# This flag is set to true in Bazel 1.0 and newer versions. We tried to migrate
# Tensorflow to the default, however test coverage wasn't enough to catch the
# errors.
# There is ongoing work on Bazel team's side to provide support for transitive
# shared libraries. As part of migrating to transitive shared libraries, we
# hope to provide a better mechanism for control over symbol exporting, and
# then tackle this issue again.
#

    "creators": [
        {
            "name": "TensorFlow Developers"
        }
    ],
    "access_right": "open",
    "notes": "Specific TensorFlow versions can be found in the \"Versions\" list on the right side of this page.<br>See the full list of authors <a href=\"https://github.com/tensorflow/tensorflow/graphs/contributors\">on GitHub</a>."

### Hardware attacks

Physical GPUs or TPUs can also be the target of attacks. [Published
research](https://scholar.google.com/scholar?q=gpu+side+channel) shows that it
might be possible to use side channel attacks on the GPU to leak data from other
running models or processes in the same system. GPUs can also have
implementation bugs that might allow attackers to leave malicious code running

///   invariants (i.e., guarantee the preconditions before calling the operation
///   and check the postconditions after the operation returns). If plugins need
///   additional invariants, they should be checked on the plugin side and the
///   `status` out variable should be updated accordingly (e.g., to include
///   plugin version information that relates to the condition change).
///

        for all the RNG in Keras. We plan to switch on the new code path by
        default in tf 2.8, and the behavior change will likely to cause some
        breakage on user side (eg if the test is checking against some golden
        number). These 3 APIs will allow user to disable and switch back to
        legacy behavior if they prefer. In future (eg TF 2.10), we expect to

// Tensor.
// TFv2 does not depend on this conversion. There is no matching
// TF_TensorFromTensorV1 because the conversion to string is performed by the
// python side of Session.
static Status TF_TensorToTensorV1(const TF_Tensor* src, Tensor* dst) {
  Status status = TF_TensorToTensor(src, dst);
  if (!status.ok()) {
    return status;
  }

#       export TF_ANY_TARGETS="quoted list of targets, like on the command line"
#       export TF_ANY_MODE="test" or "build" or "run" (default: "test")
#       ./any.sh
#
# 2. RUN ANY OTHER SCRIPT AND ENV WITH NO SIDE EFFECTS (NO UPLOADS)
#    To use:
#       export TFCI=ci/official/envs/env_goes_here
#       export TF_ANY_SCRIPT=ci/official/wheel.sh
#       ./any.sh
#
# 3. DO THE SAME WITH A LOCAL CACHE OR RBE:

// once (i.e., on the main function side) in running distributed functions.
// This test creates a cluster with two workers, create a variable on the
// second worker, and run a distributed function (VariableAddFunction) whose ops
// span the local and remote workers. If the graph optimization pass is executed
// on both the main function side and the component function side, an error will