os"):
        return "Darwin"
    if os_name.find("windows") != -1:
        return "Windows"
    result = repository_ctx.execute(["uname", "-s"])
    return result.stdout.strip()

def _is_windows(repository_ctx):
    """Returns true if the host operating system is windows."""
    return get_cpu_value(repository_ctx) == "Windows"

def _lib_name(lib, cpu_value, version = "", static = False):
    """Constructs the platform-specific name of a library.

    Args:
      lib: The name of the library, such as "cudart"
      cpu_value: The name of the host operating system.
      version: The version of the library.
      static: True the library is static or False if it is a shared object.

    Returns:
      The platform-specific name of the library.
    """
    if cpu_value in ("Linux", "FreeBSD"):
        if static:
            return "lib%s.a" % lib
        else:
            if version:
                version = ".%s" % version
            return "lib%s.so%s" % (lib, version)
    elif cpu_value == "Windows":
        return "%s.lib" % lib
    elif cpu_value == "Darwin":
        if static:
            return "lib%s.a" % lib
        elif version:
            version = ".%s" % version
        return "lib%s%s.dylib" % (lib, version)
    else:
        auto_configure_fail("Invalid cpu_value: %s" % cpu_value)

def _find_cuda_lib(
        lib,
        repository_ctx,
        cpu_value,
        basedir,
        version = "",
        static = False):
    """Finds the given CUDA or cuDNN library on the system.

    Args:
      lib: The name of the library, such as "cudart"
      repository_ctx: The repository context.
      cpu_value: The name of the host operating system.
      basedir: The install directory of CUDA or cuDNN.
      version: The version of the library.
      static: True if static library, False if shared object.

    Returns:
      Returns a struct with the following fields:
        file_name: The basename of the library found on the system.
        path: The full path to the library.
    """
    file_name = _lib_name(lib, cpu_value, version, static)
    for relative_path in CUDA_LIB_PATHS:
        path = repository_ctx.path("%s/%s%s" % (basedir, relative_path, file_name))
        if path.exists:
            return struct(file_name = file_name, path = str(path.realpath))
    auto_configure_fail("Cannot find cuda library %s" % file_name)

def _find_cupti_header_dir(repository_ctx, cuda_config):
    """Returns the path to the directory containing cupti.h

    On most systems, the cupti library is not installed in the same directory as
    the other CUDA libraries but rather in a special extras/CUPTI directory.

    Args:
      repository_ctx: The repository context.
      cuda_config: The CUDA config as returned by _get_cuda_config

    Returns:
      The path of the directory containing the cupti header.
    """
    cuda_toolkit_path = cuda_config.cuda_toolkit_path
    for relative_path in CUPTI_HEADER_PATHS:
        if repository_ctx.path("%s/%scupti.h" % (cuda_toolkit_path, relative_path)).exists:
            return ("%s/%s" % (cuda_toolkit_path, relative_path))[:-1]
    auto_configure_fail("Cannot find cupti.h under %s" % ", ".join([cuda_toolkit_path + "/" + s for s in CUPTI_HEADER_PATHS]))

def _find_cupti_lib(repository_ctx, cuda_config):
    """Finds the cupti library on the system.

    On most systems, the cupti library is not installed in the same directory as
    the other CUDA libraries but rather in a special extras/CUPTI directory.

    Args:
      repository_ctx: The repository context.
      cuda_config: The cuda configuration as returned by _get_cuda_config.

    Returns:
      Returns a struct with the following fields:
        file_name: The basename of the library found on the system.
        path: The full path to the library.
    """
    file_name = _lib_name(
        "cupti",
        cuda_config.cpu_value,
        cuda_config.cuda_version,
    )
    cuda_toolkit_path = cuda_config.cuda_toolkit_path
    for relative_path in CUPTI_LIB_PATHS:
        path = repository_ctx.path(
            "%s/%s%s" % (cuda_toolkit_path, relative_path, file_name),
        )
        if path.exists:
            return struct(file_name = file_name, path = str(path.realpath))

    auto_configure_fail("Cannot find cupti library %s" % file_name)

def _find_libs(repository_ctx, cuda_config):
    """Returns the CUDA and cuDNN libraries on the system.

