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  - type: dropdown
    id: tf-nightly
    attributes:
      label: Have you reproduced the bug with TensorFlow Nightly?
      description: It is strongly suggested that you reproduce the bug with [TensorFlow Nightly](https://www.tensorflow.org/install/pip#nightly)
      options:
        - "Yes"
        - "No"

1.  It must be a bug/performance issue or a feature request or a build issue or
    a documentation issue (for small doc fixes please send a PR instead).
1.  Make sure the Issue Template is filled out.
1.  The issue should be related to the repo it is created in.

**Here's why we have this policy:** We want to focus on the work that benefits
the whole community, e.g., fixing bugs and adding features. Individual support

What type of issue would you like to report? multiple: false options: - Bug -
Build/Install - Performance - Support - Feature Request - Documentation Feature
Request - Documentation Bug - Others validations: required: true - type:
markdown attributes: value: | Please make sure that this is a bug. As per our
[GitHub Policy](https://github.com/tensorflow/tensorflow/blob/master/ISSUES.md),we
only address code/doc bugs, performance issues, feature requests and

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;
      }

  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) {

research](https://scholar.google.com/scholar?q=gpu+side+channel) shows that it
might be possible to use side channel attacks on the GPU to leak data from other
running models or processes in the same system. GPUs can also have
implementation bugs that might allow attackers to leave malicious code running
and leak or tamper with applications from other users. Please report
vulnerabilities to the vendor of the affected hardware accelerator.

## Reporting vulnerabilities

    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