}
  }

  // Returns whether any tensor in a list of tensors is being watched and has
  // a trainable dtype.
  bool ShouldRecord(absl::Span<const int64_t> tensor_ids,
                    absl::Span<const tensorflow::DataType> dtypes) const;

  // Adds this tensor to the list of watched tensors.
  //
  // This is a no-op if the tensor is already being watched either from an

// a final shape of [2, 2] based on shape merging semantics.
//
// Returns an error into `status` if:
//   * `output` is not in `graph`.
//   * An invalid shape is being set (e.g., the shape being set
//     is incompatible with the existing shape).
TF_CAPI_EXPORT extern void TF_GraphSetTensorShape(TF_Graph* graph,
                                                  TF_Output output,

// setting the same key will lead to errors.
//
// Note that the key-values are only expected to be used for cluster
// configuration data, and should not be used for storing a large amount of data
// or being accessed very frequently.
TF_CAPI_EXPORT extern void TFE_InsertConfigKeyValue(TFE_Context* ctx,
                                                    const char* key,

  if (TF_GetCode(status) == TF_OK) {
    // This modification only updates the destination node for
    // the purposes of running this graph in a session. Thus, we don't
    // record the source node as being modified.
    RecordMutation(graph, *dst.oper, "updating input tensor");
  }
}

// Apis that are corresponding to python c api. --------------------------

TF_CAPI_EXPORT void TF_SetXlaMinClusterSize(int size);

// Gets/Sets TF/XLA flag for whether(true) or not(false) to disable constant
// folding. This is for testing to ensure that XLA is being tested rather than
// Tensorflow's CPU implementation through constant folding.
TF_CAPI_EXPORT unsigned char TF_GetXlaConstantFoldingDisabled();
TF_CAPI_EXPORT void TF_SetXlaConstantFoldingDisabled(

    size_t requested_read_length;
    if (n > INT32_MAX)
      requested_read_length = INT32_MAX;
    else
      requested_read_length = n;

    // `pread` returns a `ssize_t` on POSIX, but due to interface being
    // cross-platform, return type of `Read` is `int64_t`.
    int64_t r = int64_t{pread(posix_file->fd, dst, requested_read_length,
                              static_cast<off_t>(offset))};
    if (r > 0) {
      dst += r;

      returns without waiting for the snapshot to finish. Setting `wait=True` to
      `tf.data.Dataset.load` allows the snapshots to be read while they are
      being written.

### Bug Fixes and Other Changes

* <SIMILAR TO ABOVE SECTION, BUT FOR OTHER IMPORTANT CHANGES / BUG FIXES>
* <IF A CHANGE CLOSES A GITHUB ISSUE, IT SHOULD BE DOCUMENTED HERE>
* <NOTES SHOULD BE GROUPED PER AREA>

  // The devices operations run on.
  const std::vector<std::string>& underlying_devices() const {
    return underlying_devices_;
  }

  // Takes a description of a single operation being executed on the
  // ParallelDevice, and in turn runs one operation per component device with
  // its corresponding inputs from the input ParallelTensors. Wraps the
  // resulting per-device and per-output TFE_TensorHandles into one

  }

  const char* func_name_ = "MyFunc";
  const char* func_node_name_ = "MyFunc_0";
  TF_Status* s_;
  TF_Graph* func_graph_;
  TF_Graph* host_graph_;
  TF_Function* func_;

  // Workaround for not being able to initialize empty map using {}
  std::unordered_set<string> empty_;
};

TEST_F(CApiFunctionTest, OneOp_ZeroInputs_OneOutput) {
  /*
   *                constant
   *                   |

  /// won't be registered anymore is if this function gets called by core
  /// TensorFlow and the `TF_Filesystem*` object is destroyed. However, due to
  /// registration being done in a static instance of `Env`, the destructor of
  /// `FileSystem` is never called (see
  /// https://github.com/tensorflow/tensorflow/issues/27535). In turn, this