    Args:
      repository_ctx: The repository context.
      cuda_config: The CUDA config as returned by _get_cuda_config

    Returns:
      Map of library names to structs of filename and path.
    """
    cpu_value = cuda_config.cpu_value
    return {
        "cuda": _find_cuda_lib("cuda", repository_ctx, cpu_value, cuda_config.cuda_toolkit_path),
        "cudart": _find_cuda_lib(
            "cudart",
            repository_ctx,
            cpu_value,
            cuda_config.cuda_toolkit_path,
            cuda_config.cuda_version,
        ),
        "cudart_static": _find_cuda_lib(
            "cudart_static",
            repository_ctx,
            cpu_value,
            cuda_config.cuda_toolkit_path,
            cuda_config.cuda_version,
            static = True,
        ),
        "cublas": _find_cuda_lib(
            "cublas",
            repository_ctx,
            cpu_value,
            cuda_config.cuda_toolkit_path,
            cuda_config.cuda_version,
        ),
        "cusolver": _find_cuda_lib(
            "cusolver",
            repository_ctx,
            cpu_value,
            cuda_config.cuda_toolkit_path,
            cuda_config.cuda_version,
        ),
        "curand": _find_cuda_lib(
            "curand",
            repository_ctx,
            cpu_value,
            cuda_config.cuda_toolkit_path,
            cuda_config.cuda_version,
        ),
        "cufft": _find_cuda_lib(
            "cufft",
            repository_ctx,
            cpu_value,
            cuda_config.cuda_toolkit_path,
            cuda_config.cuda_version,
        ),
        "cudnn": _find_cuda_lib(
            "cudnn",
            repository_ctx,
            cpu_value,
            cuda_config.cudnn_install_basedir,
            cuda_config.cudnn_version,
        ),
        "cupti": _find_cupti_lib(repository_ctx, cuda_config),
    }

def _find_cuda_include_path(repository_ctx, cuda_config):
    """Returns the path to the directory containing cuda.h

    Args:
      repository_ctx: The repository context.
      cuda_config: The CUDA config as returned by _get_cuda_config

    Returns:
      The path of the directory containing the CUDA headers.
    """
    cuda_toolkit_path = cuda_config.cuda_toolkit_path
    for relative_path in CUDA_INCLUDE_PATHS:
        if repository_ctx.path("%s/%scuda.h" % (cuda_toolkit_path, relative_path)).exists:
            return ("%s/%s" % (cuda_toolkit_path, relative_path))[:-1]
    auto_configure_fail("Cannot find cuda.h under %s" % cuda_toolkit_path)

def _find_cudnn_header_dir(repository_ctx, cudnn_install_basedir):
    """Returns the path to the directory containing cudnn.h

    Args:
      repository_ctx: The repository context.
      cudnn_install_basedir: The cudnn install directory as returned by
        _cudnn_install_basedir.

    Returns:
      The path of the directory containing the cudnn header.
    """
    for relative_path in CUDA_INCLUDE_PATHS:
        if repository_ctx.path("%s/%scudnn.h" % (cudnn_install_basedir, relative_path)).exists:
            return ("%s/%s" % (cudnn_install_basedir, relative_path))[:-1]
    if repository_ctx.path("/usr/include/cudnn.h").exists:
        return "/usr/include"
    auto_configure_fail("Cannot find cudnn.h under %s" % cudnn_install_basedir)

def _find_nvvm_libdevice_dir(repository_ctx, cuda_config):
    """Returns the path to the directory containing libdevice in bitcode format.

