| sort -u
}

# Verify that, given a build target and a license-list generator target, all of
# the dependencies of that target which include a license notice file are then
# included when generating that license. Necessary because the license targets
# in TensorFlow are manually enumerated rather than generated automatically.
do_external_licenses_check(){
  BUILD_TARGET="$1"
  LICENSES_TARGET="$2"

    hdrs = [":includes"],
    strip_include_prefix="site-packages/numpy/core/include/",
)
""",
    ),
}

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

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

install_deps()

        "//tensorflow/python:pywrap_tensorflow_internal",
    ]),
)

# ** Targets for Windows build (start) **

# Build a shared library (DLL) by cc_binary from tf_custom_op_library_additional_deps_impl,
# it contains all object code from its dependencies.
# This target is only used for parsing the symbols to be exported in tensorflow.dll.
# Do NOT depend on it.
tf_native_cc_binary(

source ci/official/envs/linux_x86
TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_cpu_linux --config=tpu"
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_tpu
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_tpu"
TFCI_LIB_SUFFIX="-tpu-linux-x86_64"
TFCI_WHL_BAZEL_TEST_ENABLE=0
TFCI_WHL_IMPORT_TEST_ENABLE=0
TFCI_WHL_SIZE_LIMIT=580M

        "//tensorflow/c:tf_status",
        "//tensorflow/c/experimental/filesystem:filesystem_interface",
    ],
)

# Since building pip package and API tests require a filesystem, we provide a
# static registration target that they should link against.
cc_library(
    name = "posix_filesystem_static",
    srcs = ["posix_filesystem_static.cc"],
    visibility = ["//visibility:public"],
    deps = [
        ":posix_filesystem_impl",

    python_version = TF_PYTHON_VERSION,
)

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

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

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

# START MACOS CROSS-COMPILE CONFIGS
build:cross_compile_macos_x86 --config=cross_compile_base
build:cross_compile_macos_x86 --config=nonccl
# Target Catalina (10.15) as the minimum supported OS
build:cross_compile_macos_x86 --action_env  MACOSX_DEPLOYMENT_TARGET=10.15

# Set the target CPU to Darwin x86
build:cross_compile_macos_x86 --platforms=//tensorflow/tools/toolchains/cross_compile/config:darwin_x86_64

        "//tensorflow/core:testlib",
        "@com_google_absl//absl/strings",
    ],
)

# -----------------------------------------------------------------------------
# Python API target

tf_cuda_library(
    name = "python_api",
    srcs = ["python_api.cc"],
    hdrs = ["python_api.h"],
    visibility = ["//tensorflow/python:__pkg__"],
    deps = [
        ":c_api",

*   <IF RELEASE CONTAINS MULTIPLE FEATURES FROM SAME AREA, GROUP THEM TOGETHER>

*   Add `is_cpu_target_available`, which indicates whether or not TensorFlow was
    built with support for a given CPU target. This can be useful for skipping
    target-specific tests if a target is not supported.

*   `tf.data`
    * Support `data.experimental.distribued_save`. `distribued_save` uses
      tf.data service

TFCI_ARTIFACT_FINAL_PYPI_ARGS=
TFCI_ARTIFACT_FINAL_PYPI_ENABLE=
TFCI_ARTIFACT_LATEST_GCS_URI=
TFCI_ARTIFACT_STAGING_GCS_ENABLE=
TFCI_ARTIFACT_STAGING_GCS_URI=
TFCI_BAZEL_BAZELRC_ARGS=
TFCI_BAZEL_COMMON_ARGS=
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=
TFCI_BUILD_PIP_PACKAGE_ARGS=
TFCI_DOCKER_ARGS=
TFCI_DOCKER_ENABLE=
TFCI_DOCKER_IMAGE=
TFCI_DOCKER_PULL_ENABLE=
TFCI_DOCKER_REBUILD_ARGS=
TFCI_DOCKER_REBUILD_ENABLE=