* 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.
       * Refer [linux setup guide](https://www.tensorflow.org/install/gpu#linux_setup).

# limitations under the License.
# ==============================================================================
"""
Top-level module of TensorFlow. By convention, we refer to this module as
`tf` instead of `tensorflow`, following the common practice of importing
TensorFlow via the command `import tensorflow as tf`.

The primary function of this module is to import all of the public TensorFlow

        base: ${{ github.event.inputs.release_branch }}
        branch: ${{ github.event.inputs.release_branch }}-${{ steps.cherrypick.outputs.SHORTSHA }}
        reviewers: learning-to-play
        body: |

may exist in your changes.

#### Running unit tests

There are two ways to run TensorFlow unit tests.

1.  Using tools and libraries installed directly on your system.

    Refer to the
    [CPU-only developer Dockerfile](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/dockerfiles/dockerfiles/devel-cpu.Dockerfile)
    and

        `trace_on`.

*   `tf.estimator`

    *   The tf.estimator API is removed.

*   Keras 3.0 will be the default Keras version. You may need to update your
    script to use Keras 3.0.

*   Please refer to the new Keras documentation for Keras 3.0
    (https://keras.io/keras_3).

*   To continue using Keras 2.0, do the following.

*   1.  Install tf-keras via pip install tf-keras~=2.16

 private:
  TensorTape tensor_tape_;
  OpTape<BackwardFunction, TapeTensor> op_tape_;
  int64_t next_op_id_{0};

  // Map from tensor id to number of remaining usages (i.e. how many entries in
  // the tape refer to it); to aid in tape garbage collection.
  std::unordered_map<int64_t, int64_t> tensor_usage_;

  // If false, all activations are deleted in the first call to ComputeGradient.
  // Else, only when this is destructed.

// the corresponding function's output will equal to this input,
// instead of the original node's output.
//
// Callers must also satisfy the following constraints:
// - `inputs` cannot refer to TF_Outputs within a control flow context. For
//   example, one cannot use the output of "switch" node as input.
// - `inputs` and `outputs` cannot have reference types. Reference types are