    Args:
      repository_ctx: The repository context.
      cuda_config: The CUDA config as returned by _get_cuda_config

    Returns:
      The path of the directory containing the CUDA headers.
    """
    cuda_toolkit_path = cuda_config.cuda_toolkit_path
    for libdevice_file in NVVM_LIBDEVICE_FILES:
        for relative_path in NVVM_LIBDEVICE_PATHS:
            if repository_ctx.path("%s/%s%s" % (cuda_toolkit_path, relative_path, libdevice_file)).exists:
                return ("%s/%s" % (cuda_toolkit_path, relative_path))[:-1]
    auto_configure_fail("Cannot find libdevice*.bc files under %s" % cuda_toolkit_path)

def _cudart_static_linkopt(cpu_value):
    """Returns additional platform-specific linkopts for cudart."""
    return "" if cpu_value == "Darwin" else "\"-lrt\","

def _get_cuda_config(repository_ctx):
    """Detects and returns information about the CUDA installation on the system.

    Args:
      repository_ctx: The repository context.

    Returns:
      A struct containing the following fields:
        cuda_toolkit_path: The CUDA toolkit installation directory.
        cudnn_install_basedir: The cuDNN installation directory.
        cuda_version: The version of CUDA on the system.
        cudnn_version: The version of cuDNN on the system.
        compute_capabilities: A list of the system's CUDA compute capabilities.
        cpu_value: The name of the host operating system.
    """
    cpu_value = get_cpu_value(repository_ctx)
    cuda_toolkit_path = _cuda_toolkit_path(repository_ctx)
    cuda_version = _cuda_version(repository_ctx, cuda_toolkit_path, cpu_value)
    cudnn_install_basedir = _cudnn_install_basedir(repository_ctx)
    cudnn_version = _cudnn_version(repository_ctx, cudnn_install_basedir, cpu_value)
    return struct(
        cuda_toolkit_path = cuda_toolkit_path,
        cudnn_install_basedir = cudnn_install_basedir,
        cuda_version = cuda_version,
        cudnn_version = cudnn_version,
        compute_capabilities = _compute_capabilities(repository_ctx),
        cpu_value = cpu_value,
    )

def _tpl(repository_ctx, tpl, substitutions = {}, out = None):
    if not out:
        out = tpl.replace(":", "/")
    repository_ctx.template(
        out,
        Label("//third_party/gpus/%s.tpl" % tpl),
        substitutions,
    )

def _file(repository_ctx, label):
    repository_ctx.template(
        label.replace(":", "/"),
        Label("//third_party/gpus/%s.tpl" % label),
        {},
    )

_DUMMY_CROSSTOOL_BZL_FILE = """
def error_gpu_disabled():
  fail("ERROR: Building with --config=cuda but TensorFlow is not configured " +
       "to build with GPU support. Please re-run ./configure and enter 'Y' " +
       "at the prompt to build with GPU support.")

  native.genrule(
      name = "error_gen_crosstool",
      outs = ["CROSSTOOL"],
      cmd = "echo 'Should not be run.' && exit 1",
  )

  native.filegroup(
      name = "crosstool",
      srcs = [":CROSSTOOL"],
      output_licenses = ["unencumbered"],
  )
"""

_DUMMY_CROSSTOOL_BUILD_FILE = """
load("//crosstool:error_gpu_disabled.bzl", "error_gpu_disabled")

error_gpu_disabled()
"""

def _create_dummy_repository(repository_ctx):
    cpu_value = get_cpu_value(repository_ctx)

    # Set up BUILD file for cuda/.
    _tpl(
        repository_ctx,
        "cuda:build_defs.bzl",
        {
            "%{cuda_is_configured}": "False",
            "%{cuda_extra_copts}": "[]",
        },
    )
    _tpl(
        repository_ctx,
        "cuda:BUILD",
        {
            "%{cuda_driver_lib}": _lib_name("cuda", cpu_value),
            "%{cudart_static_lib}": _lib_name(
                "cudart_static",
                cpu_value,
                static = True,
            ),
            "%{cudart_static_linkopt}": _cudart_static_linkopt(cpu_value),
            "%{cudart_lib}": _lib_name("cudart", cpu_value),
            "%{cublas_lib}": _lib_name("cublas", cpu_value),
            "%{cusolver_lib}": _lib_name("cusolver", cpu_value),
            "%{cudnn_lib}": _lib_name("cudnn", cpu_value),
            "%{cufft_lib}": _lib_name("cufft", cpu_value),
            "%{curand_lib}": _lib_name("curand", cpu_value),
            "%{cupti_lib}": _lib_name("cupti", cpu_value),
            "%{cuda_include_genrules}": "",
            "%{cuda_headers}": "",
        },
    )

