# Assumes variables will resolve themselves correctly.
  set +u
  for env_file in ${TFCI//,/ }; do
    source "./ci/official/envs/$env_file"
  done
  set -u
  echo '==TFCI==: Evaluated the following TFCI variables from $TFCI:'
  export -p | grep TFCI

  # Load those stored pre-existing TFCI_ vars, if any
  if [[ -s "$FROM_ENV" ]]; then

  // ParallelTensor per output of the original operation.
  //
  // Attributes are forwarded to executed operations unmodified.
  //
  // The returned optional has a value if and only if `status` evaluates to
  // TF_OK. Bad statuses are forwarded from underlying `TFE_Execute` calls, or
  // if sanity checks on dtypes/metadata fail.
  absl::optional<std::vector<std::unique_ptr<ParallelTensor>>> Execute(

TF_CAPI_EXPORT extern void TF_DeleteFunction(TF_Function* func);

// Attempts to evaluate `output`. This will only be possible if `output` doesn't
// depend on any graph inputs (this function is safe to call if this isn't the
// case though).
//
// If the evaluation is successful, this function returns true and `output`s
// value is returned in `result`. Otherwise returns false. An error status is

*   The `SidecarEvaluatorModelExport` callback has been added to Keras as `keras.callbacks.SidecarEvaluatorModelExport`. This callback allows for exporting the model the best-scoring model as evaluated by a `SidecarEvaluator` evaluator. The evaluator regularly evaluates the model and exports it if the user-defined comparison function determines that it is an improvement.

    when doing so. Write an attack scenario that demonstrates how your issue
    violates the use cases and security assumptions defined in the threat model.
    This will help us evaluate your report quickly, especially if the issue is
    complex.
  - Whether this vulnerability is public or known to third parties. If it is,
    please provide details.