parameters: (self, col_mean, col_std)
return_statement: return np.clip(col_sample, 0, 255).astype('uint8')
docstring: sample from a normal distribution centered around COL_MEAN 
          with standard deviation = COL_STD.
docstring_summary: sample from a normal distribution centered around COL_MEAN 
          with standard deviation = COL_STD.
docstring_tokens: sample from a normal distribution centered around COL_MEAN with standard deviation = COL_STD .
function: def sample_normal(self, col_mean, col_std):
          """
          sample from a normal distribution centered around COL_MEAN 
          with standard deviation = COL_STD.
          """
          col_sample = col_mean + col_std * np.random.randn()
          return np.clip(col_sample, 0, 255).astype('uint8')
function_tokens: def sample_normal ( self , col_mean , col_std ) : col_sample = col_mean + col_std * np . random . randn ( ) return np . clip ( col_sample , 0 , 255 ) . astype ( 'uint8' )