const void* const* values,
                                 const size_t* lengths,
                                 int num_values) override {
    if (strcmp(attr_name, tensorflow::kColocationAttrName) == 0) {
      op_->colocation_constraints.clear();
      for (int i = 0; i < num_values; ++i) {
        op_->colocation_constraints.emplace(static_cast<const char*>(values[i]),

		message:    "Time stamp format pattern contains a valid format symbol that cannot be applied to time stamp parsing in the SQL expression.",
		statusCode: 400,
		cause:      err,
	}
}

func errEvaluatorTimestampFormatPatternDuplicateFields(err error) *s3Error {
	return &s3Error{
		code:       "EvaluatorTimestampFormatPatternDuplicateFields",

  TF_RETURN_IF_ERROR(op->Reset("ZerosLike", /*raw_device_name=*/nullptr));
  if (isa<tracing::TracingOperation>(op.get())) {
    TF_RETURN_IF_ERROR(dyn_cast<tracing::TracingOperation>(op.get())->SetOpName(
        absl::StrCat("ZerosLike", ToId(t)).c_str()));
  }
  TF_RETURN_IF_ERROR(op->AddInput(t));
  int num_outputs = 1;
  std::vector<AbstractTensorHandle*> outputs(num_outputs);
  TF_RETURN_IF_ERROR(

    int port = tensorflow::testing::PickUnusedPortOrDie();
    job_def->mutable_tasks()->insert({i, absl::StrCat("localhost:", port)});
  }
  auto* config = server_def.mutable_default_session_config();
  config->mutable_experimental()->set_collective_group_leader(
      absl::StrCat("/job:", job_name, "/replica:0/task:", 0));
  auto* rewrite_options =
      config->mutable_graph_options()->mutable_rewrite_options();

  tensorflow::JobDef* job_def = server_def->mutable_cluster()->mutable_job(0);
  int port = tensorflow::testing::PickUnusedPortOrDie();
  job_def->mutable_tasks()->at(task_index) = absl::StrCat("localhost:", port);
}

void CheckTFE_TensorHandleHasFloats(TFE_TensorHandle* handle,
                                    const std::vector<float>& expected_values) {

      session->graph, absl::StrCat("fifo_queue_enqueue_", tensor_id).c_str());
  if (enqueue_op == nullptr) {
    status->status = tensorflow::errors::Internal(
        "Unable to find the enqueue node in the TF graph.");
    return;
  }

  TF_Operation* placeholder_op = TF_GraphOperationByName(
      session->graph, absl::StrCat("arg_tensor_enqueue_", tensor_id).c_str());

        final int rlast = result.length - 1;
        int i = 0, b = 0;
        final int len = path.length();
        int strip = 0;

        do {
            if (ri == rlast) {
                result[rlast] = path.substring(b);
                result[rlast] = path.substring(b);
                return strip;
            }
            if (i == len || path.charAt(i) == '\\') {
                result[ri] = path.substring(b, i);

    if not elem.text or not elem.text.strip():
      elem.text = indent_str + '  '
    if not elem.tail or not elem.tail.strip():
      elem.tail = indent_str
    for elem in elem:
      indent_xml(elem, level + 1)
    if not elem.tail or not elem.tail.strip():
      elem.tail = indent_str
  else:
    if level and (not elem.tail or not elem.tail.strip()):
      elem.tail = indent_str

  switch (ctx.device_type) {
    case DLDeviceType::kDLCPU:
      return "CPU:0";
    case DLDeviceType::kDLCUDA:
      return absl::StrCat("GPU:", ctx.device_id);
    case DLDeviceType::kDLROCM:
      return absl::StrCat("GPU:", ctx.device_id);
    default:
      return absl::nullopt;
  }
}

// Converts DLPack data type to TF_DATATYPE.

    except subprocess.CalledProcessError as e:
      output = e.output
  else:
    output = subprocess.check_output(cmd, stderr=stderr)
  return output.decode('UTF-8').strip()


def cygpath(path):
  """Convert path from posix to windows."""
  return os.path.abspath(path).replace('\\', '/')


def get_python_path(environ_cp, python_bin_path):