# Don't fail if these modules are not available.
# For e.g. this file will be originally placed under tensorflow/_api/v1 which
# does not have "python", "core" directories. Then, it will be copied
# to tensorflow/ which does have these two directories.
try:
  del python
except NameError:
  pass
try:
  del core
except NameError:
  pass
try:
  del compiler
except NameError:
  pass

# targets matching the provided query, which start with // or @ but not
# //tensorflow (so it looks for //third_party, //external, etc.), and then
# gathers the list of all packages (i.e. directories) which contain those
# targets.
license_query() {
 bazel cquery --experimental_cc_shared_library "$1" --keep_going \
  | grep -e "^//" -e "^@" \
  | grep -E -v "^//tensorflow" \
  | sed -e 's|:.*||' \
  | sort -u

# "/path/bar". This script uses "gsutil rsync" instead, which acts on directory
# contents. About arguments to gsutil:
# "gsutil -m rsync" runs in parallel.
# "gsutil rsync -r" is recursive and makes directories work.
# "gsutil rsync -d" is "sync and delete files from destination if not present in source"

DOWNLOADS="$(mktemp -d)"
mkdir -p "$DOWNLOADS"
gsutil -m rsync -r "$TFCI_ARTIFACT_STAGING_GCS_URI" "$DOWNLOADS"

#               (affects 'source $TFCI')
set -euxo pipefail -o history -o allexport

# Set TFCI_GIT_DIR, the root directory for all commands, to two directories
# above the location of this file (setup.sh). We could also use "git rev-parse
# --show-toplevel", but that wouldn't work for non-git repos (like if someone
# downloaded TF as a zip archive).

       * Try adding the CUDA, CUPTI, and cuDNN installation directories to the %PATH% environment variable.
       * Refer [windows setup guide](https://www.tensorflow.org/install/gpu#windows_setup).
     * If you have above configuration and using _**Ubuntu/Linux**_ platform -
       * Try adding the CUDA, CUPTI, and cuDNN installation directories to the $LD_LIBRARY_PATH environment variable.

      return;
    }
  } else if (S_ISDIR(st.st_mode)) {
    TF_SetStatus(status, TF_FAILED_PRECONDITION, "target path is a directory");
    return;
  }

  // We cannot rename directories yet, so prevent this.
  if (stat(src, &st) != 0) {
    TF_SetStatusFromIOError(status, errno, src);
    return;
  } else if (S_ISDIR(st.st_mode)) {

# Don't fail if these modules are not available.
# For e.g. this file will be originally placed under tensorflow/_api/v1 which
# does not have "python", "core" directories. Then, it will be copied
# to tensorflow/ which does have these two directories.

try:
  del python
except NameError:
  pass
try:
  del core
except NameError:
  pass
try:
  del compiler
except NameError:
  pass

namespace {

using ::tensorflow::error::Code;

// As we need to test multiple URI schemes we need a parameterized test.
// Furthermore, since each test creates and deletes files, we will use the same
// fixture to create new directories in `SetUp`. Each directory will reside in
// `::testing::TempDir()`, will use a RNG component and the test name. This
// ensures that two consecutive runs are unlikely to clash.

# targets matching the provided query, which start with // or @ but not
# //tensorflow (so it looks for //third_party, //external, etc.), and then
# gathers the list of all packages (i.e. directories) which contain those
# targets.
license_query() {
 bazel cquery --experimental_cc_shared_library "$1" --keep_going \
  | grep -e "^//" -e "^@" \
  | grep -E -v "^//tensorflow" \
  | sed -e 's|:.*||' \
  | sort -u

# link in the whole aarch64-linux-gnu folder, as otherwise we're overlaying
# system gcc paths that we do not want to find.
# TODO(klimek): Automate linking in all non-gcc / non-kernel include
# directories.
mkdir -p "${TARGET}/usr/include/aarch64-linux-gnu"
PYTHON_VERSIONS=("python3.8" "python3.9" "python3.10" "python3.11")
for v in "${PYTHON_VERSIONS[@]}"; do