"""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_SYSROOT`: The sysroot to use when compiling. * `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. * `TF_CUDA_PATHS`: The base paths to look for CUDA and cuDNN. Default is `/usr/local/cuda,usr/`. * `CUDA_TOOLKIT_PATH` (deprecated): 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` (deprecated): 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 """ 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", ) _GCC_HOST_COMPILER_PATH = "GCC_HOST_COMPILER_PATH" _GCC_HOST_COMPILER_PREFIX = "GCC_HOST_COMPILER_PREFIX" _CLANG_CUDA_COMPILER_PATH = "CLANG_CUDA_COMPILER_PATH" _TF_SYSROOT = "TF_SYSROOT" _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_COMPUTE_CAPABILITIES = ["3.5", "5.2"] def to_list_of_strings(elements): """Convert the list of ["a", "b", "c"] into '"a", "b", "c"'. This is to be used to put a list of strings into the bzl file templates so it gets interpreted as list of strings in Starlark. Args: elements: list of string elements Returns: single string of elements wrapped in quotes separated by a comma.""" quoted_strings = ["\"" + element + "\"" for element in elements] return ", ".join(quoted_strings) def verify_build_defines(params): """Verify all variables that crosstool/BUILD.tpl expects are substituted. Args: params: dict of variables that will be passed to the BUILD.tpl template. """ missing = [] for param in [ "cxx_builtin_include_directories", "extra_no_canonical_prefixes_flags", "host_compiler_path", "host_compiler_prefix", "host_compiler_warnings", "linker_bin_path", "compiler_deps", "msvc_cl_path", "msvc_env_include", "msvc_env_lib", "msvc_env_path", "msvc_env_tmp", "msvc_lib_path", "msvc_link_path", "msvc_ml_path", "unfiltered_compile_flags", "win_compiler_deps", ]: if ("%{" + param + "}") not in params: missing.append(param) if missing: auto_configure_fail( "BUILD.tpl template is missing these variables: " + str(missing) + ".\nWe only got: " + str(params) + ".", ) 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 Windows 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_nvcc_tmp_dir_for_unix(repository_ctx): """Return the UNIX tmp directory for nvcc to generate intermediate source files.""" escaped_tmp_dir = escape_string( get_env_var(repository_ctx, "TMPDIR", "/tmp"), ) 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 fake vaules for Windows specific fields. # This ensures the CROSSTOOL file parser is happy. if not _is_windows(repository_ctx): return { "%{msvc_env_tmp}": "msvc_not_used", "%{msvc_env_path}": "msvc_not_used", "%{msvc_env_include}": "msvc_not_used", "%{msvc_env_lib}": "msvc_not_used", "%{msvc_cl_path}": "msvc_not_used", "%{msvc_ml_path}": "msvc_not_used", "%{msvc_link_path}": "msvc_not_used", "%{msvc_lib_path}": "msvc_not_used", } 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 = _get_python_bin(repository_ctx) 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 guaranteed to have unique name, so they can share # the same tmp directory escaped_cxx_include_directories = [ _get_nvcc_tmp_dir_for_windows(repository_ctx), ] for path in escaped_include_paths.split(";"): if path: escaped_cxx_include_directories.append(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_directories}": to_list_of_strings( 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, tf_sysroot): """Compute the list of default C or C++ include directories.""" if lang_is_cpp: lang = "c++" else: lang = "c" sysroot = [] if tf_sysroot: sysroot += ["--sysroot", tf_sysroot] result = repository_ctx.execute([cc, "-E", "-x" + lang, "-", "-v"] + sysroot) 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, tf_sysroot): """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, tf_sysroot, ) includes_c = _get_cxx_inc_directories_impl( repository_ctx, cc, False, tf_sysroot, ) return includes_cpp + [ inc for inc in includes_c if inc not in includes_cpp ] 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 _cuda_include_path(repository_ctx, cuda_config): """Generates the Starlark string with cuda include directories. Args: repository_ctx: The repository context. cc: The path to the gcc host compiler. Returns: A list of the gcc host compiler include directories. """ 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(target_dir) inc_entries.append(cuda_config.cuda_toolkit_path + "/include") return inc_entries def enable_cuda(repository_ctx): """Returns whether to build with CUDA support.""" return int(repository_ctx.os.environ.get("TF_NEED_CUDA", False)) 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 " _DEFINE_CUDNN_MAJOR = "#define CUDNN_MAJOR" 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 repository_ctx.os.name.lower().find("windows") >= 0 def lib_name(base_name, cpu_value, version = None, static = False): """Constructs the platform-specific name of a library. Args: base_name: 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. """ version = "" if not version else "." + version if cpu_value in ("Linux", "FreeBSD"): if static: return "lib%s.a" % base_name return "lib%s.so%s" % (base_name, version) elif cpu_value == "Windows": return "%s.lib" % base_name elif cpu_value == "Darwin": if static: return "lib%s.a" % base_name return "lib%s%s.dylib" % (base_name, version) else: auto_configure_fail("Invalid cpu_value: %s" % cpu_value) def find_lib(repository_ctx, paths, check_soname = True): """ Finds a library among a list of potential paths. Args: paths: List of paths to inspect. Returns: Returns the first path in paths that exist. """ objdump = repository_ctx.which("objdump") mismatches = [] for path in [repository_ctx.path(path) for path in paths]: if not path.exists: continue if check_soname and objdump != None and not _is_windows(repository_ctx): output = repository_ctx.execute([objdump, "-p", str(path)]).stdout output = [line for line in output.splitlines() if "SONAME" in line] sonames = [line.strip().split(" ")[-1] for line in output] if not any([soname == path.basename for soname in sonames]): mismatches.append(str(path)) continue return path if mismatches: auto_configure_fail( "None of the libraries match their SONAME: " + ", ".join(mismatches), ) auto_configure_fail("No library found under: " + ", ".join(paths)) 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 the path to the library. """ file_name = lib_name(lib, cpu_value, version, static) return find_lib( repository_ctx, ["%s/%s" % (basedir, file_name)], check_soname = version and not static, ) 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 stub_dir = "" if _is_windows(repository_ctx) else "/stubs" return { "cuda": _find_cuda_lib( "cuda", repository_ctx, cpu_value, cuda_config.config["cuda_library_dir"] + stub_dir, None, ), "cudart": _find_cuda_lib( "cudart", repository_ctx, cpu_value, cuda_config.config["cuda_library_dir"], cuda_config.cuda_version, ), "cudart_static": _find_cuda_lib( "cudart_static", repository_ctx, cpu_value, cuda_config.config["cuda_library_dir"], cuda_config.cuda_version, static = True, ), "cublas": _find_cuda_lib( "cublas", repository_ctx, cpu_value, cuda_config.config["cublas_library_dir"], cuda_config.cuda_lib_version, ), "cusolver": _find_cuda_lib( "cusolver", repository_ctx, cpu_value, cuda_config.config["cuda_library_dir"], cuda_config.cuda_lib_version, ), "curand": _find_cuda_lib( "curand", repository_ctx, cpu_value, cuda_config.config["cuda_library_dir"], cuda_config.cuda_lib_version, ), "cufft": _find_cuda_lib( "cufft", repository_ctx, cpu_value, cuda_config.config["cuda_library_dir"], cuda_config.cuda_lib_version, ), "cudnn": _find_cuda_lib( "cudnn", repository_ctx, cpu_value, cuda_config.config["cudnn_library_dir"], cuda_config.cudnn_version, ), "cupti": _find_cuda_lib( "cupti", repository_ctx, cpu_value, cuda_config.config["cupti_library_dir"], cuda_config.cuda_version, ), "cusparse": _find_cuda_lib( "cusparse", repository_ctx, cpu_value, cuda_config.config["cuda_library_dir"], cuda_config.cuda_lib_version, ), } def _cudart_static_linkopt(cpu_value): """Returns additional platform-specific linkopts for cudart.""" return "" if cpu_value == "Darwin" else "\"-lrt\"," # TODO(csigg): Only call once instead of from here, tensorrt_configure.bzl, # and nccl_configure.bzl. def find_cuda_config(repository_ctx, cuda_libraries): """Returns CUDA config dictionary from running find_cuda_config.py""" exec_result = repository_ctx.execute([ _get_python_bin(repository_ctx), repository_ctx.path(Label("@org_tensorflow//third_party/gpus:find_cuda_config.py")), ] + cuda_libraries) if exec_result.return_code: auto_configure_fail("Failed to run find_cuda_config.py: %s" % exec_result.stderr) # Parse the dict from stdout. return dict([tuple(x.split(": ")) for x in exec_result.stdout.splitlines()]) 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. """ config = find_cuda_config(repository_ctx, ["cuda", "cudnn"]) cpu_value = get_cpu_value(repository_ctx) toolkit_path = config["cuda_toolkit_path"] is_windows = _is_windows(repository_ctx) cuda_version = config["cuda_version"].split(".") cuda_major = cuda_version[0] cuda_minor = cuda_version[1] cuda_version = ("64_%s%s" if is_windows else "%s.%s") % (cuda_major, cuda_minor) cudnn_version = ("64_%s" if is_windows else "%s") % config["cudnn_version"] # cuda_lib_version is for libraries like cuBLAS, cuFFT, cuSOLVER, etc. # It changed from 'x.y' to just 'x' in CUDA 10.1. if (int(cuda_major), int(cuda_minor)) >= (10, 1): cuda_lib_version = ("64_%s" if is_windows else "%s") % cuda_major else: cuda_lib_version = cuda_version return struct( cuda_toolkit_path = toolkit_path, cuda_version = cuda_version, cudnn_version = cudnn_version, cuda_lib_version = cuda_lib_version, compute_capabilities = compute_capabilities(repository_ctx), cpu_value = cpu_value, config = config, ) 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), "%{cusparse_lib}": lib_name("cusparse", cpu_value), "%{copy_rules}": """ filegroup(name="cuda-include") filegroup(name="cublas-include") filegroup(name="cudnn-include") """, }, ) # 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)) repository_ctx.file("cuda/cuda/lib/%s" % lib_name("cusparse", 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}": "", "%{cuda_lib_version}": "", "%{cudnn_version}": "", "%{cuda_compute_capabilities}": ",".join([ "CudaVersion(\"%s\")" % c for c in _DEFAULT_CUDA_COMPUTE_CAPABILITIES ]), "%{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 make_copy_files_rule(repository_ctx, name, srcs, outs): """Returns a rule to copy a set of files.""" cmds = [] # Copy files. for src, out in zip(srcs, outs): cmds.append('cp -f "%s" "$(location %s)"' % (src, out)) outs = [(' "%s",' % out) for out in outs] return """genrule( name = "%s", outs = [ %s ], cmd = \"""%s \""", )""" % (name, "\n".join(outs), " && \\\n".join(cmds)) def make_copy_dir_rule(repository_ctx, name, src_dir, out_dir): """Returns a rule to recursively copy a directory.""" src_dir = _norm_path(src_dir) out_dir = _norm_path(out_dir) outs = _read_dir(repository_ctx, src_dir) outs = [(' "%s",' % out.replace(src_dir, out_dir)) for out in outs] # '@D' already contains the relative path for a single file, see # http://docs.bazel.build/versions/master/be/make-variables.html#predefined_genrule_variables