parameters: (node, **kwargs)
return_statement: return [crop_node]
docstring: Map MXNet's crop operator attributes to onnx's Crop operator
      and return the created node.
docstring_summary: Map MXNet's crop operator attributes to onnx's Crop operator
      and return the created node.
docstring_tokens: Map MXNet s crop operator attributes to onnx s Crop operator and return the created node .
function: def convert_crop(node, **kwargs):
      """Map MXNet's crop operator attributes to onnx's Crop operator
      and return the created node.
      """
      name, inputs, attrs = get_inputs(node, kwargs)
      num_inputs = len(inputs)
  
      y, x = list(parse_helper(attrs, "offset", [0, 0]))
      h, w = list(parse_helper(attrs, "h_w", [0, 0]))
      if num_inputs > 1:
          h, w = kwargs["out_shape"][-2:]
      border = [x, y, x + w, y + h]
  
      crop_node = onnx.helper.make_node(
          "Crop",
          inputs=[inputs[0]],
          outputs=[name],
          border=border,
          scale=[1, 1],
          name=name
      )
  
      logging.warning(
          "Using an experimental ONNX operator: Crop. " \
          "Its definition can change.")
  
      return [crop_node]
function_tokens: def convert_crop ( node , * * kwargs ) : name , inputs , attrs = get_inputs ( node , kwargs ) num_inputs = len ( inputs ) y , x = list ( parse_helper ( attrs , "offset" , [ 0 , 0 ] ) ) h , w = list ( parse_helper ( attrs , "h_w" , [ 0 , 0 ] ) ) if num_inputs > 1 : h , w = kwargs [ "out_shape" ] [ - 2 : ] border = [ x , y , x + w , y + h ] crop_node = onnx . helper . make_node ( "Crop" , inputs = [ inputs [ 0 ] ] , outputs = [ name ] , border = border , scale = [ 1 , 1 ] , name = name ) logging . warning ( "Using an experimental ONNX operator: Crop. " "Its definition can change." ) return [ crop_node ]