# Need a newer version of patchelf as the installed version is buggy in 20.04
# so get patchelf source from 22.04 ie 'jammy' and build it to avoid dependency
# problems that would occur with a binary package

mkdir -p /patchelf
cd /patchelf
echo deb-src http://ports.ubuntu.com/ubuntu-ports/ jammy universe>>/etc/apt/sources.list
apt-get update
apt-get -y build-dep patchelf/jammy
apt-get -b source patchelf/jammy

Michael Hudgins <******@****.***> 1695048765 +0000

tar -xvzf "glibc-2.17-c758a686-releng.tar.gz" --strip 1
sed -i '/patch0060/d' glibc.spec
/rpm-patch.sh "glibc.spec"
rm -f "glibc-2.17-317.el7.src.rpm" "glibc-2.17-c758a686.tar.gz" "glibc-2.17-c758a686-releng.tar.gz"
patch -p1 < /gcc9-fixups.patch
patch -p1 < /stringop_trunc.patch
cd ../glibc-build
../glibc-src/configure --prefix=/usr --disable-werror --enable-obsolete-rpc --disable-profile
make -j$(nproc)

potentially exploit a vulnerability in the TensorFlow code that handles videos,
which could allow them to execute arbitrary code on the system running
TensorFlow.

It is important to keep TensorFlow up to date with the latest security patches
and follow the sandboxing guideline above to protect against these types of
vulnerabilities.

## Security properties of execution modes

TensorFlow has several execution modes, with Eager-mode being the default in v2.

        "@com_google_absl//absl/log:check",
        "@com_google_googletest//:gtest_main",
        "@local_tsl//tsl/lib/core:status_test_util",
        "@local_tsl//tsl/platform:casts",
        "@local_tsl//tsl/platform:status_matchers",
        "@local_tsl//tsl/protobuf:error_codes_proto_impl_cc",
        "@local_xla//xla:shape_util",
        "@local_xla//xla/pjrt:pjrt_api",
        "@local_xla//xla/pjrt:pjrt_c_api_client",

#
# Given an RPM spec file $1, apply its patches.

SPEC="$1"
grep '%patch' "${SPEC}" |while read cmd ; do
  N=$(echo "${cmd}" |sed 's,%patch\([0-9]\+\).*,\1,')
  file=$(grep "Patch$N:" "${SPEC}" |sed 's,.*: ,,')
  parg=$(echo "${cmd}" |sed 's,.*\(-p[0-9]\).*,\1,')
  if [[ ! "${file}" =~ doxygen && "${cmd}" != \#* ]]; then
    echo "patch ${parg} -s < ${file}"
    patch ${parg} -s < "${file}"
  fi

  )
except subprocess.CalledProcessError as e:
  print("No failures found to log!")
  exit(0)

# For test cases, only show the ones that failed that have text (a log)
seen = collections.Counter()
runfiles_matcher = re.compile(r"(/.*\.runfiles/)")


for f in files.strip().splitlines():
  # Just ignore any failures, they're probably not important
  try:
    r = JUnitXml.fromfile(f)

#include "tensorflow/core/tfrt/common/async_value_tensor.h"
#include "tensorflow/core/tfrt/common/pjrt_util.h"
#include "tsl/lib/core/status_test_util.h"
#include "tsl/platform/casts.h"
#include "tsl/platform/status_matchers.h"
#include "tsl/protobuf/error_codes.pb.h"

namespace tensorflow {
namespace {

using ::testing::HasSubstr;
using ::testing::NotNull;
using ::tsl::testing::StatusIs;

PJRT_Buffer* CreateCBuffer() {