mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-06 12:20:52 +01:00
f922b58b5f
Summary: ## Context We take the first step at tackling the GPU-bazel support by adding bazel external workspaces `local_config_cuda` and `cuda`, where the first one has some hardcoded values and lists of files, and the second one provides a nicer, high-level wrapper that maps into the already expected by pytorch bazel targets that are guarded with `if_cuda` macro. The prefix `local_config_` signifies the fact that we are breaking the bazel hermeticity philosophy by explicitly relaying on the CUDA installation that is present on the machine. ## Testing Notice an important scenario that is unlocked by this change: compilation of cpp code that depends on cuda libraries (i.e. cuda.h and so on). Before: ``` sergei.vorobev@cs-sv7xn77uoy-gpu-1628706590:~/src/pytorch4$ bazelisk build --define=cuda=true //:c10 ERROR: /home/sergei.vorobev/src/pytorch4/tools/config/BUILD:12:1: no such package 'tools/toolchain': BUILD file not found in any of the following directories. Add a BUILD file to a directory to mark it as a package. - /home/sergei.vorobev/src/pytorch4/tools/toolchain and referenced by '//tools/config:cuda_enabled_and_capable' ERROR: While resolving configuration keys for //:c10: Analysis failed ERROR: Analysis of target '//:c10' failed; build aborted: Analysis failed INFO: Elapsed time: 0.259s INFO: 0 processes. FAILED: Build did NOT complete successfully (2 packages loaded, 2 targets configured) ``` After: ``` sergei.vorobev@cs-sv7xn77uoy-gpu-1628706590:~/src/pytorch4$ bazelisk build --define=cuda=true //:c10 INFO: Analyzed target //:c10 (6 packages loaded, 246 targets configured). INFO: Found 1 target... Target //:c10 up-to-date: bazel-bin/libc10.lo bazel-bin/libc10.so INFO: Elapsed time: 0.617s, Critical Path: 0.04s INFO: 0 processes. INFO: Build completed successfully, 1 total action ``` The `//:c10` target is a good testing one for this, because it has such cases where the [glob is different](075024b9a3/BUILD.bazel (L76-L81)), based on do we compile for CUDA or not. ## What is out of scope of this PR This PR is a first in a series of providing the comprehensive GPU bazel build support. Namely, we don't tackle the [cu_library](11a40ad915/tools/rules/cu.bzl (L2)) implementation here. This would be a separate large chunk of work. Pull Request resolved: https://github.com/pytorch/pytorch/pull/63604 Reviewed By: soulitzer Differential Revision: D30442083 Pulled By: malfet fbshipit-source-id: b2a8e4f7e5a25a69b960a82d9e36ba568eb64595
184 lines
4.6 KiB
Python
184 lines
4.6 KiB
Python
workspace(name = "pytorch")
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load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
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load("//tools/rules:workspace.bzl", "new_patched_local_repository", "new_empty_repository")
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http_archive(
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name = "bazel_skylib",
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urls = [
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"https://github.com/bazelbuild/bazel-skylib/releases/download/1.0.2/bazel-skylib-1.0.2.tar.gz",
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],
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)
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http_archive(
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name = "com_google_googletest",
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strip_prefix = "googletest-cd6b9ae3243985d4dc725abd513a874ab4161f3e",
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urls = [
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"https://github.com/google/googletest/archive/cd6b9ae3243985d4dc725abd513a874ab4161f3e.tar.gz",
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],
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)
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http_archive(
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name = "pybind11_bazel",
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strip_prefix = "pybind11_bazel-7f397b5d2cc2434bbd651e096548f7b40c128044",
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urls = ["https://github.com/pybind/pybind11_bazel/archive/7f397b5d2cc2434bbd651e096548f7b40c128044.zip"],
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sha256 = "e4a9536f49d4a88e3c5a09954de49c4a18d6b1632c457a62d6ec4878c27f1b5b",
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)
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new_local_repository(
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name = "pybind11",
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build_file = "@pybind11_bazel//:pybind11.BUILD",
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path = "third_party/pybind11",
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)
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http_archive(
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name = "com_github_glog",
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strip_prefix = "glog-0.4.0",
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urls = [
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"https://github.com/google/glog/archive/v0.4.0.tar.gz",
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],
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)
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http_archive(
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name = "com_github_gflags_gflags",
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strip_prefix = "gflags-2.2.2",
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urls = [
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"https://github.com/gflags/gflags/archive/v2.2.2.tar.gz",
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],
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sha256 = "34af2f15cf7367513b352bdcd2493ab14ce43692d2dcd9dfc499492966c64dcf",
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)
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new_local_repository(
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name = "gloo",
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build_file = "//third_party:gloo.BUILD",
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path = "third_party/gloo",
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)
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new_local_repository(
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name = "onnx",
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build_file = "//third_party:onnx.BUILD",
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path = "third_party/onnx",
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)
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new_local_repository(
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name = "foxi",
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build_file = "//third_party:foxi.BUILD",
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path = "third_party/foxi",
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)
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local_repository(
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name = "com_google_protobuf",
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path = "third_party/protobuf",
