class_docstr: The layer that adds up object sequences.
  
  :param input_layer: The input layer and the number of its output. If no number
      is specified, the first output will be connected.
  :type input_layer: object, tuple(object, int)
  :param name: The layer name.
  :type name: str, default=None
  
  .. rubric:: Layer inputs:
  
  (1) a set of object sequences.
      The dimensions:
  
      - **BatchLength** is the sequence length
      - **BatchWidth** is the number of sequences in the set
      - **ListSize** is 1
      - **Height** * **Width** * **Depth** * **Channels** is the object size
  
  .. rubric:: Layer outputs:
  
  (1) the results of adding up each of the sequences.
      The dimensions:
  
      - **BatchLength** is 1
      - the other dimensions are the same as for the input
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code: def __init__(self, input_layer, name=None):
      if type(input_layer) is PythonWrapper.SequenceSum:
          super().__init__(input_layer)
          return
  
      layers, outputs = check_input_layers(input_layer, 1)
  
      internal = PythonWrapper.SequenceSum(
          str(name), layers[0], int(outputs[0])
      )
      super().__init__(internal)
  
imports: import neoml.PythonWrapper
  from .Dnn import Layer
  from neoml.Utils import check_input_layers
label_desc: Use image node_id 1 to create a new SequenceSum object from inherited base classes: Layer with example: obj = SequenceSum(input_layer, name)