parameters: (self, depth_radius=5, bias=1.0, alpha=1.0, beta=0.5, norm_region="ACROSS_CHANNELS")
docstring: Initialize LRN
docstring_summary: Initialize LRN
docstring_tokens: Initialize LRN
function: def __init__(self, depth_radius=5, bias=1.0, alpha=1.0, beta=0.5, norm_region="ACROSS_CHANNELS"):
          """Initialize LRN"""
          self.init_prim_io_names(inputs=['x'], outputs=['y'])
          validator.check_value_type("depth_radius", depth_radius, [int], self.name)
          validator.check_value_type("bias", bias, [float], self.name)
          validator.check_value_type("alpha", alpha, [float], self.name)
          validator.check_value_type("beta", beta, [float], self.name)
          validator.check_value_type("norm_region", norm_region, [str], self.name)
          validator.check_string(norm_region, ['ACROSS_CHANNELS'], 'norm_region', self.name)
          validator.check_non_negative_int(depth_radius, "depth_radius", self.name)
function_tokens: def __init__ ( self , depth_radius = 5 , bias = 1.0 , alpha = 1.0 , beta = 0.5 , norm_region = "ACROSS_CHANNELS" ) : self . init_prim_io_names ( inputs = [ 'x' ] , outputs = [ 'y' ] ) validator . check_value_type ( "depth_radius" , depth_radius , [ int ] , self . name ) validator . check_value_type ( "bias" , bias , [ float ] , self . name ) validator . check_value_type ( "alpha" , alpha , [ float ] , self . name ) validator . check_value_type ( "beta" , beta , [ float ] , self . name ) validator . check_value_type ( "norm_region" , norm_region , [ str ] , self . name ) validator . check_string ( norm_region , [ 'ACROSS_CHANNELS' ] , 'norm_region' , self . name ) validator . check_non_negative_int ( depth_radius , "depth_radius" , self . name )