class_docstr: The layer that repeats the input sequences several times.
  
  :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 repeat_count: The number of repetitions.
  :type repeat_count: int, > 0
  :param name: The layer name.
  :type name: str, default=None
  
  .. rubric:: Layer inputs:
  
  (1) a sequence of objects.
  The dimensions:
  
      - **BatchLength** is the sequence length
      - **BatchWidth** * **ListSize** is the number of sequences in the set
      - **Height** * **Width** * **Depth** * **Channels** is the size of each object
  
  .. rubric:: Layer outputs:
  
  (1) the same sequence repeated repeat_count times.
  The dimensions:
  
      - **BatchLength** is repeat_count times larger than the input's **BatchLength**
      - all other dimensions are the same as for the input
docstr: Gets the number of repetitions.
          
docstr_tok: ["Gets","the","number","of","repetitions","."]
code: def repeat_count(self):
      """Gets the number of repetitions."""
      return self._internal.get_repeat_count()
  
file_path: neoml/NeoML/Python/neoml/Dnn/RepeatSequence.py
imports: import neoml.PythonWrapper
  from .Dnn import Layer
  from neoml.Utils import check_input_layers
label_desc: Use image node_id 2 for calling the RepeatSequence obj's underlying member method code with example usage: obj.repeat_count() and returns: self