)
   ```

4) Add the version to `SUPPORTED_VERSIONS` in `updater.sh`, and
   `release_updater.sh`

5) Run the `updater.sh` shell script. \
   If the base requirements file hasn't yet been updated to account for the new
   Python version, which will require different versions for at least some
   dependencies, it will need to be updated now, for the script to run
   successfully.

// Causes the calling thread to block till all ops dispatched in this executor
// have been executed. Note that "execution" here refers to kernel execution /
// scheduling of copies, etc. Similar to sync execution, it doesn't guarantee
// that lower level device queues (like GPU streams) have been flushed.
//
// This call may not block for execution of ops enqueued concurrently with this
// call.

team member will apply `ready to pull` label to your change. This means we are
working on getting your pull request submitted to our internal repository. After
the change has been submitted internally, your pull request will be merged
automatically on GitHub.

If you want to contribute, start working through the TensorFlow codebase,
navigate to the

  Status RegisterFunction(AbstractFunction* func) override {
    return errors::Unimplemented(
        "Registering graph functions has not been implemented yet.");
  }

  Status RemoveFunction(const string& func) override {
    return errors::Unimplemented(
        "GraphContext::RemoveFunction has not been implemented yet.");
  }
  // For LLVM style RTTI.
  static bool classof(const AbstractContext* ptr) {

  TFE_TensorHandle* h1_task0 = TestMatrixTensorHandle(ctx);
  std::vector<TFE_TensorHandle*> handles_task0;
  if (heavy_load_on_streaming_rpc) {
    // Send 50 tensor copy requests to simulate that there have been some RPC
    // requests been enqueued.
    for (int i = 0; i < 50; ++i) {
      handles_task0.push_back(TestMatrixTensorHandle(ctx));
    }
  }
  const char task1_name[] = "/job:localhost/replica:0/task:1/device:CPU:0";

        "operations on them have been supplied.");

  if ((ops->filesystem_ops->new_writable_file != nullptr ||
       ops->filesystem_ops->new_appendable_file != nullptr) &&
      ops->writable_file_ops == nullptr)
    return errors::FailedPrecondition(
        "Filesystem allows creation of writable files but no "
        "operations on them have been supplied.");

*   `tf.sparse.segment_sum` `tf.sparse.segment_mean` `tf.sparse.segment_sqrt_n` `SparseSegmentSum/Mean/SqrtN[WithNumSegments]`

    *   Added `sparse_gradient` option (default=false) that makes the gradient of these functions/ops sparse (`IndexedSlices`) instead of dense (`Tensor`), using new `SparseSegmentSum/Mean/SqrtNGradV2` ops.

*   `tf.nn.embedding_lookup_sparse`

   1. Definitions.

      "License" shall mean the terms and conditions for use, reproduction,
      and distribution as defined by Sections 1 through 9 of this document.

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  /// succeeded,
  ///    but the read returned a partial block, and the LRU cache contained a
  ///    block at a higher offset (indicating that the partial block should have
  ///    been a full block).
  /// 3) `TF_OUT_OF_RANGE` if the read from the remote filesystem succeeded, but
  ///    the file contents do not extend past `offset` and thus nothing was
  ///    placed in `out`.

  ///
  /// Note: the `buffer` argument is NOT a null terminated string!
  ///
  /// Plugins:
  ///   * Must set `status` to `TF_OK` if exactly `n` bytes have been read.
  ///   * Must set `status` to `TF_OUT_OF_RANGE` if fewer than `n` bytes have
  ///     been read due to EOF.
  ///   * Must return -1 for any other error and must set `status` to any
  ///     other value to provide more information about the error.