do not modify the License. You may add Your own attribution
          notices within Derivative Works that You distribute, alongside
          or as an addendum to the NOTICE text from the Work, provided
          that such additional attribution notices cannot be construed
          as modifying the License.

      You may add Your own copyright statement to Your modifications and

  TF_AbstractFunction* func =
      TF_FinalizeFunction(graph_ctx, add_outputs, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  // Note: TF_OutputList does not own the underlying AbstractTensors, those
  // need to be deleted explicitly.
  TF_DeleteAbstractTensor(TF_OutputListGet(add_outputs, 0));

  // Build eager context.
  TFE_ContextOptions* opts = TFE_NewContextOptions();

-   Changes are consistent with the [Coding Style](#c-coding-style).
-   Run the [unit tests](#running-unit-tests).

## How to become a contributor and submit your own code

![Screen Shot 2022-08-30 at 7 27 04 PM](https://user-images.githubusercontent.com/42785357/187579207-9924eb32-da31-47bb-99f9-d8bf1aa238ad.png)

### Typical Pull Request Workflow -

**1. New PR**

}

# It's unclear why, but running this on //tensorflow/... is faster than running
# only on affected targets, usually. There are targets in //tensorflow/lite that
# don't pass --nobuild, so they're on their own.
#
# Although buildifier checks for formatting as well, "bazel build nobuild"
# checks for cross-file issues like bad includes or missing BUILD definitions.
#

}

# It's unclear why, but running this on //tensorflow/... is faster than running
# only on affected targets, usually. There are targets in //tensorflow/lite that
# don't pass --nobuild, so they're on their own.
#
# Although buildifier checks for formatting as well, "bazel build nobuild"
# checks for cross-file issues like bad includes or missing BUILD definitions.
#

  //
  // Allows an accumulator which is currently processing an operation to
  // temporarily reset its state. Without pushing and popping, accumulators
  // ignore operations executed as a direct result of their own jvp
  // computations.
  void PushState() { call_state_.emplace(nullptr, false); }
  void PopState() { call_state_.pop(); }

 private:
  // Helper for Accumulate: uses a GradientTape to compute forward gradients

using MaybeParallelTensorOwned =
    absl::variant<std::unique_ptr<ParallelTensor>, TensorHandlePtr>;

using MaybeParallelTensorUnowned =
    absl::variant<ParallelTensor*, TFE_TensorHandle*>;

// A ParallelDevice on its own is not registered with a TFE_Context, and so has
// no device name (e.g. for `tf.device`). `NamedParallelDevice` associates a
// name with it, which lets us pack its `ParallelTensor`s into TFE_TensorHandles