The security impact of skipping those checks should be low, since the attack
scenario would require a malicious user to be able to control the model which as
stated above is already equivalent to code execution. In any case, the
recommendation is not to serve models using Eager mode since it also has
performance limitations.

## Multi-Tenant environments

It is possible to run multiple TensorFlow models in parallel. For example,

    states. Specifically, it no longer ever drops the `c` (memory) state of an
    `LSTMStateTuple`. The new behavior leads to proper dropout behavior for
    LSTMs and stacked LSTMs. This bug fix follows recommendations from published
    literature, but is a behavioral change. State dropout behavior may be
    customized via the new `dropout_state_filter_visitor` argument.