74 lines
3.4 KiB
Python
74 lines
3.4 KiB
Python
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load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
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load("//third_party:repo.bzl", "tf_http_archive", "tf_mirror_urls", "tf_vendored")
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load("//third_party/gpus:cuda_configure.bzl", "cuda_configure")
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load("//third_party/gpus:rocm_configure.bzl", "rocm_configure")
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load("//third_party/py:python_repo.bzl", "python_repository")
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load("//third_party/pybind11_bazel:workspace.bzl", pybind11_bazel = "repo")
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load("//third_party/tensorrt:tensorrt_configure.bzl", "tensorrt_configure")
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load("//tools/toolchains/remote:configure.bzl", "remote_execution_configure")
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def _workspace_private_impl(mctx):
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http_archive(
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name = "rules_ml_toolchain",
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sha256 = "fb78d09234528aef2be856820b69b76486829f65e4eb3c7ffaa5803b667fa441",
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strip_prefix = "rules_ml_toolchain-f4ad89fa906be2c1374785a79335c8a7dcd49df7",
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urls = [
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"https://github.com/zml/rules_ml_toolchain/archive/f4ad89fa906be2c1374785a79335c8a7dcd49df7.tar.gz",
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],
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)
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# Use cuda_configure from XLA to make it work with bzlmod.
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# A pure bzlmod solution for rules_ml_toolchain is impossible because of the legacy design.
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# It relies on a "generate-then-load" pattern that creates a deadlock in Bazel's architecture:
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# - Generate: First, it runs a rule to generate a .bzl file containing configuration data.
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# - Load: Then, it requires a load() statement to load that same file to continue the setup.
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# This fails in bzlmod because Bazel's Loading Phase (when load() statements are processed) happens before
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# the Analysis Phase (when repository rules are run).
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# This creates a fundamental chicken-and-egg problem: the build tries to load a file that has not been generated yet.
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# Without using the official WORKSPACE.bzlmod escape hatch,
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# this incompatibility cannot be resolved without modifying the upstream rules.
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cuda_configure(name = "local_config_cuda")
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remote_execution_configure(name = "local_config_remote_execution")
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rocm_configure(name = "local_config_rocm")
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tensorrt_configure(name = "local_config_tensorrt")
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tf_vendored(name = "tsl", relpath = "third_party/tsl")
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pybind11_bazel()
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tf_http_archive(
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name = "com_github_grpc_grpc",
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sha256 = "afbc5d78d6ba6d509cc6e264de0d49dcd7304db435cbf2d630385bacf49e066c",
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strip_prefix = "grpc-1.68.2",
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patch_file = [
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"//third_party/grpc:grpc.patch",
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],
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urls = tf_mirror_urls("https://github.com/grpc/grpc/archive/refs/tags/v1.68.2.tar.gz"),
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)
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tf_http_archive(
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name = "com_google_protobuf",
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patch_file = ["//third_party/protobuf:protobuf.patch"],
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sha256 = "f645e6e42745ce922ca5388b1883ca583bafe4366cc74cf35c3c9299005136e2",
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strip_prefix = "protobuf-5.28.3",
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urls = tf_mirror_urls("https://github.com/protocolbuffers/protobuf/archive/refs/tags/v5.28.3.zip"),
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)
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python_repository(
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name = "python_version_repo",
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requirements_versions = ["3.11"],
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requirements_locks = ["//:requirements_lock_3_11.txt"],
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local_wheel_workspaces = [],
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local_wheel_dist_folder = None,
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default_python_version = None,
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local_wheel_inclusion_list = ["*"],
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local_wheel_exclusion_list = [],
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)
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return mctx.extension_metadata(
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reproducible = True,
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root_module_direct_deps = "all",
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root_module_direct_dev_deps = [],
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)
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workspace_private = module_extension(
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implementation = _workspace_private_impl,
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)
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