requires all optimizer variables to be created at the first
        `apply_gradients()` or `minimize()` call. If your workflow calls
        optimizer to update different parts of model in multiple stages,
        please call `optimizer.build(model.trainable_variables)` before the
        training loop.
    *   **Performance regression on `ParameterServerStrategy`.** This could be

                          type: integer
                        perTryTimeout:
                          description: Timeout per attempt for a given request, including
                            the initial call and any retries.
                          type: string
                        retryOn:
                          description: Specifies the conditions under which retry
                            takes place.

                          type: integer
                        perTryTimeout:
                          description: Timeout per attempt for a given request, including
                            the initial call and any retries.
                          type: string
                        retryOn:
                          description: Specifies the conditions under which retry
                            takes place.