prove that your code works correctly, and b) guard against future breaking
    changes to lower the maintenance cost.
*   Bug fixes also generally require unit tests, because the presence of bugs
    usually indicates insufficient test coverage.
*   Keep API compatibility in mind when you change code in core TensorFlow,
    e.g., code in

  EXPECT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  EXPECT_EQ("bunny", string(static_cast<const char*>(value.get()), 5));
}

TEST_F(CApiAttributesTest, StringList) {
  std::vector<string> list = {"bugs", "bunny", "duck"};
  std::unique_ptr<const void*[]> list_ptrs;
  std::unique_ptr<size_t[]> list_lens;
  StringVectorToArrays(list, &list_ptrs, &list_lens);
  int list_total_size = 0;
  for (const auto& s : list) {

    *   Customize request timeouts for the GCS filesystem.
    *   Improve GCS filesystem caching.
*   Bug Fixes:
    *   Fix bug where partitioned integer variables got their wrong shapes.
        Before
    *   Fix correctness bug in CPU and GPU implementations of Adadelta.
    *   Fix a bug in `import_meta_graph`'s handling of partitioned variables

libcudnn8=8.9.6.50-1+cuda12.2
libcudnn8-dev=8.9.6.50-1+cuda12.2

# This can be removed once NVIDIA publishes a cuda-12.3.2 Docker image.
# For now it ensures that we install at least version 12.3.107 of PTXAS,
# since 12.3.103 has a bug.

COPY cuda.packages.txt /cuda.packages.txt
RUN /setup.sources.sh && /setup.packages.sh /devel.packages.txt

# Install various tools.
# - bats: bash unit testing framework
#         NOTE: v1.6.0 seems to have a bug that made "git" in setup_file break
# - bazelisk: always use the correct bazel version
# - buildifier: clean bazel build deps
# - buildozer: clean bazel build deps

      if (prefix != nullptr && !absl::StartsWith(n->name(), prefix_cmp)) {
        status->status = tensorflow::errors::Internal(
            "BUG: The gradients prefix have been unexpectedly altered when "
            "adding the nodes to the graph. This is a bug. Please file an "
            "issue at https://github.com/tensorflow/tensorflow/issues.");
        return;
      }