class_docstr: The layer that finds the maximum element along the given dimension. 
  
  :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 dimension: The dimension along which the maximum is to be found.
  :type dimension: str, {'batch_length', 'batch_width', 'list_size', 'height', 'width',
      'depth', 'channels'}, default='channels'
  :param name: The layer name.
  :type name: str, default=None
  
  .. rubric:: Layer inputs:
  
  (1) a data blob of any size
  
  .. rubric:: Layer outputs:
  
  (1) contains the coordinate of the maximum
      The dimensions:
  
      - 'dimension' along which the maximum is found is equal to 1
      - all other dimensions are equal to the first input dimensions
docstr: Sets the dimension along which the maximum is to be found.
          
docstr_tok: ["Sets","the","dimension","along","which","the","maximum","is","to","be","found","."]
code: def dimension(self, dimension):
      """Sets the dimension along which the maximum is to be found."""
      dimension_index = self.dimensions.index(dimension)
  
      self._internal.set_dimension(dimension_index)
  
file_path: neoml/NeoML/Python/neoml/Dnn/Argmax.py
imports: import neoml.PythonWrapper
  from .Dnn import Layer
  from neoml.Utils import check_input_layers
label_desc: Use image node_id 3 for calling the Argmax obj's underlying member method code with example usage: obj.dimension(dimension) without return types