WORKSPACE

workspace(name = "larq_compute_engine")

load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")

# To update TensorFlow to a new revision.
# 1. Update the git hash in the urls and the 'strip_prefix' parameter.
# 2. Get the sha256 hash of the archive with a command such as...
#    curl -L https://github.com/tensorflow/tensorflow/archive/<git hash>.tar.gz | shasum -a 256
#    and update the 'sha256' arg with the result.
# 3. Request the new archive to be mirrored on mirror.bazel.build for more
#    reliable downloads.
http_archive(
    name = "org_tensorflow",
    patch_args = ["-p1"],
    patch_tool = "patch",
    patches = [
        "//third_party/tensorflow_patches:disable_forced_mkl.patch",
    ],
    sha256 = "c729e56efc945c6df08efe5c9f5b8b89329c7c91b8f40ad2bb3e13900bd4876d",
    strip_prefix = "tensorflow-2.16.1",
    urls = [
        "https://github.com/tensorflow/tensorflow/archive/v2.16.1.tar.gz",
    ],
)

# We must initialize hermetic python first.
http_archive(
    name = "bazel_skylib",
    sha256 = "74d544d96f4a5bb630d465ca8bbcfe231e3594e5aae57e1edbf17a6eb3ca2506",
    urls = [
        "https://storage.googleapis.com/mirror.tensorflow.org/github.com/bazelbuild/bazel-skylib/releases/download/1.3.0/bazel-skylib-1.3.0.tar.gz",
        "https://github.com/bazelbuild/bazel-skylib/releases/download/1.3.0/bazel-skylib-1.3.0.tar.gz",
    ],
)

http_archive(
    name = "rules_python",
    sha256 = "9d04041ac92a0985e344235f5d946f71ac543f1b1565f2cdbc9a2aaee8adf55b",
    strip_prefix = "rules_python-0.26.0",
    url = "https://github.com/bazelbuild/rules_python/releases/download/0.26.0/rules_python-0.26.0.tar.gz",
)

load("@rules_python//python:repositories.bzl", "py_repositories", "python_register_toolchains")

py_repositories()

load(
    "@org_tensorflow//tensorflow/tools/toolchains/python:python_repo.bzl",
    "python_repository",
)

python_repository(name = "python_version_repo")

load("@python_version_repo//:py_version.bzl", "TF_PYTHON_VERSION")

python_register_toolchains(
    name = "python",
    ignore_root_user_error = True,
    python_version = TF_PYTHON_VERSION,
)

load("@python//:defs.bzl", "interpreter")
load("@rules_python//python:pip.bzl", "package_annotation", "pip_parse")

NUMPY_ANNOTATIONS = {
    "numpy": package_annotation(
        additive_build_content = """\
filegroup(
    name = "includes",
    srcs = glob(["site-packages/numpy/core/include/**/*.h"]),
)
cc_library(
    name = "numpy_headers",
    hdrs = [":includes"],
    strip_include_prefix="site-packages/numpy/core/include/",
)
""",
    ),
}

pip_parse(
    name = "pypi",
    annotations = NUMPY_ANNOTATIONS,
    python_interpreter_target = interpreter,
    requirements = "@org_tensorflow//:requirements_lock_" + TF_PYTHON_VERSION.replace(".", "_") + ".txt",
)

load("@pypi//:requirements.bzl", tf_install_deps = "install_deps")

tf_install_deps()

pip_parse(
    name = "pypi_lce",
    python_interpreter_target = interpreter,
    requirements = "//larq_compute_engine:requirements.txt",
)

load("@pypi_lce//:requirements.bzl", lce_install_deps = "install_deps")

lce_install_deps()

load("@org_tensorflow//tensorflow:workspace3.bzl", "tf_workspace3")

tf_workspace3()

load("@org_tensorflow//tensorflow:workspace2.bzl", "tf_workspace2")

tf_workspace2()

load("@org_tensorflow//tensorflow:workspace1.bzl", "tf_workspace1")

tf_workspace1()

load("@org_tensorflow//tensorflow:workspace0.bzl", "tf_workspace0")

tf_workspace0()