original_docstring: Map MXNet's square operator attributes to onnx's Pow operator
      and return the created node.
      
docstring: Map MXNet's square operator attributes to onnx's Pow operator
  and return the created node.
docstring_tokens: Map MXNet ' s square operator attributes to onnx ' s Pow operator and return the created node .
code: def convert_square(node, **kwargs):
      """Map MXNet's square operator attributes to onnx's Pow operator
      and return the created node.
      """
      onnx = import_onnx_modules()
      name = node["name"]
      proc_nodes = kwargs["proc_nodes"]
      inputs = node["inputs"]
  
      input_node_a_id = kwargs["index_lookup"][inputs[0][0]]
      input_node_a = proc_nodes[input_node_a_id].name
  
      initializer = kwargs["initializer"]
      data_type = onnx.mapping.NP_TYPE_TO_TENSOR_TYPE[np.dtype('int64')]
  
      power2_name = "square_tensor" + str(kwargs["idx"])
      tensor_node = onnx.helper.make_tensor_value_info(power2_name, data_type, (1,))
      initializer.append(
          onnx.helper.make_tensor(
              name=power2_name,
              data_type=data_type,
              dims=(1,),
              vals=[2],
              raw=False,
          )
      )
  
      node = onnx.helper.make_node(
          "Pow",
          [input_node_a, power2_name],
          [name],
          name=name
      )
      return [tensor_node, node]
code_tokens: def convert_square ( node , ** kwargs ) : onnx = import_onnx_modules ( ) name = node [ "name" ] proc_nodes = kwargs [ "proc_nodes" ] inputs = node [ "inputs" ] input_node_a_id = kwargs [ "index_lookup" ] [ inputs [ 0 ] [ 0 ] ] input_node_a = proc_nodes [ input_node_a_id ] . name initializer = kwargs [ "initializer" ] data_type = onnx . mapping . NP_TYPE_TO_TENSOR_TYPE [ np . dtype ( 'int64' ) ] power2_name = "square_tensor" + str ( kwargs [ "idx" ] ) tensor_node = onnx . helper . make_tensor_value_info ( power2_name , data_type , ( 1 , ) ) initializer . append ( onnx . helper . make_tensor ( name = power2_name , data_type = data_type , dims = ( 1 , ) , vals = [ 2 ] , raw = False , ) ) node = onnx . helper . make_node ( "Pow" , [ input_node_a , power2_name ] , [ name ] , name = name ) return [ tensor_node , node ]
short_docstring: Map MXNet's square operator attributes to onnx's Pow operator
  and return the created node.
short_docstring_tokens: Map MXNet ' s square operator attributes to onnx ' s Pow operator and return the created node .
comment: """Map MXNet's square operator attributes to onnx's Pow operator
      and return the created node.
      """