    # Create dummy files for the CUDA toolkit since they are still required by
    # tensorflow/core/platform/default/build_config:cuda.
    repository_ctx.file("cuda/cuda/include/cuda.h", "")
    repository_ctx.file("cuda/cuda/include/cublas.h", "")
    repository_ctx.file("cuda/cuda/include/cudnn.h", "")
    repository_ctx.file("cuda/cuda/extras/CUPTI/include/cupti.h", "")
    repository_ctx.file("cuda/cuda/lib/%s" % _lib_name("cuda", cpu_value))
    repository_ctx.file("cuda/cuda/lib/%s" % _lib_name("cudart", cpu_value))
    repository_ctx.file("cuda/cuda/lib/%s" % _lib_name("cudart_static", cpu_value))
    repository_ctx.file("cuda/cuda/lib/%s" % _lib_name("cublas", cpu_value))
    repository_ctx.file("cuda/cuda/lib/%s" % _lib_name("cusolver", cpu_value))
    repository_ctx.file("cuda/cuda/lib/%s" % _lib_name("cudnn", cpu_value))
    repository_ctx.file("cuda/cuda/lib/%s" % _lib_name("curand", cpu_value))
    repository_ctx.file("cuda/cuda/lib/%s" % _lib_name("cufft", cpu_value))
    repository_ctx.file("cuda/cuda/lib/%s" % _lib_name("cupti", cpu_value))

    # Set up cuda_config.h, which is used by
    # tensorflow/stream_executor/dso_loader.cc.
    _tpl(
        repository_ctx,
        "cuda:cuda_config.h",
        {
            "%{cuda_version}": _DEFAULT_CUDA_VERSION,
            "%{cudnn_version}": _DEFAULT_CUDNN_VERSION,
            "%{cuda_compute_capabilities}": ",".join([
                "CudaVersion(\"%s\")" % c
                for c in _DEFAULT_CUDA_COMPUTE_CAPABILITIES
            ]),
            "%{cuda_toolkit_path}": _DEFAULT_CUDA_TOOLKIT_PATH,
        },
        "cuda/cuda/cuda_config.h",
    )

    # If cuda_configure is not configured to build with GPU support, and the user
    # attempts to build with --config=cuda, add a dummy build rule to intercept
    # this and fail with an actionable error message.
    repository_ctx.file(
        "crosstool/error_gpu_disabled.bzl",
        _DUMMY_CROSSTOOL_BZL_FILE,
    )
    repository_ctx.file("crosstool/BUILD", _DUMMY_CROSSTOOL_BUILD_FILE)

def _execute(
        repository_ctx,
        cmdline,
        error_msg = None,
        error_details = None,
        empty_stdout_fine = False):
    """Executes an arbitrary shell command.

    Args:
      repository_ctx: the repository_ctx object
      cmdline: list of strings, the command to execute
      error_msg: string, a summary of the error if the command fails
      error_details: string, details about the error or steps to fix it
      empty_stdout_fine: bool, if True, an empty stdout result is fine, otherwise
        it's an error
    Return:
      the result of repository_ctx.execute(cmdline)
    """
    result = repository_ctx.execute(cmdline)
    if result.stderr or not (empty_stdout_fine or result.stdout):
        auto_configure_fail(
            "\n".join([
                error_msg.strip() if error_msg else "Repository command failed",
                result.stderr.strip(),
                error_details if error_details else "",
            ]),
        )
    return result

def _norm_path(path):
    """Returns a path with '/' and remove the trailing slash."""
    path = path.replace("\\", "/")
    if path[-1] == "/":
        path = path[:-1]
    return path

def symlink_genrule_for_dir(
        repository_ctx,
        src_dir,
        dest_dir,
        genrule_name,
        src_files = [],
        dest_files = []):
    """Returns a genrule to symlink(or copy if on Windows) a set of files.

