`max_batch_size` for building TensorRT engines. Add parameters
        `use_dynamic_shape` to enable dynamic shape support. The default is to
        disable dynamic shape support. Add `dynamic_shape_profile_strategy` for
        selecting a dynamic shape profile strategy. The default is profile
        strategy is `Range`.
    *   Issue a warning when function get_tensorrt_rewriter_config is used.

  if (reader_ != nullptr) {
    status = reader_->GetTensor(name, out_tensor);
  } else {
    tensorflow::DataType dtype;
    tensorflow::TensorShape shape;
    status = v2_reader_->LookupDtypeAndShape(name, &dtype, &shape);
    if (status.ok()) {
      out_tensor->reset(new Tensor(dtype, shape));
      status = v2_reader_->Lookup(name, out_tensor->get());
      if (!status.ok()) out_tensor->reset();
    }
  }
  if (!status.ok()) {

                    /*input_tensors*/ {},
                    /*expected_shape*/ make_shape({3, kUnknownDim}));

  // Infer shape when some dimensions are unknown.
  CheckOutputShapes(
      matmul_op,
      /*input_shapes*/ {make_shape({kUnknownDim, 2}), make_shape({2, 4})},
      /*input_tensors*/ {},
      /*expected_shape*/ make_shape({kUnknownDim, 4}));

  // Infer shape when everything is unknown.

    /**
     * 
     */
    public static final int SMB2_SHARE_CAP_DFS = 0x8;

    /**
     * 
     */
    public static final int SMB2_SHARE_CAP_CONTINUOUS_AVAILABILITY = 0x10;

    /**
     * 
     */
    public static final int SMB2_SHARE_CAP_SCALEOUT = 0x20;

    /**
     * 
     */
    public static final int SMB2_SHARE_CAP_CLUSTER = 0x40;

    /**
     * 
     */

  auto c_api_client = down_cast<xla::PjRtCApiClient*>(pjrt_client->get());
  std::vector<int32_t> data(1, 0);
  xla::Shape shape = xla::ShapeUtil::MakeShape(xla::S32, {1});

  auto buffer = c_api_client->pjrt_c_client()->client->BufferFromHostBuffer(
      data.data(), shape.element_type(), shape.dimensions(),
      /*byte_strides=*/std::nullopt,
      xla::PjRtClient::HostBufferSemantics::kImmutableOnlyDuringCall, nullptr,

    private String share;            // Can be null
    private long createTime;
    private long lastModified;
    private int attributes;
    private long attrExpiration;
    private long size;
    private long sizeExpiration;
    private boolean isExists;
    private int shareAccess = FILE_SHARE_READ | FILE_SHARE_WRITE | FILE_SHARE_DELETE;
    private SmbComBlankResponse blank_resp = null;

    sequence_shapes = {
        SHAPE_LIST,
        SHAPE_SET,
        SHAPE_FROZENSET,
        SHAPE_TUPLE,
        SHAPE_SEQUENCE,
        SHAPE_TUPLE_ELLIPSIS,
    }
    sequence_shape_to_type = {
        SHAPE_LIST: list,
        SHAPE_SET: set,
        SHAPE_TUPLE: tuple,
        SHAPE_SEQUENCE: list,
        SHAPE_TUPLE_ELLIPSIS: list,
    }

    @dataclass

    /**
     * 
     */
    private TestProperties () {}

    static final String TEST_SHARE_URL_MAIN = "test.share.main.url";
    static final String TEST_SHARE_URL_DFSROOT = "test.share.dfsroot.url";

    static final String TEST_SHARE_MAIN = "test.share.main";
    static final String TEST_SHARE_GUEST = "test.share.guest";

    static final String TEST_USER_NAME = "test.user.name";

  // devices of a ParallelDevice. If called, ParallelTensor::Shape inspects
  // `components` to determine a shape.
  static std::unique_ptr<ParallelTensor> FromTensorHandles(
      const ParallelDevice& parallel_device,
      std::vector<TensorHandlePtr> components, TF_Status* status);
  // Uses the provided shape without additional checks, which avoids blocking
  // when ParallelTensor::Shape is called.

  std::vector<int64_t> shape;
  int rank = -1;
  *status = handle.NumDims(&rank);
  if (!status->ok()) {
    return shape;
  }
  shape.reserve(rank);
  for (int i = 0; i < rank; ++i) {
    int64_t dim;
    *status = handle.Dim(i, &dim);
    if (!status->ok()) {
      return shape;
    }
    shape.push_back(dim);
  }
  return shape;
}

}  // namespace

extern "C" {