parameters: (self, axis, p=2, keep_dims=False, epsilon=1e-12)
docstring: Initialize LpNorm
docstring_summary: Initialize LpNorm
docstring_tokens: Initialize LpNorm
function: def __init__(self, axis, p=2, keep_dims=False, epsilon=1e-12):
          """Initialize LpNorm"""
          validator.check_value_type("p", p, [int], self.name)
          validator.check_value_type("axis", axis, [int, tuple, list], self.name)
          validator.check_value_type("keep_dims", keep_dims, [bool], self.name)
          validator.check_value_type("epsilon", epsilon, [float], self.name)
          validator.check_non_negative_int(p, "p", self.name)
          validator.check_non_negative_float(epsilon, "epsilon", self.name)
          if isinstance(axis, int):
              self.add_prim_attr('axis', [self.axis])
          else:
              for element_of_axis in axis:
                  validator.check_value_type("element_of_axis", element_of_axis, [int], self.name)
          self.init_prim_io_names(inputs=['input'], outputs=['output'])
function_tokens: def __init__ ( self , axis , p = 2 , keep_dims = False , epsilon = 1e-12 ) : validator . check_value_type ( "p" , p , [ int ] , self . name ) validator . check_value_type ( "axis" , axis , [ int , tuple , list ] , self . name ) validator . check_value_type ( "keep_dims" , keep_dims , [ bool ] , self . name ) validator . check_value_type ( "epsilon" , epsilon , [ float ] , self . name ) validator . check_non_negative_int ( p , "p" , self . name ) validator . check_non_negative_float ( epsilon , "epsilon" , self . name ) if isinstance ( axis , int ) : self . add_prim_attr ( 'axis' , [ self . axis ] ) else : for element_of_axis in axis : validator . check_value_type ( "element_of_axis" , element_of_axis , [ int ] , self . name ) self . init_prim_io_names ( inputs = [ 'input' ] , outputs = [ 'output' ] )