come with the compiler are not designed to be used with untrusted data and
should be used with caution when working with untrusted models.

### Saved graphs and checkpoints

When loading untrusted serialized computation graphs (in form of a `GraphDef`,
`SavedModel`, or equivalent on-disk format), the set of computation primitives
available to TensorFlow is powerful enough that you should assume that the
TensorFlow process effectively executes arbitrary code.

    you, it may be us who may have hit a snag. Please be patient while we work
    to fix this.
-   Once the internal tests pass, we go ahead and merge the code internally as
    well as externally on GitHub.

In a graphical form, the entire lifetime of a PR looks like

![image](https://github.com/tensorflow/tensorflow/assets/52792999/3eea4ca5-daa0-4570-b0b5-2a2b03a724a3)

### Contributor License Agreements

*   Update docstring for gather to properly describe the non-empty `batch_dims`
    case.
*   Added `tf.sparse.from_dense` utility function.
*   Improved ragged tensor support in `TensorFlowTestCase`.
*   Makes the a-normal form transformation in Pyct configurable as to which
    nodes are converted to variables and which are not.
*   `ResizeInputTensor` now works for all delegates.
*   Add `EXPAND_DIMS` support to NN API delegate TEST: expand_dims_test

# Enable the runfiles symlink tree on Windows. This makes it possible to build
# the pip package on Windows without an intermediate data-file archive, as the
# build_pip_package script in its current form (as of Aug 2023) uses the
# runfiles symlink tree to decide what to put into the Python wheel.
startup --windows_enable_symlinks
build:windows --enable_runfiles

# Default paths for TF_SYSTEM_LIBS