    If src_dir is passed, files will be read from the given directory; otherwise
    we assume files are in src_files and dest_files
    """
    if src_dir != None:
        src_dir = _norm_path(src_dir)
        dest_dir = _norm_path(dest_dir)
        files = "\n".join(sorted(_read_dir(repository_ctx, src_dir).splitlines()))

        # Create a list with the src_dir stripped to use for outputs.
        dest_files = files.replace(src_dir, "").splitlines()
        src_files = files.splitlines()
    command = []
    if not _is_windows(repository_ctx):
        # We clear folders that might have been generated previously to avoid
        # undesired inclusions
        command.append('if [ -d "$(@D)/extras" ]; then rm $(@D)/extras -drf; fi')
        command.append('if [ -d "$(@D)/include" ]; then rm $(@D)/include -drf; fi')
        command.append('if [ -d "$(@D)/lib" ]; then rm $(@D)/lib -drf; fi')
        command.append('if [ -d "$(@D)/nvvm" ]; then rm $(@D)/nvvm -drf; fi')
    outs = []
    for i in range(len(dest_files)):
        if dest_files[i] != "":
            # If we have only one file to link we do not want to use the dest_dir, as
            # $(@D) will include the full path to the file.
            dest = "$(@D)/" + dest_dir + dest_files[i] if len(dest_files) != 1 else "$(@D)/" + dest_files[i]

            # On Windows, symlink is not supported, so we just copy all the files.
            cmd = "cp -f" if _is_windows(repository_ctx) else "ln -s"
            command.append(cmd + ' "%s" "%s"' % (src_files[i], dest))
            outs.append('        "' + dest_dir + dest_files[i] + '",')
    genrule = _genrule(
        src_dir,
        genrule_name,
        " && ".join(command),
        "\n".join(outs),
    )
    return genrule

def _genrule(src_dir, genrule_name, command, outs):
    """Returns a string with a genrule.

    Genrule executes the given command and produces the given outputs.
    """
    return (
        "genrule(\n" +
        '    name = "' +
        genrule_name + '",\n' +
        "    outs = [\n" +
        outs +
        "\n    ],\n" +
        '    cmd = """\n' +
        command +
        '\n   """,\n' +
        ")\n"
    )

def _read_dir(repository_ctx, src_dir):
    """Returns a string with all files in a directory.

    Finds all files inside a directory, traversing subfolders and following
    symlinks. The returned string contains the full path of all files
    separated by line breaks.
    """
    if _is_windows(repository_ctx):
        src_dir = src_dir.replace("/", "\\")
        find_result = _execute(
            repository_ctx,
            ["cmd.exe", "/c", "dir", src_dir, "/b", "/s", "/a-d"],
            empty_stdout_fine = True,
        )

        # src_files will be used in genrule.outs where the paths must
        # use forward slashes.
        result = find_result.stdout.replace("\\", "/")
    else:
        find_result = _execute(
            repository_ctx,
            ["find", src_dir, "-follow", "-type", "f"],
            empty_stdout_fine = True,
        )
        result = find_result.stdout
    return result

def _flag_enabled(repository_ctx, flag_name):
    if flag_name in repository_ctx.os.environ:
        value = repository_ctx.os.environ[flag_name].strip()
        return value == "1"
    return False

def _use_cuda_clang(repository_ctx):
    return _flag_enabled(repository_ctx, "TF_CUDA_CLANG")

def _compute_cuda_extra_copts(repository_ctx, compute_capabilities):
    if _use_cuda_clang(repository_ctx):
        capability_flags = ["--cuda-gpu-arch=sm_" +
                            cap.replace(".", "") for cap in compute_capabilities]
    else:
        # Capabilities are handled in the "crosstool_wrapper_driver_is_not_gcc" for nvcc
        capability_flags = []
    return str(capability_flags)

def _create_local_cuda_repository(repository_ctx):
    """Creates the repository containing files set up to build with CUDA."""
    cuda_config = _get_cuda_config(repository_ctx)

    cuda_include_path = _find_cuda_include_path(repository_ctx, cuda_config)
    cudnn_header_dir = _find_cudnn_header_dir(
        repository_ctx,
        cuda_config.cudnn_install_basedir,
    )
    cupti_header_dir = _find_cupti_header_dir(repository_ctx, cuda_config)
    nvvm_libdevice_dir = _find_nvvm_libdevice_dir(repository_ctx, cuda_config)

