class_docstr: AutoCorrelation Mechanism with the following two phases:
  (1) period-based dependencies discovery
  (2) time delay aggregation
  This block can replace the self-attention family mechanism seamlessly.
class_docstr_tok: ["AutoCorrelation","Mechanism","with","the","following","two","phases",":","(","1",")","period-based","dependencies","discovery","(","2",")","time","delay","aggregation","This","block","can","replace","the","self-attention","family","mechanism","seamlessly","."]
code: def __init__(
      self,
      mask_flag=True,
      factor=1,
      scale=None,
      attention_dropout=0.1,
      output_attention=False,
  ):
      super(AutoCorrelation, self).__init__()
      self.factor = factor
      self.scale = scale
      self.mask_flag = mask_flag
      self.output_attention = output_attention
      self.dropout = nn.Dropout(attention_dropout)
  
imports: import os
  import math
  import numpy
  from math import sqrt
  from scipy.fftpack import next_fast_len
label_desc: Use image node_id 1 to create a new AutoCorrelation object from inherited base classes: nn with example: obj = AutoCorrelation(mask_flag, factor, scale, attention_dropout, output_attention)