[**sandbox**](https://developers.google.com/code-sandboxing). Memory corruptions
in TensorFlow ops can be recognized as security issues only if they are
reachable and exploitable through production-grade, benign models.

### Compilation

Compiling models via the recommended entry points described in
[XLA](https://www.tensorflow.org/xla) and
[JAX](https://jax.readthedocs.io/en/latest/jax-101/02-jitting.html)

        ":fuchsia",
        ":emscripten",
        ":ios",
    ],
    visibility = ["//visibility:public"],
)

# This flag disables all google production dependencies, intended for
# applications run with non-prod environment.
# TODO(timshen): Currently this option only disables some dependencies.
# See b/122528503.
# copybara:uncomment_begin(google-only)
# bool_flag(

 *   Added utility `tf.keras.utils.FeatureSpace`, a one-stop shop for structured data preprocessing and encoding.

TensorFlow enables developers to experiment with novel optimizations and training algorithms. TensorFlow supports a variety of applications, with a focus on training and inference on deep neural networks. Several Google services use TensorFlow in production, we have released it as an open-source project, and it has become widely used for machine learning research. In this paper, we describe the TensorFlow dataflow model and demonstrate the compelling performance that TensorFlow achieves for several...