srcs = [
        ":device_headers",
        ":lib_headers",
    ],
    visibility = ["//tensorflow/python:__pkg__"],
)

filegroup(
    name = "sources",
    srcs = [
        ":device_sources",
        ":lib_sources",
    ],
    visibility = ["//tensorflow/python:__pkg__"],
)

cc_library(
    name = "parallel_device",
    srcs = [":device_sources"],
    hdrs = [":device_headers"],

# "manylinux_xyz" into the wheel filename.
set -euxo pipefail

for wheel in /tf/pkg/*.whl; do
  echo "Checking and renaming $wheel..."
  time python3 -m auditwheel repair --plat manylinux2014_aarch64 "$wheel" --wheel-dir /tf/pkg 2>&1 | tee check.txt

  # We don't need the original wheel if it was renamed
  new_wheel=$(grep --extended-regexp --only-matching '/tf/pkg/\S+.whl' check.txt)
  if [[ "$new_wheel" != "$wheel" ]]; then
    rm "$wheel"

# The profile can be viewed by visiting chrome://tracing in a Chrome browser.
# See https://docs.bazel.build/versions/main/skylark/performance.html#performance-profiling
build --profile=/tf/pkg/profile.json.gz

# Use the rebuilt gcc toolchain to compile for manylinux2014
build --crosstool_top="@ml2014_aarch64_config_aarch64//crosstool:toolchain"
test --crosstool_top="@ml2014_aarch64_config_aarch64//crosstool:toolchain"

py_test(
    name = "test_import_api_packages",
    srcs = ["test_import_api_packages.py"],
    deps = ["@pypi_tensorflow//:pkg"],

    $pkg_url = \"https://dl.google.com/dl/cloudsdk/channels/rapid/downloads/google-cloud-cli-396.0.0-windows-x86_64.zip\"; \
    $pkg_zip = \"c:/temp/gcloud.zip\"; \
    $pkg_extracted_path = \"c:/google-cloud-sdk\"; \
    (New-Object Net.WebClient).DownloadFile($pkg_url, $pkg_zip); \
    [System.IO.Compression.ZipFile]::ExtractToDirectory($pkg_zip, \"c:/\"); \

    ],
)

filegroup(
    name = "pywrap_tf_session_hdrs",
    srcs = [
        "python_api.h",
    ],
    visibility = [
        "//tensorflow/core:__pkg__",
        "//tensorflow/python:__pkg__",
    ],
)

cc_library(
    name = "tf_attrtype",
    hdrs = ["tf_attrtype.h"],
    visibility = ["//visibility:public"],
)

cc_library(
    name = "c_api_macros_hdrs",

set -euxo pipefail

# Run this from inside the tensorflow github directory.
# Usage: setup_venv_test.sh venv_and_symlink_name "glob pattern for one wheel file"
# Example: setup_venv_test.sh bazel_pip "/tf/pkg/*.whl"
# 
# This will create a venv with that wheel file installed in it, and a symlink
# in ./venv_and_symlink_name/tensorflow to ./tensorflow. We use this for the
# "pip" tests.

python -m venv /$1
mkdir -p $1

# ==============================================================================
# Suite of verification tests for the SINGLE TensorFlow wheel in /tf/pkg
# or whatever path is set as $TF_WHEEL.

setup_file() {
    cd /tf/pkg
    if [[ -z "$TF_WHEEL" ]]; then
        export TF_WHEEL=$(find /tf/pkg -iname "*.whl")
    fi
}

teardown_file() {
    rm -rf /tf/venv
}

@test "Wheel is manylinux2014 (manylinux_2_17) compliant" {

"""

import logging
import unittest
import pkg_resources

logging.basicConfig(level=logging.INFO)


class ImportApiPackagesTest(unittest.TestCase):
  """ImportApiPackagesTest class. See description at the top of the file."""

  def setUp(self):
    def _get_api_packages_v2():
      api_packages_path = pkg_resources.resource_filename(
          "tensorflow", "_api/v2/api_packages.txt"
      )

# The profile can be viewed by visiting chrome://tracing in a Chrome browser.
# See https://docs.bazel.build/versions/main/skylark/performance.html#performance-profiling
build --profile=/tf/pkg/profile.json.gz

# Use the rebuilt gcc toolchain to compile for manylinux2014
build --crosstool_top="@ml2014_clang_aarch64_config_aarch64//crosstool:toolchain"

build --copt="-mtune=generic" --copt="-march=armv8-a" --copt="-O3"