docker stop $running_containers;
          fi
          docker container prune -f
      - name: Clean repository
        shell: bash
        run: find /home/ubuntu/actions-runner/_work/tensorflow/tensorflow/. -name . -o -prune -exec sudo rm -rf -- {} + || true
      - name: Checkout repository
        uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1

      ReluModel, ReluGradModel, immediate_execution_ctx_.get(), {X.get()},
      UseFunction()));

  // Mathematically, Relu isn't differentiable at `0`. So `gradient_checker`
  // does not work with it.
  AbstractTensorHandlePtr Y;
  {
    AbstractTensorHandle* Y_raw;
    status_ = TestScalarTensorHandle<float, TF_FLOAT>(
        immediate_execution_ctx_.get(), 0.0f, &Y_raw);

      // and hence expect the input to be forwarded to the return tensor.
      EXPECT_EQ(orig_ptr, TF_TensorData(t));
    } else {
      // In async mode we expect forwarding to work without releasing the input
      // handle since by the time the kernel is executed we have released the
      // handle in the client code.
      EXPECT_EQ(orig_ptr, TF_TensorData(t));
    }
  } else {

    TF_SetStatus(status, TF_OK, "");
    return n;
  };
  tf_gcs_filesystem::RamFileBlockCache cache(block_size, block_size, 0,
                                             fetcher);
  // Fork off thread for parallel read.
  std::unique_ptr<Thread> concurrent(
      Env::Default()->StartThread({}, "concurrent", [block_size, &cache] {
        std::vector<char> out;

  TF_Status* s = TF_NewStatus();
  const char* tags[] = {tensorflow::kSavedModelTagServe};
  TF_Graph* graph = TF_NewGraph();
  // NULL run_options and meta_graph_def should work.
  TF_Session* session = TF_LoadSessionFromSavedModel(
      opt, nullptr, saved_model_dir.c_str(), tags, 1, graph, nullptr, s);
  EXPECT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_DeleteSessionOptions(opt);

            docker stop $running_containers;
          fi
          docker container prune -f
      - name: Clean repository
        shell: bash
        run: find /home/ubuntu/actions-runner/_work/tensorflow/tensorflow/. -name . -o -prune -exec sudo rm -rf -- {} + || true
      - name: Checkout repository for nightly (skipped for releases)
        if: ${{ github.event_name == 'schedule' }}

          fi
          docker container prune -f
          docker image prune -af
      - name: Clean repository
        shell: bash
        run: find /home/ubuntu/actions-runner/_work/tensorflow/tensorflow/. -name . -o -prune -exec sudo rm -rf -- {} + || true
      - name: Checkout repository for nightly (skipped for releases)
        if: ${{ github.event_name == 'schedule' }}

  options->stack_size = 0;
  options->guard_size = 0;
  options->numa_node = -1;
}

TF_Thread* TF_StartThread(const TF_ThreadOptions* options,
                          const char* thread_name, void (*work_func)(void*),
                          void* param) {
  ::tensorflow::ThreadOptions cc_options;
  cc_options.stack_size = options->stack_size;
  cc_options.guard_size = options->guard_size;

  * If you work for a company that wants to allow you to contribute your work, then you'll need to sign a [corporate CLA](https://code.google.com/legal/corporate-cla-v1.0.html).

cd ..

# Symlinks in the binary distribution are set up for installation in /usr, we
# need to fix up all the links to stay within /${TARGET}.
/fixlinks.sh "/${TARGET}"

# Patch to allow non-glibc 2.12 compatible builds to work.
sed -i '54i#define TCP_USER_TIMEOUT 18' "/${TARGET}/usr/include/netinet/tcp.h"

# Download specific version of libstdc++ shared library based on the value of
# the `VERSION` parameter