    # Set up symbolic links for the cuda toolkit by creating genrules to do
    # symlinking. We create one genrule for each directory we want to track under
    # cuda_toolkit_path
    cuda_toolkit_path = cuda_config.cuda_toolkit_path
    genrules = [symlink_genrule_for_dir(
        repository_ctx,
        cuda_include_path,
        "cuda/include",
        "cuda-include",
    )]
    genrules.append(symlink_genrule_for_dir(
        repository_ctx,
        nvvm_libdevice_dir,
        "cuda/nvvm/libdevice",
        "cuda-nvvm",
    ))
    genrules.append(symlink_genrule_for_dir(
        repository_ctx,
        cupti_header_dir,
        "cuda/extras/CUPTI/include",
        "cuda-extras",
    ))

    cuda_libs = _find_libs(repository_ctx, cuda_config)
    cuda_lib_src = []
    cuda_lib_dest = []
    for lib in cuda_libs.values():
        cuda_lib_src.append(lib.path)
        cuda_lib_dest.append("cuda/lib/" + lib.file_name)
    genrules.append(symlink_genrule_for_dir(
        repository_ctx,
        None,
        "",
        "cuda-lib",
        cuda_lib_src,
        cuda_lib_dest,
    ))

    # Set up the symbolic links for cudnn if cndnn was not installed to
    # CUDA_TOOLKIT_PATH.
    included_files = _read_dir(repository_ctx, cuda_include_path).replace(
        cuda_include_path,
        "",
    ).splitlines()
    if "/cudnn.h" not in included_files:
        genrules.append(symlink_genrule_for_dir(
            repository_ctx,
            None,
            "cuda/include/",
            "cudnn-include",
            [cudnn_header_dir + "/cudnn.h"],
            ["cudnn.h"],
        ))
    else:
        genrules.append(
            "filegroup(\n" +
            '    name = "cudnn-include",\n' +
            "    srcs = [],\n" +
            ")\n",
        )

    # Set up BUILD file for cuda/
    _tpl(
        repository_ctx,
        "cuda:build_defs.bzl",
        {
            "%{cuda_is_configured}": "True",
            "%{cuda_extra_copts}": _compute_cuda_extra_copts(
                repository_ctx,
                cuda_config.compute_capabilities,
            ),
        },
    )
    _tpl(
        repository_ctx,
        "cuda:BUILD.windows" if _is_windows(repository_ctx) else "cuda:BUILD",
        {
            "%{cuda_driver_lib}": cuda_libs["cuda"].file_name,
            "%{cudart_static_lib}": cuda_libs["cudart_static"].file_name,
            "%{cudart_static_linkopt}": _cudart_static_linkopt(
                cuda_config.cpu_value,
            ),
            "%{cudart_lib}": cuda_libs["cudart"].file_name,
            "%{cublas_lib}": cuda_libs["cublas"].file_name,
            "%{cusolver_lib}": cuda_libs["cusolver"].file_name,
            "%{cudnn_lib}": cuda_libs["cudnn"].file_name,
            "%{cufft_lib}": cuda_libs["cufft"].file_name,
            "%{curand_lib}": cuda_libs["curand"].file_name,
            "%{cupti_lib}": cuda_libs["cupti"].file_name,
            "%{cuda_include_genrules}": "\n".join(genrules),
            "%{cuda_headers}": ('":cuda-include",\n' +
                                '        ":cudnn-include",'),
        },
        "cuda/BUILD",
    )

    is_cuda_clang = _use_cuda_clang(repository_ctx)

    should_download_clang = is_cuda_clang and _flag_enabled(
        repository_ctx,
        _TF_DOWNLOAD_CLANG,
    )
    if should_download_clang:
        download_clang(repository_ctx, "crosstool/extra_tools")

