some form of isolation when dealing with untrusted data. As a result, this
document also outlines what issues we consider as TensorFlow security
vulnerabilities.

We recognize issues as vulnerabilities only when they occur in scenarios that we
outline as safe; issues that have a security impact only when TensorFlow is used
in a discouraged way (e.g. running untrusted models or checkpoints, data parsing

        and `tf.keras.layers.LocallyConnected1D`. The new mode
        (`implementation=2`) performs forward pass as a single dense matrix
        multiplication, allowing dramatic speedups in certain scenarios (but
        worse performance in others - see docstring). The option also allows to
        use `padding=same`.
    *   Add documentation clarifying the differences between tf.fill and
        tf.constant.