If the behavior is threatening or harassing, or for other reasons requires immediate escalation, please see below.

However, for the vast majority of issues, we aim to empower individuals to first resolve conflicts themselves, asking for help when needed, and only after that fails to escalate further. This approach gives people more control over the outcome of their dispute. 

if [[ "$TFCI_ARTIFACT_FINAL_GCS_ENABLE" == 1 ]]; then
  gcloud auth activate-service-account --key-file="$TFCI_ARTIFACT_FINAL_GCS_SA_PATH"

  # $TF_VER_FULL will resolve to e.g. "2.15.0-rc2". Since $TF_VER_FULL comes
  # from get_versions.sh, which must be run *after* update_version.py, FINAL_URI
  # can't be set inside the rest of the _upload envs.

  # Source the default ci values
  source ./ci/official/envs/ci_default

  # TODO(angerson) write this documentation
  # Sources every env, in order, from the comma-separated list "TFCI"
  # 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

}

inline Status AbstractOperation::SetAttrStringList(
    const char* attr_name, absl::Span<string const> values) {
  std::vector<const char*> raw_strs;
  std::vector<size_t> lengths;
  raw_strs.reserve(values.size());
  lengths.reserve(values.size());
  for (const auto& s : values) {
    raw_strs.emplace_back(s.data());
    lengths.emplace_back(s.size());
  }
  return SetAttrStringList(attr_name,

-    __attribute__ ((weak, alias (#name), __visibility__ ("hidden")));
+    __attribute__ ((weak, alias (#name), __visibility__ ("hidden"))) \
+    __attribute_copy__ (name);
 
 /* Declare SYMBOL as weak undefined symbol (resolved to 0 if not defined).  */
 # define weak_extern(symbol) _weak_extern (weak symbol)
@@ -528,7 +536,8 @@ for linking")
 #  define __hidden_ver1(local, internal, name) \

    tensorflow::shape_inference::InferenceContext* ic, int num_dims,
    const int64_t* dims) {
  if (num_dims != -1) {
    std::vector<tensorflow::shape_inference::DimensionHandle> dim_vec;
    dim_vec.reserve(num_dims);
    for (int i = 0; i < num_dims; ++i) {
      dim_vec.push_back(ic->MakeDim(dims[i]));
    }
    return ic->MakeShape(dim_vec);
  } else {
    return ic->UnknownShape();
  }
}

*   Clone the TensorFlow repo and switch to the corresponding branch for your
    desired TensorFlow version, for example, branch `r2.8` for version 2.8.
*   Apply (that is, cherry-pick) the desired changes and resolve any code
    conflicts.
*   Run TensorFlow tests and ensure they pass.
*   [Build](https://www.tensorflow.org/install/source) the TensorFlow pip
    package from source.

## Continuous build status

  // Returns the device ID which created the handle.
  virtual int DeviceId(Status* status) const = 0;
  // Returns a tensor for the handle. If tensor is remote, it will be copied.
  virtual AbstractTensorInterface* Resolve(Status* status) = 0;

  std::string DebugString() const override;

  // Returns a Boolean hint indicating whether callers should prefer
  // `SummarizeValue` to resolving this handle and formatting the tensor.
  //

    return result;
  }
  std::vector<ParallelTensor*> parallel_inputs;
  std::vector<std::unique_ptr<ParallelTensor>> implicitly_broadcast_tensors;
  parallel_inputs.reserve(inputs.size());
  implicitly_broadcast_tensors.reserve(inputs.size());  // not tight
  for (const auto& input : inputs) {
    if (absl::holds_alternative<TFE_TensorHandle*>(input)) {
      if (operation_name == std::string("_EagerConst")) {

      # to remove it.
      key = re.sub(r"0x\w+", "", p.getparent().get("name", "")) + p.text
      if key in seen:
        testsuite._elem.remove(p.getparent())
      seen[key] += 1
    # Remove this testsuite if it doesn't have anything in it any more
    if len(testsuite) == 0:  # pylint: disable=g-explicit-length-test
      r._elem.remove(testsuite._elem)