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)
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new_local_repository(
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name = "eigen",
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build_file = "//third_party:eigen.BUILD",
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path = "third_party/eigen",
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)
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new_local_repository(
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name = "fbgemm",
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build_file = "//third_party:fbgemm/BUILD.bazel",
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path = "third_party/fbgemm",
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)
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new_local_repository(
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name = "ideep",
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build_file = "//third_party:ideep.BUILD",
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path = "third_party/ideep",
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)
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new_local_repository(
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name = "mkl_dnn",
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build_file = "//third_party:mkl-dnn.BUILD",
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path = "third_party/ideep/mkl-dnn",
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)
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new_local_repository(
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name = "cpuinfo",
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build_file = "//third_party:cpuinfo.BUILD",
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path = "third_party/cpuinfo",
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)
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new_local_repository(
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name = "asmjit",
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build_file = "//third_party:fbgemm/third_party/asmjit.BUILD",
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path = "third_party/fbgemm/third_party/asmjit",
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)
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new_local_repository(
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name = "sleef",
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build_file = "//third_party:sleef.BUILD",
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path = "third_party/sleef",
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)
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new_local_repository(
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name = "fmt",
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build_file = "//third_party:fmt.BUILD",
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path = "third_party/fmt",
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)
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new_patched_local_repository(
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name = "tbb",
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patches = [
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"@//third_party:tbb.patch",
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],
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patch_strip = 1,
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build_file = "//third_party:tbb.BUILD",
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path = "third_party/tbb",
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)
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new_local_repository(
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name = "tensorpipe",
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build_file = "//third_party:tensorpipe.BUILD",
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path = "third_party/tensorpipe",
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)
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http_archive(
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name = "mkl",
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build_file = "//third_party:mkl.BUILD",
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strip_prefix = "lib",
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sha256 = "59154b30dd74561e90d547f9a3af26c75b6f4546210888f09c9d4db8f4bf9d4c",
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urls = [
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"https://anaconda.org/anaconda/mkl/2020.0/download/linux-64/mkl-2020.0-166.tar.bz2",
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],
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)
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http_archive(
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name = "mkl_headers",
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build_file = "//third_party:mkl_headers.BUILD",
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sha256 = "2af3494a4bebe5ddccfdc43bacc80fcd78d14c1954b81d2c8e3d73b55527af90",
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urls = [
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"https://anaconda.org/anaconda/mkl-include/2020.0/download/linux-64/mkl-include-2020.0-166.tar.bz2",
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],
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)
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http_archive(
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name = "rules_python",
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url = "https://github.com/bazelbuild/rules_python/releases/download/0.0.1/rules_python-0.0.1.tar.gz",
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sha256 = "aa96a691d3a8177f3215b14b0edc9641787abaaa30363a080165d06ab65e1161",
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)
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load("@pybind11_bazel//:python_configure.bzl", "python_configure")
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python_configure(name = "local_config_python")
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load("@com_google_protobuf//:protobuf_deps.bzl", "protobuf_deps")
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protobuf_deps()
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load("@rules_python//python:repositories.bzl", "py_repositories")
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py_repositories()
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local_repository(
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name = "local_config_cuda",
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path = "third_party/tensorflow_cuda_bazel_build",
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)
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# Wrapper to expose local_config_cuda in an agnostic way
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new_empty_repository(
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name = "cuda",
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build_file = "//third_party:cuda.BUILD",
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)
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