* <a href="https://fastapi.tiangolo.com/tutorial/dependencies/dependencies-in-path-operation-decorators/" class="external-link" target="_blank">Tutorial - Dependencies - Dependencies in path operation decorators</a>.
    * <a href="https://fastapi.tiangolo.com/tutorial/dependencies/global-dependencies/" class="external-link" target="_blank">Tutorial - Dependencies - Global Dependencies</a>.

    * Add experimental supports conversion of models that may be larger than 2GB before buffer deduplication

### Bug Fixes and Other Changes

* `tf.py_function` and `tf.numpy_function` can now be used as function decorators for clearer code:
   ```
   @tf.py_function(Tout=tf.float32)
   def my_fun(x):
     print("This always executes eagerly.")
     return x+1
   ```

* `tf.lite`