mirror of
https://github.com/tensorflow/tensorflow.git
synced 2024-11-21 21:05:19 +00:00
89 lines
2.5 KiB
Python
89 lines
2.5 KiB
Python
workspace(name = "org_tensorflow")
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# We must initialize hermetic python first.
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load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
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http_archive(
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name = "bazel_skylib",
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sha256 = "74d544d96f4a5bb630d465ca8bbcfe231e3594e5aae57e1edbf17a6eb3ca2506",
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urls = [
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"https://storage.googleapis.com/mirror.tensorflow.org/github.com/bazelbuild/bazel-skylib/releases/download/1.3.0/bazel-skylib-1.3.0.tar.gz",
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"https://github.com/bazelbuild/bazel-skylib/releases/download/1.3.0/bazel-skylib-1.3.0.tar.gz",
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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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sha256 = "29a801171f7ca190c543406f9894abf2d483c206e14d6acbd695623662320097",
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strip_prefix = "rules_python-0.18.1",
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url = "https://github.com/bazelbuild/rules_python/releases/download/0.18.1/rules_python-0.18.1.tar.gz",
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)
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load("@rules_python//python:repositories.bzl", "python_register_toolchains")
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load(
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"//tensorflow/tools/toolchains/python:python_repo.bzl",
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"python_repository",
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)
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python_repository(name = "python_version_repo")
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load("@python_version_repo//:py_version.bzl", "HERMETIC_PYTHON_VERSION")
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python_register_toolchains(
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name = "python",
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ignore_root_user_error = True,
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python_version = HERMETIC_PYTHON_VERSION,
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)
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load("@python//:defs.bzl", "interpreter")
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load("@rules_python//python:pip.bzl", "package_annotation", "pip_parse")
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NUMPY_ANNOTATIONS = {
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"numpy": package_annotation(
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additive_build_content = """\
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filegroup(
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name = "includes",
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srcs = glob(["site-packages/numpy/core/include/**/*.h"]),
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)
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cc_library(
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name = "numpy_headers",
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hdrs = [":includes"],
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strip_include_prefix="site-packages/numpy/core/include/",
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)
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""",
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),
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}
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pip_parse(
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name = "pypi",
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annotations = NUMPY_ANNOTATIONS,
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python_interpreter_target = interpreter,
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requirements = "//:requirements_lock_" + HERMETIC_PYTHON_VERSION.replace(".", "_") + ".txt",
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)
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load("@pypi//:requirements.bzl", "install_deps")
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install_deps()
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# Initialize the TensorFlow repository and all dependencies.
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#
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# The cascade of load() statements and tf_workspace?() calls works around the
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# restriction that load() statements need to be at the top of .bzl files.
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# E.g. we can not retrieve a new repository with http_archive and then load()
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# a macro from that repository in the same file.
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load("@//tensorflow:workspace3.bzl", "tf_workspace3")
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tf_workspace3()
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load("@//tensorflow:workspace2.bzl", "tf_workspace2")
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tf_workspace2()
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load("@//tensorflow:workspace1.bzl", "tf_workspace1")
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tf_workspace1()
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load("@//tensorflow:workspace0.bzl", "tf_workspace0")
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tf_workspace0()
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