// Note that `matches` is allocated by the plugin and freed by core
  // TensorFlow, so we need to use `plugin_memory_free_` here.
  char** matches = nullptr;
  const int num_matches = ops_->get_matching_paths(
      filesystem_.get(), pattern.c_str(), &matches, plugin_status.get());
  if (num_matches >= 0) {
    for (int i = 0; i < num_matches; i++) {
      result->push_back(std::string(matches[i]));

# nightly job. update_version.py affects TF_VER_SUFFIX, TF_VER_PYTHON, and
# TF_VER_FULL.

# Note: in awk, the command '/search/ {commands}' applies the commands to any line that
# matches the /search/ regular expression. "print $N" prints the Nth "field",
# where fields are strings separated by whitespace.
export TF_VER_MAJOR=$(awk '/#define TF_MAJOR_VERSION/ {print $3}' tensorflow/core/public/version.h)

  )
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)

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
#
# 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 (!status->status.ok()) {
    return nullptr;
  }

  TF_DataType dtype = TFE_TensorHandleDataType(components[0].get());
  // Verify that the combined TensorHandle's dtype matches all of the component
  // dtypes.
  for (TensorHandlePtr& component : components) {
    TFE_TensorHandleGetStatus(component.get(), status);
    if (!status->status.ok()) {
      return nullptr;
    }

} TF_Output;

// TF_Function is a grouping of operations with defined inputs and outputs.
// Once created and added to graphs, functions can be invoked by creating an
// operation whose operation type matches the function name.
typedef struct TF_Function TF_Function;

// Function definition options. TODO(iga): Define and implement
typedef struct TF_FunctionOptions TF_FunctionOptions;

  }

  // Returns whether any tensor in a list of tensors is being watched and has
  // a trainable dtype.
  bool ShouldRecord(absl::Span<const int64_t> tensor_ids,
                    absl::Span<const tensorflow::DataType> dtypes) const;

  // Adds this tensor to the list of watched tensors.
  //
  // This is a no-op if the tensor is already being watched either from an

    sdkmanager 'extras;m2repository;com;android;support;constraint;constraint-layout;1.0.0'; \
    sdkmanager 'extras;m2repository;com;android;support;constraint;constraint-layout-solver;1.0.2'; \
    sdkmanager 'patcher;v4'; \
    sdkmanager 'ndk;25.1.8937393'; \
    sdkmanager 'build-tools;27.0.3';

# Install Scoop and packages
RUN iex \"& {$(irm get.scoop.sh)} -RunAsAdmin\"; \
    scoop install perl; \

  rpm2cpio "devtoolset-10-gcc-10.2.1-11.2.el7.src.rpm" |cpio -idmv
  tar -xvf "gcc-10.2.1-20210130.tar.xz" --strip 1
  ;;
esac

# Apply the devtoolset patches to gcc.
/rpm-patch.sh "gcc.spec"

./contrib/download_prerequisites

mkdir -p "${TARGET}-build"
cd "${TARGET}-build"

"${TARGET}-src/configure" \
      --prefix="${TARGET}/usr" \

// TFE_NewTensorHandleFromDeviceMemory.
void DeallocatorWrapperFunc(void* data, size_t len, void* dlmt_vptr) {
  TFE_CallDLManagedTensorDeleter(dlmt_vptr);
}

// Checks whether the stride array matches the layout of compact, row-majored
// data.
bool IsValidStrideCompactRowMajorData(int64_t* shape_arr, int64_t* stride_arr,
                                      int ndim) {
  bool valid = true;