parameters: (node, **kwargs)
return_statement: return nodes
docstring: Map MXNet's min operator attributes to onnx's ReduceMin operator
      and return the created node.
docstring_summary: Map MXNet's min operator attributes to onnx's ReduceMin operator
      and return the created node.
docstring_tokens: Map MXNet s min operator attributes to onnx s ReduceMin operator and return the created node .
function: def convert_npi_max(node, **kwargs):
      """Map MXNet's min operator attributes to onnx's ReduceMin operator
      and return the created node.
      """
      from onnx.helper import make_node
      name, input_nodes, attrs = get_inputs(node, kwargs)
  
      mx_axis = str(attrs.get("axis", 'None'))
      axes = convert_string_to_list(mx_axis) if mx_axis != 'None' else None
  
      keepdims = get_boolean_attribute_value(attrs, "keepdims")
  
      if axes is not None:
          create_tensor(axes, name+'_axes', kwargs['initializer'])
          if keepdims:
              nodes = [
                  make_node('ReduceMax', [input_nodes[0]], [name], axes=axes,
                            keepdims=keepdims),
              ]
          else:
              create_tensor([1], name+'_1', kwargs['initializer'])
              create_tensor([0], name+'_0', kwargs['initializer'])
              nodes = [
                  make_node('ReduceMax', [input_nodes[0]], [name+'_reduce'], axes=axes,
                            keepdims=keepdims),
                  make_node('Shape', [name+'_reduce'], [name+'_reduce_shape']),
                  make_node('Concat', [name+'_1', name+'_reduce_shape'], [name+'_concat'], axis=0),
                  make_node('Reshape', [name+'_reduce', name+'_concat'], [name+'_reshape']),
                  make_node('Squeeze', [name+'_reshape', name+'_0'], [name]),
              ]
      else:
          if keepdims:
              nodes = [
                  make_node('ReduceMax', [input_nodes[0]], [name], keepdims=keepdims),
              ]
          else:
              create_tensor([1], name+'_1', kwargs['initializer'])
              nodes = [
                  make_node('ReduceMax', [input_nodes[0]], [name], keepdims=keepdims),
              ]
      return nodes
function_tokens: def convert_npi_max ( node , * * kwargs ) : from onnx . helper import make_node name , input_nodes , attrs = get_inputs ( node , kwargs ) mx_axis = str ( attrs . get ( "axis" , 'None' ) ) axes = convert_string_to_list ( mx_axis ) if mx_axis != 'None' else None keepdims = get_boolean_attribute_value ( attrs , "keepdims" ) if axes is not None : create_tensor ( axes , name + '_axes' , kwargs [ 'initializer' ] ) if keepdims : nodes = [ make_node ( 'ReduceMax' , [ input_nodes [ 0 ] ] , [ name ] , axes = axes , keepdims = keepdims ) , ] else : create_tensor ( [ 1 ] , name + '_1' , kwargs [ 'initializer' ] ) create_tensor ( [ 0 ] , name + '_0' , kwargs [ 'initializer' ] ) nodes = [ make_node ( 'ReduceMax' , [ input_nodes [ 0 ] ] , [ name + '_reduce' ] , axes = axes , keepdims = keepdims ) , make_node ( 'Shape' , [ name + '_reduce' ] , [ name + '_reduce_shape' ] ) , make_node ( 'Concat' , [ name + '_1' , name + '_reduce_shape' ] , [ name + '_concat' ] , axis = 0 ) , make_node ( 'Reshape' , [ name + '_reduce' , name + '_concat' ] , [ name + '_reshape' ] ) , make_node ( 'Squeeze' , [ name + '_reshape' , name + '_0' ] , [ name ] ) , ] else : if keepdims : nodes = [ make_node ( 'ReduceMax' , [ input_nodes [ 0 ] ] , [ name ] , keepdims = keepdims ) , ] else : create_tensor ( [ 1 ] , name + '_1' , kwargs [ 'initializer' ] ) nodes = [ make_node ( 'ReduceMax' , [ input_nodes [ 0 ] ] , [ name ] , keepdims = keepdims ) , ] return nodes