text: import numpy as np
  import tensorflow as tf
  
  from onnx_tf.handlers.backend_handler import BackendHandler
  from onnx_tf.handlers.handler import onnx_op
  from onnx_tf.common import data_type
  from onnx import mapping
  
  
  @onnx_op("SequenceEmpty")
  class SequenceEmpty(BackendHandler):
  
    @classmethod
    def version_11(cls, node, **kwargs):
      default_dtype = mapping.NP_TYPE_TO_TENSOR_TYPE[np.dtype('float32')]
      dtype = data_type.onnx2tf(node.attrs.get("dtype", default_dtype))
  
      ragged = tf.RaggedTensor.from_row_lengths(values=[], row_lengths=[])
      sparse = tf.cast(ragged.to_sparse(), dtype)
      return [tf.RaggedTensor.from_sparse(sparse)]
  