"${TARGET}-src/configure" \
      --prefix="${TARGET}/usr" \
      --with-sysroot="/${TARGET}" \
      --disable-bootstrap \
      --disable-libmpx \
      --enable-libsanitizer \
      --disable-libunwind-exceptions \
      --disable-libunwind-exceptions \
      --disable-lto \
      --disable-multilib \
      --enable-__cxa_atexit \
      --enable-gnu-indirect-function \
      --enable-gnu-unique-object \
      --enable-initfini-array \

#ifndef TENSORFLOW_C_C_OP_REQUIRES_H_
#define TENSORFLOW_C_C_OP_REQUIRES_H_

#include "tensorflow/core/platform/macros.h"

namespace tensorflow {

// Convenience macros for asserting and handling exceptional conditions, for
// C structs, including `TF_OpKernelContext`, `TF_Status`, etc. This is analogus
// to the macros in tensorflow/core/framework/op_requires.h. This is provided
// for plugin OpKernel developer's convenience.

#   which mounts your TensorFlow directory into the container.
#
#   Important: because the container is persistent, you cannot change TFCI
#   variables in between script executions. To forcibly remove the
#   container and start fresh, run "docker rm -f tf". Removing the container
#   destroys some temporary bazel data and causes longer builds.
#

variables as part of those interactions (ex: using a string variable to build a
filesystem path), a maliciously created checkpoint might be able to change the
targets of those operations, which could result in arbitrary
read/write/executions.

### Running a TensorFlow server

TensorFlow is a platform for distributed computing, and as such there is a
TensorFlow server (`tf.train.Server`). The TensorFlow server is intended for

      # skip non-importable paths
      if short_package_name not in self.packages_for_skip:
        try:
          __import__(short_package_name)
        except ImportError:
          logging.exception("error importing %s", short_package_name)
          failed_packages.append(package_name)

    if failed_packages:
      self.fail(
          "Failed to import"

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)
  except Exception as e:  # pylint: disable=broad-except
    print("Ignoring this XML parse failure in {}: ".format(f), str(e))

  source_file = re.search(
      r"/(bazel_pip|tensorflow)/.*", f.decode("utf-8")
  ).group(0)