    # Set up crosstool/
    cc = find_cc(repository_ctx)
    cc_fullpath = cc if not should_download_clang else "crosstool/" + cc

    host_compiler_includes = _host_compiler_includes(repository_ctx, cc_fullpath)
    cuda_defines = {}
    # Bazel sets '-B/usr/bin' flag to workaround build errors on RHEL (see
    # https://github.com/bazelbuild/bazel/issues/760).
    # However, this stops our custom clang toolchain from picking the provided
    # LLD linker, so we're only adding '-B/usr/bin' when using non-downloaded
    # toolchain.
    # TODO: when bazel stops adding '-B/usr/bin' by default, remove this
    #       flag from the CROSSTOOL completely (see
    #       https://github.com/bazelbuild/bazel/issues/5634)
    if should_download_clang:
      cuda_defines["%{linker_bin_path_flag}"] = ""
    else:
      cuda_defines["%{linker_bin_path_flag}"] = 'flag: "-B/usr/bin"'

    if is_cuda_clang:
        cuda_defines["%{host_compiler_path}"] = str(cc)
        cuda_defines["%{host_compiler_warnings}"] = """
        # Some parts of the codebase set -Werror and hit this warning, so
        # switch it off for now.
        flag: "-Wno-invalid-partial-specialization"
    """
        cuda_defines["%{host_compiler_includes}"] = host_compiler_includes
        _tpl(repository_ctx, "crosstool:BUILD", {"%{linker_files}": ":empty", "%{win_linker_files}": ":empty"})
        repository_ctx.file("crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc", "")
        repository_ctx.file("crosstool/windows/msvc_wrapper_for_nvcc.py", "")
        repository_ctx.file("crosstool/windows/msvc_wrapper_for_nvcc.bat", "")
    else:
        cuda_defines["%{host_compiler_path}"] = "clang/bin/crosstool_wrapper_driver_is_not_gcc"
        cuda_defines["%{host_compiler_warnings}"] = ""

        # TODO(klimek): We currently need to inject "/" as builtin directory path
        # to disable bazel's dependency checks.
        # The problem is that:
        # - the python rules symlink the python headers into the bazel root
        # - the rules use 'includes' in the BUILD file to redirect includes of the
        #   python headers through those paths
        # - bazel currently uses -isystem for include paths specified via 'includes'
        # - gcc follows symlinks when resolving files via -isystem paths, and puts
        #   the resolved paths into the .d file, which makes the dependency check
        #   fail for bazel
        # There are multiple possible ways to solve this:
        # 1. make bazel not use -isystem for paths specified via 'includes'
        # 2. cp the headers instead of symlinking them
        #
        # Once this is fixed, the right builtin directory path is:
        # (host_compiler_includes +
        #    "\n  cxx_builtin_include_directory: \"%s\"" % cuda_include_path)
        # The cuda directory needs to be passed, as there is currently no rule
        # providing the cuda headers in the same way the python headers are
        # provided.
        cuda_defines["%{host_compiler_includes}"] = "\n  cxx_builtin_include_directory: \"/\""
        nvcc_path = str(repository_ctx.path("%s/bin/nvcc%s" %
                                            (
                                                cuda_config.cuda_toolkit_path,
                                                ".exe" if _is_windows(repository_ctx) else "",
                                            )))
        _tpl(
            repository_ctx,
            "crosstool:BUILD",
            {
                "%{linker_files}": ":crosstool_wrapper_driver_is_not_gcc",
                "%{win_linker_files}": ":windows_msvc_wrapper_files",
            },
        )
        wrapper_defines = {
            "%{cpu_compiler}": str(cc),
            "%{cuda_version}": cuda_config.cuda_version,
            "%{nvcc_path}": nvcc_path,
            "%{gcc_host_compiler_path}": str(cc),
            "%{cuda_compute_capabilities}": ", ".join(
                ["\"%s\"" % c for c in cuda_config.compute_capabilities],
            ),
            "%{nvcc_tmp_dir}": _get_nvcc_tmp_dir_for_windows(repository_ctx),
        }
        _tpl(
            repository_ctx,
            "crosstool:clang/bin/crosstool_wrapper_driver_is_not_gcc",
            wrapper_defines,
        )
        _tpl(
            repository_ctx,
            "crosstool:windows/msvc_wrapper_for_nvcc.py",
            wrapper_defines,
        )
        _tpl(
            repository_ctx,
            "crosstool:windows/msvc_wrapper_for_nvcc.bat",
            {
                "%{python_binary}": _get_python_bin(repository_ctx),
            },
        )