out_dir = "$(@D)/%s" % out_dir if len(outs) > 1 else "$(@D)" return """genrule( name = "%s", outs = [ %s ], cmd = \"""cp -rLf "%s/." "%s/" \""", )""" % (name, "\n".join(outs), src_dir, out_dir) 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 sorted(result.splitlines()) 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 _tf_sysroot(repository_ctx): if _TF_SYSROOT in repository_ctx.os.environ: return repository_ctx.os.environ[_TF_SYSROOT] return "" def _compute_cuda_extra_copts(repository_ctx, compute_capabilities): capability_flags = [ "--cuda-gpu-arch=sm_" + cap.replace(".", "") for cap in compute_capabilities ] # Capabilities are handled in the "crosstool_wrapper_driver_is_not_gcc" for nvcc # TODO(csigg): Make this consistent with cuda clang and pass unconditionally. return "if_cuda_clang(%s)" % 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 = cuda_config.config["cuda_include_dir"] cublas_include_path = cuda_config.config["cublas_include_dir"] cudnn_header_dir = cuda_config.config["cudnn_include_dir"] cupti_header_dir = cuda_config.config["cupti_include_dir"] nvvm_libdevice_dir = cuda_config.config["nvvm_library_dir"] # Create genrule to copy files from the installed CUDA toolkit into execroot. copy_rules = [ make_copy_dir_rule( repository_ctx, name = "cuda-include", src_dir = cuda_include_path, out_dir = "cuda/include", ), make_copy_dir_rule( repository_ctx, name = "cuda-nvvm", src_dir = nvvm_libdevice_dir, out_dir = "cuda/nvvm/libdevice", ), make_copy_dir_rule( repository_ctx, name = "cuda-extras", src_dir = cupti_header_dir, out_dir = "cuda/extras/CUPTI/include", ), ] copy_rules.append(make_copy_files_rule( repository_ctx, name = "cublas-include", srcs = [ cublas_include_path + "/cublas.h", cublas_include_path + "/cublas_v2.h", cublas_include_path + "/cublas_api.h", ], outs = [ "cublas/include/cublas.h", "cublas/include/cublas_v2.h", "cublas/include/cublas_api.h", ], )) cuda_libs = _find_libs(repository_ctx, cuda_config) cuda_lib_srcs = [] cuda_lib_outs = [] for path in cuda_libs.values(): cuda_lib_srcs.append(str(path)) cuda_lib_outs.append("cuda/lib/" + path.basename) copy_rules.append(make_copy_files_rule( repository_ctx, name = "cuda-lib", srcs = cuda_lib_srcs, outs = cuda_lib_outs, )) # copy files mentioned in third_party/nccl/build_defs.bzl.tpl copy_rules.append(make_copy_files_rule( repository_ctx, name = "cuda-bin", srcs = [ cuda_config.cuda_toolkit_path + "/bin/" + "crt/link.stub", cuda_config.cuda_toolkit_path + "/bin/" + "nvlink", cuda_config.cuda_toolkit_path + "/bin/" + "fatbinary", cuda_config.cuda_toolkit_path + "/bin/" + "bin2c", ], outs = [ "cuda/bin/" + "crt/link.stub", "cuda/bin/" + "nvlink", "cuda/bin/" + "fatbinary", "cuda/bin/" + "bin2c", ], )) copy_rules.append(make_copy_files_rule( repository_ctx, name = "cudnn-include", srcs = [cudnn_header_dir + "/cudnn.h"], outs = ["cudnn/include/cudnn.h"], )) # 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"].basename, "%{cudart_static_lib}": cuda_libs["cudart_static"].basename, "%{cudart_static_linkopt}": _cudart_static_linkopt(cuda_config.cpu_value), "%{cudart_lib}": cuda_libs["cudart"].basename, "%{cublas_lib}": cuda_libs["cublas"].basename, "%{cusolver_lib}": cuda_libs["cusolver"].basename, "%{cudnn_lib}": cuda_libs["cudnn"].basename, "%{cufft_lib}": cuda_libs["cufft"].basename, "%{curand_lib}": cuda_libs["curand"].basename, "%{cupti_lib}": cuda_libs["cupti"].basename, "%{cusparse_lib}": cuda_libs["cusparse"].basename, "%{copy_rules}": "\n".join(copy_rules), }, "cuda/BUILD", ) is_cuda_clang = _use_cuda_clang(repository_ctx) tf_sysroot = _tf_sysroot(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 = get_cxx_inc_directories( repository_ctx, cc_fullpath, tf_sysroot, ) cuda_defines = {} cuda_defines["%{builtin_sysroot}"] = tf_sysroot cuda_defines["%{cuda_toolkit_path}"] = "" if is_cuda_clang: cuda_defines["%{cuda_toolkit_path}"] = cuda_config.config["cuda_toolkit_path"] host_compiler_prefix = "/usr/bin" if _GCC_HOST_COMPILER_PREFIX in repository_ctx.os.environ: host_compiler_prefix = repository_ctx.os.environ[_GCC_HOST_COMPILER_PREFIX].strip() cuda_defines["%{host_compiler_prefix}"] = host_compiler_prefix # 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}"] = "" else: cuda_defines["%{linker_bin_path}"] = host_compiler_prefix cuda_defines["%{extra_no_canonical_prefixes_flags}"] = "" cuda_defines["%{unfiltered_compile_flags}"] = "" 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. "-Wno-invalid-partial-specialization" """ cuda_defines["%{cxx_builtin_include_directories}"] = to_list_of_strings(host_compiler_includes) cuda_defines["%{compiler_deps}"] = ":empty" cuda_defines["%{win_compiler_deps}"] = ":empty" repository_ctx.file( "crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc", "", ) repository_ctx.file("crosstool/windows/msvc_wrapper_for_nvcc.py", "") else: cuda_defines["%{host_compiler_path}"] = "clang/bin/crosstool_wrapper_driver_is_not_gcc" cuda_defines["%{host_compiler_warnings}"] = "" # nvcc has the system include paths built in and will automatically # search them; we cannot work around that, so we add the relevant cuda # system paths to the allowed compiler specific include paths. cuda_defines["%{cxx_builtin_include_directories}"] = to_list_of_strings( host_compiler_includes + _cuda_include_path( repository_ctx, cuda_config, ) + [cupti_header_dir, cudnn_header_dir], ) # For gcc, do not canonicalize system header paths; some versions of gcc # pick the shortest possible path for system includes when creating the # .d file - given that includes that are prefixed with "../" multiple # time quickly grow longer than the root of the tree, this can lead to # bazel's header check failing. cuda_defines["%{extra_no_canonical_prefixes_flags}"] = "\"-fno-canonical-system-headers\"" nvcc_path = str( repository_ctx.path("%s/nvcc%s" % ( cuda_config.config["cuda_binary_dir"], ".exe" if _is_windows(repository_ctx) else "", )), ) cuda_defines["%{compiler_deps}"] = ":crosstool_wrapper_driver_is_not_gcc" cuda_defines["%{win_compiler_deps}"] = ":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, ) cuda_defines.update(_get_win_cuda_defines(repository_ctx)) verify_build_defines(cuda_defines) # Only expand template variables in the BUILD file _tpl(repository_ctx, "crosstool:BUILD", cuda_defines) # No templating of cc_toolchain_config - use attributes and templatize the # BUILD file. _file(repository_ctx, "crosstool:cc_toolchain_config.bzl") # 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, "%{cuda_lib_version}": cuda_config.cuda_lib_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), ), }, ) repository_ctx.template( "cuda/BUILD", Label(remote_config_repo + "/cuda:BUILD"), {}, ) repository_ctx.template( "cuda/build_defs.bzl", Label(remote_config_repo + "/cuda:build_defs.bzl"), {}, ) repository_ctx.template( "cuda/cuda/cuda_config.h", Label(remote_config_repo + "/cuda:cuda/cuda_config.h"), {}, ) 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: if (_TF_CUDA_VERSION not in repository_ctx.os.environ or _TF_CUDNN_VERSION not in repository_ctx.os.environ): auto_configure_fail("%s and %s must also be set if %s is specified" % (_TF_CUDA_VERSION, _TF_CUDNN_VERSION, _TF_CUDA_CONFIG_REPO)) _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, _GCC_HOST_COMPILER_PREFIX, _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, "TMP", "TMPDIR", "TF_CUDA_PATHS", ], ) """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. """