    _tpl(
        repository_ctx,
        "crosstool:CROSSTOOL",
        cuda_defines + _get_win_cuda_defines(repository_ctx),
        out = "crosstool/CROSSTOOL",
    )

    # Set up cuda_config.h, which is used by
    # tensorflow/stream_executor/dso_loader.cc.
    _tpl(
        repository_ctx,
        "cuda:cuda_config.h",
        {
            "%{cuda_version}": cuda_config.cuda_version,
            "%{cudnn_version}": cuda_config.cudnn_version,
            "%{cuda_compute_capabilities}": ",".join(
                [
                    "CudaVersion(\"%s\")" % c
                    for c in cuda_config.compute_capabilities
                ],
            ),
            "%{cuda_toolkit_path}": cuda_config.cuda_toolkit_path,
        },
        "cuda/cuda/cuda_config.h",
    )

def _create_remote_cuda_repository(repository_ctx, remote_config_repo):
    """Creates pointers to a remotely configured repo set up to build with CUDA."""
    _tpl(
        repository_ctx,
        "cuda:build_defs.bzl",
        {
            "%{cuda_is_configured}": "True",
            "%{cuda_extra_copts}": _compute_cuda_extra_copts(
                repository_ctx,
                _compute_capabilities(repository_ctx),
            ),
        },
    )
    _tpl(
        repository_ctx,
        "cuda:remote.BUILD",
        {
            "%{remote_cuda_repo}": remote_config_repo,
        },
        "cuda/BUILD",
    )
    _tpl(repository_ctx, "crosstool:remote.BUILD", {
        "%{remote_cuda_repo}": remote_config_repo,
    }, "crosstool/BUILD")

def _cuda_autoconf_impl(repository_ctx):
    """Implementation of the cuda_autoconf repository rule."""
    if not _enable_cuda(repository_ctx):
        _create_dummy_repository(repository_ctx)
    elif _TF_CUDA_CONFIG_REPO in repository_ctx.os.environ:
        _create_remote_cuda_repository(
            repository_ctx,
            repository_ctx.os.environ[_TF_CUDA_CONFIG_REPO],
        )
    else:
        _create_local_cuda_repository(repository_ctx)

cuda_configure = repository_rule(
    implementation = _cuda_autoconf_impl,
    environ = [
        _GCC_HOST_COMPILER_PATH,
        _CLANG_CUDA_COMPILER_PATH,
        "TF_NEED_CUDA",
        "TF_CUDA_CLANG",
        _TF_DOWNLOAD_CLANG,
        _CUDA_TOOLKIT_PATH,
        _CUDNN_INSTALL_PATH,
        _TF_CUDA_VERSION,
        _TF_CUDNN_VERSION,
        _TF_CUDA_COMPUTE_CAPABILITIES,
        _TF_CUDA_CONFIG_REPO,
        "NVVMIR_LIBRARY_DIR",
        _PYTHON_BIN_PATH,
    ],
)

"""Detects and configures the local CUDA toolchain.

Add the following to your WORKSPACE FILE:

```python
cuda_configure(name = "local_config_cuda")
```

Args:
  name: A unique name for this workspace rule.
"""